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In social interaction, age-related differences in emotional processing may lead to varied social decision making between young and older adults. However, previous studies of social decision making have paid less attention to the interactants' emotions, leaving age differences and underlying neural mechanisms unexplored. To address this gap, the present study combined functional and structural magnetic resonance imaging, employing a modified dictator game task with recipients displaying either neutral or sad facial expressions. Behavioral results indicated that although older adults' overall allocations did not differ significantly from those of young adults, older adults' allocations showing a decrease in emotion-related generosity compared to young adults. Using representational similarity analysis, we found that older adults showed reduced neural representations of recipients' emotions and gray matter volume in the right anterior cingulate gyrus (ACC), right insula, and left dorsomedial prefrontal cortex (DMPFC) compared to young adults. More importantly, mediation analyses indicated that age influenced allocations not only through serial mediation of neural representations of the right insula and left DMPFC, but also through serial mediation of the mean gray matter volume of the right ACC and left DMPFC. This study identifies the potential neural pathways through which age affects emotion-related social decision making, advancing our understanding of older adults' social interaction behavior that they may not be less generous unless confronted with individuals with specific emotions.

The structure of large-scale intrinsic connectivity networks is atypical in adolescents diagnosed with autism spectrum disorder (ASD or autism). However, the degree to which alterations occur in younger children, and whether these differences vary by sex, is unknown. We utilized structural magnetic resonance imaging (MRI) data from a sex- and age- matched sample of 122 autistic and 122 typically developing (TD) children (2-4 years old) to investigate differences in underlying network structure in preschool-aged autistic children within three large scale intrinsic connectivity networks implicated in ASD: the Socioemotional Salience, Executive Control, and Default Mode Networks. Utilizing structural covariance MRI (scMRI), we report network-level differences in autistic versus TD children, and further report preliminary findings of sex-dependent differences within network topology.

• Task-preferential modulations of functional connectivity via white matter are visualized. • Task-preferential connectivity enhancement occurs hundreds of ms before overt response. • Reading preferentially enhances connectivity from left occipital-temporal areas. • Stroop task preferentially enhances connectivity from left middle frontal gyrus. Cognitive control processes enable the suppression of automatic behaviors and the initiation of appropriate responses. The Stroop color naming task serves as a benchmark paradigm for understanding the neurobiological model of verbal cognitive control. Previous research indicates a predominant engagement of the prefrontal and premotor cortex during the Stroop task compared to reading. We aim to further this understanding by creating a dynamic atlas of task-preferential modulations of functional connectivity through white matter. Patients undertook word-reading and Stroop tasks during intracranial EEG recording. We quantified task-related high-gamma amplitude modulations at 547 nonepileptic electrode sites, and a mixed model analysis identified regions and timeframes where these amplitudes differed between tasks. We then visualized white matter pathways with task-preferential functional connectivity enhancements at given moments. Word reading, compared to the Stroop task, exhibited enhanced functional connectivity in inter- and intra-hemispheric white matter pathways from the left occipital-temporal region 350–600 ms before response, including the posterior callosal fibers as well as the left vertical occipital, inferior longitudinal, inferior fronto-occipital, and arcuate fasciculi. The Stroop task showed enhanced functional connectivity in the pathways from the left middle-frontal pre-central gyri, involving the left frontal u-fibers and anterior callosal fibers. Automatic word reading largely utilizes the left occipital-temporal cortices and associated white matter tracts. Verbal cognitive control predominantly involves the left middle frontal and precentral gyri and its connected pathways. Our dynamic tractography atlases may serve as a novel resource providing insights into the unique neural dynamics and pathways of automatic reading and verbal cognitive control. [ABSTRACT FROM AUTHOR]

• Left-lateralized occipito-frontal functional connectivity correlated with individual Braille reading proficiency. • Increased bidirectional LOC-IFC information flow with predominant top-down communication emerged in a natural Braille reading task. • Greater top-down modulation contributed to higher Braille reading proficiency. • A 'two-tale' model of the LOC-IFC neural link better predicts individual differences in natural Braille reading among late blind people. Natural Braille reading presents significant challenges to the brain networks of late blind individuals, yet its underlying neural mechanisms remain largely unexplored. Using natural Braille texts in behavioral assessments and functional MRI, we sought to pinpoint the neural pathway and information flow crucial for Braille reading performance in late blind individuals. In the resting state, we discovered a unique neural connection between the higher-order 'visual' cortex, the lateral occipital cortex (LOC), and the inferior frontal cortex (IFC) in late blind individuals, but not in sighted controls. The left-lateralized LOC-IFC connectivity was correlated with individual Braille reading proficiency. Prolonged Braille reading practice led to increased strength of this connectivity. During a natural Braille reading task, bidirectional information flow between the LOC and the IFC was positively modulated, with a predominantly stronger top-down modulation from the IFC to the LOC. This stronger top-down modulation contributed to higher Braille reading proficiency. We thus proposed a two-predictor multiple regression model to predict individual Braille reading proficiency, incorporating both static connectivity and dynamic top-down communication between the LOC-IFC link. This work highlights the dual contributions of the occipito-frontal neural pathway and top-down cognitive strategy to superior natural Braille reading performance, offering guidance for training late blind individuals. [ABSTRACT FROM AUTHOR]

