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Highlights
• Pre-service teachershave stereotypes towards pupils with autism, Down syndrome and dyslexia.
• Pupils with Down syndrome, autism and dyslexia are associated with distinctive stereotypes.
• These stereotypes can be classified in three resp. four different dimensions.
Abstract
Stereotypes about pupils with special educational needs are prevalent both in society and among pre- and in-service teachers. However, little is known about the specific stereotypes pre-service teachers associate with autistic pupils, pupils with Down syndrome, and pupils with dyslexia. We explored these in two studies. Study 1 (N=13) involved qualitative interviews to identify potential stereotype content. Study 2 (N=213) used these findings to create a questionnaire to quantify these stereotypes. We found distinct stereotypes associated with all three groups of pupils. For successful inclusion, teachers must recognize the uniqueness of each pupil, including those with different diagnoses.
Can prediction error explain predictability effects on the N1 during picture-word verification?
(2024)
Do early effects of predictability in visual word recognition reflect prediction error? Electrophysiological research investigating word processing has demonstrated predictability effects in the N1, or first negative component of the event-related potential (ERP). However, findings regarding the magnitude of effects and potential interactions of predictability with lexical variables have been inconsistent. Moreover, past studies have typically used categorical designs with relatively small samples and relied on by-participant analyses. Nevertheless, reports have generally shown that predicted words elicit less negative-going (i.e., lower amplitude) N1s, a pattern consistent with a simple predictive coding account. In our preregistered study, we tested this account via the interaction between prediction magnitude and certainty. A picture-word verification paradigm was implemented in which pictures were followed by tightly matched picture-congruent or picture-incongruent written nouns. The predictability of target (picture-congruent) nouns was manipulated continuously based on norms of association between a picture and its name. ERPs from 68 participants revealed a pattern of effects opposite to that expected under a simple predictive coding framework.
The hippocampal-dependent memory system and striatal-dependent memory system modulate reinforcement learning depending on feedback timing in adults, but their contributions during development remain unclear. In a 2-year longitudinal study, 6-to-7-year-old children performed a reinforcement learning task in which they received feedback immediately or with a short delay following their response. Children’s learning was found to be sensitive to feedback timing modulations in their reaction time and inverse temperature parameter, which quantifies value-guided decision-making. They showed longitudinal improvements towards more optimal value-based learning, and their hippocampal volume showed protracted maturation. Better delayed model-derived learning covaried with larger hippocampal volume longitudinally, in line with the adult literature. In contrast, a larger striatal volume in children was associated with both better immediate and delayed model-derived learning longitudinally. These findings show, for the first time, an early hippocampal contribution to the dynamic development of reinforcement learning in middle childhood, with neurally less differentiated and more cooperative memory systems than in adults.
Dual coding theories of knowledge suggest that meaning is represented in the brain by a double code, which comprises language-derived representations in the Anterior Temporal Lobe and sensory-derived representations in perceptual and motor regions. This approach predicts that concrete semantic features should activate both codes, whereas abstract features rely exclusively on the linguistic code. Using magnetoencephalography (MEG), we adopted a temporally resolved multiple regression approach to identify the contribution of abstract and concrete semantic predictors to the underlying brain signal. Results evidenced early involvement of anterior-temporal and inferior-frontal brain areas in both abstract and concrete semantic information encoding. At later stages, occipito-temporal regions showed greater responses to concrete compared to abstract features. The present findings shed new light on the temporal dynamics of abstract and concrete semantic representations in the brain and suggest that the concreteness of words processed first with a transmodal/linguistic code, housed in frontotemporal brain systems, and only after with an imagistic/sensorimotor code in perceptual and motor regions.
The purpose of this study was to examine if prosodic patterns in oral reading derived from Recurrence Quantification Analysis (RQA) could distinguish between struggling and skilled German readers in Grades 2 (n = 67) and 4 (n = 69). Furthermore, we investigated whether models estimated with RQA measures outperformed models estimated with prosodic features derived from prosodic transcription. According to the findings, struggling second graders appear to have a slower reading rate, longer intervals between pauses, and more repetitions of recurrent amplitudes and pauses, whereas struggling fourth graders appear to have less stable pause patterns over time, more pitch repetitions, more similar amplitude patterns over time, and more repetitions of pauses. Additionally, the models with prosodic patterns outperformed models with prosodic features. These findings suggest that the RQA approach provides additional information about prosody that complements an established approach.
Objects that are congruent with a scene are recognised more efficiently than objects that are incongruent. Further, semantic integration of incongruent objects elicits a stronger N300/N400 EEG component. Yet, the time course and mechanisms of how contextual information supports access to semantic object information is unclear. We used computational modelling and EEG to test how context influences semantic object processing. Using representational similarity analysis, we established that EEG patterns dissociated between objects in congruent or incongruent scenes from around 300 ms. By modelling semantic processing of objects using independently normed properties, we confirm that the onset of semantic processing of both congruent and incongruent objects is similar (∼150 ms). Critically, after ∼275 ms, we discover a difference in the duration of semantic integration, lasting longer for incongruent compared to congruent objects. These results constrain our understanding of how contextual information supports access to semantic object information.
Behavioral and psychological syndromes such as depression and psychosis often occur along with cognitive (esp. executive) deficits in vascular cognitive disorder (VCD) in the elderly. We present the case of an 85-year-old woman with deficits in executive functions as well as a persistent and clearly circumscribed paranoid hallucinatory syndrome (most probably due to VCD) which could not be adequately treated with antipsychotic medication. The patient also suffered from severe depression (independent of psychotic symptoms). Both psychosis and depression were successfully managed in a home treatment based on Flexible Assertive Community Treatment (FACT). Interestingly, a thematic association between the delusional contents and early childhood traumata could be reconstructed, and late-onset trauma-related symptoms could be successfully treated with cognitive-behavioral therapy (CBT) as well. In sum, behavioral management of psychotic syndromes is possible in the absence of adequate pharmacological treatment options, and multiprofessional and person-centered home treatment may be successful in the elderly, even in severe and complex disorders.
Adaptive decision-making is governed by at least two types of memory processes. On the one hand, learned predictions through integrating multiple experiences, and on the other hand, one-shot episodic memories. These two processes interact, and predictions – particularly prediction errors – influence how episodic memories are encoded. However, studies using computational models disagree on the exact shape of this relationship, with some findings showing an effect of signed prediction errors and others showing an effect of unsigned prediction errors on episodic memory. We argue that the choice-confirmation bias, which reflects stronger learning from choice-confirming compared to disconfirming outcomes, could explain these seemingly diverging results. Our perspective implies that the influence of prediction errors on episodic encoding critically depends on whether people can freely choose between options (i.e., instrumental learning tasks) or not (Pavlovian learning tasks). The choice-confirmation bias on memory encoding might have evolved to prioritize memory representations that optimize reward-guided decision-making. We conclude by discussing open issues and implications for future studies.
Can prediction error explain predictability effects on the N1 during picture-word verification?
(2023)
Do early effects of predictability in visual word recognition reflect prediction error? Electrophysiological research investigating word processing has demonstrated predictability effects in the N1, or first negative component of the event-related potential (ERP). However, findings regarding the magnitude of effects and potential interactions of predictability with lexical variables have been inconsistent. Moreover, past studies have typically used categorical designs with relatively small samples and relied on by-participant analyses. Nevertheless, reports have generally shown that predicted words elicit less negative-going (i.e., lower amplitude) N1s, a pattern consistent with a simple predictive coding account. In our preregistered study, we tested this account via the interaction between prediction magnitude and certainty. A picture-word verification paradigm was implemented in which pictures were followed by tightly matched picture-congruent or picture-incongruent written nouns. The predictability of target (picture-congruent) nouns was manipulated continuously based on norms of association between a picture and its name. ERPs from 68 participants revealed a pattern of effects opposite to that expected under a simple predictive coding framework.
Current deep learning methods are regarded as favorable if they empirically perform well on dedicated test sets. This mentality is seamlessly reflected in the resurfacing area of continual learning, where consecutively arriving data is investigated. The core challenge is framed as protecting previously acquired representations from being catastrophically forgotten. However, comparison of individual methods is nevertheless performed in isolation from the real world by monitoring accumulated benchmark test set performance. The closed world assumption remains predominant, i.e. models are evaluated on data that is guaranteed to originate from the same distribution as used for training. This poses a massive challenge as neural networks are well known to provide overconfident false predictions on unknown and corrupted instances. In this work we critically survey the literature and argue that notable lessons from open set recognition, identifying unknown examples outside of the observed set, and the adjacent field of active learning, querying data to maximize the expected performance gain, are frequently overlooked in the deep learning era. Hence, we propose a consolidated view to bridge continual learning, active learning and open set recognition in deep neural networks. Finally, the established synergies are supported empirically, showing joint improvement in alleviating catastrophic forgetting, querying data, selecting task orders, while exhibiting robust open world application.
Despite the recent popularity of predictive processing models of brain function, the term prediction is often instantiated very differently across studies. These differences in definition can substantially change the type of cognitive or neural operation hypothesised and thus have critical implications for the corresponding behavioural and neural correlates during visual perception. Here, we propose a five-dimensional scheme to characterise different parameters of prediction. Namely, flow of information, mnemonic origin, specificity, complexity, and temporal precision. We describe these dimensions and provide examples of their application to previous work. Such a characterisation not only facilitates the integration of findings across studies, but also helps stimulate new research questions.
Recent findings indicate that visual feedback derived from episodic memory can be traced down to the earliest stages of visual processing, whereas feedback stemming from schema-related memories only reach intermediate levels in the visual processing hierarchy. In this opinion piece, we examine these differences in light of the 'what' and 'where' streams of visual perception. We build upon this new framework to propose that the memory deficits observed in aphantasics might be better understood as a difference in high-level feedback processing along the ‘what’ stream, rather than an episodic memory impairment.
Attribute amnesia describes the failure to unexpectedly report the attribute of an attended stimulus, likely reflecting a lack of working memory consolidation. Previous studies have shown that unique meaningful objects are immune to attribute amnesia. However, these studies used highly dissimilar foils to test memory, raising the possibility that good performance at the surprise test was based on an imprecise (gist-like) form of long-term memory. In Experiment 1, we explored whether a more sensitive memory test would reveal attribute amnesia in meaningful objects. We used a four-alternative-forced-choice test with foils having mis-matched exemplar (e.g., apple pie/pumpkin pie) and/or state (e.g., cut/full) information. Errors indicated intact exemplar, but not state information. Thus, meaningful objects are vulnerable to attribute amnesia under the right conditions. In Experiments 2A-2D, we manipulated the familiarity signals of test items by introducing a critical object as a pre-surprise target. In the surprise trial, this critical item matched one of the foil choices. Participants selected the critical object more often than other items. By demonstrating that familiarity influences responses in this paradigm, we suggest that meaningful objects are not immune to attribute amnesia but instead side-step the effects of attribute amnesia.
When experienced in-person, engagement with art has been associated with positive outcomes in well-being and mental health. However, especially in the last decade, art viewing, cultural engagement, and even ‘trips’ to museums have begun to take place online, via computers, smartphones, tablets, or in virtual reality. Similarly, to what has been reported for in-person visits, online art engagements—easily accessible from personal devices—have also been associated to well-being impacts. However, a broader understanding of for whom and how online-delivered art might have well-being impacts is still lacking. In the present study, we used a Monet interactive art exhibition from Google Arts and Culture to deepen our understanding of the role of pleasure, meaning, and individual differences in the responsiveness to art. Beyond replicating the previous group-level effects, we confirmed our pre-registered hypothesis that trait-level inter-individual differences in aesthetic responsiveness predict some of the benefits that online art viewing has on well-being and further that such inter-individual differences at the trait level were mediated by subjective experiences of pleasure and especially meaningfulness felt during the online-art intervention. The role that participants' experiences play as a possible mechanism during art interventions is discussed in light of recent theoretical models.
Spontaneous brain activity builds the foundation for human cognitive processing during external demands. Neuroimaging studies based on functional magnetic resonance imaging (fMRI) identified specific characteristics of spontaneous (intrinsic) brain dynamics to be associated with individual differences in general cognitive ability, i.e., intelligence. However, fMRI research is inherently limited by low temporal resolution, thus, preventing conclusions about neural fluctuations within the range of milliseconds. Here, we used resting-state electroencephalographical (EEG) recordings from 144 healthy adults to test whether individual differences in intelligence (Raven’s Advanced Progressive Matrices scores) can be predicted from the complexity of temporally highly resolved intrinsic brain signals. We compared different operationalizations of brain signal complexity (multiscale entropy, Shannon entropy, Fuzzy entropy, and specific characteristics of microstates) regarding their relation to intelligence. The results indicate that associations between brain signal complexity measures and intelligence are of small effect sizes (r ∼ 0.20) and vary across different spatial and temporal scales. Specifically, higher intelligence scores were associated with lower complexity in local aspects of neural processing, and less activity in task-negative brain regions belonging to the default-mode network. Finally, we combined multiple measures of brain signal complexity to show that individual intelligence scores can be significantly predicted with a multimodal model within the sample (10-fold cross-validation) as well as in an independent sample (external replication, N = 57). In sum, our results highlight the temporal and spatial dependency of associations between intelligence and intrinsic brain dynamics, proposing multimodal approaches as promising means for future neuroscientific research on complex human traits.
