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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.
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.
Studying the neural basis of human dynamic visual perception requires extensive experimental data to evaluate the large swathes of functionally diverse brain neural networks driven by perceiving visual events. Here, we introduce the BOLD Moments Dataset (BMD), a repository of whole-brain fMRI responses to over 1,000 short (3s) naturalistic video clips of visual events across ten human subjects. We use the videos’ extensive metadata to show how the brain represents word- and sentence-level descriptions of visual events and identify correlates of video memorability scores extending into the parietal cortex. Furthermore, we reveal a match in hierarchical processing between cortical regions of interest and video-computable deep neural networks, and we showcase that BMD successfully captures temporal dynamics of visual events at second resolution. With its rich metadata, BMD offers new perspectives and accelerates research on the human brain basis of visual event perception.
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.
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.
Understanding effects of emotional valence and stress on children’s memory is important for educational and legal contexts. This study disentangles the effects of emotional content of to-be-remembered information (i.e., items differing in emotional valence and arousal), stress exposure, and associated cortisol secretion on children’s memory. We also examine whether girls’ memory is more affected by stress induction. 143 6-to-7-year-old children were randomly allocated to the Trier Social Stress Test for Children (n = 103) or a control condition (n = 40). 25 minutes after stressor onset, children incidentally encoded 75 objects varying in emotional valence (crossed with arousal) together with neutral scene backgrounds. We found that response-bias corrected memory was worse for low arousing negative items than neutral and positive items, with the latter two categories not being different from each other. Whilst boys’ memory was largely unaffected by stress, girls in the stress condition showed worse memory for negative items, especially the low arousing ones, than girls in the control condition. Girls, compared to boys, reported higher subjective stress increases following stress exposure, and had higher cortisol stress responses. Whilst a higher cortisol stress response was associated with better emotional memory in girls in the stress condition, boys’ memory was not associated with their cortisol secretion. Taken together, our study suggests that 6-to-7-year-old children, more so girls, show memory suppression for negative information. Girls’ memory for negative information, compared to boys, is also more strongly modulated by stress experience and the associated cortisol response.
In recent decades, the assessment of instructional quality has grown into a popular and well-funded arm of educational research. The present study contributes to this field by exploring first impressions of untrained raters as an innovative approach of assessment. We apply the thin slice procedure to obtain ratings of instructional quality along the dimensions of cognitive activation, classroom management, and constructive support based on only 30 s of classroom observations. Ratings were compared to the longitudinal data of students taught in the videos to investigate the connections between the brief glimpses into instructional quality and student learning. In addition, we included samples of raters with different backgrounds (university students, middle school students and educational research experts) to understand the differences in thin slice ratings with respect to their predictive power regarding student learning. Results suggest that each group provides reliable ratings, as measured by a high degree of agreement between raters, as well predictive ratings with respect to students’ learning. Furthermore, we find experts’ and middle school students’ ratings of classroom management and constructive support, respectively, explain unique components of variance in student test scores. This incremental validity can be explained with the amount of implicit knowledge (experts) and an attunement to assess specific cues that is attributable to an emotional involvement (students).
Solving the problem of consciousness remains one of the biggest challenges in modern science. One key step towards understanding consciousness is to empirically narrow down neural processes associated with the subjective experience of a particular content. To unravel these neural correlates of consciousness (NCC) a common scientific strategy is to compare perceptual conditions in which consciousness of a particular content is present with those in which it is absent, and to determine differences in measures of brain activity (the so called "contrastive analysis"). However, this comparison appears not to reveal exclusively the NCC, as the NCC proper can be confounded with prerequisites for and consequences of conscious processing of the particular content. This implies that previous results cannot be unequivocally interpreted as reflecting the neural correlates of conscious experience. Here we review evidence supporting this conjecture and suggest experimental strategies to untangle the NCC from the prerequisites and consequences of conscious experience in order to further develop the otherwise valid and valuable contrastive methodology.
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.
This thesis develops a naturalist theory of phenomenal consciousness. In a first step, it is argued on phenomenological grounds that consciousness is a representational state and that explaining consciousness requires a study of the brain’s representational capacities. In a second step, Bayesian cognitive science and predictive processing are introduced as the most promising attempts to understand mental representation to date. Finally, in a third step, the thesis argues that the so-called “hard problem of consciousness” can be resolved if one adopts a form of metaphysical anti-realism that can be motivated in terms of core principles of Bayesian cognitive science.
Rhythmic neural spiking and attentional sampling arising from cortical receptive field interactions
(2018)
Summary: Growing evidence suggests that distributed spatial attention may invoke theta (3-9 Hz) rhythmic sampling processes. The neuronal basis of such attentional sampling is however not fully understood. Here we show using array recordings in visual cortical area V4 of two awake macaques that presenting separate visual stimuli to the excitatory center and suppressive surround of neuronal receptive fields elicits rhythmic multi-unit activity (MUA) at 3-6 Hz. This neuronal rhythm did not depend on small fixational eye movements. In the context of a distributed spatial attention task, during which the monkeys detected a spatially and temporally uncertain target, reaction times (RT) exhibited similar rhythmic fluctuations. RTs were fast or slow depending on the target occurrence during high or low MUA, resulting in rhythmic MUA-RT cross-correlations at at theta frequencies. These findings suggest that theta-rhythmic neuronal activity arises from competitive receptive field interactions and that this rhythm may subserve attentional sampling.