Individuals at clinical high-risk (CHR) for psychosis are characterized by attenuated psychotic symptoms. Only a minority of CHR individuals convert to full-blown psychosis. Therefore, there is a strong interest in identifying neurobiological abnormalities underlying the psychosis risk syndrome. Dynamic functional connectivity (DFC) captures time-varying connectivity over short time scales, and has the potential to reveal complex brain functional organization. Based on resting-state functional magnetic resonance imaging (fMRI) data from 70 healthy controls (HCs), 53 CHR individuals, and 58 early illness schizophrenia (ESZ) patients, we applied a novel group information guided ICA (GIG-ICA) to estimate inherent connectivity states from DFC, and then investigated group differences. We found that ESZ patients showed more aberrant connectivities and greater alterations than CHR individuals. Results also suggested that disease-related connectivity states occurred in CHR and ESZ groups. Regarding the dominant state with the highest contribution to dynamic connectivity, ESZ patients exhibited greater impairments than CHR individuals primarily in the cerebellum, frontal cortex, thalamus and temporal cortex, while CHR and ESZ populations shared common aberrances mainly in the supplementary motor area, parahippocampal gyrus and postcentral cortex. CHR-specific changes were also found in the connections between the superior frontal gyrus and calcarine cortex in the dominant state. Our findings suggest that CHR individuals generally show an intermediate functional connectivity pattern between HCs and SZ patients but also have unique connectivity alterations.

• Age differences in emotion-related social decisions were examined. • Older adults showed a decline in emotion-related generosity. • Multimodal neuroimaging was used to uncover potential neural bases. • The potential neural pathways were identified. In social interaction, age-related differences in emotional processing may lead to varied social decision making between young and older adults. However, previous studies of social decision making have paid less attention to the interactants' emotions, leaving age differences and underlying neural mechanisms unexplored. To address this gap, the present study combined functional and structural magnetic resonance imaging, employing a modified dictator game task with recipients displaying either neutral or sad facial expressions. Behavioral results indicated that although older adults' overall allocations did not differ significantly from those of young adults, older adults' allocations showing a decrease in emotion-related generosity compared to young adults. Using representational similarity analysis, we found that older adults showed reduced neural representations of recipients' emotions and gray matter volume in the right anterior cingulate gyrus (ACC), right insula, and left dorsomedial prefrontal cortex (DMPFC) compared to young adults. More importantly, mediation analyses indicated that age influenced allocations not only through serial mediation of neural representations of the right insula and left DMPFC, but also through serial mediation of the mean gray matter volume of the right ACC and left DMPFC. This study identifies the potential neural pathways through which age affects emotion-related social decision making, advancing our understanding of older adults' social interaction behavior that they may not be less generous unless confronted with individuals with specific emotions. [ABSTRACT FROM AUTHOR]

• Our study utilized stereo-electroencephalogram to investigate the dynamic interaction between attentional control and habituation processes in the prefrontal cortex, providing insights into how these fundamental mechanisms synergize during cognitive tasks. • Two distinct neural pathways within the subregions of prefrontal cortex are identified – a bottom-up dominant pathway orchestrated by the IFG, facilitating habitual responses, and a top-down dominant pathway modulated by the OFC, enabling attentional control to override ingrained habits. • Through an information model, we unveil unique patterns of information flow within the subregions of prefrontal cortex, particularly during color-word congruent and incongruent conditions, contributing to a comprehensive understanding of attentional regulation mechanisms. Attentional control, guided by top-down processes, enables selective focus on pertinent information, while habituation, influenced by bottom-up factors and prior experiences, shapes cognitive responses by emphasizing stimulus relevance. These two fundamental processes collaborate to regulate cognitive behavior, with the prefrontal cortex and its subregions playing a pivotal role. Nevertheless, the intricate neural mechanisms underlying the interaction between attentional control and habituation are still a subject of ongoing exploration. To our knowledge, there is a dearth of comprehensive studies on the functional connectivity between subsystems within the prefrontal cortex during attentional control processes in both primates and humans. Utilizing stereo-electroencephalogram (SEEG) recordings during the Stroop task, we observed top-down dominance effects and corresponding connectivity patterns among the orbitofrontal cortex (OFC), the middle frontal gyrus (MFG), and the inferior frontal gyrus (IFG) during heightened attentional control. These findings highlighting the involvement of OFC in habituation through top-down attention. Our study unveils unique connectivity profiles, shedding light on the neural interplay between top-down and bottom-up attentional control processes, shaping goal-directed attention. [ABSTRACT FROM AUTHOR]