The hippocampal-dependent memory system and striatal-dependent memory system modulate reinforcement learning depending on feedback timing in adults, but their contributions during development remain unclear. In a 2-year longitudinal study, 6-to-7-year-old children performed a reinforcement learning task in which they received feedback immediately or with a short delay following their response. Children’s learning was found to be sensitive to feedback timing modulations in their reaction time and inverse temperature parameter, which quantifies value-guided decision-making. They showed longitudinal improvements towards more optimal value-based learning, and their hippocampal volume showed protracted maturation. Better delayed model-derived learning covaried with larger hippocampal volume longitudinally, in line with the adult literature. In contrast, a larger striatal volume in children was associated with both better immediate and delayed model-derived learning longitudinally. These findings show, for the first time, an early hippocampal contribution to the dynamic development of reinforcement learning in middle childhood, with neurally less differentiated and more cooperative memory systems than in adults.
The hippocampal-dependent memory system and striatal-dependent memory system modulate reinforcement learning depending on feedback timing in adults, but their contributions during development remain unclear. In a 2-year longitudinal study, 6-to-7-year-old children performed a reinforcement learning task in which they received feedback immediately or with a short delay following their response. Children’s learning was found to be sensitive to feedback timing modulations in their reaction time and inverse temperature parameter, which quantifies value-guided decision-making. They showed longitudinal improvements towards more optimal value-based learning, and their hippocampal volume showed protracted maturation. Better delayed model-derived learning covaried with larger hippocampal volume longitudinally, in line with the adult literature. In contrast, a larger striatal volume in children was associated with both better immediate and delayed model-derived learning longitudinally. These findings show, for the first time, an early hippocampal contribution to the dynamic development of reinforcement learning in middle childhood, with neurally less differentiated and more cooperative memory systems than in adults.
The hippocampal-dependent memory system and striatal-dependent memory system modulate reinforcement learning depending on feedback timing in adults, but their contributions during development remain unclear. In a 2-year longitudinal study, 6-to-7-year-old children performed a reinforcement learning task in which they received feedback immediately or with a short delay following their response. Children’s learning was found to be sensitive to feedback timing modulations in their reaction time and inverse temperature parameter, which quantifies value-guided decision-making. They showed longitudinal improvements towards more optimal value-based learning, and their hippocampal volume showed protracted maturation. Better delayed model-derived learning covaried with larger hippocampal volume longitudinally, in line with the adult literature. In contrast, a larger striatal volume in children was associated with both better immediate and delayed model-derived learning longitudinally. These findings show, for the first time, an early hippocampal contribution to the dynamic development of reinforcement learning in middle childhood, with neurally less differentiated and more cooperative memory systems than in adults.
Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities – which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5% of 10min resting-state fMRI) can significantly predict individual differences in intelligence (N = 263, p < .001). Against previous expectations, individual’s network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.
An important question concerning inter-areal communication in the cortex is whether these interactions are synergistic, i.e. brain signals can either share common information (redundancy) or they can encode complementary information that is only available when both signals are considered together (synergy). Here, we dissociated cortical interactions sharing common information from those encoding complementary information during prediction error processing. To this end, we computed co-information, an information-theoretical measure that distinguishes redundant from synergistic information among brain signals. We analyzed auditory and frontal electrocorticography (ECoG) signals in five common awake marmosets performing two distinct auditory oddball tasks and investigated to what extent event-related potentials (ERP) and broadband (BB) dynamics encoded redundant and synergistic information during auditory prediction error processing. In both tasks, we observed multiple patterns of synergy across the entire cortical hierarchy with distinct dynamics. The information conveyed by ERPs and BB signals was highly synergistic even at lower stages of the hierarchy in the auditory cortex, as well as between auditory and frontal regions. Using a brain-constrained neural network, we simulated the spatio-temporal patterns of synergy and redundancy observed in the experimental results and further demonstrated that the emergence of synergy between auditory and frontal regions requires the presence of strong, long-distance, feedback and feedforward connections. These results indicate that the distributed representations of prediction error signals across the cortical hierarchy can be highly synergistic.
Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities – which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5% of 10min resting-state fMRI) can significantly predict individual differences in intelligence (N = 263, p < .001). Against previous expectations, individual’s network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.
Highlights
• Brain connectivity states identified by cofluctuation strength.
• CMEP as new method to robustly predict human traits from brain imaging data.
• Network-identifying connectivity ‘events’ are not predictive of cognitive ability.
• Sixteen temporally independent fMRI time frames allow for significant prediction.
• Neuroimaging-based assessment of cognitive ability requires sufficient scan lengths.
Abstract
Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities – which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5% of 10 min resting-state fMRI) can significantly predict individual differences in intelligence (N = 263, p < .001). Against previous expectations, individual's network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.
Probing the association between resting-state brain network dynamics and psychological resilience
(2022)
Abstract
This study aimed at replicating a previously reported negative correlation between node flexibility and psychological resilience, that is, the ability to retain mental health in the face of stress and adversity. To this end, we used multiband resting-state BOLD fMRI (TR = .675 sec) from 52 participants who had filled out three psychological questionnaires assessing resilience. Time-resolved functional connectivity was calculated by performing a sliding window approach on averaged time series parcellated according to different established atlases. Multilayer modularity detection was performed to track network reconfigurations over time, and node flexibility was calculated as the number of times a node changes community assignment. In addition, node promiscuity (the fraction of communities a node participates in) and node degree (as proxy for time-varying connectivity) were calculated to extend previous work. We found no substantial correlations between resilience and node flexibility. We observed a small number of correlations between the two other brain measures and resilience scores that were, however, very inconsistently distributed across brain measures, differences in temporal sampling, and parcellation schemes. This heterogeneity calls into question the existence of previously postulated associations between resilience and brain network flexibility and highlights how results may be influenced by specific analysis choices.
Author Summary
We tested the replicability and generalizability of a previously proposed negative association between dynamic brain network reconfigurations derived from multilayer modularity detection (node flexibility) and psychological resilience. Using multiband resting-state BOLD fMRI data and exploring several parcellation schemes, sliding window approaches, and temporal resolutions of the data, we could not replicate previously reported findings regarding the association between node flexibility and resilience. By extending this work to other measures of brain dynamics (node promiscuity, degree) we observe a rather inconsistent pattern of correlations with resilience that strongly varies across analysis choices. We conclude that further research is needed to understand the network neuroscience basis of mental health and discuss several reasons that may account for the variability in results.
Das Projekt »Re:Start nach der Krise« der Psychotherapeutischen Beratungsstelle an der Goethe-Universität hat das Ziel, Studierenden bei der Rückkehr an die Universität Hilfe und Orientierung anzubieten. Gerhard Hellmeister, Psychologe und Therapeut, hat mit seinem Team das Angebot entwickelt und spricht im Interview mit dem UniReport über das Prinzip des Design Thinking, über die Bedeutung von Krisen und Neuanfängen und über die Unterschiede des Angebots zu Selbstoptimierungsseminaren und Karrierecoachings.
Viewpoint effects on object recognition interact with object-scene consistency effects. While recognition of objects seen from “accidental” viewpoints (e.g., a cup from below) is typically impeded compared to processing of objects seen from canonical viewpoints (e.g., the string-side of a guitar), this effect is reduced by meaningful scene context information. In the present study we investigated if these findings established by using photographic images, generalise to 3D models of objects. Using 3D models further allowed us to probe a broad range of viewpoints and empirically establish accidental and canonical viewpoints. In Experiment 1, we presented 3D models of objects from six different viewpoints (0°, 60°, 120°, 180° 240°, 300°) in colour (1a) and grayscaled (1b) in a sequential matching task. Viewpoint had a significant effect on accuracy and response times. Based on the performance in Experiments 1a and 1b, we determined canonical (0°-rotation) and non-canonical (120°-rotation) viewpoints for the stimuli. In Experiment 2, participants again performed a sequential matching task, however now the objects were paired with scene backgrounds which could be either consistent (e.g., a cup in the kitchen) or inconsistent (e.g., a guitar in the bathroom) to the object. Viewpoint interacted significantly with scene consistency in that object recognition was less affected by viewpoint when consistent scene information was provided, compared to inconsistent information. Our results show that viewpoint-dependence and scene context effects generalize to depth rotated 3D objects. This supports the important role object-scene processing plays for object constancy.
Electroencephalography (EEG) has been used for decades to identify neurocognitive processes related to intelligence. Evidence is accumulating for associations with neural markers of higher-order cognitive processes (e.g., working memory); however, whether associations are specific to complex processes or also relate to earlier processing stages remains unclear. Addressing these issues has implications for improving our understanding of intelligence and its neural correlates. The mismatch negativity (MMN) is an event-related brain potential (ERP) that is elicited when, within a series of frequent standard stimuli, rare deviant stimuli are presented. As stimuli are typically presented outside the focus of attention, the MMN is suggested to capture automatic pre-attentive discrimination processes. However, the MMN and its relation to intelligence has largely only been studied in the auditory domain, thus preventing conclusions about the involvement of automatic discrimination processes in humans’ dominant sensory modality vision. Electroencephalography was recorded from 50 healthy participants during a passive visual oddball task that presented simple sequence violations as well as deviations within a more complex hidden pattern. Signed area amplitudes and fractional area latencies of the visual mismatch negativity (vMMN) were calculated with and without Laplacian transformation. Correlations between vMMN and intelligence (Raven’s Advanced Progressive Matrices) were of negligible to small effect sizes, differed critically between measurement approaches, and Bayes Factors provided anecdotal to substantial evidence for the absence of an association. We discuss differences between the auditory and visual MMN, the implications of different measurement approaches, and offer recommendations for further research in this evolving field.
We predicted that chronic pain patients have a more negative stress mindset and a lower level of social identification than people without chronic pain and that this, in turn, influences well-being through less adaptive coping. 1240 participants (465 chronic pain patients; 775 people in the control group) completed a cross-sectional online-survey. Chronic pain patients had a more negative stress mindset and a lower level of social identification than people without chronic pain. However, a positive stress mindset was linked to better well-being and fewer depressive symptoms, through the use of the adaptive coping behaviors positive reframing and active coping. A higher level of social identification did not impact well-being or depression through the use of instrumental and emotional support coping, but through the more frequent use of positive reframing and active coping. For chronic pain therapy, we propose including modules that foster social identification and a positive stress mindset.
Academic self-efficacy (ASE) refers to a student’s global belief in his/her ability to master the various academic challenges at university and is an essential antecedent of wellbeing and performance. The five-item General Academic Self-Efficacy Scale (GASE) showed promise as a short and concise measure for overall ASE. However, of its validity and reliability outside of Scandinavia is limited. Therefore, this paper aimed to investigate the psychometric properties, longitudinal invariance, and criterion validity of the GASE within a sample of university students (Time 1: n = 1056 & Time 2: n = 592) in the USA and Western Europe. The results showed that a unidimensional factorial model of overall ASE fitted the data well was reliable and invariant across time. Further, criterion validity was established by finding a positive relationship with task performance at different time stamps. Therefore, the GASE can be used as a valid and reliable measure for general ASE.
Spontaneous brain activity builds the foundation for human cognitive processing during external demands. A huge number of neuroimaging studies identified specific characteristics of spontaneous (intrinsic) brain dynamics to be associated with individual differences in general cognitive ability, i.e., intelligence. However, respective research is inherently limited by low temporal resolution, thus, preventing conclusions about neural fluctuations within the range of milliseconds. Here, we used resting-state electroencephalographical (EEG) recordings from 144 healthy adults to test whether individual differences in intelligence (Raven’s Advanced Progressive Matrices scores) can be predicted from the complexity of temporally highly resolved intrinsic brain signals. We compared different operationalizations of brain signal complexity (multiscale entropy, Shannon entropy, Fuzzy entropy, and specific characteristics of microstates) in regard to their relation to intelligence. The results indicate that associations between brain signal complexity measures and intelligence are of small effect sizes (r ~ .20) and vary across different spatial and temporal scales. Specifically, higher intelligence scores were associated with lower complexity in local aspects of neural processing, and less activity in task-negative brain regions belonging to the default-mode network. Finally, we combined multiple measures of brain signal complexity to show that individual intelligence scores can be significantly predicted with a multimodal model within the sample (10-fold cross-validation) as well as in an independent sample (external replication, N = 57). In sum, our results highlight the temporal and spatial dependency of associations between intelligence and intrinsic brain dynamics, proposing multimodal approaches as promising means for future neuroscientific research on complex human traits.
Significance Statement Spontaneous brain activity builds the foundation for intelligent processing - the ability of humans to adapt to various cognitive demands. Using resting-state EEG, we extracted multiple aspects of temporally highly resolved intrinsic brain dynamics to investigate their relationship with individual differences in intelligence. Single associations were of small effect sizes and varied critically across spatial and temporal scales. However, combining multiple measures in a multimodal cross-validated prediction model, allows to significantly predict individual intelligence scores in unseen participants. Our study adds to a growing body of research suggesting that observable associations between complex human traits and neural parameters might be rather small and proposes multimodal prediction approaches as promising tool to derive robust brain-behavior relations despite limited sample sizes.
Objects that are congruent with a scene are recognised more efficiently than objects that are incongruent. Further, semantic integration of incongruent objects elicits a stronger N300/N400 EEG component. Yet, the time course and mechanisms of how contextual information supports access to semantic object information is unclear. We used computational modelling and EEG to test how context influences semantic object processing. Using representational similarity analysis, we established that EEG patterns dissociated between objects in congruent or incongruent scenes from around 300 ms. By modelling semantic processing of objects using independently normed properties, we confirm that the onset of semantic processing of both congruent and incongruent objects is similar (∼150 ms). Critically, after ∼275 ms, we discover a difference in the duration of semantic integration, lasting longer for incongruent compared to congruent objects. These results constrain our understanding of how contextual information supports access to semantic object information.