Highlights:
* Center-surround interactions induce theta-rhythmic MUA of visual cortex neurons
* The MUA rhythm does not depend on small fixational eye movements
* Reaction time fluctuations lock to the neuronal rhythm under distributed attention
Highlights
• Microstimulation of visual area V4 improves visual stimulus detection
• Effects of V4 microstimulation extend to the other hemifield
• Microstimulation effects are time dependent and consistent with attention dynamics
Summary
Neuronal activity in visual area V4 is well known to be modulated by selective attention, and there are reports on V4 lesions leading to attentional deficits. However, it remains unclear whether V4 microstimulation can elicit attentional benefits. To test this hypothesis, we performed local microstimulation in area V4 and explored its spatial and time dynamics in two macaque monkeys performing a visual detection task. Microstimulation was delivered via chronically implanted multi-electrode arrays. We found that microstimulation increases average performance by 35% and reduces luminance detection thresholds by −30%. This benefit critically depends on the onset of microstimulation relative to the stimulus, consistent with known dynamics of endogenous attention. These results show that local microstimulation of V4 can improve behavior and highlight the critical role of V4 for attention.
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.
Conduct Disorder (CD) is an impairing psychiatric disorder of childhood and adolescence characterized by aggressive and dissocial behavior. Environmental factors such as maternal smoking during pregnancy, socio-economic status, trauma, or early life stress are associated with CD. Although the number of females with CD is rising in Western societies, CD is under-researched in female cohorts. We aimed at exploring the epigenetic signature of females with CD and its relation to psychosocial and environmental risk factors. We performed HpaII sensitive genome-wide methylation sequencing of 49 CD girls and 50 matched typically developing controls and linear regression models to identify differentially methylated CpG loci (tags) and regions. Significant tags and regions were mapped to the respective genes and tested for enrichment in pathways and brain developmental processes. Finally, epigenetic signatures were tested as mediators for CD-associated risk factors. We identified a 12% increased methylation 5’ of the neurite modulator SLITRK5 (FDR = 0.0046) in cases within a glucocorticoid receptor binding site. Functionally, methylation positively correlated with gene expression in lymphoblastoid cell lines. At systems-level, genes (uncorr. P < 0.01) were associated with development of neurons, neurite outgrowth or neuronal developmental processes. At gene expression level, the associated gene-networks are activated perinatally and during early childhood in neocortical regions, thalamus and striatum, and expressed in amygdala and hippocampus. Specifically, the epigenetic signatures of the gene network activated in the thalamus during early childhood correlated with the effect of parental education on CD status possibly mediating its protective effect. The differential methylation patterns identified in females with CD are likely to affect genes that are expressed in brain regions previously indicated in CD. We provide suggestive evidence that protective effects are likely mediated by epigenetic mechanisms impairing specific brain developmental networks and therefore exerting a long-term effect on neural functions in CD. Our results are exploratory and thus, further replication is needed.
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.
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.
Understanding the brain's proactive nature and its ability to anticipate the future has been a longstanding pursuit in philosophy and scientific research. The predictive processing framework explains how the brain generates predictions based on environmental regularities and adapts to both predicted and unpredicted events. Prediction errors (PE) occur when sensory evidence deviates from predictions, triggering cognitive and neural processes that enhance learning and subsequent memory. However, the effects of PE on episodic memory have not been clearly explained. This dissertation aims to address three key questions to advance our understanding of PE and episodic memory. First, how does the degree of PE influence episodic memory, and how do expected and unexpected events interact in this process? Second, what insights can be gained from studying the electrophysiological activity associated with prediction violations, and what role does PE play in subsequent memory benefits? Lastly, how do memory processes change across the lifespan, and how does this impact the brain's ability to remember events? By answering these questions, this dissertation contributes to advancing our understanding of the cognitive and neural mechanisms underlying the relationship PE and episodic memory.
Do leaders who build a sense of shared social identity in their teams thereby protect them from the adverse effects of workplace stress? This is a question that the present paper explores by testing the hypothesis that identity leadership contributes to stronger team identification among employees and, through this, is associated with reduced burnout. We tested this model with unique datasets from the Global Identity Leadership Development (GILD) project with participants from all inhabited continents. We compared two datasets from 2016/2017 (n = 5290; 20 countries) and 2020/2021 (n = 7294; 28 countries) and found very similar levels of identity leadership, team identification and burnout across the five years. An inspection of the 2020/2021 data at the onset of and later in the COVID-19 pandemic showed stable identity leadership levels and slightly higher levels of both burnout and team identification. Supporting our hypotheses, we found almost identical indirect effects (2016/2017, b = −0.132; 2020/2021, b = −0.133) across the five-year span in both datasets. Using a subset of n = 111 German participants surveyed over two waves, we found the indirect effect confirmed over time with identity leadership (at T1) predicting team identification and, in turn, burnout, three months later. Finally, we explored whether there could be a “too-much-of-a-good-thing” effect for identity leadership. Speaking against this, we found a u-shaped quadratic effect whereby ratings of identity leadership at the upper end of the distribution were related to even stronger team identification and a stronger indirect effect on reduced burnout.
