BASCO: a toolbox for task-related functional connectivity

The well-worn route revisited: Striatal and hippocampal system contributions to familiar route navigation

Classic research has shown a division in the neuroanatomical structures that support flexible (e.g., short-cutting) and habitual (e.g., familiar route following) navigational behavior, with hippocampal-caudate systems associated with the former and putamen systems with the latter. There is, however, disagreement about whether the neural structures involved in navigation process particular forms of spatial information, such as associations between constellations of cues forming a cognitive map, versus single landmark-action associations, or alternatively, perform particular reinforcement learning algorithms that allow the use of different spatial strategies, so-called model-based (flexible) or model-free (habitual) forms of learning. We sought to test these theories by asking participants (N = 24) to navigate within a virtual environment through a previously learned, 9-junction route with distinctive landmarks at each junction while undergoing functional magnetic resonance imaging (fMRI). In a series of probe trials, we distinguished knowledge of individual landmark-action associations along the route versus knowledge of the correct sequence of landmark-action associations, either by having absent landmarks, or "out-of-sequence" landmarks. Under a map-based perspective, sequence knowledge would not require hippocampal systems, because there are no constellations of cues available for cognitive map formation. Within a learning-based model, however, responding based on knowledge of sequence would require hippocampal systems because prior context has to be utilized. We found that hippocampal-caudate systems were more active in probes requiring sequence knowledge, supporting the learning-based model. However, we also found greater putamen activation in probes where navigation based purely on sequence memory could be planned, supporting models of putamen function that emphasize its role in action sequencing.

Reconfiguration of the costly punishment network architecture in punishment decision-making

Human costly punishment is rooted in multiple regions across large-scale functional systems, a collection of which constitutes the costly punishment network (CPN). Our previous study found that the CPN is intrinsically organized in an optimized and reliable manner to support individual costly punishment propensity. However, it remains unknown how the CPN is reconfigured in response to external cognitive demands in punishment decision-making. Here, we combined resting-state and task-functional magnetic resonance imaging to examine the task-related reconfigurations of intrinsic organizations of the CPN when participants made decisions of costly punishment in the Ultimatum Game. Although a strong consistency was observed in the overall pattern and each nodal profile between the intrinsic (task-free) and extrinsic (task-evoked) functional connectivity of the CPN, condition-general and condition-specific reconfigurations were also evident. Specifically, both unfair and fair conditions induced increases in functional connectivity between a few specific pairs of regions, and the unfair condition additionally induced increases in network efficiency of the CPN. Intriguingly, the specific changes in global efficiency of the CPN in the unfair condition were associated with individual differences in costly punishment after adjusting for the corresponding results in the fair condition, which were further identified for females but not for males. These findings were largely reproducible on independent samples. Collectively, our findings provide novel insights into how the CPN adaptively reconfigures its network architecture to support costly punishment.

Addressing multi-site functional MRI heterogeneity through dual-expert collaborative learning for brain disease identification

Several studies employ multi-site rs-fMRI data for major depressive disorder (MDD) identification, with a specific site as the to-be-analyzed target domain and other site(s) as the source domain. But they usually suffer from significant inter-site heterogeneity caused by the use of different scanners and/or scanning protocols and fail to build generalizable models that can well adapt to multiple target domains. In this article, we propose a dual-expert fMRI harmonization (DFH) framework for automated MDD diagnosis. Our DFH is designed to simultaneously exploit data from a single labeled source domain/site and two unlabeled target domains for mitigating data distribution differences across domains. Specifically, the DFH consists of a domain-generic student model and two domain-specific teacher/expert models that are jointly trained to perform knowledge distillation through a deep collaborative learning module. A student model with strong generalizability is finally derived, which can be well adapted to unseen target domains and analysis of other brain diseases. To the best of our knowledge, this is among the first attempts to investigate multi-target fMRI harmonization for MDD diagnosis. Comprehensive experiments on 836 subjects with rs-fMRI data from 3 different sites show the superiority of our method. The discriminative brain functional connectivities identified by our method could be regarded as potential biomarkers for fMRI-related MDD diagnosis.