Children with chromosome 22q11.2 deletion syndrome (22q11.2DS), Fragile X syndrome (FXS), or Turner syndrome (TS) are considered to belong to distinct genetic groups, as each disorder is caused by separate genetic alterations. Even so, they have similar cognitive and behavioral dysfunctions, particularly in visuospatial and numerical abilities. To assess evidence for common underlying neural microstructural alterations, we set out to determine whether these groups have partially overlapping white matter abnormalities, relative to typically developing controls. We scanned 101 female children between 7 and 14years old: 25 with 22q11.2DS, 18 with FXS, 17 with TS, and 41 aged-matched controls using diffusion tensor imaging (DTI). Anisotropy and diffusivity measures were calculated and all brain scans were nonlinearly aligned to population and site-specific templates. We performed voxel-based statistical comparisons of the DTI-derived metrics between each disease group and the controls, while adjusting for age. Girls with 22q11.2DS showed lower fractional anisotropy (FA) than controls in the association fibers of the superior and inferior longitudinal fasciculi, the splenium of the corpus callosum, and the corticospinal tract. FA was abnormally lower in girls with FXS in the posterior limbs of the internal capsule, posterior thalami, and precentral gyrus. Girls with TS had lower FA in the inferior longitudinal fasciculus, right internal capsule and left cerebellar peduncle. Partially overlapping neurodevelopmental anomalies were detected in all three neurogenetic disorders. Altered white matter integrity in the superior and inferior longitudinal fasciculi and thalamic to frontal tracts may contribute to the behavioral characteristics of all of these disorders.

The brain is a complex, dynamic organ that shows differences in the same subject at various periods. Understanding how brain activity changes across age as a function of the brain networks has been greatly abetted by fMRI. Canonical analysis consists of determining how alterations in connectivity patterns (CPs) of certain regions are affected. An alternative approach is taken here by not considering connectivity but rather features computed from recordings at the regions of interest (ROIs). Using machine learning (ML) we assess how neural signals are altered by and prospectively predictive of age and sex via a methodology that is novel in drawing upon pairwise classification across six decades of subjects' chronological ages. ML is used to answer the equally important questions of what properties of the computed features are most predictive as well as which brain networks are most affected by aging. It was found that there is decreased differentiation among the neural signals of older subjects that are separated in age by the same number of years as younger subjects. Furthermore, the burstiness of the signals change at different rates between males and females. The findings provide insight into brain aging via an ROI-based analysis, the consideration of several feature groups, and a novel classification-based ML pipeline. There is also a contribution to understanding the effects of data aggregated from different recording centers on the conclusions of fMRI studies., Competing Interests: Declaration of competing interest The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 The Author. Published by Elsevier Inc. All rights reserved.)

The corticospinal tracts and the basal ganglia continue to develop during childhood and adolescence, and indices of their maturation can be obtained using diffusion-weighted imaging. Here we show that a simple measure of visuomotor function is correlated with diffusion parameters in the corticospinal tracts and neostriatum. In a cohort of 75 typically-developing children aged 7 to 13years, mean 5-choice reaction times (RTs) were assessed. We hypothesised that children with faster choice RTs would show lower mean diffusivity (MD) in the corticospinal tracts and neostriatum and higher fractional anisotropy (FA) in the corticospinal tracts, after controlling for age, gender, and handedness. Mean MD and/or FA were extracted from the right and left corticospinal tracts, putamen, and caudate nuclei. As predicted, faster 5-choice RTs were associated with lower MD in the corticospinal tracts, putamen, and caudate. MD effects on RT were bilateral in the corticospinal tracts and putamen, whilst right caudate MD was more strongly related to performance than was left caudate MD. Our results suggest a link between motor performance variability in children and diffusivity in the motor system, which may be related to: individual differences in the phase of fibre tract and neostriatal maturation in children of similar age, individual differences in motor experience during childhood (i.e., use-dependent plasticity), and/or more stable individual differences in the architecture of the motor system.