In recent years, the notion of infrastructure has enjoyed growing scholarly attention; infrastructure being precisely that which allows for the kind of interfacing between local and global scales the term 'glocalization' resists on. In order to connect this discourse to the studies of language and literature, this article revisits Jacques Lacan's paper "Of Structure as an Inmixing Prerequisite to Any Subject Whatever". Rather than taking Lacan's notorious claim that "the best image to sum up the unconscious is Baltimore in the early morning" as the absurdity it may seem at first glance, the article proposes to read the claim seriously. Taking the scenic route through the extensive work on the Baltimore region undertaken in urban studies since the 1950s, the article outlines how Lacan's connection of the unconscious to a Baltimore street scene is actually closely tied to the interest in the notion of 'structure' at the core of his paper: Since Jean Gottmann's groundbreaking work on the topic, the extended Baltimore region - the 'Northeastern Megalopolis' - has continued to exert a twofold fascination over urban geography: not only does it represent a cultural and economic center of global importance, but also a type of structure characterized by change and accident rather than by unity and planning. 'Structured', in this context, must adopt a new meaning, which, in turn, sheds a new light on Lacan's famous claim in the same paper that the unconscious is "structured like a language". Lacan's seemingly offhand remark, thus, serves as an entrance into a possible configuration of language, literature, and infrastructure.
Background: ICD-11 features Complex Posttraumatic Stress Disorder (CPTSD) as a new diagnosis. To date, very few studies have investigated CPTSD in young patients, and there is a need for evidence on effective treatment.
Objective: The present study evaluates the applicability of developmentally adapted cognitive processing therapy (D-CPT) for CPTSD in young patients in a secondary analysis of the treatment condition of a randomized controlled trial (RCT) investigating the efficacy of D-CPT.
Methods: The D-CPT treatment group in the original study included 44 patients (14–21 years) with DSM-IV PTSD after childhood abuse. We used the ICD-11 algorithm to divide the sample into a probable CPTSD and a non-CPTSD group. We performed multilevel models for interviewer-rated and self-rated PTSD symptoms with fixed effects of group (CPTSD, non-CPTSD) and time (up to 12 months follow-up) and their interaction. Treatment response rates for both groups were calculated.
Results: Nineteen (43.2%) patients fulfilled criteria for probable ICD-11 CPTSD while 25 (56.8%) did not. Both CPTSD and non-CPTSD groups showed symptom reduction over time. The CPTSD group reported higher symptom severity before and after treatment. Linear improvement and treatment response rates were similar for both groups. D-CPT reduced symptoms of disturbances in self-regulation in both groups.
Discussion: Both, patients with and without probable ICD-11 CPTSD seemed to benefit from D-CPT and the treatment also reduced disturbances in self-regulation.
Conclusion: This study presents initial evidence of the applicability of D-CPT in clinical practice for young patients with CPTSD. It remains debatable whether CPTSD implies different treatment needs as opposed to PTSD.
Our mind has the function of representing the physical and social world we are in, so that we can efficiently interact with it. This results in a constant and dynamic interaction between mind and world that produces a balance when representations are at the same time accurate with respect to what the world is communicating to our organism, but also compatible with how our mind works.
A paradigmatic case of this interaction is offered by perception, which is the mental function that represents contingent aspects of the world built from what is captured by our senses. Indeed, the dominant philosophical view in cognitive science is that our perceptual states are representations of the world and not direct access to that world. These representational perceptual states therefor include the aspects of the world they represent and that initiate the perception by stimulating our sensory organs.
Perceptual representations are built using information from the sensory system, i.e., bottom-up information, but are also integrated with information previously acquired, i.e., top-down information, so that perception interacts with memory through language and other mental functions. Such organization is believed to reflect a general mechanism of our mind/brain, which is to acquire and use information to make efficient predictions about the future, continuously updating older information with present information.
This predictive processing works because the world is not random, but shows a regular structure from which reliable expectations can be built. One way that our minds make these predictions is by adapting to the structure of the world in an implicit, automatic and unconscious way, a process that has been called Implicit Statistical Learning (ISL). ISL is a learning process that does not require awareness and happens in an incidental and spontaneous way, with mere exposure to statistical regularities of the world. It is what happens when we learn a language during early childhood, and that allows us to be implicitly sensitive to the phonological structure of speech, or to associate speech patterns with objects and events to learn word meaning.
A specific case of ISL is the learning of spatial configuration in the visual world, which we apply to abstract arrays of items, but most importantly, also to more ecological settings such as the visual scenes we are immersed in during our everyday life. The knowledge we acquire about the structure of visual scenes has been called “Scene Grammar”, because it informs about presence and position of objects in a similar way to what linguistic grammar tells us about the presence and position of words. So, we implicitly acquire the semantics of scenes, learning which objects are consistent with a certain scene, as well as the syntax of scenes, learning where objects are positioned in a consistent way within a certain scene.
More recent developments have proposed that scene grammar knowledge might be organized based on a hierarchical system: objects are arranged in the scene, which offers the more general context, but within a scene we can identify different spatial and functional clusters of objects, called “phrases”, that offer a second level of context; within every phrase, then, objects have different status, with usually one object (“anchor object”) offering strong prediction of where and which are the other objects within the phrase (“local objects”). However, these further aspects of the organization of objects In scenes remain poorly understood.
Another problem relates to the way we measure the structure of scenes to compare the organization of the visual world with the organization in the mind. Typically, to decide if an object appears or not in a certain scene, and whether or not it appears in a certain position within a scene, researchers based their decision on intuition and common-sense, maybe validating those decisions with independent raters. But it has been shown that often these decisions can be limited and more complex information about objects’ arrangement in scenes can be lost.