Anticipating social feedback involves basal forebrain and mesolimbic functional connectivity

The mesolimbic system and basal forebrain (BF) are implicated in processing rewards and punishment, but their interplay and functional properties of subregions with respect to future social outcomes remain unclear. Therefore, this study investigated regional responses and interregional functional connectivity of the lateral (l), medial (m), and ventral (v) Substantia Nigra (SN), Nucleus Accumbens (NAcc), Nucleus basalis of Meynert (NBM), and Medial Septum/Diagonal Band (MS/DB) during reward and punishment anticipation in a social incentive delay task with neutral, positive, and negative feedback using high-resolution fMRI (1.5mm³). Neuroimaging data (n=36 healthy humans) of the anticipation phase was analyzed using mass-univariate, functional connectivity, and multivariate-pattern analysis. As expected, participants responded faster when anticipating positive and negative compared to neutral social feedback. At the neural level, anticipating social information engaged valence-related and valence-unrelated functional connectivity patterns involving the BF and mesolimbic areas. Precisely, valence-related connectivity between the lSN and NBM was associated with anticipating neutral social feedback, while connectivity between the vSN and NBM was associated with anticipating positive social feedback. A more complex pattern was observed for anticipating negative social feedback, including connectivity between the lSN and MS/DB, lSN and NAcc, as well as mSN and NAcc. To conclude, behavioral responses are modulated by the possibility to obtain positive and avoid negative social feedback. The neural processing of feedback anticipation relies on functional connectivity patterns between the BF and mesolimbic areas associated with the emotional valence of the social information. As such, our findings give novel insights into the underlying neural processes of social information processing.

Unraveling the functional attributes of the language connectome: crucial subnetworks, flexibility and variability

Language processing is a highly integrative function, intertwining linguistic operations (processing the language code intentionally used for communication) and extra-linguistic processes (e.g., attention monitoring, predictive inference, long-term memory). This synergetic cognitive architecture requires a distributed and specialized neural substrate. Brain systems have mainly been examined at rest. However, task-related functional connectivity provides additional and valuable information about how information is processed when various cognitive states are involved. We gathered thirteen language fMRI tasks in a unique database of one hundred and fifty neurotypical adults (InLang [Interactive networks of Language] database), providing the opportunity to assess language features across a wide range of linguistic processes. Using this database, we applied network theory as a computational tool to model the task-related functional connectome of language (LANG atlas). The organization of this data-driven neurocognitive atlas of language was examined at multiple levels, uncovering its major components (or crucial subnetworks), and its anatomical and functional correlates. In addition, we estimated its reconfiguration as a function of linguistic demand (flexibility) or several factors such as age or gender (variability). We observed that several discrete networks could be specifically shaped to promote key functional features of language: coding-decoding (Net1), control-executive (Net2), abstract-knowledge (Net3), and sensorimotor (Net4) functions. The architecture of these systems and the functional connectivity of the pivotal brain regions varied according to the nature of the linguistic process, gender, or age. By accounting for the multifaceted nature of language and modulating factors, this study can contribute to enriching and refining existing neurocognitive models of language. The LANG atlas can also be considered a reference for comparative or clinical studies involving various patients and conditions.

Altered neural mechanism of social reward anticipation in individuals with schizophrenia and social anhedonia

Altered social reward anticipation could be found in schizophrenia (SCZ) patients and individuals with high levels of social anhedonia (SA). However, few research investigated the putative neural processing for altered social reward anticipation in these populations on the SCZ spectrum. This study aimed to examine the underlying neural mechanisms of social reward anticipation in these populations. Twenty-three SCZ patients and 17 healthy controls (HC), 37 SA individuals and 50 respective HCs completed the Social Incentive Delay (SID) imaging task while they were undertaking MRI brain scans. We used the group contrast to examine the alterations of BOLD activation and functional connectivity (FC, psychophysiological interactions analysis). We then characterized the beta-series social brain network (SBN) based on the meta-analysis results from NeuroSynth and examined their prediction effects on real-life social network (SN) characteristics using the partial least squared regression analysis. The results showed that SCZ patients exhibited hypo-activation of the left medial frontal gyrus and the negative FCs with the left parietal regions, while individuals with SA showed the hyper-activation of the left middle frontal gyrus when anticipating social reward. For the beta-series SBNs, SCZ patients had strengthened cerebellum-temporal FCs, while SA individuals had strengthened left frontal regions FCs. However, such FCs of the SBN failed to predict the real-life SN characteristics. These preliminary findings suggested that SCZ patients and SA individuals appear to exhibit altered neural processing for social reward anticipation, and such neural activities showed a weakened association with real-life SN characteristics.