For information from sensory organs to be processed by the brain, it is usually passed to appropriate areas of the cerebral cortex. Almost all of this information passes through the thalamus, a relay structure that reciprocally connects to the vast majority of the cortex. The thalamus facilitates this information transfer through a set of thalamocortical connections that vary in cellular structure, molecular profiles, innervation patterns, and firing rates. Additionally, corticothalamic connections allow for intracortical information transfer through the thalamus. These efferent and afferent connections between the thalamus and cortex have been the focus of many studies, and the importance of cortical connectivity in defining thalamus anatomy is demonstrated by multiple studies that parcellate the thalamus based on cortical connectivity profiles. Here, we examine correlated morphological variation between the thalamus and cortex, or thalamocortical structural covariance. For each voxel in the thalamus as a seed, we construct a cortical structural covariance map that represents correlated cortical volume variation, and examine whether high structural covariance is observed in cortical areas that are functionally relevant to the seed. Then, using these cortical structural covariance maps as features, we subdivide the thalamus into six non-overlapping regions (clusters of voxels), and assess whether cortical structural covariance is associated with cortical connectivity that specifically originates from these regions. We show that cortical structural covariance is high in areas of the cortex that are functionally related to the seed voxel, cortical structural covariance varies along cortical depth, and sharp transitions in cortical structural covariance profiles are observed when varying seed locations in the thalamus. Subdividing the thalamus based on structural covariance, we additionally demonstrate that the six thalamic clusters of voxels stratify cortical structural covariance along the dorsal-ventral, medial-lateral, and anterior-posterior axes. These cluster-associated structural covariance patterns are prominently detected in cortical regions innervated by fibers projecting out of their related thalamic subdivisions. Together, these results advance our understanding of how the thalamus and the cortex couple in their volumes. Our results indicate that these volume correlations reflect functional organization and structural connectivity, and further provides a novel segmentation of the mouse thalamus that can be used to examine thalamic structural variation and thalamocortical structural covariation in disease models., Competing Interests: Declaration of competing interest None., (Copyright © 2023. Published by Elsevier Inc.)

The role of the thalamus in mediating the effects of lysergic acid diethylamide (LSD) was recently proposed in a model of communication and corroborated by imaging studies. However, a detailed analysis of LSD effects on nuclei-resolved thalamocortical connectivity is still missing. Here, in a group of healthy volunteers, we evaluated whether LSD intake alters the thalamocortical coupling in a nucleus-specific manner. Structural and resting-state functional Magnetic Resonance Imaging (MRI) data were acquired in a placebo-controlled study on subjects exposed to acute LSD administration. Structural MRI was used to parcel the thalamus into its constituent nuclei based on individual anatomy. Nucleus-specific changes of resting-state functional MRI (rs-fMRI) connectivity were mapped using a seed-based approach. LSD intake selectively increased the thalamocortical functional connectivity (FC) of the ventral complex, pulvinar, and non-specific nuclei. Functional coupling was increased between these nuclei and sensory cortices that include the somatosensory and auditory networks. The ventral and pulvinar nuclei also exhibited increased FC with parts of the associative cortex that are dense in serotonin type 2A receptors. These areas are hyperactive and hyper-connected upon LSD intake. At subcortical levels, LSD increased the functional coupling among the thalamus's ventral, pulvinar, and non-specific nuclei, but decreased the striatal-thalamic connectivity. These findings unravel some LSD effects on the modulation of subcortical-cortical circuits and associated behavioral outputs., Competing Interests: Declaration of Competing Interest Robin Carhart-Harris is a scientific advisor to TRYP, Mydecine, Usona Institute, Synthesis Institute, Journey Collab', Journey Space, Osmind, Maya Health, Beckley Psytech, Anuma, MindState, Entheos Labs. The authors declare no conflict of interest., (Copyright © 2023. Published by Elsevier Inc.)

fMRI of the human brain reveals spatiotemporal patterns of functional connectivity (FC), forming distinct cortical networks. Lately, subcortical contributions to these configurations are receiving renewed interest, but investigations rarely focus explicitly on their effects on cortico-cortical FC. Here, we employ a straightforward multivariable approach and graph-theoretic tools to assess subcortical impact on topological features of cortical networks. Given recent evidence showing that structures like the thalamus and basal ganglia integrate input from multiple networks, we expect increased segregation between cortical networks after removal of subcortical effects on their FC patterns. We analyze resting state data of young and healthy participants (male and female; N = 100) from the human connectome project. We find that overall, the cortical network architecture becomes less segregated, and more integrated, when subcortical influences are accounted for. Underlying these global effects are the following trends: 'Transmodal' systems become more integrated with the rest of the network, while 'unimodal' networks show the opposite effect. For single nodes this hierarchical organization is reflected by a close correspondence with the spatial layout of the principal gradient of FC (Margulies et al., 2016). Lastly, we show that the limbic system is significantly less coherent with subcortical influences removed. The findings are validated in a (split-sample) replication dataset. Our results provide new insight regarding the interplay between subcortex and cortical networks, by putting the integrative impact of subcortex in the context of macroscale patterns of cortical organization., Competing Interests: Declaration of Competing Interest The authors declare that they have no competing financial or personal interests that might have influenced the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)