Spontaneous brain activity builds the foundation for human cognitive processing during external demands. Neuroimaging studies based on functional magnetic resonance imaging (fMRI) identified specific characteristics of spontaneous (intrinsic) brain dynamics to be associated with individual differences in general cognitive ability, i.e., intelligence. However, fMRI research is inherently limited by low temporal resolution, thus, preventing conclusions about neural fluctuations within the range of milliseconds. Here, we used resting-state electroencephalographical (EEG) recordings from 144 healthy adults to test whether individual differences in intelligence (Raven’s Advanced Progressive Matrices scores) can be predicted from the complexity of temporally highly resolved intrinsic brain signals. We compared different operationalizations of brain signal complexity (multiscale entropy, Shannon entropy, Fuzzy entropy, and specific characteristics of microstates) regarding their relation to intelligence. The results indicate that associations between brain signal complexity measures and intelligence are of small effect sizes (r ~ .20) and vary across different spatial and temporal scales. Specifically, higher intelligence scores were associated with lower complexity in local aspects of neural processing, and less activity in task-negative brain regions belonging to the defaultmode network. Finally, we combined multiple measures of brain signal complexity to show that individual intelligence scores can be significantly predicted with a multimodal model within the sample (10-fold cross-validation) as well as in an independent sample (external replication, N = 57). In sum, our results highlight the temporal and spatial dependency of associations between intelligence and intrinsic brain dynamics, proposing multimodal approaches as promising means for future neuroscientific research on complex human traits.
Significance Statement Spontaneous brain activity builds the foundation for intelligent processing - the ability of humans to adapt to various cognitive demands. Using resting-state EEG, we extracted multiple aspects of temporally highly resolved intrinsic brain dynamics to investigate their relationship with individual differences in intelligence. Single associations were of small effect sizes and varied critically across spatial and temporal scales. However, combining multiple measures in a multimodal cross-validated prediction model, allows to significantly predict individual intelligence scores in unseen participants. Our study adds to a growing body of research suggesting that observable associations between complex human traits and neural parameters might be rather small and proposes multimodal prediction approaches as promising tool to derive robust brain-behavior relations despite limited sample sizes.
Abstract
To characterize the functional role of the left-ventral occipito-temporal cortex (lvOT) during reading in a quantitatively explicit and testable manner, we propose the lexical categorization model (LCM). The LCM assumes that lvOT optimizes linguistic processing by allowing fast meaning access when words are familiar and filtering out orthographic strings without meaning. The LCM successfully simulates benchmark results from functional brain imaging described in the literature. In a second evaluation, we empirically demonstrate that quantitative LCM simulations predict lvOT activation better than alternative models across three functional magnetic resonance imaging studies. We found that word-likeness, assumed as input into a lexical categorization process, is represented posteriorly to lvOT, whereas a dichotomous word/non-word output of the LCM could be localized to the downstream frontal brain regions. Finally, training the process of lexical categorization resulted in more efficient reading. In sum, we propose that word recognition in the ventral visual stream involves word-likeness extraction followed by lexical categorization before one can access word meaning.
Author summary
Visual word recognition is a critical process for reading and relies on the human brain’s left ventral occipito-temporal (lvOT) regions. However, the lvOTs specific function in visual word recognition is not yet clear. We propose that these occipito-temporal brain systems are critical for lexical categorization, i.e., the process of determining whether an orthographic percept is a known word or not, so that further lexical and semantic processing can be restricted to those percepts that are part of our "mental lexicon". We demonstrate that a computational model implementing this process, the lexical categorization model, can explain seemingly contradictory benchmark results from the published literature. We further use functional magnetic resonance imaging to show that the lexical categorization model successfully predicts brain activation in the left ventral occipito-temporal cortex elicited during a word recognition task. It does so better than alternative models proposed so far. Finally, we provide causal evidence supporting this model by empirically demonstrating that training the process of lexical categorization improves reading performance.
Free gaze and moving images are typically avoided in EEG experiments due to the expected generation of artifacts and noise. Yet for a growing number of research questions, loosening these rigorous restrictions would be beneficial. Among these is research on visual aesthetic experiences, which often involve open-ended exploration of highly variable stimuli. Here we systematically compare the effect of conservative vs. more liberal experimental settings on various measures of behavior, brain activity and physiology in an aesthetic rating task. Our primary aim was to assess EEG signal quality. 43 participants either maintained fixation or were allowed to gaze freely, and viewed either static images or dynamic (video) stimuli consisting of dance performances or nature scenes. A passive auditory background task (auditory steady-state response; ASSR) was added as a proxy measure for overall EEG recording quality. We recorded EEG, ECG and eye tracking data, and participants rated their aesthetic preference and state of boredom on each trial. Whereas both behavioral ratings and gaze behavior were affected by task and stimulus manipulations, EEG SNR was barely affected and generally robust across all conditions, despite only minimal preprocessing and no trial rejection. In particular, we show that using video stimuli does not necessarily result in lower EEG quality and can, on the contrary, significantly reduce eye movements while increasing both the participants’ aesthetic response and general task engagement. We see these as encouraging results indicating that — at least in the lab — more liberal experimental conditions can be adopted without significant loss of signal quality.
How much data do we need? Lower bounds of brain activation states to predict human cognitive ability
(2022)
Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Despite their low frequency of occurrence, states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture (derived from resting-state fMRI) and to be highly subject-specific. However, it is currently unclear whether such network-defining states of high cofluctuation also contribute to individual variations in cognitive abilities – which strongly rely on the interactions among distributed brain regions. By introducing CMEP, an eigenvector-based prediction framework, we show that functional connectivity estimates from as few as 20 temporally separated time frames (< 3% of a 10 min resting-state fMRI scan) are significantly predictive of individual differences in intelligence (N = 281, p < .001). In contrast and against previous expectations, individual’s network-defining time frames of particularly high cofluctuation do not achieve significant prediction of intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest brain connectivity, temporally distributed information is necessary to extract information about cognitive abilities from functional connectivity time series. This information, however, is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.
Drawing on the role of teachers for peer ecologies, we investigated whether students favored ethnically homogenous over ethnically diverse relationships, depending on classroom diversity and perceived teacher care. We specifically studied students’ intra- and interethnic relationships in classrooms with different ethnic compositions, accounting for homogeneous subgroups forming on the basis of ethnicity and gender diversity (i.e., ethnic-demographic faultlines). Based on multilevel social network analyses of dyadic networks between 1299 early adolescents in 70 German fourth grade classrooms, the results indicated strong ethnic homophily, particularly driven by German students who favored ethnically homogenous dyads over mixed dyads. As anticipated, the results showed that there was more in-group bias if perceived teacher care was low rather than high. Moreover, stronger faultlines were associated with stronger in-group bias; however, this relation was moderated by teacher care: If students perceived high teacher care, they showed a higher preference for mixed-ethnic dyads, even in classrooms with strong faultlines. These findings highlight the central role of teachers as agents of positive diversity management and the need to consider contextual classroom factors other than ethnic diversity when investigating intergroup relations in schools.
Repeated search studies are a hallmark in the investigation of the interplay between memory and attention. Due to a usually employed averaging, a substantial decrease in response times occurring between the first and second search through the same search environment is rarely discussed. This search initiation effect is often the most dramatic decrease in search times in a series of sequential searches. The nature of this initial lack of search efficiency has thus far remained unexplored. We tested the hypothesis that the activation of spatial priors leads to this search efficiency profile. Before searching repeatedly through scenes in VR, participants either (1) previewed the scene, (2) saw an interrupted preview, or (3) started searching immediately. The search initiation effect was present in the latter condition but in neither of the preview conditions. Eye movement metrics revealed that the locus of this effect lies in search guidance instead of search initiation or decision time, and was beyond effects of object learning or incidental memory. Our study suggests that upon visual processing of an environment, a process of activating spatial priors to enable orientation is initiated, which takes a toll on search time at first, but once activated it can be used to guide subsequent searches.
The ability to learn sequential contingencies of actions for predicting future outcomes is indispensable for flexible behavior in many daily decision-making contexts. It remains open whether such ability may be enhanced by transcranial direct current stimulation (tDCS). The present study combined tDCS with functional near-infrared spectroscopy (fNIRS) to investigate potential tDCS-induced effects on sequential decision-making and the neural mechanisms underlying such modulations. Offline tDCS and sham stimulation were applied over the left and right dorsolateral prefrontal cortex (dlPFC) in young male adults (N = 29, mean age = 23.4 years, SD = 3.2) in a double-blind between-subject design using a three-state Markov decision task. The results showed (i) an enhanced dlPFC hemodynamic response during the acquisition of sequential state transitions that is consistent with the findings from a previous functional magnetic resonance imaging (fMRI) study; (ii) a tDCS-induced increase of the hemodynamic response in the dlPFC, but without accompanying performance-enhancing effects at the behavioral level; and (iii) a greater tDCS-induced upregulation of hemodynamic responses in the delayed reward condition that seems to be associated with faster decision speed. Taken together, these findings provide empirical evidence for fNIRS as a suitable method for investigating hemodynamic correlates of sequential decision-making as well as functional brain correlates underlying tDCS-induced modulation. Future research with larger sample sizes for carrying out subgroup analysis is necessary in order to decipher interindividual differences in tDCS-induced effects on sequential decision-making process at the behavioral and brain levels.
Vom Boulevard bis zur seriösen Wochenzeitung, vom Lokalsender bis zu den öffentlich-rechtlichen – Mitte Juni ging eine Wissenschaftsnachricht aus der Goethe-Universität »viral«, die ein ernüchterndes Bild vom Distanzlernen in Pandemiezeiten zeichnete. Ein systematisches Review, das die Ergebnisse einzelner anderer Studien auswertete, hat ergeben, dass Kinder und Jugendliche im ersten Lockdown 2020 im Durchschnitt nicht nur weniger gelernt haben als im Präsenzunterricht, sondern dass ihre Leistungen teilweise auch zurückgegangen sind – »wie nach den Sommerferien«, beschrieb es Studienleiter Prof. Dr. Andreas Frey. Ein Interview mit dem Pädagogischen Psychologen über seine Untersuchungsergebnisse – und die Reaktionen darauf.
Diese Dissertation befasst sich mit Validierungsstrategien von Tests zur Erfassung studentischer Kompetenzen. Kompetenzen von Studierenden werden zu verschiedenen Zwecken erhoben. Dies beginnt beim Eintritt in das Studium durch Zulassungstests und wird im Studium fortgesetzt z.B. durch Tests zur Zertifizierung von Kompetenz (Benotung von Leistung) oder zur Zuteilung auf bestimmte Kurse (Einteilung in Sprachniveaus). Neben diesen internen Tests zur Erfassung studentischer Kompetenzen werden auch externe Tests genutzt um etwa die Lehre zu verbessern (Evaluation von Veranstaltungen). Die mit dem Einsatz von Tests verbundenen Konsequenzen können sowohl für Studierende als auch Lehrpersonen und Entscheidungsträger*innen schwerwiegend sein. Daher sollten Tests wissenschaftlichen Gütekriterien genügen.
Das wichtigste Kriterium für die Beurteilung von wissenschaftlichen Tests ist Validität. In dieser Dissertation wird ein argumentationsbasiertes Validierungsansatz verfolgt. In diesem wird nicht die Validität eines Tests untersucht, sondern die Plausibilität der Interpretation beurteilt, die mit den Testwerten verbunden ist. Bislang fehlt jedoch für viele der wissenschaftlichen Tests für den deutschen Hochschulbereich ein auf die Testwertinterpretation abgestimmtes Validitätskonzept.
In dieser Arbeit wird ein Validierungsschema vorgestellt, in das übliche Testnutzen der Erfassung studentischer Kompetenzen an deutschen Hochschulen eingeordnet werden können. Die Einordnung von Testnutzen in das Schema erlaubt die Ableitung von passenden Validitätsevidenzen. Im Fokus stehen das Verhältnis von Test zu 1) Konstrukt, 2) Lehre und 3) beruflichen Anforderungen.
Das Validierungsschema wird angewandt, um Testwertinterpretationen eines empirischen Forschungsprojektes zur Erfassung von Kompetenz in Nachhaltigkeitsmanagement bei Studierenden zu validieren. Der Schwerpunkt dieser Arbeit liegt auf der Validierung der Interpretation, dass die Testwerte von drei nachhaltigkeitsbezogenen Tests Indikatoren für hochschulisch vermittelte Kompetenz in Nachhaltigkeitsmanagement sind. Die Analysen zur Gewinnung von Validitätsevidenzen konzentrieren sich auf die Grundannahme, dass Lernfortschritte in den nachhaltigkeitsbezogenen Tests vorwiegend hochschulisch vermittelt werden. Dafür wurde ein Messwiederholungsdesign mit zwei Gruppen von Studierenden realisiert. Studierende in der Schwerpunktgruppe besuchten ein Semester lang eine reguläre Lehrveranstaltungen mit Bezug zu Nachhaltigkeitsthemen und Nachhaltigkeitsmanagement, Studierende der Kontrollgruppe besuchten keine solchen Lehrveranstaltung. Die Einteilung in Schwerpunkgruppe und Kontrollgruppe erfolgte über Analyse von Modulhandbüchern und verwendeten Lehrmaterialien. Die Ergebnisse zeigen, dass Studierende aus der Schwerpunktgruppe in zwei der drei Tests höhere Lernfortschritte zeigen als Studierende der Kontrollgruppe. Selbstberichte der Studierenden zu hochschulischen und außerhochschulischen Lerngelegenheiten lassen darauf schließen, dass Studierende der Schwerpunkgruppe auch außerhochschulisch ein höheres Interesse an Nachhaltigkeitsthemen zeigen, dies schlägt sich jedoch nicht in höherem Vorwissen in den verwendeten Tests nieder. Insgesamt wird daher für die zwei Tests mit höheren Lernfortschritten in der Schwerpunktgruppe die Interpretation als plausibel bewertet, dass die Testwerte hochschulisch vermittelte Kompetenz in Nachhaltigkeitsmanagement abbilden.