Striatal hub of dynamic and stabilized prediction coding in forebrain networks for olfactory reinforcement learning

Identifying the circuits responsible for cognition and understanding their embedded computations is a challenge for neuroscience. We establish here a hierarchical cross-scale approach, from behavioral modeling and fMRI in task-performing mice to cellular recordings, in order to disentangle local network contributions to olfactory reinforcement learning. At mesoscale, fMRI identifies a functional olfactory-striatal network interacting dynamically with higher-order cortices. While primary olfactory cortices respectively contribute only some value components, the downstream olfactory tubercle of the ventral striatum expresses comprehensively reward prediction, its dynamic updating, and prediction error components. In the tubercle, recordings reveal two underlying neuronal populations with non-redundant reward prediction coding schemes. One population collectively produces stabilized predictions as distributed activity across neurons; in the other, neurons encode value individually and dynamically integrate the recent history of uncertain outcomes. These findings validate a cross-scale approach to mechanistic investigations of higher cognitive functions in rodents.

Where and how the brain learns from experience is not fully understood. Here the authors use a hierarchical approach from behavioural modelling to systems fMRI to cellular coding reveals brain mechanisms for history informed updating of future predictions.

Future Directions for Chemosensory Connectomes: Best Practices and Specific Challenges

Ecological chemosensory stimuli almost always evoke responses in more than one sensory system. Moreover, any sensory processing takes place along a hierarchy of brain regions. So far, the field of chemosensory neuroimaging is dominated by studies that examine the role of brain regions in isolation. However, to completely understand neural processing of chemosensation, we must also examine interactions between regions. In general, the use of connectivity methods has increased in the neuroimaging field, providing important insights to physical sensory processing, such as vision, audition, and touch. A similar trend has been observed in chemosensory neuroimaging, however, these established techniques have largely not been rigorously applied to imaging studies on the chemical senses, leaving network insights overlooked. In this article, we first highlight some recent work in chemosensory connectomics and we summarize different connectomics techniques. Then, we outline specific challenges for chemosensory connectome neuroimaging studies. Finally, we review best practices from the general connectomics and neuroimaging fields. We recommend future studies to develop or use the following methods we perceive as key to improve chemosensory connectomics: (1) optimized study designs, (2) reporting guidelines, (3) consensus on brain parcellations, (4) consortium research, and (5) data sharing.

Interconnected sub-networks of the macaque monkey gustatory connectome

Macroscopic taste processing connectivity was investigated using functional magnetic resonance imaging during the presentation of sour, salty, and sweet tastants in anesthetized macaque monkeys. This examination of taste processing affords the opportunity to study the interactions between sensory regions, central integrators, and effector areas. Here, 58 brain regions associated with gustatory processing in primates were aggregated, collectively forming the gustatory connectome. Regional regression coefficients (or β-series) obtained during taste stimulation were correlated to infer functional connectivity. This connectivity was then evaluated by assessing its laterality, modularity and centrality. Our results indicate significant correlations between same region pairs across hemispheres in a bilaterally interconnected scheme for taste processing throughout the gustatory connectome. Using unbiased community detection, three bilateral sub-networks were detected within the graph of the connectome. This analysis revealed clustering of 16 medial cortical structures, 24 lateral structures, and 18 subcortical structures. Across the three sub-networks, a similar pattern was observed in the differential processing of taste qualities. In all cases, the amplitude of the response was greatest for sweet, but the network connectivity was strongest for sour and salty tastants. The importance of each region in taste processing was computed using node centrality measures within the connectome graph, showing centrality to be correlated across hemispheres and, to a smaller extent, region volume. Connectome hubs exhibited varying degrees of centrality with a prominent leftward increase in insular cortex centrality. Taken together, these criteria illustrate quantifiable characteristics of the macaque monkey gustatory connectome and its organization as a tri-modular network, which may reflect the general medial-lateral-subcortical organization of salience and interoception processing networks.

Uncovering the global task-modulated brain network in chunk decomposition with Chinese characters