A potential solution to this problem might be using large set of real-world images, that have annotations and segmentations of objects, to measures statistics about how objects are arranged in the environment. This idea exploits the nowadays larger availability of this kind of datasets due to increasing developments of computer vision algorithms, and also parallels with the established usage of large text corpora in language research.
The goals of the current investigation were to extract object statistics from this image datasets and test if they reliably predict behavioural responses during object processing, as well as to use these statistics to investigate more complex aspects of scene grammar, such as its hierarchical organization, to see if this organization is reflected in the organization of objects in our mind.
Despite its popularity in practice, the Grit-O Scale has shown inconsistent factorial structures and differing levels of internal consistency in samples outside the USA. The validity of the Grit-O Scale in different contexts is, therefore, questionable. As such, the purpose of this paper was to determine whether the Grit-O Scale could be used as a valid and reliable measure to compare grit across different nations. Specifically, the aim was to investigate the factorial validity, reliability, and concurrent validity of the Grit-O Scale and to investigate measurement invariance across three national cohorts (Europe, the USA, and Hong Kong). Data were gathered from 1888 respondents stemming from one USA- (n = 471), two Hong Kong- (n = 361) and four European (n = 1056) universities. A series of traditional CFA and less restrictive ESEM models were estimated and systematically compared to determine the best factorial form of the Grit-O Scale. The results showed that a bifactor ESEM model, with one general factor of overall grit and two specific factors (consistency of interest and perseverance of effort), fitted the data best, showed strong measurement invariance across the three samples, and showed itself to be a reliable measure. Furthermore, concurrent validity was established by showing that the three grit factors were directly and positively related to task performance. Meaningful latent comparisons between the three cultural cohorts could therefore be made. The results imply that cross-national comparisons of grit may only be problematic when traditional CFA approaches are favoured. In contrast, ESEM modelling approaches may compensate for cross-national differences in understanding grit and control for differences in the interpretation of the scale’s items. Therefore, the bifactor ESEM approach may be more appropriate for cross-cultural and cross-national comparison studies, as it allows for these differences to be meaningfully captured, modelled, and controlled for.
Lexical access speed and the development of phonological recoding during immediate serial recall
(2022)
A recent Registered Replication Report (RRR) of the development of verbal rehearsal during serial recall revealed that children verbalized at younger ages than previously thought, but did not identify sources of individual differences. Here, we use mediation analysis to reanalyze data from the 934 children ranging from 5 to 10 years old from the RRR for that purpose. From ages 5 to 7, the time taken for a child to label pictures (i.e. isolated naming speed) predicted the child’s spontaneous use of labels during a visually presented serial reconstruction task, despite no need for spoken responses. For 6- and 7-year-olds, isolated naming speed also predicted recall. The degree to which verbalization mediated the relation between isolated naming speed and recall changed across development. All relations dissipated by age 10. The same general pattern was observed in an exploratory analysis of delayed recall for which greater demands are placed on rehearsal for item maintenance. Overall, our findings suggest that spontaneous phonological recoding during a standard short-term memory task emerges around age 5, increases in efficiency during the early elementary school years, and is sufficiently automatic by age 10 to support immediate serial recall in most children. Moreover, the findings highlight the need to distinguish between phonological recoding and rehearsal in developmental studies of short-term memory.
Als Ausgangspunkt dieser Arbeit dienen Ansätze, die eine narrative Perspektive für das Verständnis von Psychopathologie und die psychotherapeutische Praxis vorschlagen. Im Hinblick auf die Fragen, welche Vorteile die Analyse von Patient*innenerzählungen bieten kann, und durch welche Merkmale psychopathologische Narrative sich auszeichnen, wird ein Überblick über ausgewählte Fallberichte, empirische Untersuchungen und theoretische Überlegungen gegeben. Diese werden unter den drei Kategorien Kohärenz, „Agency“ und Perspektiven beschrieben. Die Arbeit mag einen Impuls geben, ein tieferes Verständnis für narrative Dysfunktionen zu entwickeln und ihre Ursprünge sowie ihre Bedeutung für psychische Störungen und deren Behandlung vermitteln.
The neural processing of speech and music is still a matter of debate. A long tradition that assumes shared processing capacities for the two domains contrasts with views that assume domain-specific processing. We here contribute to this topic by investigating, in a functional magnetic imaging (fMRI) study, ecologically valid stimuli that are identical in wording and differ only in that one group is typically spoken (or silently read), whereas the other is sung: poems and their respective musical settings. We focus on the melodic properties of spoken poems and their sung musical counterparts by looking at proportions of significant autocorrelations (PSA) based on pitch values extracted from their recordings. Following earlier studies, we assumed a bias of poem-processing towards the left and a bias for song-processing on the right hemisphere. Furthermore, PSA values of poems and songs were expected to explain variance in left- vs. right-temporal brain areas, while continuous liking ratings obtained in the scanner should modulate activity in the reward network. Overall, poem processing compared to song processing relied on left temporal regions, including the superior temporal gyrus, whereas song processing compared to poem processing recruited more right temporal areas, including Heschl's gyrus and the superior temporal gyrus. PSA values co-varied with activation in bilateral temporal regions for poems, and in right-dominant fronto-temporal regions for songs. Continuous liking ratings were correlated with activity in the default mode network for both poems and songs. The pattern of results suggests that the neural processing of poems and their musical settings is based on their melodic properties, supported by bilateral temporal auditory areas and an additional right fronto-temporal network known to be implicated in the processing of melodies in songs. These findings take a middle ground in providing evidence for specific processing circuits for speech and music in the left and right hemisphere, but simultaneously for shared processing of melodic aspects of both poems and their musical settings in the right temporal cortex. Thus, we demonstrate the neurobiological plausibility of assuming the importance of melodic properties in spoken and sung aesthetic language alike, along with the involvement of the default mode network in the aesthetic appreciation of these properties.