Aims: The purpose of this paper was to investigate the relationship between high-involvement human resource management, autonomy, affective organisational commitment and innovative behaviours of nursing staff who care for elderly clients.
Background: Nursing teams are increasingly required to demonstrate innovative behaviours that enhance care quality. Nursing leaders need to create environments where nursing staff have sufficient autonomy and feel a sense of commitment to support these behaviours. The appropriate implementation of these processes and practices may lead to greater involvement.
Methods: A cross-sectional survey-based research design was employed to explore the experiences of involvement practices, autonomy, affective organisational commitment and innovative behaviours of 567 nursing staff workers from four elderly care organisations in the Netherlands.
Results: The results demonstrate that a bundle of high-involvement practices positively influences innovative behaviour and that affective commitment and autonomy fully mediate this relationship.
Conclusions: The study highlights the role of autonomy and commitment as routes towards translating involvement practices into nurses’ innovativeness.
Implications for Nursing Management: To create an innovative environment, leaders need to create a positive climate by providing nurses with opportunities to enhance their competence, relatedness and autonomy through active involvement. Leaders should, therefore, encourage involvement as a mechanism to promote innovation.
This paper addresses the development of performance-based assessment items for ICT skills, skills in dealing with information and communication technologies, a construct which is rather broadly and only operationally defined. Item development followed a construct-driven approach to ensure that test scores could be interpreted as intended. Specifically, ICT-specific knowledge as well as problem-solving and the comprehension of text and graphics were defined as components of ICT skills and cognitive ICT tasks (i.e., accessing, managing, integrating, evaluating, creating). In order to capture the construct in a valid way, design principles for constructing the simulation environment and response format were formulated. To empirically evaluate the very heterogeneous items and detect malfunctioning items, item difficulties were analyzed and behavior-related indicators with item-specific thresholds were developed and applied. The 69 item’s difficulty scores from the Rasch model fell within a comparable range for each cognitive task. Process indicators addressing time use and test-taker interactions were used to analyze whether most test-takers executed the intended processes, exhibited disengagement, or got lost among the items. Most items were capable of eliciting the intended behavior; for the few exceptions, conclusions for item revisions were drawn. The results affirm the utility of the proposed framework for developing and implementing performance-based items to assess ICT skills.
Several psychotherapy treatments exist for posttraumatic stress disorder. This study examines the treatment preferences of treatment-seeking traumatized adults in Germany and investigates the reasons for their treatment choices. Preferences for prolonged exposure, cognitive behavioral therapy (CBT), eye movement desensitization and reprocessing (EMDR), psychodynamic psychotherapy and stabilization were assessed via an online survey. Reasons for preferences were analyzed by means of thematic coding by two independent rates. 104 traumatized adults completed the survey. Prolonged exposure and CBT were each preferred by nearly 30%, and EMDR and psychodynamic psychotherapy were preferred by nearly 20%. Stabilization was significantly less preferred than all other options, by only 4%. Significantly higher proportions of patients were disinclined to choose EMDR and stabilization. Patients who preferred psychodynamic psychotherapy were significantly older than those who preferred CBT. Reasons underlying preferences included the perceived treatment mechanisms and treatment efficacy. Traumatized patients vary in their treatment preferences. Preference assessments may help clinicians comprehensively address patients' individual needs and thus improve therapy outcomes.
Treatment outcomes of a CBT-based group intervention for adolescents with internet use disorders
(2021)
Background and aims: Instances of Internet use disorders (IUD) including Internet gaming disorder (IGD) and non-gaming pathological Internet use (ng-PIU) have the extent that they are now a growing mental health issue. Individuals suffering from IUD show a large range of symptoms, high comorbidities and impairments in different areas of life. To date there is a lack of efficient and evidence-based treatment programs for such adolescents. The present registered single-arm trial (ClinicalTrials.gov: NCT03582839) aimed to investigate the long-term effects of a brief manualized cognitive behavioral therapy (CBT) program for adolescents with IUD. Methods: N = 54 patients (16.7% female), aged 9–19 years (M = 13.48, SD = 1.72) received the CBT group program PROTECT+. IUD symptom severity (primary outcome variable) as well as comorbid symptoms, risk-related variables and potentially protective skills (secondary outcome variables) were assessed at pretest, posttest, as well as 4 and 12 months after admission. Results: Patients showed a significant reduction in IUD symptom severity at the 12-month follow-up. Effect sizes were medium to large depending on the measure. Beyond the statistical significance, the clinical significance was confirmed using the reliable change index. Secondary outcome variables showed a significant reduction in self-reported depression, social anxiety, performance anxiety and school anxiety as well as in parental-reported general psychopathology. Discussion and conclusions: The present study shows long-term effects of a manual-based CBT treatment for adolescents suffering from IUD. The results indicate that even a 4-session brief intervention can achieve a medium to large effect over 12 months. Future work is needed to confirm the efficacy within a randomized controlled trial (RCT).
Visual working memory (VWM) is reliably predictive of fluid intelligence and academic achievements. The objective of the current study was to investigate individual differences in pre-schoolers’ VWM processing by examining the association between behaviour, brain function and parent-reported measures related to the child's environment. We used a portable functional near-infrared spectroscopy system to record from the frontal and parietal cortices of 4.5-year-old children (N = 74) as they completed a colour change-detection VWM task in their homes. Parents were asked to fill in questionnaires on temperament, academic aspirations, home environment and life stress. Children were median-split into a low-performing (LP) and a high-performing (HP) group based on the number of items they could successfully remember during the task. LPs increasingly activated channels in the left frontal and bilateral parietal cortices with increasing load, whereas HPs showed no difference in activation. Our findings suggest that LPs recruited more neural resources than HPs when their VWM capacity was challenged. We employed mediation analyses to examine the association between the difference in activation between the highest and lowest loads and variables from the questionnaires. The difference in activation between loads in the left parietal cortex partially mediated the association between parent-reported stressful life events and VWM performance. Critically, our findings show that the association between VWM capacity, left parietal activation and indicators of life stress is important to understand the nature of individual differences in VWM in pre-school children.
Visual search in natural scenes is a complex task relying on peripheral vision to detect potential targets and central vision to verify them. The segregation of the visual fields has been particularly established by on-screen experiments. We conducted a gaze-contingent experiment in virtual reality in order to test how the perceived roles of central and peripheral visions translated to more natural settings. The use of everyday scenes in virtual reality allowed us to study visual attention by implementing a fairly ecological protocol that cannot be implemented in the real world. Central or peripheral vision was masked during visual search, with target objects selected according to scene semantic rules. Analyzing the resulting search behavior, we found that target objects that were not spatially constrained to a probable location within the scene impacted search measures negatively. Our results diverge from on-screen studies in that search performances were only slightly affected by central vision loss. In particular, a central mask did not impact verification times when the target was grammatically constrained to an anchor object. Our findings demonstrates that the role of central vision (up to 6 degrees of eccentricities) in identifying objects in natural scenes seems to be minor, while the role of peripheral preprocessing of targets in immersive real-world searches may have been underestimated by on-screen experiments.
Innovative ideas are essential to sustainable development. Students’ innovative potential in higher education for sustainable development (HESD) has so far been neglected. Innovation is often associated with an interdisciplinary approach. However, the results of research on diversity and its role in innovation are inconsistent. The present study takes a longitudinal approach to investigating student teams in project-based learning courses in HESD in Germany. This study examines how innovation develops in interdisciplinary student teams in contrast to monodisciplinary student teams. The results of the latent change approach from a sample of 69 student teams indicate significant changes in students’ innovation over time. Monodisciplinary student teams outperform interdisciplinary student teams in idea promotion (convincing potential allies) at the beginning, whereas interdisciplinary student teams outperform monodisciplinary student teams in idea generation (production of novel and useful ideas) in the midterm. There is no difference in the long term. The results indicate that interdisciplinary student teams have an advantage in the generation of novel ideas but need time to leverage their access to different discipline-based knowledge. We discuss practical implications for the design of interdisciplinary learning with strategies to support students in the formation phase in project-based learning in HESD.
Background: Abnormalities of heart rate (HR) and its variability are characteristic of major depressive disorder (MDD). However, circadian rhythm is rarely taken into account when statistically exploring state or trait markers for depression. Methods: A 4-day electrocardiogram was recorded for 16 treatment-resistant patients with MDD and 16 age- and sex-matched controls before, and for the patient group only, after a single treatment with the rapid-acting antidepressant ketamine or placebo (clinical trial registration available on https://www.clinicaltrialsregister.eu/ with EUDRACT number 2016-001715-21). Circadian rhythm differences of HR and the root mean square of successive differences (RMSSD) were compared between groups and were explored for classification purposes. Baseline HR/RMSSD were tested as predictors for treatment response, and physiological measures were assessed as state markers. Results: Patients showed higher HR and lower RMSSD alongside marked reductions in HR amplitude and RMSSD variation throughout the day. Excellent classification accuracy was achieved using HR during the night, particularly between 2 and 3 a.m. (90.6%). A positive association between baseline HR and treatment response (r = 0.55, p = 0.046) pointed toward better treatment outcome in patients with higher HR. Heart rate also decreased significantly following treatment but was not associated with improved mood after a single infusion of ketamine. Limitations: Our study had a limited sample size, and patients were treated with concomitant antidepressant medication. Conclusion: Patients with depression show a markedly reduced amplitude for HR and dysregulated RMSSD fluctuation. Higher HR and lower RMSSD in depression remain intact throughout a 24-h day, with the highest classification accuracy during the night. Baseline HR levels show potential for treatment response prediction but did not show potential as state markers in this study.
From age 5 to 7, there are remarkable improvements in children’s cognitive abilities (“5–7 shift”). In many countries, including Germany, formal schooling begins in this age range. It is, thus, unclear to what extent exposure to formal schooling contributes to the “5–7 shift.” In this longitudinal study, we investigated if schooling acts as a catalyst of maturation. We tested 5-year-old children who were born close to the official cutoff date for school entry and who were still attending a play-oriented kindergarten. One year later, the children were tested again. Some of the children had experienced their first year of schooling whereas the others had remained in kindergarten. Using 2 functional magnetic resonance imaging tasks that assessed episodic memory formation (i.e., subsequent memory effect), we found that children relied strongly on the medial temporal lobe (MTL) at both time points but not on the prefrontal cortex (PFC). In contrast, older children and adults typically show subsequent memory effects in both MTL and PFC. Both children groups improved in their memory performance, but there were no longitudinal changes nor group differences in neural activation. We conclude that successful memory formation in this age group relies more heavily on the MTL than in older age groups.
To a crucial extent, the efficiency of reading results from the fact that visual word recognition is faster in predictive contexts. Predictive coding models suggest that this facilitation results from pre-activation of predictable stimulus features across multiple representational levels before stimulus onset. Still, it is not sufficiently understood which aspects of the rich set of linguistic representations that are activated during reading – visual, orthographic, phonological, and/or lexical-semantic – contribute to context-dependent facilitation. To investigate in detail which linguistic representations are pre-activated in a predictive context and how they affect subsequent stimulus processing, we combined a well-controlled repetition priming paradigm, including words and pseudowords (i.e., pronounceable nonwords), with behavioral and magnetoencephalography measurements. For statistical analysis, we used linear mixed modeling, which we found had a higher statistical power compared to conventional multivariate pattern decoding analysis. Behavioral data from 49 participants indicate that word predictability (i.e., context present vs. absent) facilitated orthographic and lexical-semantic, but not visual or phonological processes. Magnetoencephalography data from 38 participants show sustained activation of orthographic and lexical-semantic representations in the interval before processing the predicted stimulus, suggesting selective pre-activation at multiple levels of linguistic representation as proposed by predictive coding. However, we found more robust lexical-semantic representations when processing predictable in contrast to unpredictable letter strings, and pre-activation effects mainly resembled brain responses elicited when processing the expected letter string. This finding suggests that pre-activation did not result in ‘explaining away’ predictable stimulus features, but rather in a ‘sharpening’ of brain responses involved in word processing.
Probing the association between resting state brain network dynamics and psychological resilience
(2021)
Abstract
This study aimed at replicating a previously reported negative correlation between node flexibility and psychological resilience, i.e., the ability to retain mental health in the face of stress and adversity. To this end, we used multiband resting-state BOLD fMRI (TR = .675 sec) from 52 participants who had filled out three psychological questionnaires assessing resilience. Time-resolved functional connectivity was calculated by performing a sliding window approach on averaged time series parcellated according to different established atlases. Multilayer modularity detection was performed to track network reconfigurations over time and node flexibility was calculated as the number of times a node changes community assignment. In addition, node promiscuity (the fraction of communities a node participates in) and node degree (as proxy for time-varying connectivity) were calculated to extend previous work. We found no substantial correlations between resilience and node flexibility. We observed a small number of correlations between the two other brain measures and resilience scores, that were however very inconsistently distributed across brain measures, differences in temporal sampling, and parcellation schemes. This heterogeneity calls into question the existence of previously postulated associations between resilience and brain network flexibility and highlights how results may be influenced by specific analysis choices.
Author Summary We tested the replicability and generalizability of a previously proposed negative association between dynamic brain network reconfigurations derived from multilayer modularity detection (node flexibility) and psychological resilience. Using multiband resting-state BOLD fMRI data and exploring several parcellation schemes, sliding window approaches, and temporal resolutions of the data, we could not replicate previously reported findings regarding the association between node flexibility and resilience. By extending this work to other measures of brain dynamics (node promiscuity, degree) we observe a rather inconsistent pattern of correlations with resilience, that strongly varies across analysis choices. We conclude that further research is needed to understand the network neuroscience basis of mental health and discuss several reasons that may account for the variability in results.