Chunk decomposition, which requires the mental representation transformation in accordance with behavioral goals, is of vital importance to problem solving and creative thinking. Previous studies have identified that the frontal, parietal, and occipital cortex in the cognitive control network selectively activated in response to chunk tightness, however, functional localization strategy may overlook the interaction brain regions. Based on the notion of a global brain network, we proposed that multiple specialized regions have to be interconnected to maintain goal representation during the course of chunk decomposition. Therefore, the present study applied a beta-series correlation method to investigate interregional functional connectivity in the event-related design of chunk decomposition tasks using Chinese characters, which would highlight critical nodes irrespective to chunk tightness. The results reveal a network of functional hubs with highly within or between module connections, including the orbitofrontal cortex, superior/inferior parietal lobule, hippocampus, and thalamus. We speculate that the thalamus integrates information across modular as an integrative hub while the orbitofrontal cortex tracks the mental states of chunk decomposition on a moment-to-moment basis. The superior and inferior parietal lobule collaborate to manipulate the mental representation of chunk decomposition and the hippocampus associates the relationship between elements in the question and solution phase. Furthermore, the tightness of chunks is not only associated with different processors in visual systems but also leads to increased intermodular connections in right superior frontal gyrus and left precentral gyrus. To summary up, the present study first reveals the task-modulated brain network of chunk decomposition in addition to the tightness-related nodes in the frontal and occipital cortex.

Functional coupling between CA3 and laterobasal amygdala supports schema dependent memory formation

The medial temporal lobe drives semantic congruence dependent memory formation. However, the exact roles of hippocampal subfields and surrounding brain regions remain unclear. Here, we used an established paradigm and high-resolution functional magnetic resonance imaging of the medial temporal lobe together with cytoarchitectonic probability estimates in healthy humans. Behaviorally, robust congruence effects emerged in young and older adults, indicating that schema dependent learning is unimpaired during healthy aging. Within the medial temporal lobe, semantic congruence was associated with hemodynamic activity in the subiculum, CA1, CA3 and dentate gyrus, as well as the entorhinal cortex and laterobasal amygdala. Importantly, a subsequent memory analysis showed increased activity for later remembered vs. later forgotten congruent items specifically within CA3, and this subfield showed enhanced functional connectivity to the laterobasal amygdala. As such, our findings extend current models on schema dependent learning by pinpointing the functional properties of subregions within the medial temporal lobe.

Partial Similarity Reveals Dynamics in Brainstem-Midbrain Networks during Trigeminal Nociception

Imaging studies help us understand the important role of brainstem and midbrain regions in human trigeminal pain processing without solving the question of how these regions actually interact. In the current study, we describe this connectivity and its dynamics during nociception with a novel analytical approach called Partial Similarity (PS). We developed PS specifically to estimate the communication between individual hubs of the network in contrast to the overall communication within that network. Partial Similarity works on trial-to-trial variance of neuronal activity acquired with functional magnetic resonance imaging. It discovers direct communication between two hubs considering the remainder of the network as confounds. A similar method to PS is Representational Similarity, which works with ordinary correlations and does not consider any external influence on the communication between two hubs. Particularly the combination of Representational Similarity and Partial Similarity analysis unravels brainstem dynamics involved in trigeminal pain using the spinal trigeminal nucleus (STN)—the first relay station of peripheral trigeminal input—as a seed region. The combination of both methods can be valuable tools in discovering the network dynamics in fMRI and an important instrument for future insight into the nature of various neurological diseases like primary headaches.

Cognitive fatigue and cortical-striatal network in old age

Cognitive fatigue (CF) is among the most common and disturbing aging symptoms, and substantially interferes with activities demanding sustained mental effort. Here we examined the relationship between the cortical-striatal network and CF (assessed by the 18-item visual analogue scale) when a group of cognitively and physically healthy older adults participated in a 30-minute cognitively fatiguing task-related fMRI experiment. We also explored whether CF would interfere with the “Posterior-Anterior Shifting in Aging” (PASA) phenomenon, an aging-associated neural reliance on frontal regions to support cognitive capacity. We revealed that decreased connectivity strength of the cortical-striatal network over the course of the task was related to higher CF. Correlation between CF and the cortical-striatal network was more robust in anterior relative to posterior components. Moreover, a positive relationship between reliance on the anterior part of the cortical-striatal network and cognitive performance only existed among older adults experiencing low CF. These findings suggest a crucial role of the cortical-striatal network, especially the anterior component, in linking to CF. The PASA phenomenon may only be applicable to older adults without vulnerability to CF.

Shared striatal activity in decisions to satisfy curiosity and hunger at the risk of electric shocks

Curiosity is often portrayed as a desirable feature of human faculty. However, curiosity may come at a cost that sometimes puts people in harmful situations. Here, using a set of behavioural and neuroimaging experiments with stimuli that strongly trigger curiosity (for example, magic tricks), we examine the psychological and neural mechanisms underlying the motivational effect of curiosity. We consistently demonstrate that across different samples, people are indeed willing to gamble, subjecting themselves to electric shocks to satisfy their curiosity for trivial knowledge that carries no apparent instrumental value. Also, this influence of curiosity shares common neural mechanisms with that of hunger for food. In particular, we show that acceptance (compared to rejection) of curiosity-driven or incentive-driven gambles is accompanied by enhanced activity in the ventral striatum when curiosity or hunger was elicited, which extends into the dorsal striatum when participants made a decision.