The human structural brain network, or connectome, has a rich-club organization with a small number of brain regions showing high network connectivity, called hubs. Hubs are centrally located in the network, energy costly, and critical for human cognition. Aging has been associated with changes in brain structure, function, and cognitive decline, such as processing speed. At a molecular level, the aging process is a progressive accumulation of oxidative damage, which leads to subsequent energy depletion in the neuron and causes cell death. However, it is still unclear how age affects hub connections in the human connectome. The current study aims to address this research gap by constructing structural connectome using fiber bundle capacity (FBC). FBC is derived from Constrained Spherical Deconvolution (CSD) modeling of white-matter fiber bundles, which represents the capacity of a fiber bundle to transfer information. Compared to the raw number of streamlines, FBC is less bias for quantifying connection strength within biological pathways. We found that hubs exhibit longer-distance connections and higher metabolic rates compared to peripheral brain regions, suggesting that hubs are biologically costly. Although the landscape of structural hubs was relatively age-invariant, there were wide-spread age effects on FBC in the connectome. Critically, these age effects were larger in connections within hub compared to peripheral brain connections. These findings were supported by both a cross-sectional sample with wide age-range (N = 137) and a longitudinal sample across 5 years (N = 83). Moreover, our results demonstrated that associations between FBC and processing speed were more concentrated in hub connections than chance level, and FBC in hub connections mediated the age-effects on processing speed. Overall, our findings indicate that structural connections of hubs, which demonstrate greater energy demands, are particular vulnerable to aging. The vulnerability may contribute to age-related impairments in processing speed among older adults., Competing Interests: Declaration of Competing Interest The authors state that there are no actual or potential conflicts of interest associated with the research., (Copyright © 2023. Published by Elsevier Inc.)

Cognitive control is of great plasticity. Training programs targeted on improving it have been suggested to yield neural changes in the brain. However, until recently, the relationship between training-induced brain changes and improvements in cognitive control is still an open issue. Besides, although the literature has attributed the operation of cognitive control to interactions between large-scale networks, the neural pathways directly associated with it remain unclear. The current study aimed to examine these issues by focusing on conflict processing. In particular, we employed a training program with a randomized controlled design. The main findings were as follows: 1) In behavior, the training group showed reduced conflict effect after training, relative to the control group; 2) In the pretest stage, the behavioral conflict effect was negatively correlated with a number of neural pathways, including the connectivity from the cingulo-opercular network (CON) to the cerebellum and to sub-regions of the dorsal visual network; 3) increase in the connectivity strength of several network interactions, such as the connectivity from the CON to the cerebellum and to the primary visual network, was associated with behavioral gains; 4) there were also nonlinear correlations between behavioral and neural changes. These findings highlighted a critical role of the modulation of CON on other networks in mediating conflict processing and its plasticity, and raised the significance of investigating nonlinear relationship in the field of cognitive training. [ABSTRACT FROM AUTHOR]

Musicians are highly trained to discriminate fine pitch changes but the neural bases of this ability are poorly understood. It is unclear whether such training-dependent differences in pitch processing arise already in the subcortical auditory system or are linked to more central stages. To address this question, we combined psychoacoustic testing with functional MRI to measure cortical and subcortical responses in musicians and non-musicians during a pitch-discrimination task. First, we estimated behavioral pitch-discrimination thresholds for complex tones with harmonic components that were either resolved or unresolved in the auditory system. Musicians outperformed non-musicians, showing lower pitch-discrimination thresholds in both conditions. The same participants underwent task-related functional MRI, while they performed a similar pitch-discrimination task. To account for the between-group differences in pitch-discrimination, task difficulty was adjusted to each individual's pitch-discrimination ability. Relative to non-musicians, musicians showed increased neural responses to complex tones with either resolved or unresolved harmonics especially in right-hemispheric areas, comprising the right superior temporal gyrus, Heschl's gyrus, insular cortex, inferior frontal gyrus, and in the inferior colliculus. Both subcortical and cortical neural responses predicted the individual pitch-discrimination performance. However, functional activity in the inferior colliculus correlated with differences in pitch discrimination across all participants, but not within the musicians group alone. Only neural activity in the right auditory cortex scaled with the fine pitch-discrimination thresholds within the musicians. These findings suggest two levels of neuroplasticity in musicians, whereby training-dependent changes in pitch processing arise at the collicular level and are preserved and further enhanced in the right auditory cortex. [ABSTRACT FROM AUTHOR]

Cognitive control is a construct that refers to the set of functions that enable decision-making and task performance through the representation of task states, goals, and rules. The neural correlates of cognitive control have been studied in humans using a wide variety of neuroimaging modalities, including structural MRI, resting-state fMRI, and task-based fMRI. The results from each of these modalities independently have implicated the involvement of a number of brain regions in cognitive control, including dorsal prefrontal cortex, and frontal parietal and cingulo-opercular brain networks. However, it is not clear how the results from a single modality relate to results in other modalities. Recent developments in multimodal image analysis methods provide an avenue for answering such questions and could yield more integrated models of the neural correlates of cognitive control. In this study, we used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) to identify multimodal patterns of variation related to cognitive control. We used two independent cohorts of participants from the Human Connectome Project, each of which had data from four imaging modalities. We replicated the findings from the first cohort in the second cohort using both independent and predictive analyses. The independent analyses identified a component in each cohort that was highly similar to the other and significantly correlated with cognitive control performance. The replication by prediction analyses identified two independent components that were significantly correlated with cognitive control performance in the first cohort and significantly predictive of performance in the second cohort. These components identified positive relationships across the modalities in neural regions related to both dynamic and stable aspects of task control, including regions in both the frontal-parietal and cingulo-opercular networks, as well as regions hypothesized to be modulated by cognitive control signaling, such as visual cortex. Taken together, these results illustrate the potential utility of multi-modal analyses in identifying the neural correlates of cognitive control across different indicators of brain structure and function. [ABSTRACT FROM AUTHOR]