In the COVID-19 pandemic, human solidarity plays a crucial role in meeting this maybe greatest modern societal challenge. Public health communication targets enhancing collective compliance with protective health and safety regulations. Here, we asked whether authoritarian/controlling message framing as compared to a neutral message framing may be more effective than moralizing/prosocial message framing and whether recipients’ self-rated trait autonomy might lessen these effects. In a German sample (n = 708), we measured approval of seven regulations (e.g., reducing contact, wearing a mask) before and after presenting one of three Twitter messages (authoritarian, moralizing, neutral/control) presented by either a high-authority sender (state secretary) or a low-authority sender (social worker). We found that overall, the messages successfully increased participants’ endorsement of the regulations, but only weakly so because of ceiling effects. Highly autonomous participants showed more consistent responses across the two measurements, i.e., lower response shifting, in line with the concept of reactive autonomy. Specifically, when the sender was a social worker, response shifting correlated negatively with trait autonomy. We suggest that a trusted sender encourages more variable responses to imposed societal regulations in individuals low in autonomy, and we discuss several aspects that may improve health communication.
Many cross-sectional findings suggest that volumes of specific hippocampal subfields increase in middle childhood and early adolescence. In contrast, a small number of available longitudinal studies observed decreased volumes in most subfields over this age range. Further, it remains unknown whether structural changes in development are associated with corresponding gains in children’s memory. Here we report cross-sectional age differences in children’s hippocampal subfield volumes together with longitudinal developmental trajectories and their relationships with memory performance. In two waves, 109 healthy participants aged 6 to 10 years (wave 1: MAge=7.25, wave 2: MAge=9.27) underwent high-resolution magnetic resonance imaging to assess hippocampal subfield volumes, and completed cognitive tasks assessing hippocampus dependent memory processes. We found that cross-sectional age-associations and longitudinal developmental trends in hippocampal subfield volumes were highly discrepant, both by subfields and in direction. Further, volumetric changes were largely unrelated to changes in memory, with the exception that increase in subiculum volume was associated with gains in spatial memory. Importantly, the observed longitudinal patterns of brain-cognition coupling could not be inferred from cross-sectional findings. We discuss potential sources of these discrepancies. This study underscores that children’s structural brain development and its relationship to cognition cannot be inferred from cross-sectional age comparisons.
Highlights
The subiculum undergoes volumetric increase between 6-10 years of age
Change across two years in CA1-2 and DG-CA3 was not observed in this age window
Change across two years did not reflect age differences spanning two years
Cross-sectional and longitudinal slopes in stark contrast for hippocampal subfields
Longitudinal brain-cognition coupling cannot be inferred from cross-sectional data
Across languages, the speech signal is characterized by a predominant modulation of the amplitude spectrum between about 4.3-5.5Hz, reflecting the production and processing of linguistic information chunks (syllables, words) every ∼200ms. Interestingly, ∼200ms is also the typical duration of eye fixations during reading. Prompted by this observation, we demonstrate that German readers sample written text at ∼5Hz. A subsequent meta-analysis with 142 studies from 14 languages replicates this result, but also shows that sampling frequencies vary across languages between 3.9Hz and 5.2Hz, and that this variation systematically depends on the complexity of the writing systems (character-based vs. alphabetic systems, orthographic transparency). Finally, we demonstrate empirically a positive correlation between speech spectrum and eye-movement sampling in low-skilled readers. Based on this convergent evidence, we propose that during reading, our brain’s linguistic processing systems imprint a preferred processing rate, i.e., the rate of spoken language production and perception, onto the oculomotor system.
Theoretischer Hintergrund: Für die Behandlung der Posttraumatischen Belastungsstörung (PTBS) im Jugend- und jungen Erwachsenenalter liegen diverse evidenzbasierte Interventionen (EBIs) vor. Fragestellung: Inwiefern sind EBIs für Jugendliche und junge Erwachsene mit PTBS nach sexualisierter und physischer Gewalt in Deutschland verfügbar? Methode: Es wurden die Daten von 39 Teilnehmenden einer multizentrischen Behandlungsstudie analysiert, die für die Diagnose einer PTBS ambulante Behandlungsempfehlungen erhalten hatten. Ergebnisse: In den folgenden sieben Monaten erhielten 21 der Teilnehmenden eine Behandlung; bei nur acht wurden in deren Rahmen die traumatischen Erfahrungen adressiert. Alle Teilnehmenden verbesserten sich hinsichtlich der PTBS-Symptomatik unabhängig von der Art der Behandlung. Diskussion und Schlussfolgerung: Die Ergebnisse weisen auf Barrieren für den Zugang zu EBIs in unserer Stichprobe hin. Künftige Forschung sollte die Hintergründe für diese Barrieren fokussieren.
Estimating power in (generalized) linear mixed models: An open introduction and tutorial in R
(2021)
Mixed-effects models are a powerful tool for modeling fixed and random effects simultaneously, but do not offer a feasible analytic solution for estimating the probability that a test correctly rejects the null hypothesis. Being able to estimate this probability, however, is critical for sample size planning, as power is closely linked to the reliability and replicability of empirical findings. A flexible and very intuitive alternative to analytic power solutions are simulation-based power analyses. Although various tools for conducting simulation-based power analyses for mixed-effects models are available, there is lack of guidance on how to appropriately use them. In this tutorial, we discuss how to estimate power for mixed-effects models in different use cases: first, how to use models that were fit on available (e.g. published) data to determine sample size; second, how to determine the number of stimuli required for sufficient power; and finally, how to conduct sample size planning without available data. Our examples cover both linear and generalized linear models and we provide code and resources for performing simulation-based power analyses on openly accessible data sets. The present work therefore helps researchers to navigate sound research design when using mixed-effects models, by summarizing resources, collating available knowledge, providing solutions and tools, and applying them to real-world problems in sample sizing planning when sophisticated analysis procedures like mixed-effects models are outlined as inferential procedures.
Research has suggested that teachers’ beliefs toward culturally diverse classrooms are affected during teacher education. Text reading, as one of the major learning activities in initial teacher education, is supposed to affect teachers’ educational concepts and beliefs. We conducted two experiments to test the impact of reading a positively or negatively oriented persuasive text about diversity on preservice teachers’ belief change. In Study 1 (N = 42), we found that belief change varied significantly as a function of the direction of the text condition, and that the reading of the texts led to a significantly stronger belief change if the text was in alignment with participants’ prior beliefs. Study 2 (N = 57) revealed a middle-sized but non-significant moderator effect for prior knowledge (p = .08, η2p = .06), suggesting that participants with more prior knowledge were less likely to be persuaded by the text. The results provide new insights into factors that may affect the development of preservice teachers’ diversity beliefs.
Pathophysiological models are urgently needed for personalized treatments of mental disorders. However, most potential neural markers for psychopathology are limited by low interpretability, prohibiting reverse inference from brain measures to clinical symptoms and traits. Neural signatures—i.e. multivariate brain-patterns trained to be both sensitive and specific to a construct of interest—might alleviate this problem, but are rarely applied to mental disorders. We tested whether previously developed neural signatures for negative affect and discrete emotions distinguish between healthy individuals and those with mental disorders characterized by emotion dysregulation, i.e. Borderline Personality Disorder (BPD) and complex Post-traumatic Stress Disorder (cPTSD). In three different fMRI studies, a total sample of 192 women (49 BPD, 62 cPTSD, 81 healthy controls) were shown pictures of scenes with negative or neutral content. Based on pathophysiological models, we hypothesized higher negative and lower positive reactivity of neural emotion signatures in participants with emotion dysregulation. The expression of neural signatures differed strongly between neutral and negative pictures (average Cohen's d = 1.17). Nevertheless, a mega-analysis on individual participant data showed no differences in the reactivity of neural signatures between participants with and without emotion dysregulation. Confidence intervals ruled out even small effect sizes in the hypothesized direction and were further supported by Bayes factors. Overall, these results support the validity of neural signatures for emotional states during fMRI tasks, but raise important questions concerning their link to individual differences in emotion dysregulation.
Pathophysiological models are urgently needed for personalized treatments of mental disorders. However, most potential neural markers for psychopathology are limited by low interpretability, prohibiting reverse inference from brain measures to clinical symptoms and traits. Neural signatures—i.e. multivariate brain-patterns trained to be both sensitive and specific to a construct of interest—might alleviate this problem, but are rarely applied to mental disorders. We tested whether previously developed neural signatures for negative affect and discrete emotions distinguish between healthy individuals and those with mental disorders characterized by emotion dysregulation, i.e. Borderline Personality Disorder (BPD) and complex Post-traumatic Stress Disorder (cPTSD). In three different fMRI studies, a total sample of 192 women (49 BPD, 62 cPTSD, 81 healthy controls) were shown pictures of scenes with negative or neutral content. Based on pathophysiological models, we hypothesized higher negative and lower positive reactivity of neural emotion signatures in participants with emotion dysregulation. The expression of neural signatures differed strongly between neutral and negative pictures (average Cohen’s d = 1.17). Nevertheless, a mega-analysis on individual participant data showed no differences in the reactivity of neural signatures between participants with and without emotion dysregulation. Confidence intervals ruled out even small effect sizes in the hypothesized direction and were further supported by Bayes factors. Overall, these results support the validity of neural signatures for emotional states during fMRI tasks, but raise important questions concerning their link to individual differences in emotion dysregulation.
To a crucial extent, the efficiency of reading results from the fact that visual word recognition is faster in predictive contexts. Predictive coding models suggest that this facilitation results from pre-activation of predictable stimulus features across multiple representational levels before stimulus onset. Still, it is not sufficiently understood which aspects of the rich set of linguistic representations that are activated during reading—visual, orthographic, phonological, and/or lexical-semantic—contribute to context-dependent facilitation. To investigate in detail which linguistic representations are pre-activated in a predictive context and how they affect subsequent stimulus processing, we combined a well-controlled repetition priming paradigm, including words and pseudowords (i.e., pronounceable nonwords), with behavioral and magnetoencephalography measurements. For statistical analysis, we used linear mixed modeling, which we found had a higher statistical power compared to conventional multivariate pattern decoding analysis. Behavioral data from 49 participants indicate that word predictability (i.e., context present vs. absent) facilitated orthographic and lexical-semantic, but not visual or phonological processes. Magnetoencephalography data from 38 participants show sustained activation of orthographic and lexical-semantic representations in the interval before processing the predicted stimulus, suggesting selective pre-activation at multiple levels of linguistic representation as proposed by predictive coding. However, we found more robust lexical-semantic representations when processing predictable in contrast to unpredictable letter strings, and pre-activation effects mainly resembled brain responses elicited when processing the expected letter string. This finding suggests that pre-activation did not result in “explaining away” predictable stimulus features, but rather in a “sharpening” of brain responses involved in word processing.
The COVID-19 pandemic and resulting measures can be regarded as a global stressor. Cross-sectional studies showed rather negative impacts on people’s mental health, while longitudinal studies considering pre-lockdown data are still scarce. The present study investigated the impact of COVID-19 related lockdown measures in a longitudinal German sample, assessed since 2017. During lockdown, 523 participants completed additional weekly online questionnaires on e.g., mental health, COVID-19-related and general stressor exposure. Predictors for and distinct trajectories of mental health outcomes were determined, using multilevel models and latent growth mixture models, respectively. Positive pandemic appraisal, social support, and adaptive cognitive emotion regulation were positively, whereas perceived stress, daily hassles, and feeling lonely negatively related to mental health outcomes in the entire sample. Three subgroups (“recovered,” 9.0%; “resilient,” 82.6%; “delayed dysfunction,” 8.4%) with different mental health responses to initial lockdown measures were identified. Subgroups differed in perceived stress and COVID-19-specific positive appraisal. Although most participants remained mentally healthy, as observed in the resilient group, we also observed inter-individual differences. Participants’ psychological state deteriorated over time in the delayed dysfunction group, putting them at risk for mental disorder development. Consequently, health services should especially identify and allocate resources to vulnerable individuals.
Aim: There is ongoing debate about the role of cortical and subcortical brain areas in force modulation. In a whole-brain approach, we sought to investigate the anatomical basis of grip force whilst acknowledging interindividual differences in connectivity patterns. We tested if brain lesion mapping in patients with unilateral motor deficits can inform whole-brain structural connectivity analysis in healthy controls to uncover the networks underlying grip force.
Methods: Using magnetic resonance imaging (MRI) and whole-brain voxel-based morphometry in chronic stroke patients (n=55) and healthy controls (n=67), we identified the brain regions in both grey and white matter significantly associated with grip force strength. The resulting statistical parametric maps (SPMs) provided seed areas for whole-brain structural covariance analysis in a large-scale community dwelling cohort (n=977) that included beyond volume estimates, parameter maps sensitive to myelin, iron and tissue water content.
Results: The SPMs showed symmetrical bilateral clusters of correlation between upper limb motor performance, basal ganglia, posterior insula and cortico-spinal tract. The covariance analysis with the seed areas derived from the SPMs demonstrated a widespread anatomical pattern of brain volume and tissue properties, including both cortical, subcortical nodes of motor networks and sensorimotor areas projections.
Conclusion: We interpret our covariance findings as a biological signature of brain networks implicated in grip force. The data-driven definition of seed areas obtained from chronic stroke patients showed overlapping structural covariance patterns within cortico-subcortical motor networks across different tissue property estimates. This cumulative evidence lends face validity of our findings and their biological plausibility.