Multivariate classification of schizophrenia and its familial risk based on load-dependent attentional control brain functional connectivity

Patients with schizophrenia (SCZ), as well as their unaffected siblings (SIB), show functional connectivity (FC) alterations during performance of tasks involving attention. As compared with SCZ, these alterations are present in SIB to a lesser extent and are more pronounced during high cognitive demand, thus possibly representing one of the pathways in which familial risk is translated into the SCZ phenotype. Our aim is to measure the separability of SCZ and SIB from healthy controls (HC) using attentional control-dependent FC patterns, and to test to which extent these patterns span a continuum of neurofunctional alterations between HC and SCZ. 65 SCZ with 65 age and gender-matched HC and 39 SIB with 39 matched HC underwent the Variable Attentional Control (VAC) task. Load-dependent connectivity matrices were generated according to correct responses in each VAC load. Classification performances of high, intermediate and low VAC load FC on HC-SCZ and HC-SIB cohorts were tested through machine learning techniques within a repeated nested cross-validation framework. HC-SCZ classification models were applied to the HC-SIB cohort, and vice-versa. A high load-related decreased FC pattern discriminated between HC and SCZ with 66.9% accuracy and with 57.7% accuracy between HC and SIB. A high load-related increased FC network separated SIB from HC (69.6% accuracy), but not SCZ from HC (48.5% accuracy). Our findings revealed signatures of attentional FC abnormalities shared by SCZ and SIB individuals. We also found evidence for potential, SIB-specific FC signature, which may point to compensatory neurofunctional mechanisms in persons at familial risk for schizophrenia.

Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI

Schizophrenia has been proposed to result from impairment of functional connectivity. We aimed to use machine learning to distinguish schizophrenic subjects from normal controls using a publicly available functional MRI (fMRI) data set. Global and local parameters of functional connectivity were extracted for classification. We found decreased global and local network connectivity in subjects with schizophrenia, particularly in the anterior right cingulate cortex, the superior right temporal region, and the inferior left parietal region as compared to healthy subjects. Using support vector machine and 10-fold cross-validation, nine features reached 92.1% prediction accuracy, respectively. Our results suggest that there are significant differences between control and schizophrenic subjects based on regional brain activity detected with fMRI.

Neural processing of food and monetary rewards is modulated by metabolic state

In humans, food is considered a powerful primary reinforcer, whereas money is a secondary reinforcer, as it gains a value through learning experience. Here, we aimed to identify the neural regions supporting the processing of food-related reinforcers, relate it to the neural underpinnings of monetary reinforcers, and explore their modulation by metabolic state (hunger vs satiety). Twenty healthy male participants were tested in two experimental sessions, once hungry and once satiated, using functional magnetic resonance imaging. Participants performed an associative learning task, receiving food or monetary rewards (in the form of images) on separate blocks. Irrespective of incentive type, both food and monetary rewards engaged ventral striatum, medial orbitofrontal cortex and amygdala, regions that have been previously associated with reward processing. Food incentives additionally engaged the opercular part of the inferior frontal gyrus and the insula, collectively known as a primary gustatory cortex. Moreover, in response to negative feedback (here, reward omission), robust activation was observed in anterior insula, supplementary motor area and lateral parts of the prefrontal cortex, including middle and inferior frontal gyrus. Furthermore, the interaction between metabolic state and incentive type resulted in supramarginal gyrus (SMG) activity, among other motor and sensory-related regions. Finally, functional connectivity analysis showed correlation in the hungry state between the SMG and mesolimbic regions, including the hippocampus, midbrain and cingulate areas. Also, the interaction between metabolic state and incentive type revealed coupling between SMG and ventral striatum. Whereas general purpose reward-related regions process incentives of different kinds, the current results suggest that the SMG might play a key role in integrating the information related to current metabolic state and available incentive type.