"Autonomy is the condition under which what one does reflects who one is" (Weinrib, 2019, p.8). This quote encapsulates the core idea of autonomy, namely the correspondence of one’s inner values with one’s actions. This is a beautiful idea. After all, who wants their actions to be determined or controlled from the outside?
The classical definition of autonomy is precisely about this independence from external circumstances, which Murray (1938) primarily coined. Among other things, Murray characterizes autonomy as resistance to influence and defiance of authority. Similarly, Piaget (1983) describes individuals as autonomous, independent of external influences, in their thinking and actions, and foremost, adult authority. Subsequent work criticized this equation of autonomy with separation or independence (Bekker, 1993; Chirkov et al., 2003; Hmel & Pincus, 2002). In lieu thereof, autonomy is defined as an ability (Chirkov, 2011; Rössler, 2017) and as an essential human need (Ryan & Deci, 2006). Focus is now
on self-governing while relying on rationally determined values to pursue a happy life (Chirkov, 2011). According to Social Determination Theory (SDT), autonomy is about a sense of initiative and responsibility for one’s own actions. The experience of interest and appreciation can strengthen autonomy, whereas experiences of external control, e.g., through rewards or punishments, limit autonomy (Ryan & Deci, 2020). In the psychological discourse of autonomy, SDT is strongly represented (Chirkov et al., 2003; Koestner & Losier, 1996; Weinstein et al., 2012). Notably, SDT distinguishes between autonomy and independence as follows. While a person can autonomously ask for help or rely on others, a person can also be involuntarily alone and independent. Interestingly, these definitions are again closer to its etymological meaning as self-governing, originating from Greek αυτòνoμζ (autonomous).
The two strands of autonomy as independence and autonomy as self-determination are also reflected in the vital differentiation into reactive and reflective autonomy by Koestner and Losier (1996). Resisting external influence, particularly interpersonal in fluence, is what reactive autonomy entails. This interpretation is closely related to the classical concept of autonomy as separation and independence from others (Murray, 1938). On the other hand, reflective autonomy concerns intrapersonal processes, such as self-governing or self-regulation, as defined in Self-Determination Theory (Ryan et al., 2021). In this dissertation, we investigated the concept in three different approaches while focusing on its assessment and operationalization: To begin, in Article 1, we compared the layperson’s and the scientific perspective to each other to gain insight into the characteristics of autonomy. Then, in Articles 2 and 3, we experimentally tested behavioral autonomy as resistance to external influences. Simultaneously, we investigated the link between various autonomy trait measures and autonomous behavior. As a result, in Article 2, we looked at how people reacted to the effects of message framing and sender authority on social distancing behavior during the early COVID-19 pandemic. Finally, in Article 3 we investigated the resistance to a descriptive norm in answering factual questions, in the context of autonomous personality. In our first article, we used a semi-qualitative bottom-up approach to gain insights into the laypersons’ perspective on autonomy and compare it to the scientific notion. We followed a design proposed by Kraft-Todd and Rand (2019) on the term heroism. We derived five components from philosophical and psychological literature: dignity, independence from others, morality, self-awareness, and unconventionality. In three preregistered online studies, we compared these scientific components to the laypersons’ understanding of autonomy. In Study 1, participants (N = 222) listed at least three and up to ten examples of autonomous (self-determined) behaviors. Here, the participants named 807 meaningful examples, which we systematically categorized into 34 representative items for Study 2. Next, new participants (N = 114) rated these regarding their autonomy. Finally, we transferred the five highest-rated autonomy and the five lowest-rated autonomy items to Study 3 (N = 175). We asked participants to rate how strongly the items represented dignity, independence from others, morality, self-awareness, and unconventionality. We found all components to distinguish between high and low autonomy items but not for unconventionality. Thus, we conclude that laypersons’ view corresponds with the scientific characteristics of dignity, independence from others, self-awareness, and morality. A qualitative analysis of the examples also showed that both reactive and reflective definitions of autonomy are prevalent.
Nature affects human well-being in multiple ways. However, the association between species diversity and human well-being at larger spatial scales remains largely unexplored. Here, we examine the relationship between species diversity and human well-being at the continental scale, while controlling for other known drivers of well-being. We related socio-economic data from more than 26,000 European citizens across 26 countries with macroecological data on species diversity and nature characteristics for Europe. Human well-being was measured as self-reported life-satisfaction and species diversity as the species richness of several taxonomic groups (e.g. birds, mammals and trees). Our results show that bird species richness is positively associated with life-satisfaction across Europe. We found a relatively strong relationship, indicating that the effect of bird species richness on life-satisfaction may be of similar magnitude to that of income. We discuss two, non-exclusive pathways for this relationship: the direct multisensory experience of birds, and beneficial landscape properties which promote both bird diversity and people's well-being. Based on these results, this study argues that management actions for the protection of birds and the landscapes that support them would benefit humans. We suggest that political and societal decision-making should consider the critical role of species diversity for human well-being.
Metacognition plays a pivotal role in human development. The ability to realize that we do not know something, or meta-ignorance, emerges after approximately five years of age. We sought for the brain systems that underlie the developmental emergence of this ability in a preschool sample.