The social identity approach to stress proposes that the beneficial effects of social identification develop through individual and group processes, but few studies have addressed both levels simultaneously. Using a multilevel person–environment fit framework, we investigate the group-level relationship between team identification (TI) and exhaustion, the individual-level relationship for people within a group, and the cross-level moderation effect to test whether individual-level exhaustion depends on the level of (in)congruence in TI between individuals and their group as a whole. We test our hypotheses in a sample of 525 employees from 82 teams. Multilevel polynomial regression analysis revealed a negative linear relationship between individual-level identification and exhaustion. Surprisingly, the relation between group-level identification and exhaustion was curvilinear, indicating that group-level identification was more beneficial at low and high levels compared with medium levels. As predicted, the cross-level moderation of the individual-level relationship by group-level identification was also significant, showing that as individuals became more incongruent in a positive direction (i.e., they identified more strongly than the average team member), they reported less exhaustion, but only if the group-level identification was average or high. These results emphasize the benefits of analyzing TI in a multilevel framework, with both theoretical and practical implications.
Finding a bottle of milk in the bathroom would probably be quite surprising to most of us. Such a surprised reaction is driven by our strong expectations, learned through experience, that a bottle of milk belongs in the kitchen. Our environment is not randomly organized but governed by regularities that allow us to predict what objects can be found in which types of scene. These scene semantics are thought to play an important role in the recognition of objects. But when during development are the semantic predictions so far implemented that such scene-object inconsistencies would lead to semantic processing difficulties? Here we investigated how toddlers perceive their environments, and what expectations govern their attention and perception. To this aim, we used a purely visual paradigm in an ERP experiment and presented 24-month-olds with familiar scenes in which either a semantically consistent or an inconsistent object would appear. The scene-inconsistency effect has been previously studied in adults by means of the N400, a neural marker responding to semantic inconsistencies across many types of stimuli. Our results show that semantic object-scene inconsistencies indeed elicited an enhanced N400 over the left anterior brain region between 750 and 1150 ms post stimulus onset. This modulation of the N400 marker provides first indications that by the age of two toddlers have already established their scene semantics allowing them to detect a purely visual, semantic object-scene inconsistency. Our data suggest the presence of specific semantic knowledge regarding what objects occur in a certain scene category.
Children with reading and/or spelling disorders have increased rates of behavioral and emotional problems and combinations of these. Some studies also find increased rates of attention-deficit/hyperactivity disorder (ADHD), conduct disorder, anxiety disorder, and depression. However, the comorbidities of, e.g., arithmetic disorders with ADHD, anxiety disorder, and depression have been addressed only rarely. The current study explored the probability of children with specific learning disorders (SLD) in reading, spelling, and/or arithmetic to also have anxiety disorder, depression, ADHD, and/or conduct disorder. The sample consisted of 3,014 German children from grades 3 and 4 (mean age 9;9 years) who completed tests assessing reading, spelling as well as arithmetic achievement and intelligence via a web-based application. Psychopathology was assessed using questionnaires filled in by the parents. In children with a SLD we found high rates of anxiety disorder (21%), depression (28%), ADHD (28%), and conduct disorder (22%). Children with SLD in multiple learning domains had a higher risk for psychopathology and had a broader spectrum of psychopathology than children with an isolated SLD. The results highlight the importance of screening for and diagnosing psychiatric comorbidities in children with SLD.
Central and peripheral fields of view extract information of different quality and serve different roles during visual tasks. Past research has studied this dichotomy on-screen in conditions remote from natural situations where the scene would be omnidirectional and the entire field of view could be of use. In this study, we had participants looking for objects in simulated everyday rooms in virtual reality. By implementing a gaze-contingent protocol we masked central or peripheral vision (masks of 6 deg. of radius) during trials. We analyzed the impact of vision loss on visuo-motor variables related to fixation (duration) and saccades (amplitude and relative directions). An important novelty is that we segregated eye, head and the general gaze movements in our analyses. Additionally, we studied these measures after separating trials into two search phases (scanning and verification). Our results generally replicate past on-screen literature and teach about the role of eye and head movements. We showed that the scanning phase is dominated by short fixations and long saccades to explore, and the verification phase by long fixations and short saccades to analyze. One finding indicates that eye movements are strongly driven by visual stimulation, while head movements serve a higher behavioral goal of exploring omnidirectional scenes. Moreover, losing central vision has a smaller impact than reported on-screen, hinting at the importance of peripheral scene processing for visual search with an extended field of view. Our findings provide more information concerning how knowledge gathered on-screen may transfer to more natural conditions, and attest to the experimental usefulness of eye tracking in virtual reality.
The paper reports an investigation on whether valid results can be achieved in analyzing the structure of datasets although a large percentage of data is missing without replacement. Two types of confirmatory factor analysis (CFA) models were employed for this purpose: the missing data CFA model with an additional latent variable for representing the missing data and the semi-hierarchical CFA model that also includes the additional latent variable and reflects the hierarchical structure assumed to underlie the data. Whereas, the missing data CFA model assumes that the model is equally valid for all participants, the semi-hierarchical CFA model is implicitly specified differently for subgroups of participants with and without omissions. The comparison of these models with the regular one-factor model in investigating simulated binary data revealed that the modeling of missing data prevented negative effects of missing data on model fit. The investigation of the accuracy in estimating the factor loadings yielded the best results for the semi-hierarchical CFA model. The average estimated factor loadings for items with and without omissions showed the expected equal sizes. But even this model tended to underestimate the expected values.
In the present paper, we tested the ability of individuals to judge correctly whether athletes are lying or telling the truth. For this purpose, we first generated 28 videos as stimulus material: in half of the videos, soccer players were telling the truth, while in the other half, the same soccer players were lying. Next, we tested the validity of these video clips by asking N = 65 individuals in a laboratory experiment (Study 1a) and N = 52 individuals in an online experiment (Study 1b) to rate the level of veracity of each video clip. Results suggest that participants can distinguish between true and false statements, but only for some clips and not for others, indicating that some players were better at deceiving than others. In Study 2, participants again had to make veracity estimations, but we manipulated the level of information given, as participants (N = 145) were randomly assigned to one of three conditions (regular video clips, mute video clips, and only the audio stream of each statement). The results revealed that participants from the mute condition were less accurate in their veracity ratings. The theoretical and practical implications of these findings are discussed.
This article reports an investigation of how inhibition contributes to fluid reasoning when it is decomposed into the reasoning ability, item-position, and speed components to control for possible method effects. Working memory was also taken into consideration. A sample of 223 university students completed a fluid reasoning scale, two tasks tapping prepotent response inhibition, and two working memory tasks. Fixed-links modeling was used to separate the effect of reasoning ability from the effects of item-position and speed. The goodness-of-fit results confirmed the necessity to consider the reasoning ability, item-position, and speed components simultaneously. Prepotent response inhibition was only associated with reasoning ability. This association disappeared when working memory served as a mediator. Taken together, these results reflect the inhomogeneity of what is tapped by the fluid reasoning scale on one hand and, on the other, suggest inhibition as an important component of working memory.
Das Projekt »Digi_Gap – Digitale Lücken in der Lehrkräftebildung schließen« wird von 2020 bis 2023 vom Bundesministerium für Bildung und Forschung im Rahmen der Qualitätsoffensive Lehrerbildung (QLB) gefördert (Fördersumme: 1 678 023 Euro) und umfasst fünf Teilprojekte mit 19 WissenschaftlerInnen aus neun Fachbereichen an der Goethe-Universität. Geleitet wird das Projekt von Prof. Dr. Holger Horz (wissenschaftliche Gesamtprojektleitung) und Dr. Claudia Burger (operative Leitung). An der Goethe-Universität ebenfalls durch die QLB gefördert wird »The Next Level«, das Nachfolgeprojekt von »Level« (»Lehrerbildung vernetzt entwickeln)«, mit dem Digi_Gap inhaltlich und strukturell eng verbunden ist. Das Leitungs- und Koordinationsteam (Leitung: Holger Horz & Claudia Burger; Koordination: Johannes Appel und Annika Kreft) von Digi_Gap hat sich den Fragen des UniReport auch zum aktuellen Thema »Homeschooling« gestellt.
This study examined age‐related differences in the effectiveness of two generative learning strategies (GLSs). Twenty‐five children aged 9–11 and 25 university students aged 17–29 performed a facts learning task in which they had to generate either a prediction or an example before seeing the correct result. We found a significant Age × Learning Strategy interaction, with children remembering more facts after generating predictions rather than examples, whereas both strategies were similarly effective in adults. Pupillary data indicated that predictions stimulated surprise, whereas the effectiveness of example‐based learning correlated with children’s analogical reasoning abilities. These findings suggest that there are different cognitive prerequisites for different GLSs, which results in varying degrees of strategy effectiveness by age.
Dopaminerge Neurone sind vor allem im Mittelhirn lokalisiert und modulieren die Funktion der Basalganglien, welche eine wichtige Rolle bei motorischem, kognitivem und emotionalem Verhalten spielen. Eine Dysregulation dopaminerger Neurotransmission, speziell die veränderte Belohnungsverarbeitung, spielt eine zentrale Rolle in der Ätiopathogenese der Aufmerksamkeitsdefizit- und Hyperaktivitätsstörung (ADHS), die im Erwachsenenalter häufig durch Komorbiditäten wie affektive Störungen, Angststörungen, Substanzgebrauch-Störungen, Persönlichkeitsstörungen oder Adipositas geprägt ist. Im Rahmen einer Teilstudie eines multizentrischen europäischen Projekts, CoCA (englisch: Comorbid Conditions in ADHD) genannt, soll die Modulation des dopaminergen Belohnungssystems bei gesunden Probanden durch einen pharmakologischen Provokationstest geprüft werden. Die funktionelle Magnetresonanztomographie (MRT) stellt hierbei ein nützliches bildgebendes Verfahren dar, das nicht-invasiv und bei hoher örtlicher Auflösung Veränderungen des sogenannten BOLD-Signals (englisch: blood oxygen level dependent) misst.
Die vorliegende Arbeit untersucht, inwiefern das dopaminerge Belohnungssystem durch einen pharmakologischen Provokationstest mit einem Dopaminagonisten sowie einem Dopaminantagonisten im Vergleich zu Placebo zu modulieren ist. Dazu wurde die BOLD-Antwort mittels funktionellem MRT während eines Gewinnspiels (Monetary Incentive Delay Tasks) mit inbegriffener Antizipations- und Feedback-Phase erforscht. Es wurde zuvor postuliert, dass sich die Aktivität belohnungsabhängiger Strukturen (wie ventrales Striatum, Putamen, Caudatus, anteriore Insula und medialer präfrontaler Kortex) während des Monetary Incentive Delay Tasks in einem pharmakologisch neutralen Haupteffekt reproduzieren lässt. Außerdem wurde ein Unterschied im Aktivitätsniveau des Belohnungssystems unter Pharmaka-Administration versus Placebo erwartet, sodass unter Amisulprid eine Dämpfung, und unter Levodopa eine Aktivitätssteigerung dessen darstellbar werden sollte.
Ein kontrolliert randomisiertes, doppelblindes Cross-over-Studiendesign, umfasste 45 gesunde Probanden, die durchschnittlich circa 23 Jahre alt (SD = 2,71 Jahre) waren. Die Studienteilnehmer absolvierten einen pharmakologischen Provokationstest mit Levodopa (100mg/ 25mg Carbidopa), Amisulprid (200mg) und Placebo sowie anschließender fMRT-Messung in einem 3 Tesla Scanner in randomisierter Reihenfolge. Die Analyse der fMRT-Daten erfolgte anhand von zwei primär definierten Kontrasten: Antizipation Gewinnbedingung > Feedback Gewinnbedingung und Antizipation Gewinnbedingung > Antizipation Kontrollbedingung zur Untersuchung von Belohnungserwartung und Feedback mittels der gemessenen BOLD-Antworten. Das verwendete GewinnspielParadigma, Monetary Incentive Delay Task genannt, erlaubt hierbei eine Beobachtung verschiedener Anteile der Belohnungsverarbeitung.
Im Haupteffekt der beiden Kontraste konnte eine signifikante BOLD-Aktivität in belohnungsabhängigen Gehirnregionen wie Putamen, anteriore Insula und Thalamus dargestellt werden. Unter Amisulprid-Administration konnte ein signifikanter dämpfender Effekt im Vergleich zu Placebo gezeigt werden. Für Levodopa ergab sich wider Erwarten jedoch kein signifikanter Unterschied im Aktivitätsniveau des Belohnungssystems.
Die vorhandenen Ergebnisse der durchgeführten Studie bieten eine Basis, die veränderte Regulation dopaminerger Neurotransmission im Rahmen psychiatrischer Erkrankungen besser zu beurteilen und weiter zu erforschen. Um ADHS mit seinen Komorbiditäten umfänglicher zu erfassen, ist es unvermeidbar, den Pathomechanismus der Dysregulation dopaminerger Neurotransmission, mit der daraus folgenden veränderten Belohnungsverarbeitung, in zukünftigen Studien genauer zu untersuchen.
With increasing importance of organizational effectivity and efficiency measures like Balanced Scorecard and optimization of employee work behavior to achieve higher organizational efficiency, Human Resource activities concerning leadership development and academic leadership research are growing. Throughout the course of the twentieth century, a multitude of empirical studies show primarily positive relationships between different constructs of leadership models and desirable variables of organizational behavior. It becomes apparent, though, that in academic research the selection of analyzed leadership models and their consequences is very heterogeneous. This Master Thesis has the objective to contribute to Leadership Research by applying a comparative empirical study in the–until today–often neglected study population of in-house and sales personnel within the pharmaceutical industry. For this purpose, an online employee survey with N = 137 participants from a leading pharmaceutical company in Germany was conducted. Based on contemporary leadership theory, a range of Hypotheses regarding consequences of modern leadership models is empirically tested. The results of the study reconfirm Identification with Manager, Trust & Loyalty and Employee Satisfaction as consequences of Authentic as well as Transformational leadership. Work context as in-house vs. sales setting shows moderating effects on some of the leadership-consequences relationships. As the research involves multiple structurally different variables as well as constructs and compares feedback of different study populations, tangible management implications to boost desirable work attitudes and behaviors can be derived and appropriately adapted to match the respective work context. Ramifications for future scientific research are also presented.
