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Efficient processing of visual environment necessitates the integration of incoming sensory evidence with concurrent contextual inputs and mnemonic content from our past experiences. To delineate how this integration takes place in the brain, we studied modulations of feedback neural patterns in non-stimulated areas of the early visual cortex in humans (i.e., V1 and V2). Using functional magnetic resonance imaging and multivariate pattern analysis, we show that both, concurrent contextual and time-distant mnemonic information, coexist in V1/V2 as feedback signals. The extent to which mnemonic information is reinstated in V1/V2 depends on whether the information is retrieved episodically or semantically. These results demonstrate that our stream of visual experience contains not just information from the visual surrounding, but also memory-based predictions internally generated in the brain.
Systemic therapy considers the complex dynamics of relational factors and resources contributing to psychological symptoms. Negative maintaining factors have been well researched for people suffering from Alcohol-use Disorders (AUD). However, we know little about the complex dynamics of these negative factors and resources. We interviewed fifty-five participants suffering or fully remitted from Alcohol-use disorders in this cross-sectional study (M = 52 years; 33% female). The interviews focused on relational factors (e.g., social support and social negativity) referring to a Support Social Network and a Craving Social Network (CSN). The CSN included all significant others who were associated with craving situations. We compared the network characteristics of the group suffering from Alcohol-use Disorders (n = 38) to a fully remitted control group (n = 17). The abstinent group with full remission named on average fewer individuals in the CSNs. They had lower social negativity mean scores in the Support Social Network compared to the non-remitted group (d = 0.74). In the CSN, the mean scores of social support were significantly higher than the median for both groups (d = 2.50). These findings reveal the complex interplay of relational patterns contributing to the etiology, maintenance, and recovery from Alcohol-use disorders. A successful recovery can be linked to increased social resources and reduced relations associated with craving. However, craving-associated relations represent an important source of social support. Future research should investigate this ambivalence for the systemic perspective on the explanation and treatment of Alcohol-use disorders.
Cultural and biographical influences on the expression of emotions manifest themselves in so-called “display rules.” These rules determine the time, intensity, and situations in which an emotion is expressed. To date, only a small number of empirical studies deal with this transformation of how migrants, who are faced with a new culture, may change their emotional expression. The present, cross-sectional study focuses on changes in anger expression as part of a complex acculturation process among Iranian migrants. To this end, Iranian citizens in Iran (n = 61), German citizens (n = 61), and Iranian migrants in Germany (n = 60) were compared in terms of anger expression behavior and acculturation strategy (assimilation, separation, integration, marginalization) was assessed among the migrants, using the Frankfurt Acculturation Scale (FRACC). A questionnaire developed in a preliminary study was used to measure anger expression via subjective anger experience and anger expression within 16 hypothetical situations. Multivariate Analyses of Variance (MANOVA) revealed that Iranians and Iranian migrants reported higher anger experience ratings than Germans and directed their anger more often inward (anger-in). Further findings suggest that transformation processes may have affected Iranian migrants in terms of suppressed anger (anger-in): Iranian migrants with a higher orientation toward German culture reported lower average anger-in scores. These results suggest that there was different emotional expression among Iranian migrants, depending on their acculturation. The results provide new insight into socio-cultural and individual adjustment processes.
Trajectories of internalizing disorders and behavioral addictions are still largely unknown. Research shows that both disorders are highly comorbid. Previous longitudinal studies have focused on associations between internalizing disorders and behavioral addictions using screening instruments. Our aim was to develop and examine a theory-based model of trajectories, according to which internalizing disorders foster symptoms of Internet use disorders, mediated by a reward deprivation and maladaptive emotion regulation. We applied clinically relevant measures for depression and social anxiety in a prospective longitudinal study with a 12-month follow-up investigation. On the basis of an at-risk population of 476 students (mean age = 14.99 years, SD = 1.99), we investigated the predictive influence of clinically relevant depression and social anxiety at baseline (t1) on Internet use disorder symptoms at 12-month follow-up (t2) using multiple linear regression analyses. Our results showed that both clinically relevant depression and social anxiety significantly predicted symptom severity of Internet use disorders one year later after controlling for baseline symptoms of Internet use disorders, gender and age. These results remained robust after including both depression and social anxiety simultaneously in the model, indicating an independent influence of both predictors on Internet use disorder symptoms. The present study enhances knowledge going beyond a mere association between internalizing disorders and Internet use disorders. To our knowledge, this is the first study investigating clinically relevant depression and social anxiety to predict future Internet use disorder symptoms at 12-month follow-up. In line with our model of trajectories, a significant temporal relationship between clinically relevant internalizing disorders and Internet use disorder symptoms at 12-month follow-up was confirmed. Further studies should investigate the mediating role of reward deprivation and maladaptive emotion regulation, as postulated in our model. One implication of these findings is that clinicians should pay particular attention to the increased risk of developing behavioral addictions for adolescents with depression and social anxiety.
Interest is an important factor for successful learning that has been the subject of intensive research for decades. Although interest in nature is of great importance for environmental education, to date there is no valid and reliable measurement tool. Therefore, the purpose of this study was to develop and test a scale for interest in nature, the Nature Interest Scale (NIS). In study 1, nine items were selected based on the three dimensions of the psychological interest construct to represent interest in nature. The factor structure of this new measurement instrument, was tested using confirmatory factor analyses. The results show that the instrument represents the three dimensions of the interest construct well. In study 2 the validity (discriminant and convergent validity) as well as the reliability (internal consistency, composite reliability, test-retest reliability) of the NIS were demonstrated. In study 3, the applicability of the NIS was tested with a different target group, students with learning disabilities. The results of this factor analysis also confirm the factor structure of the scale. Thus, this study provides a valid and reliable measurement tool for individual interest in nature that can be used for future research.
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.