Twenty-four children aged between five and six years answered questions under three conditions. In the critical partial knowledge condition, an experimenter first showed two toys to a child, then announced that she would place one of them in a box, out of sight from the child. The experimenter then asked the child whether she knew which toy was in the box.
Children who gave consistently correct answers to this question (n = 9) showed greater cortical thickness in a cluster within left medial orbitofrontal cortex than children who did not (n = 15). Further, seed-based functional connectivity analyses of the brain during resting state revealed that this region is functionally connected to the medial orbitofrontal gyrus, posterior cingulate gyrus and precuneus, and mid- and inferior temporal gyri.
This finding suggests that the default mode network, critically through its prefrontal regions, supports introspective processing. It leads to the emergence of metacognitive monitoring allowing children to explicitly report their own ignorance.
Metacognition plays a pivotal role in human development. The ability to realize that we do not know something, or meta-ignorance, emerges after approximately five years of age. We aimed at identifying the brain systems that underlie the developmental emergence of this ability in a preschool sample.
Twenty-four children aged between five and six years answered questions under three conditions of a meta-ignorance task twice. In the critical partial knowledge condition, an experimenter first showed two toys to a child, then announced that she would place one of them in a box behind a screen, out of sight from the child. The experimenter then asked the child whether or not she knew which toy was in the box.
Children who answered correctly both times to the metacognitive question in the partial knowledge condition (n=9) showed greater cortical thickness in a cluster within left medial orbitofrontal cortex than children who did not (n=15). Further, seed-based functional connectivity analyses of the brain during resting state revealed that this region is functionally connected to the medial orbitofrontal gyrus, posterior cingulate gyrus and precuneus, and mid- and inferior temporal gyri.
This finding suggests that the default mode network, critically through its prefrontal regions, supports introspective processing. It leads to the emergence of metacognitive monitoring allowing children to explicitly report their own ignorance.
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.
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.
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.
The implications of telework are discussed controversially and research on its positive and negative effects has produced contradictory results. We explore voluntariness of employee telework as a boundary condition which may underpin these contradictory findings. Under normal circumstances, individuals who do more telework should perceive fewer disadvantages. However, during the COVID-19 pandemic, employees could no longer voluntarily choose to telecommute, as many organizations were forced to introduce telework by governmental regulations. In two studies, we examine whether the voluntary nature of telework moderates the association between the amount of telework and perceptions of disadvantage. In Study 1, we collected data before and during the COVID-19 pandemic (N = 327). Results show that pre-pandemic participants (who were more likely to voluntarily choose this form of work) reported fewer disadvantages the more telework they did, but this was not the case for employees during the COVID-19 pandemic. To validate these findings, we measured employees’ voluntariness of telework in Study 2 (N = 220). Results support the importance of voluntariness: Individuals who experience a high degree of voluntariness in choosing telework perceive fewer disadvantages the more they telework. However, the amount of telework was not related to reduced perceptions of disadvantages for those who experienced low voluntariness regarding the telecommuting arrangement. Our findings help to understand when telework is related to the perception of disadvantages and they can provide organizations with starting points for practical interventions to reduce the negative effects of telework.
The implications of telework are discussed controversially and research on its positive and negative effects has produced contradictory results. We explore voluntariness of employee telework as a boundary condition which may underpin these contradictory findings. Under normal circumstances, individuals who do more telework should perceive fewer disadvantages. However, during the COVID-19 pandemic, employees could no longer voluntarily choose to telecommute, as many organizations were forced to introduce telework by governmental regulations. In two studies, we examine whether the voluntary nature of telework moderates the association between the amount of telework and perceptions of disadvantage. In Study 1, we collected data before and during the COVID-19 pandemic (N = 327). Results show that pre-pandemic participants (who were more likely to voluntarily choose this form of work) reported fewer disadvantages the more telework they did, but this was not the case for employees during the COVID-19 pandemic. To validate these findings, we measured employees’ voluntariness of telework in Study 2 (N = 220). Results support the importance of voluntariness: Individuals who experience a high degree of voluntariness in choosing telework perceive fewer disadvantages the more they telework. However, the amount of telework was not related to reduced perceptions of disadvantages for those who experienced low voluntariness regarding the telecommuting arrangement. Our findings help to understand when telework is related to the perception of disadvantages and they can provide organizations with starting points for practical interventions to reduce the negative effects of telework.
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.
In many neural systems anatomical motifs are present repeatedly, but despite their structural similarity they can serve very different tasks. A prime example for such a motif is the canonical microcircuit of six-layered neo-cortex, which is repeated across cortical areas, and is involved in a number of different tasks (e.g. sensory, cognitive, or motor tasks). This observation has spawned interest in finding a common underlying principle, a ‘goal function’, of information processing implemented in this structure. By definition such a goal function, if universal, cannot be cast in processing-domain specific language (e.g. ‘edge filtering’, ‘working memory’). Thus, to formulate such a principle, we have to use a domain-independent framework. Information theory offers such a framework. However, while the classical framework of information theory focuses on the relation between one input and one output (Shannon’s mutual information), we argue that neural information processing crucially depends on the combination of multiple inputs to create the output of a processor. To account for this, we use a very recent extension of Shannon Information theory, called partial information decomposition (PID). PID allows to quantify the information that several inputs provide individually (unique information), redundantly (shared information) or only jointly (synergistic information) about the output. First, we review the framework of PID. Then we apply it to reevaluate and analyze several earlier proposals of information theoretic neural goal functions (predictive coding, infomax and coherent infomax, efficient coding). We find that PID allows to compare these goal functions in a common framework, and also provides a versatile approach to design new goal functions from first principles. Building on this, we design and analyze a novel goal function, called ‘coding with synergy’, which builds on combining external input and prior knowledge in a synergistic manner. We suggest that this novel goal function may be highly useful in neural information processing.