Previous reports of improved oral reading performance for dyslexic children but not for regular readers when between-letter spacing was enlarged led to the proposal of a dyslexia-specific deficit in visual crowding. However, it is in this context also critical to understand how letter spacing affects visual word recognition and reading in unimpaired readers. Adopting an individual differences approach, the present study, accordingly, examined whether wider letter spacing improves reading performance also for non-impaired adults during silent reading and whether there is an association between letter spacing and crowding sensitivity. We report eye movement data of 24 German students who silently read texts presented either with normal or wider letter spacing. Foveal and parafoveal crowding sensitivity were estimated using two independent tests. Wider spacing reduced first fixation durations, gaze durations, and total fixation time for all participants, with slower readers showing stronger effects. However, wider letter spacing also reduced skipping probabilities and elicited more fixations, especially for faster readers. In terms of words read per minute, wider letter spacing did not provide a benefit, and faster readers in particular were slowed down. Neither foveal nor parafoveal crowding sensitivity correlated with the observed letter-spacing effects. In conclusion, wide letter spacing reduces single word processing time in typically developed readers during silent reading, but affects reading rates negatively since more words must be fixated. We tentatively propose that wider letter spacing reinforces serial letter processing in slower readers, but disrupts parallel processing of letter chunks in faster readers. These effects of letter spacing do not seem to be mediated by individual differences in crowding sensitivity.
Body dysmorphic disorder (BDD), together with its subtype muscle dysmorphia (MD), has been relocated from the Somatoform Disorders category in the DSM-IV to the newly created Obsessive-Compulsive and Related Disorders category in the DSM-5. Both categorizations have been criticized, and an empirically derived classification of BDD is lacking. A community sample of N = 736 participants completed an online survey assessing different psychopathologies. Using a structural equation modeling approach, six theoretically derived models, which differed in their allocation of BDD symptoms to various factors (i.e. general psychopathology, somatoform, obsessive-compulsive and related disorders, affective, body image, and BDD model) were tested in the full sample and in a restricted sample (n = 465) which indicated primary concerns other than shape and weight. Furthermore, measurement invariance across gender was examined. Of the six models, only the body image model showed a good fit (CFI = 0.972, RMSEA = 0.049, SRMR = 0.027, TLI = 0.959), and yielded better AIC and BIC indices than the competing models. Analyses in the restricted sample replicated these findings. Analyses of measurement invariance of the body image model showed partial metric invariance across gender. The findings suggest that a body image model provides the best fit for the classification of BDD and MD. This is in line with previous studies showing strong similarities between eating disorders and BDD, including MD. Measurement invariance across gender indicates a comparable presentation and comorbid structure of BDD in males and females, which also corresponds to the equal prevalence rates of BDD across gender.
Within the context of eHealth interventions, a shared understanding of what constitutes engagement in and with eHealth technologies is missing. A clearer understanding of engagement could provide a valuable starting point for guidelines relating to the design and development of eHealth technologies. Given the cross-disciplinary use of the term “engagement,” investigating how engagement (and its components) is conceptualized in different domains could lead to determining common components that are deemed important for eHealth technological design. As such, the aim of this paper was 3-fold: (a) to investigate in which domains engagement features, (b) to determine what constitutes engagement in these different domains, and (c) to determine whether there are any common components that seem to be important. A comprehensive systematic scoping review of the existing literature was conducted in order to identify the domains in which engagement is used, to extract the associated definitions of engagement, and to identify the dimensionality or components thereof. A search of five bibliographic databases yielded 1,231 unique records. All titles, abstracts, and full texts were screened based on specific inclusion and exclusion criteria. This led to 69 articles being included for further analyses. The results showed that engagement is used in seven functional domains, categorized as follows: student (n = 18), customer (n = 12), health (n = 11), society (n = 10), work (n = 9), digital (n = 8), and transdisciplinary (n = 1) domains. It seems that some domains are more mature regarding their conceptualization and theorizing on engagement than others. Further, engagement was found to be predominantly conceptualized as a multidimensional construct with three common components (behavior, cognition, and affective) shared between domains. Although engagement is prolifically used in different disciplines, it is evident that little shared consensus as to its conceptualization within and between domains exists. Despite this, engagement is foremost seen as a state of being engaged in/with something, which is part of, but should not be confused with, the process of engagement. Behavior, cognition, and affect are important components of engagement and should be specified for each new context.
Virtual reality (VR) headsets offer a large and immersive workspace for displaying visualizations with stereoscopic vision, as compared to traditional environments with monitors or printouts. The controllers for these devices further allow direct three-dimensional interaction with the virtual environment. In this paper, we make use of these advantages to implement a novel multiple and coordinated view (MCV) system in the form of a vertical stack, showing tilted layers of geospatial data. In a formal study based on a use-case from urbanism that requires cross-referencing four layers of geospatial urban data, we compared it against more conventional systems similarly implemented in VR: a simpler grid of layers, and one map that allows for switching between layers. Performance and oculometric analyses showed a slight advantage of the two spatial-multiplexing methods (the grid or the stack) over the temporal multiplexing in blitting. Subgrouping the participants based on their preferences, characteristics, and behavior allowed a more nuanced analysis, allowing us to establish links between e.g., saccadic information, experience with video games, and preferred system. In conclusion, we found that none of the three systems are optimal and a choice of different MCV systems should be provided in order to optimally engage users.
How is semantic information stored in the human mind and brain? Some philosophers and cognitive scientists argue for vectorial representations of concepts, where the meaning of a word is represented as its position in a high-dimensional neural state space. At the intersection of natural language processing and artificial intelligence, a class of very successful distributional word vector models has developed that can account for classic EEG findings of language, that is, the ease versus difficulty of integrating a word with its sentence context. However, models of semantics have to account not only for context-based word processing, but should also describe how word meaning is represented. Here, we investigate whether distributional vector representations of word meaning can model brain activity induced by words presented without context. Using EEG activity (event-related brain potentials) collected while participants in two experiments (English and German) read isolated words, we encoded and decoded word vectors taken from the family of prediction-based Word2vec algorithms. We found that, first, the position of a word in vector space allows the prediction of the pattern of corresponding neural activity over time, in particular during a time window of 300 to 500 ms after word onset. Second, distributional models perform better than a human-created taxonomic baseline model (WordNet), and this holds for several distinct vector-based models. Third, multiple latent semantic dimensions of word meaning can be decoded from brain activity. Combined, these results suggest that empiricist, prediction-based vectorial representations of meaning are a viable candidate for the representational architecture of human semantic knowledge.
Despite the popularity of the term Positive Psychological Coaching within the literature, there is no consensus as to how it should be defined (framed) or what the components of a positive coaching “model” should include. The aim of this systematic review was to define positive psychological coaching and to construct a clear demarcated positive psychological coaching model based on the literature. A systematic literature review led to the extraction of 2,252 records. All records were screened using specific inclusion/exclusion criteria, which resulted in the exclusion of records based on duplicates (n = 1,232), titles (n = 895), abstracts (n = 78), and criteria violations (n = 23). Twenty-four academic, peer-reviewed publications on positive psychological coaching were included. Data relating to conceptual definitions and coaching models/phases/frameworks were extracted and processed through thematic content analysis. Our results indicate that positive psychological coaching can be defined as a short to medium term professional, collaborative relationship between a client and coach, aimed at the identification, utilization, optimization, and development of personal strengths and resources in order to enhance positive states, traits and behaviors. Utilizing Socratic goal setting and positive psychological evidence-based approaches to facilitate personal growth, optimal functioning, enhanced wellbeing, and the actualization of people's potential. Further, eight critical components of a positive psychological coaching model were identified and discussed. The definition and coaching process identified in this study will provide coaches with a fundamental positive psychological framework for optimizing people's potential.
The purpose of this study was to examine the psychometric properties (i.e., factorial validity, measurement invariance, and reliability) of the Grit-Original scale (Grit-O) within the Netherlands. The Grit-O scale was subjected to a competing measurement modeling strategy that sequentially compared both independent cluster model confirmatory factor analytical- and exploratory structural equation modeling approaches. The results showed that both a two first order, bi-factor structure as well as a less restrictive two factor ESEM factorial structure best-fitted the data. The instrument showed to be reliable at both a lower- (Cronbach’s alpha) and upper-level (composite reliability) limit. However, measurement invariance between genders could only be established for the B-ICM-CFA model. Finally, concurrent validity was established through relating the GRIT-O to task performance. The linear use of the Grit-O scale should therefore carefully be considered.
Editorial: Positive organizational interventions: contemporary theories, approaches and applications
(2020)
The purpose of this study was to identify distinctive mental health profiles for industrial psychologists based on the Mental Health Continuum. Further, it aimed to determine how these profiles differ with respect to work-role fit, meaningfulness and work engagement. It also aimed to investigate whether industrial psychologists within managerial or specialist differ in respect of different types of mental health. An online cross-sectional survey design was employed to draw a census sample (n = 274) from all South African industrial psychologists. A biographical questionnaire, the Work-Role Fit Scale, the Psychological Meaningfulness Scale, the Work Engagement Scale, and the Mental Health Continuum–Short Form were administered. Descriptive statistics, correlations, latent profile analysis, MANOVAs and ANOVAs were computed. Three mental health profiles for industrial psychologists were identified: languishing, moderately mentally healthy and flourishing. Significant differences between the three mental health profiles and experiences of meaningful work-role fit and work engagement were found, but not between experiences of managerial roles. The results show that individuals with different mental health profiles, experience work and its related outcomes, differently. Therefore, in order to enhance meaningful work-role fit and work engagement of industrial psychologists, a one-size-fits-all model may not be appropriate.
Background: Depression is a widespread disorder with severe impacts for individuals and society, especially in its chronic form. Current treatment approaches for persistent depression have focused primarily on reducing negative affect and have paid little attention to promoting positive affect. Previous studies have shown that metta meditation increases positive affect in chronically depressed patients. Results from previous trials provide evidence for the efficacy of a stand-alone metta meditation group treatment in combination with mindfulness-based approaches. Further research is needed to better understand the implementation of meditation practice into everyday life. Therefore, mindfulness and metta meditation in a group setting are combined with individual cognitive behavioral therapy (CBT) into a new, low-intensity, cost-effective treatment (“MeCBT”) for chronic depression. Methods/design: In this single-center, randomized, observer-blinded, parallel-group clinical trial we will test the efficacy of MeCBT in reducing depression compared to a wait-list control condition. Forty-eight participants in a balanced design will be allocated randomly to a treatment group or a wait-list control group. Metta-based group meditation will be offered in eight weekly sessions and one additional half-day retreat. Subsequent individual CBT will be conducted in eight fortnightly sessions. Outcome measures will be assessed at four time points: before intervention (T0); after group meditation (T1); after individual CBT (T2); and, in the treated group only, at 6-month follow-up (T3). Changes in depressive symptoms (clinician rating), assessed with the Quick Inventory of Depressive Symptoms (QIDS-C) are the primary outcome. We expect a significant decline of depressive symptoms at T2 compared to the wait-list control group. Secondary outcome measures include self-rated depression, mindfulness, benevolence, rumination, emotion regulation, social connectedness, social functioning, as well as behavioral and cognitive avoidance. We will explore changes at T1 and T2 in all these secondary outcome variables. Discussion: To our knowledge this is the first study to combine a group program focusing on Metta meditation with stateof-the art individual CBT specifically tailored to chronic depression. Implications for further refinement and examination of the treatment program are discussed. Trial registration: ISRCTN, ISRCTN97264476. Registered 29 March 2018 (applied on 14 December 2017)—retrospectively registered.
Successful consolidation of associative memories relies on the coordinated interplay of slow oscillations and sleep spindles during non-rapid eye movement (NREM) sleep. This enables the transfer of labile information from the hippocampus to permanent memory stores in the neocortex. During senescence, the decline of the structural and functional integrity of the hippocampus and neocortical regions is paralleled by changes of the physiological events that stabilize and enhance associative memories during NREM sleep. However, the currently available evidence is inconclusive as to whether and under which circumstances memory consolidation is impacted during aging. To approach this question, 30 younger adults (19–28 years) and 36 older adults (63–74 years) completed a memory task based on scene–word associations. By tracing the encoding quality of participants’ individual memory associations, we demonstrate that previous learning determines the extent of age-related impairments in memory consolidation. Specifically, the detrimental effects of aging on memory maintenance were greatest for mnemonic contents of intermediate encoding quality, whereas memory gain of poorly encoded memories did not differ by age. Ambulatory polysomnography (PSG) and structural magnetic resonance imaging (MRI) data were acquired to extract potential predictors of memory consolidation from each participant’s NREM sleep physiology and brain structure. Partial Least Squares Correlation was used to identify profiles of interdependent alterations in sleep physiology and brain structure that are characteristic for increasing age. Across age groups, both the ‘aged’ sleep profile, defined by decreased slow-wave activity (0.5–4.5 Hz), and a reduced presence of slow oscillations (0.5–1 Hz), slow, and fast spindles (9–12.5 Hz; 12.5–16 Hz), as well as the ‘aged’ brain structure profile, characterized by gray matter reductions in the medial prefrontal cortex, thalamus, entorhinal cortex, and hippocampus, were associated with reduced memory maintenance. However, inter-individual differences in neither sleep nor structural brain integrity alone qualified as the driving force behind age differences in sleep-dependent consolidation in the present study. Our results underscore the need for novel and age-fair analytic tools to provide a mechanistic understanding of age differences in memory consolidation.