Research into visual neural activity has focused almost exclusively on onset- or change-driven responses and little is known about how information is encoded in the brain during sustained periods of visual perception. We used intracranial recordings in humans to determine the degree to which the presence of a visual stimulus is persistently encoded by neural activity. The correspondence between stimulus duration and neural response duration was strongest in early visual cortex and gradually diminished along the visual hierarchy, such that is was weakest in inferior-temporal category-selective regions. A similar posterior-anterior gradient was found within inferior temporal face-selective regions, with posterior but not anterior sites showing persistent face-selective activity. The results suggest that regions that appear uniform in terms of their category selectivity are dissociated by how they temporally represent a stimulus in support of ongoing visual perception, and delineate a large-scale organizing principle of the ventral visual stream. [ABSTRACT FROM AUTHOR]

Characterizing how representations of moral violations are organized, cognitively and neurally, is central to understanding how people conceive and judge them. Past work has identified brain regions that represent morally relevant features and distinguish moral domains, but has not yet advanced a broader account of where and on what basis neural representations of moral violations are organized. With searchlight representational similarity analysis, we investigate where category membership drives similarity in neural patterns during moral judgment of violations from two key moral domains: Harm and Purity. Representations converge across domains in a network of regions resembling the mentalizing network. However, Harm and Purity violation representations respectively converge in different regions: precuneus (PC) and left inferior frontal gyrus (LIFG). Examining substructure within moral domains, Harm violations converge in PC regardless of subdomain (physical harms, psychological harms), while Purity subdomains (pathogen-related violations, sex-related violations) converge in distinct sets of regions – mirroring a dissociation observed in principal-component analysis of behavioral data. Further, we find initial evidence for representation of morally relevant features within these two domain-encoding regions. The present analyses offer a case study for understanding how organization within the complex conceptual space of moral violations is reflected in the organization of neural patterns across the cortex. [ABSTRACT FROM AUTHOR]

A major goal in neuroscience is to understand the neural pathways underlying human behavior. We introduce the recently developed Joint and Individual Variation Explained (JIVE) method to the neuroscience community to simultaneously analyze imaging and behavioral data from the Human Connectome Project. Motivated by recent computational and theoretical improvements in the JIVE approach, we simultaneously explore the joint and individual variation between and within imaging and behavioral data. In particular, we demonstrate that JIVE is an effective and efficient approach for integrating task fMRI and behavioral variables using three examples: one example where task variation is strong, one where task variation is weak and a reference case where the behavior is not directly related to the image. These examples are provided to visualize the different levels of signal found in the joint variation including working memory regions in the image data and accuracy and response time from the in-task behavioral variables. Joint analysis provides insights not available from conventional single block decomposition methods such as Singular Value Decomposition. Additionally, the joint variation estimated by JIVE appears to more clearly identify the working memory regions than Partial Least Squares (PLS), while Canonical Correlation Analysis (CCA) gives grossly overfit results. The individual variation in JIVE captures the behavior unrelated signals such as a background activation that is spatially homogeneous and activation in the default mode network. The information revealed by this individual variation is not examined in traditional methods such as CCA and PLS. We suggest that JIVE can be used as an alternative to PLS and CCA to improve estimation of the signal common to two or more datasets and reveal novel insights into the signal unique to each dataset. [ABSTRACT FROM AUTHOR]

Learning and speaking a second language (L2) may result in profound changes in the human brain. Here, we investigated local structural differences along two language-related white matter trajectories, the arcuate fasciculus and the inferior fronto-occipital fasciculus (IFOF), between early simultaneous bilinguals and late sequential bilinguals. We also examined whether early exposure to two languages might lead to a more bilateral structural organization of the arcuate fasciculus. Fractional anisotropy, mean and radial diffusivities (FA, MD, and RD respectively) were extracted to analyse tract-specific changes. Additionally, global voxel-wise effects were investigated with Tract-Based Spatial Statistics (TBSS). We found that relative to late exposure, early exposure to L2 leads to increased FA along a phonology-related segment of the arcuate fasciculus, but induces no modulations along the IFOF, associated to semantic processing. Late sequential bilingualism, however, was associated with decreased MD along the bilateral IFOF. Our results suggest that early vs. late bilingualism may lead to qualitatively different kind of changes in the structural language-related network. Furthermore, we show that early bilingualism contributes to the structural laterality of the arcuate fasciculus, leading to a more bilateral organization of these perisylvian language-related tracts. [ABSTRACT FROM AUTHOR]