Motives motivate human behavior. Most behaviors are driven by more than one motive, yet it is unclear how different motives interact and how such motive combinations affect the neural computation of the behaviors they drive. To answer this question, we induced two prosocial motives simultaneously (multi-motive condition) and separately (single motive conditions). After the different motive inductions, participants performed the same choice task in which they allocated points in favor of the other person (prosocial choice) or in favor of themselves (egoistic choice). We used fMRI to assess prosocial choice-related brain responses and drift diffusion modeling to specify how motive combinations affect individual components of the choice process. Our results showed that the combination of the two motives in the multi-motive condition increased participants’ choice biases prior to the behavior itself. On the neural level, these changes in initial prosocial bias were associated with neural responses in the bilateral dorsal striatum. In contrast, the efficiency of the prosocial decision process was comparable between the multi-motive and the single-motive conditions. These findings provide insights into the computation of prosocial choices in complex motivational states, the motivational setting that drives most human behaviors.
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.
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.
The ability to delay gratification, to wait for a larger but delayed reward in the presence of a smaller but constantly available reward, has been shown to be predictive for various aspects of everyday life. For instance, preschool children who were better able to delay gratification achieved better school grades, a higher education, a better ability to cope with stress, as well as a reduced risk for being overweight or consume drugs up to 30 years later (Mischel et al., 2011). However, despite the importance of delay of gratification cognitive factors underlying individual differences are only poorly understood. Wittmann and Paulus (2008) suggested that individuals who overestimate the duration of time intervals experience waiting times as more costly and are, therefore, less likely to delay gratification. Furthermore, a recent study revealed an association between less accurate internal clock speed and a behavioral choice delay task (Corvi, Juergensen, Weaver, & Demaree, 2012). Further evidence for an association between temporal processing and delay of gratification can be derived from studies using clinical samples. For instance, children with attention-deficit/hyperactivity disorder (ADHD) consistently prefer smaller, immediate rewards over larger, delayed rewards and show impaired temporal processing (Sonuga-Barke, Bitsakou, & Thompson, 2010). However, no study has directly tested an association between a measure of temporal processing and a classical delay of gratification task in children with and without ADHD so far.
As part of a larger study, 64 children (29 with ADHD) aged between 8 to 12 years performed a version of an auditory duration discrimination task and a delay of gratification task. In the duration discrimination task, the children were presented with two unfilled intervals indicated by two brief tones each. The baseline interval lasted for 400 ms, while the comparison interval was always longer and adjusted up or down in 10 ms steps securing an accuracy of 80%. In the delay of gratification task, the children were instructed that they could either opt for one chocolate bar immediately or that they could wait to receive two chocolate bars. Unbeknownst to the children, the waiting time lasted 25 minutes but children were told that they could decide for the immediate chocolate bar at any time by ringing a bell.
Children with ADHD did not differ in their performance from children without ADHD in the duration discrimination task or the delay of gratification task. However, in the whole sample of children with and without ADHD, children who waited for the additional chocolate bar showed a better duration discrimination than children who failed to wait for the additional chocolate bar [t(62) = -2.52, p = .01].
We demonstrated an association between temporal processing ability and the ability to delay gratification. These results need to be replicated in further studies with larger sample sizes. Moreover, different tasks measuring temporal processing and delay of gratification should be used to further clarify the relationship of temporal processing, delay of gratification, and ADHD.
This cross-sectional study examined gender differences between male- and female-typed housework during the early COVID-19 lockdowns in 2020. Participants in Germany, India, Nigeria, and South Africa (N = 823) rated their housework share before and during the lockdown, then speculated about the division of housework performed by men and women in general, before and post-lockdown. Women spent more time on female-typed tasks and men (in Nigeria and South Africa) on male-typed tasks before and during the lockdown. Irrespective of participants’ gender, they speculated that men's and women's housework was more pronounced post-lockdown than before, but we only found gender differences in South Africa and India. Gender role ideology (GRI) moderated the gender‒housework relationship in Germany, but gender did not moderate the paid work hours and housework relationship in any country. Our findings suggest that gendered housework persisted in these countries and raises concerns that this pattern is likely to continue post-lockdown.
Childhood and adolescent sexual abuse (CSA) is a traumatic experience associated with a variety of short- and long-term negative consequences. Theoretical models assume that an abuse related and learned distorted image of sexuality might lead CSA survivors to feel obligated to provide sex or engage in unwanted sexual practices in order to gain affection or prevent abandonment. Dialectical behavioral therapy for posttraumatic stress disorder (DBT-PTSD) is tailored to people with PTSD and comorbid emotion regulation deficits. This case study presents the results of an outpatient DBT-PTSD treatment of an adult patient with posttraumatic stress disorder following sexual and physical abuse. DBT-PTSD was used to treat the patient’s complex psychopathological problems and to decrease her risky sexual behavior, which manifested itself in highly dangerous sexual practices with her partner. The treatment took place over a period of 18 months, with a total of 72 sessions. At the end of the treatment, the patient no longer met criteria for PTSD as indicated by large reductions in the assessments used. Furthermore, she managed to distance herself from risky sexual practices and to remain in a satisfying relationship.