As a relevant cognitive-motivational aspect of ICT literacy, a new construct ICT Engagement is theoretically based on self-determination theory and involves the factors ICT interest, Perceived ICT competence, Perceived autonomy related to ICT use, and ICT as a topic in social interaction. In this manuscript, we present different sources of validity supporting the construct interpretation of test scores in the ICT Engagement scale, which was used in PISA 2015. Specifically, we investigated the internal structure by dimensional analyses and investigated the relation of ICT Engagement aspects to other variables. The analyses are based on public data from PISA 2015 main study from Switzerland (n = 5860) and Germany (n = 6504). First, we could confirm the four-dimensional structure of ICT Engagement for the Swiss sample using a structural equation modelling approach. Second, ICT Engagement scales explained the highest amount of variance in ICT Use for Entertainment, followed by Practical use. Third, we found significantly lower values for girls in all ICT Engagement scales except ICT Interest. Fourth, we found a small negative correlation between the scores in the subscale “ICT as a topic in social interaction” and reading performance in PISA 2015. We could replicate most results for the German sample. Overall, the obtained results support the construct interpretation of the four ICT Engagement subscales.
Imageability and emotionality ratings for 2592 German nouns (3–10 letters, one to three phonological syllables) were obtained from younger adults (21–31 years) and older adults (70–86 years). Valid ratings were obtained on average from 20 younger and 23 older adults per word for imageability, and from 18 younger and 19 older adults per word for emotionality. The internal consistency (Cronbach’s α) and retest rank-order stability of the ratings were high for both age groups (α and r ≥ .97). Also, the validity of our ratings was found to be high, as compared to previously published ratings (r ≥ .86). The ratings showed substantial rank-order stability across younger and older adults (imageability, r = .94; emotionality, r = .85). At the same time, systematic differences between age groups were found in the mean levels of ratings (imageability, d = 0.38; emotionality, d = 0.20) and in the extent to which the rating scales were used (imageability, SD = 24 vs. 19, scale of 0 to 100; emotionality, SD = 26 vs. 31, scale of −100 to 100). At the descriptive level, our data hint at systematically different evaluations of semantic categories regarding imageability and emotionality across younger and older adults. Given that imageability and emotionality have been reported, for instance, as important determinants for the recognition and recall of words, our findings highlight the importance of considering age-specific information in age-comparative cognitive (neuroscience) experimental studies using word materials. The age-specific imageability and emotionality ratings for the 2592 German nouns can be found in the electronic supplementary material...
Background/Objectives: Sharing the bed with a partner is common among adults and impacts sleep quality with potential implications for mental health. However, hitherto findings are contradictory and particularly polysomnographic data on co-sleeping couples are extremely rare. The present study aimed to investigate the effects of a bed partner's presence on individual and dyadic sleep neurophysiology.
Methods: Young healthy heterosexual couples underwent sleep-lab-based polysomnography of two sleeping arrangements: individual sleep and co-sleep. Individual and dyadic sleep parameters (i.e., synchronization of sleep stages) were collected. The latter were assessed using cross-recurrence quantification analysis. Additionally, subjective sleep quality, relationship characteristics, and chronotype were monitored. Data were analyzed comparing co-sleep vs. individual sleep. Interaction effects of the sleeping arrangement with gender, chronotype, or relationship characteristics were moreover tested.
Results: As compared to sleeping individually, co-sleeping was associated with about 10% more REM sleep, less fragmented REM sleep (p = 0.008), longer undisturbed REM fragments (p = 0.0006), and more limb movements (p = 0.007). None of the other sleep stages was significantly altered. Social support interacted with sleeping arrangement in a way that individuals with suboptimal social support showed the biggest impact of the sleeping arrangement on REM sleep. Sleep architectures were more synchronized between partners during co-sleep (p = 0.005) even if wake phases were excluded (p = 0.022). Moreover, sleep architectures are significantly coupled across a lag of ± 5min. Depth of relationship represented an additional significant main effect regarding synchronization, reflecting a positive association between the two. Neither REM sleep nor synchronization was influenced by gender, chronotype, or other relationship characteristics.
Conclusion: Depending on the sleeping arrangement, couple's sleep architecture and synchronization show alterations that are modified by relationship characteristics. We discuss that these alterations could be part of a self-enhancing feedback loop of REM sleep and sociality and a mechanism through which sociality prevents mental illness.
Existing social stressor concepts disregard the variety of task-related situations at work that require skillful social behavior to maintain good social relationships while achieving certain task goals. In this article, we challenge the view that social stressors at work are solely dysfunctional aspects evoking employee ill health. Drawing from the challenge-hindrance stressor framework, we introduce the concept of social challenge stressors as a job characteristic and examine their relationships with individual well-and ill-being. In study 1, we developed a new scale for the measurement of social challenge stressors and tested the validity of the scale. Results from two independent samples indicated support for a single-factor structure and showed that social challenge stressors are distinct from related stressor concepts. Using two samples, one of which was already used to test the factor structure, we analyzed the unique contribution of social challenge stressors in predicting employee well- and ill-being. As expected, social challenge stressors were simultaneously related to psychological strain and well-being. Using time-lagged data, study 2 investigated mechanisms that may explain how social challenge stressors are linked to well-being and strain. In line with the stress-as-offense-to-self approach, we expected indirect relationships via self-esteem. Additionally, social support was expected to moderate the relationships between social stressors and self-esteem. Whereas the indirect relationships were mostly confirmed, we found no support for the buffering role of social support in the social hindrance stressors-self-esteem link. Although we found a moderation effect for social challenge stressors, results indicated a compensation model that conflicted with expectations.
Background: Chronic autoimmune demyelinating polyneuropathies (CADP) result in impaired sensorimotor function. However, anecdotal clinical observations suggest the development of cognitive deficits during the course of disease.
Methods: We tested 16 patients with CADP (11 patients with chronic inflammatory demyelinating polyneuropathy, 4 patients with multifocal motor neuropathy and 1 patient with multifocal acquired demyelinating sensory and motor neuropathy) and 40 healthy controls (HC) with a neuropsychological test battery. Blood-brain-barrier dysfunction (BBBd) in patients was assessed retrospectively by analysing the cerebral spinal fluid (CSF) status at the time the diagnosis of CAPD was established.
Results: CADP patients failed on average in 1.7 out of 9 neuropsychological tests (SD ± 1.25, min. 0, max. 5). 50% of the CADP patients failed in at least two neuropsychological tests and 44.3% of the patients failed in at least two different cognitive domains. CADP patients exhibiting BBBd at the time of first diagnosis failed in more neuropsychological tests than patients with intact integrity of the BBB (p < 0.05). When compared directly with the HC group, CADP patients performed worse than HC in tests measuring information processing ability and speed as well as phonemic verbal fluency after adjusting for confounding covariates.
Conclusions: Our results suggest that mild to moderate cognitive deficits might be present in patients with CAPD. One possible tentative explanation, albeit strong evidence is still lacking for this pathophysiological mechanism, refers to the effect of autoimmune antibodies entering the CNS via the dysfunctional blood-brain barrier typically seen in some of the CADP patients.
Although researchers and practitioners increasingly focus on health promotion in organizations, research has been mainly fragmented and fails to integrate different organizational levels in terms of their effects on employee health. Drawing on organizational climate and social identity research, we present a cascading model of organizational health climate and demonstrate how and when leaders' perceptions of organizational health climate are linked to employee well‐being. We tested our model in two multisource studies (NStudy 1 = 65 leaders and 291 employees; NStudy 2 = 401 leader–employee dyads). Results showed that leaders' perceptions of organizational health climate were positively related to their health mindsets (i.e., their health awareness). These in turn were positively associated with their health‐promoting leadership behavior, which ultimately went along with better employee well‐being. Additionally, in Study 1, the relationship between perceived organizational health climate and leaders' health mindsets was moderated by their organizational identification. High leader identification strengthened the relationship between perceived organizational health climate and leaders' health mindsets. These findings have important implications for theory and practice as they show how the dynamics of an organizational health climate can unfold in organizations and how it is related to employee well‐being via the novel concept of health‐promoting leadership.
Recent research has identified significant correlations between traumatic events and depression in refugees. However, few studies have addressed the role of acculturation strategies in this relationship. This study explored the relationship between cultural orientation, traumatic events and depression in female refugees from Syria, Afghanistan, Eritrea, Iran, Iraq, and Somalia living in Germany. We expected acculturation strategies to moderate the effect of traumatic experiences on depression. The sample included 98 female refugees in Germany. The depression scale of the Hopkins Symptom Checklist (HSCL) represented the dependent measure. The trauma checklists derived from the Post-traumatic Diagnostic Scale (PDS) and the Harvard Trauma Questionnaire (HTQ) as well as the Frankfurt Acculturation Scale (FRACC) were used as independent measures for traumatic events and orientation toward the host culture as well as orientation toward the culture of origin, respectively. A moderation analysis was conducted to examine whether the relationship between the number of traumatic events and depression was influenced by the women’s orientation toward the culture of origin and the host culture. We identified a significant model explaining 26.85% of the variance in depressive symptoms (Cohen’s f2 = 0.37). The number of traumatic events and the orientation toward the host culture exerted significant effects on depressive symptoms. The moderating effect was not significant, indicating that the effect of the number of traumatic events was not influenced by cultural orientation. Based on our results, orientation toward the host culture as well as traumatic experiences exert independent effects on depressive symptoms in refugees.
In this explorative study, we investigate how sequences of behaviour are related to success or failure in complex problem‐solving (CPS). To this end, we analysed log data from two different tasks of the problem‐solving assessment of the Programme for International Student Assessment 2012 study (n = 30,098 students). We first coded every interaction of students as (initial or repeated) exploration, (initial or repeated) goal‐directed behaviour, or resetting the task. We then split the data according to task successes and failures. We used full‐path sequence analysis to identify groups of students with similar behavioural patterns in the respective tasks. Double‐checking and minimalistic behaviour was associated with success in CPS, while guessing and exploring task‐irrelevant content was associated with failure. Our findings held for both tasks investigated, from two different CPS measurement frameworks. We thus gained detailed insight into the behavioural processes that are related to success and failure in CPS.
Objective: Although meaning making and specifically autobiographical reasoning are expected to relate to well‐being, findings tend to be mixed. Attempts at meaning making do not always lead to meaning made. We aimed to disentangle these complex relationships and also explore the role of level of education.
Method: Ninety participants (mean age 36.73 years, SD = 7.27; 74.4% women, 25.6% men) who had experienced the loss of a parent through death, going missing, or Alzheimer's disease narrated this loss, a sad, a turning point, and a self‐defining memory, and completed questionnaires assessing depression, trauma symptoms, and protracted grief. Three aspects of autobiographical reasoning (quantity, valence, and change‐relatedness of self‐event connections) were related to meaning made (sophistication of meaning making) and symptom level.
Results: Years of education correlated both with positive implications of autobiographical reasoning and with meaning made. The quantity, positivity, and change‐relatedness of attempts at meaning making (self‐event connections) predicted accomplished meaning made, and positivity alone predicted less prolonged grief.
Conclusions: Adapting the life story after a loss such that change of the self is acknowledged and positive change can be constructed helps finding meaning and lowering protracted grief. These changes in narrative identity are supported by more years of education.
Ergodic subspace analysis
(2020)
Properties of psychological variables at the mean or variance level can differ between persons and within persons across multiple time points. For example, cross-sectional findings between persons of different ages do not necessarily reflect the development of a single person over time. Recently, there has been an increased interest in the difference between covariance structures, expressed by covariance matrices, that evolve between persons and within a single person over multiple time points. If these structures are identical at the population level, the structure is called ergodic. However, recent data confirms that ergodicity is not generally given, particularly not for cognitive variables. For example, the <i>g</i> factor that is dominant for cognitive abilities between persons seems to explain far less variance when concentrating on a single person’s data. However, other subdimensions of cognitive abilities seem to appear both between and within persons; that is, there seems to be a lower-dimensional subspace of cognitive abilities in which cognitive abilities are in fact ergodic. In this article, we present ergodic subspace analysis (ESA), a mathematical method to identify, for a given set of variables, which subspace is most important within persons, which is most important between person, and which is ergodic. Similar to the common spatial patterns method, the ESA method first whitens a joint distribution from both the between and the within variance structure and then performs a principle component analysis (PCA) on the between distribution, which then automatically acts as an inverse PCA on the within distribution. The difference of the eigenvalues allows a separation of the rotated dimensions into the three subspaces corresponding to within, between, and ergodic substructures. We apply the method to simulated data and to data from the COGITO study to exemplify its usage.
Background: Research on desired emotions revealed that individuals want to feel negative emotions if they expect these emotions to yield certain benefits. In previous studies, the pursuit of sadness (e.g., via pursuing art that evokes sadness) has been attributed to hedonic motives, i.e., to feel pleasure. We propose that in individuals with major depressive disorder (MDD) the pursuit of sadness may be more strongly related to self-verification motives, i.e., to sustain their sense of self through feeling sad.
Methods: Participants with MDD (n = 50) were compared to non-depressed controls (n = 50) in their desired emotional states, as indicated by selected music (sad, happy and neutral), and in their motives (hedonic vs. self-verification) for choosing sad music. Groups were also compared in their self-reported general preference for sadness and the perceived functionality of sadness.
Results: MDD participants showed a significant higher desire for sadness; more than half of them deliberately chose sad music. Whereas MDD participants had a marked preference for self-verification over hedonic motives, the reverse was true for non-depressed controls. MDD participants also agreed more strongly with self-verifying functions of sadness and expressed a stronger general preference for sadness.
Conclusion: Findings indicate that emotion regulation in MDD might be driven by self-verification motives. They point to the relevance of exploring patients’ desired emotional states and associated motives. The systematic integration of positive affect into the self-image of depressed patients might help to deemphasize the self-verifying function of sadness, thereby overcoming the depression.