Mechanisms of attention assign priority to sensory inputs on the basis of current task goals. Previous studies have shown that lateralized neural oscillations within the alpha (8–14 Hz) range are associated with the voluntary allocation of attention to the contralateral visual field. It is currently unknown, however, whether similar oscillatory signatures instantiate the involuntary capture of spatial attention by goal-relevant stimulus properties. Here we investigated the roles of theta (4–8 Hz), alpha, and beta (14–30 Hz) oscillations in human goal-directed visual attention. Across two experiments, we had participants respond to a brief target of a particular color among heterogeneously colored distractors. Prior to target onset, we cued one location with a lateralized, non-predictive cue that was either target- or non-target-colored. During the behavioral task, we recorded brain activity using electroencephalography (EEG), with the aim of analyzing cue-elicited oscillatory activity. We found that theta oscillations lateralized in response to all cues, and this lateralization was stronger if the cue matched the target color. Alpha oscillations lateralized relatively later, and only in response to target-colored cues, consistent with the capture of spatial attention. Our findings suggest that stimulus induced changes in theta and alpha amplitude reflect task-based modulation of signals by feature-based and spatial attention, respectively. [ABSTRACT FROM AUTHOR]

Visual scenes are initially processed via segregated neural pathways dedicated to either of the two visual hemifields. Although higher-order visual areas are generally believed to utilize invariant object representations (abstracted away from features such as stimulus position), recent findings suggest they retain more spatial information than previously thought. Here, we assessed the nature of such higher-order object representations in human cortex using high-resolution fMRI at 7T, supported by corroborative 3T data. We show that multi-voxel activation patterns in both the contra- and ipsilateral hemisphere can be exploited to successfully classify the object category of unilaterally presented stimuli. Moreover, robustly identified rank order-based response profiles demonstrated a strong contralateral bias which frequently outweighed object category preferences. Finally, we contrasted different combinatorial operations to predict the responses during bilateral stimulation conditions based on responses to their constituent unilateral elements. Results favored a max operation predominantly reflecting the contralateral stimuli. The current findings extend previous work by showing that configuration-dependent modulations in higher-order visual cortex responses as observed in single unit activity have a counterpart in human neural population coding. They furthermore corroborate the emerging view that position coding is a fundamental functional characteristic of ventral visual stream processing. [ABSTRACT FROM AUTHOR]

Dynamic models of ongoing BOLD fMRI brain dynamics and models of communication strategies have been two important approaches to understanding how brain network structure constrains function. However, dynamic models have yet to widely incorporate one of the most important insights from communication models: the brain may not use all of its connections in the same way or at the same time. Here we present a variation of a phase delayed Kuramoto coupled oscillator model that dynamically limits communication between nodes on each time step. An active subgraph of the empirically derived anatomical brain network is chosen in accordance with the local dynamic state on every time step, thus coupling dynamics and network structure in a novel way. We analyze this model with respect to its fit to empirical time-averaged functional connectivity, finding that, with the addition of only one parameter, it significantly outperforms standard Kuramoto models with phase delays. We also perform analyses on the novel time series of active edges it produces, demonstrating a slowly evolving topology moving through intermittent episodes of integration and segregation. We hope to demonstrate that the exploration of novel modeling mechanisms and the investigation of dynamics of networks in addition to dynamics on networks may advance our understanding of the relationship between brain structure and function., Competing Interests: Declaration of Competing Interest There are no declarations of interest., (Copyright © 2023. Published by Elsevier Inc.)

Connector 'hubs' are brain regions with links to multiple networks. These regions are hypothesized to play a critical role in brain function. While hubs are often identified based on group-average functional magnetic resonance imaging (fMRI) data, there is considerable inter-subject variation in the functional connectivity profiles of the brain, especially in association regions where hubs tend to be located. Here we investigated how group hubs are related to locations of inter-individual variability. To answer this question, we examined inter-individual variation at group-level hubs in both the Midnight Scan Club and Human Connectome Project datasets. The top group hubs defined based on the participation coefficient did not overlap strongly with the most prominent regions of inter-individual variation (termed 'variants' in prior work). These hubs have relatively strong similarity across participants and consistent cross-network profiles, similar to what was seen for many other areas of cortex. Consistency across participants was further improved when these hubs were allowed to shift slightly in local position. Thus, our results demonstrate that the top group hubs defined with the participation coefficient are generally consistent across people, suggesting they may represent conserved cross-network bridges. More caution is warranted with alternative hub measures, such as community density (which are based on spatial proximity to network borders) and intermediate hub regions which show higher correspondence to locations of individual variability., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)