This review provides an overview of the current state of research concerning the role of mental imagery (MI) in mental disorders and evaluates treatment methods for changing MI in childhood. A systematic literature search using PubMed/Medline, Web of Science, and PsycINFO from 1872 to September 2020 was conducted. Fourteen studies were identified investigating MI, and fourteen studies were included referring to interventions for changing MI. Data from the included studies was entered into a data extraction sheet. The methodological quality was then evaluated. MI in childhood is vivid, frequent, and has a significant influence on cognitions and behavior in posttraumatic stress disorder (PTSD), social anxiety disorder (SAD), and depression. The imagery’s perspective might mediate the effect of MI on the intensity of anxiety. Imagery rescripting, emotive imagery, imagery rehearsal therapy, and rational-emotive therapy with imagery were found to have significant effects on symptoms of anxiety disorders and nightmares. In childhood, MI seems to contribute to the maintenance of SAD, PTSD, and depression. If adapted to the developmental stages of children, interventions targeting MI are effective in the treatment of mental disorders.
Based on the stressor-detachment model, previous research has assumed that work-related ICT use in the evening impairs psychological detachment. However, since most of the studies to date have assessed cross-sectional relationships, little is known about the actual direction of effects. In this 5-day diary study, we implemented a day-level longitudinal model to shed light on the causal relationships between work-related ICT use, detachment, and task progress (N = 340 employees, N = 1289 day-level cases). We also investigated the role of unfinished work tasks because we assumed, based on boundary theory, that they are a driving force leading to impaired detachment and work-related ICT use in the evening. Contrary to current research consensus but in line with our expectations, we found that low psychological detachment increased work-related ICT use and task progress. We found no evidence for reversed lagged effects. These results applied both to planned and unplanned ICT use. Furthermore, our results support the notion that unfinished work tasks precede ICT use and detachment. Thus, our findings suggest that work-related ICT use should not be treated as a stressor in its own right in the stressor-detachment model. Instead, it needs to be investigated as a behavioral outcome that employees engage in when they cannot detach from work.
Rezension zu: Social preferences: an introduction to behavioural economics and experimental research, by Michalis Drouvelis, Newcastle upon Tyne: Agenda Publishing, 2021, 205 pages, £22.99, ISBN 978-1-78821-417-9 (paperback).
Adaptive threshold estimation procedures sample close to a subject’s perceptual threshold by dynamically adapting the stimulation based on the subject’s performance. Yet, perceptual thresholds not only depend on the observers’ sensory capabilities but also on any bias in terms of their expectations and response preferences, thus distorting the precision of the threshold estimates. Using the framework of signal detection theory (SDT), independent estimates of both, an observer’s sensitivity and internal processing bias can be delineated from threshold estimates. While this approach is commonly available for estimation procedures engaging the method of constant stimuli (MCS), correction procedures for adaptive methods (AM) are only scarcely applied. In this article, we introduce a new AM that takes individual biases into account, and that allows for a bias-corrected assessment of subjects’ sensitivity. This novel AM is validated with simulations and compared to a typical MCS-procedure, for which the implementation of bias correction has been previously demonstrated.
Comparing AM and MCS demonstrates the viability of the presented AM. Besides its feasibility, the results of the simulation reveal both, advantages, and limitations of the proposed AM. The procedure has considerable practical implications, in particular for the design of shaping procedures in sensory training experiments, in which task difficulty has to be constantly adapted to an observer’s performance, to improve training efficiency.
Innovation is considered essential for today's organizations to survive and thrive. Researchers have also stressed the importance of leadership as a driver of followers' innovative work behavior (FIB). Yet, despite a large amount of research, three areas remain understudied: (a) The relative importance of different forms of leadership for FIB; (b) the mechanisms through which leadership impacts FIB; and (c) the degree to which relationships between leadership and FIB are generalizable across cultures. To address these lacunae, we propose an integrated model connecting four types of positive leadership behaviors, two types of identification (as mediating variables), and FIB. We tested our model in a global data set comprising responses of N = 7,225 participants from 23 countries, grouped into nine cultural clusters. Our results indicate that perceived LMX quality was the strongest relative predictor of FIB. Furthermore, the relationships between both perceived LMX quality and identity leadership with FIB were mediated by social identification. The indirect effect of LMX on FIB via social identification was stable across clusters, whereas the indirect effects of the other forms of leadership on FIB via social identification were stronger in countries high versus low on collectivism. Power distance did not influence the relations.
Objectives: Interpersonal factors, such as impairments in social interaction or lack of social support, have an important share when it comes to the development, maintenance, and progression of various mental disorders.
Methods: Individuals suffering from prolonged grief disorder (PGD) and matched bereaved healthy controls (n = 54) underwent a thorough diagnostic procedure, further completed the Inventory of Interpersonal Problems (IIP-D-32), and participated in a finitely iterated prisoner's dilemma (FIPD).
Results: Individuals suffering from PGD reported significantly more interpersonal problems. Both groups behaved differently in the FIPD with healthy controls being more carefully, adapting their behavior more flexible, whereas PGD patients displayed a lower responsiveness, which may indicate an inability to adapt to changes in relationships.
Conclusion: We conclude that interpersonal problems appear to be a relevant feature of PGD. Future studies need to clarify the causal relation behind this link, and should also include measures of attachment, social support, and disconnectedness.