• Prestimulus heartbeat-evoked responses can affect perception of subject's own name. • Subject's own name can affect heartbeat-evoked responses. • Dual interactions between heartbeat-evoked responses and subject's own name are associated with two distinct neural pathways. Heartbeat-evoked responses (HERs) can interact with external stimuli and play a crucial role in shaping perception, self-related processes, and emotional processes. On the one hand, the external stimulus could modulate HERs. On the other hand, the HERs could affect cognitive processing of the external stimulus. Whether the same neural mechanism underlies these two processes, however, remains unclear. Here, we investigated this interactive mechanism by measuring HERs using magnetoencephalography (MEG) and two name perception tasks. Specifically, we tested (1) how hearing a subject's own name (SON) modulates HERs and (2) how the judgment of an SON is biased by prestimulus HERs. The results showed a dual interaction between HERs and SON. In particular, SON can modulate HERs for heartbeats occurring from 200 to 1200 ms after SON presentation. In addition, prestimulus HERs can bias the SON judgment when a stimulus is presented. Importantly, MEG activities from these two types of interactions differed in spatial and temporal patterns, suggesting that they may be associated with distinct neural pathways. These findings extend our understanding of brain-heart interactions. [ABSTRACT FROM AUTHOR]

Conscientiousness, and related constructs impulsivity and self-control, have been related to structural and functional properties of regions in the prefrontal cortex (PFC) and anterior insula. Network-based conceptions of brain function suggest that these regions belong to a single large-scale network, labeled the salience/ventral attention network (SVAN). The current study tested associations between conscientiousness and resting-state functional connectivity in this network using two community samples (N's = 244 and 239) and data from the Human Connectome Project (N = 1000). Individualized parcellation was used to improve functional localization accuracy and facilitate replication. Functional connectivity was measured using an index of network efficiency, a graph theoretical measure quantifying the capacity for parallel information transfer within a network. Efficiency of a set of parcels in the SVAN was significantly associated with conscientiousness in all samples. Findings are consistent with a theory of conscientiousness as a function of variation in neural networks underlying effective prioritization of goals., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023. Published by Elsevier Inc.)

The default-mode network (DMN) is a distributed functional brain system integral for social and higher-order cognition in humans with implications in a myriad of neuropsychological disorders. In this study, we compared the functional architecture of the DMN between humans and marmosets to assess their similarities and differences using joint gradients. This approach permits simultaneous large-scale mapping of functional systems across the cortex of humans and marmosets, revealing evidence of putative homologies between them. In doing so, we find that the DMN architecture of the marmoset exhibits differences along its anterolateral-posterior axis. Specifically, the anterolateral node of the DMN (dorsolateral prefrontal cortex) displayed weak connections and inconsistent connection topographies as compared to its posterior DMN-nodes (posterior cingulate and posterior parietal cortices). We also present evidence that the marmoset medial prefrontal cortex and temporal lobe areas correspond to other macroscopical distributed functional systems that are not part of the DMN. Given the importance of the marmoset as a pre-clinical primate model for higher-order cognitive functioning and the DMN's relevance to cognition, our results suggest that the marmoset may lack the capacity to integrate neural information to subserve cortical dynamics that are necessary for supporting diverse cognitive demands., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Copyright © 2023. Published by Elsevier Inc.)

The human brain is a complex network that exhibits dynamic fluctuations in activity across space and time. Depending on the analysis method, canonical brain networks identified from resting-state fMRI (rs-fMRI) are typically constrained to be either orthogonal or statistically independent in their spatial and/or temporal domains. We avoid imposing these potentially unnatural constraints through the combination of a temporal synchronization process ("BrainSync") and a three-way tensor decomposition method ("NASCAR") to jointly analyze rs-fMRI data from multiple subjects. The resulting set of interacting networks comprises minimally constrained spatiotemporal distributions, each representing one component of functionally coherent activity across the brain. We show that these networks can be clustered into six distinct functional categories and naturally form a representative functional network atlas for a healthy population. This functional network atlas could help explore group and individual differences in neurocognitive function, as we demonstrate in the context of ADHD and IQ prediction., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2023. Published by Elsevier Inc.)

Mindfulness practice is beneficial for emotion regulation; however, the neural mechanisms underlying this effect are poorly understood. The current study focuses on effects of attention-to-breath (ATB) as a basic mindfulness practice on aversive emotions at behavioral and brain levels. A key finding across different emotion regulation strategies is the modulation of amygdala and prefrontal activity. It is unclear how ATB relevant brain areas in the prefrontal cortex integrate with amygdala activation during emotional stimulation. We proposed that, during emotional stimulation, ATB down-regulates activation in the amygdala and increases its integration with prefrontal regions. To address this hypothesis, 26 healthy controls were trained in mindfulness-based attention-to-breath meditation for two weeks and then stimulated with aversive pictures during both attention-to-breath and passive viewing while undergoing fMRI. Data were controlled for breathing frequency. Results indicate that (1) ATB was effective in regulating aversive emotions. (2) Left dorso-medial prefrontal cortex was associated with ATB in general. (3) A fronto-parietal network was additionally recruited during emotional stimulation. (4) ATB down regulated amygdala activation and increased amygdala–prefrontal integration, with such increased integration being associated with mindfulness ability. Results suggest amygdala–dorsal prefrontal cortex integration as a potential neural pathway of emotion regulation by mindfulness practice. [ABSTRACT FROM AUTHOR]