Regulating Craving by Anticipating Positive and Negative Outcomes: A Multivariate Pattern Analysis and Network Connectivity Approach

During self-control, we may resist short-term temptations in order to reach a favorable future (e.g., resisting cake to stay healthy). The neural basis of self-control is typically attributed to "cold," unemotional cognitive control mechanisms which inhibit affect-related regions via the prefrontal cortex (PFC). Here, we investigate the neural underpinnings of regulating cravings by mentally evoking the positive consequences of resisting a temptation (e.g., being healthy) as opposed to evoking the negative consequences of giving in to a temptation (e.g., becoming overweight). It is conceivable that when using these types of strategies, regions associated with emotional processing [e.g., striatum, ventromedial prefrontal cortex (vmPFC)] are involved in addition to control-related prefrontal and parietal regions. Thirty-one participants saw pictures of unhealthy snacks in the fMRI scanner and, depending on the trial, regulated their craving by thinking of the positive consequences of resisting, or the negative consequences of not resisting. In a control condition, they anticipated the pleasure of eating and thus, allowed the craving to occur (now-condition). In line with previous studies, we found activation of a cognitive control network during self-regulation. In the negative future thinking condition, the insula was more active than in the positive condition, while there were no activations that were stronger in the positive (> negative) future thinking condition. However, additionally, multivariate pattern analysis showed that during craving regulation, information about the valence of anticipated emotions was present in the vmPFC, the posterior cingulate cortex (PCC) and the insula. Moreover, a network including vmPFC and PCC showed higher connectivity during the positive (> negative) future thinking condition. Since these regions are often associated with affective processing, these findings suggest that "hot," affective processes may, at least in certain circumstances, play a role in self-control.

Negative Schizotypy and Altered Functional Connectivity During Facial Emotion Processing

BACKGROUND

Impairment in facial emotion perception is an important domain of social cognition deficits in schizophrenia. Although impaired facial emotion perception has been found in individuals with negative schizotypy (NS), little is known about the corresponding change in brain functional connectivity.

METHODS

Sixty-four participants were classified into a high NS group (n = 34) and a low NS group (n = 30) based on their total scores on the Chapman scales for physical and social anhedonia. All participants undertook a facial emotion discrimination functional imaging task that consisted of four emotional valences (angry, fear, happy, and neutral). For univariate analysis, the signal change at the bilateral amygdala was compared for each emotional contrast using SPSS (P < .05). For the functional connectivity analysis, we calculated the beta-series functional connectivity of the bilateral amygdala with the medial prefrontal cortex (mPFC) and compared the group differences in SPM12 (P < .05, small volume family-wise error correction).

RESULTS

No significant differences were found between the high and low NS groups in accuracy and reaction time in the facial emotion discrimination task. The high NS group showed reduced brain activations at the amygdala under fearful and neutral conditions. Reduced functional connectivity between the amygdala and the mPFC/dorsal anterior cingulate cortex under the happy and fearful conditions in the high NS group was also found.

CONCLUSIONS

Our findings suggest that the individuals with high NS showed altered brain activity and functional connectivity at the amygdala during facial emotion processing and provide new evidence for understanding social cognition deficits in at-risk individuals.

Multisensory integration processing during olfactory-visual stimulation-An fMRI graph theoretical network analysis

In this study, we aimed to understand how whole-brain neural networks compute sensory information integration based on the olfactory and visual system. Task-related functional magnetic resonance imaging (fMRI) data was obtained during unimodal and bimodal sensory stimulation. Based on the identification of multisensory integration processing (MIP) specific hub-like network nodes analyzed with network-based statistics using region-of-interest based connectivity matrices, we conclude the following brain areas to be important for processing the presented bimodal sensory information: right precuneus connected contralaterally to the supramarginal gyrus for memory-related imagery and phonology retrieval, and the left middle occipital gyrus connected ipsilaterally to the inferior frontal gyrus via the inferior fronto-occipital fasciculus including functional aspects of working memory. Applied graph theory for quantification of the resulting complex network topologies indicates a significantly increased global efficiency and clustering coefficient in networks including aspects of MIP reflecting a simultaneous better integration and segregation. Graph theoretical analysis of positive and negative network correlations allowing for inferences about excitatory and inhibitory network architectures revealed-not significant, but very consistent-that MIP-specific neural networks are dominated by inhibitory relationships between brain regions involved in stimulus processing.

Losing Control in Social Situations: How the Presence of Others Affects Neural Processes Related to Sense of Agency

Social contexts substantially influence individual behavior, but little is known about how they affect cognitive processes related to voluntary action. Previously, it has been shown that social context reduces participants' sense of agency over the outcomes of their actions and outcome monitoring. In this fMRI study on human volunteers, we investigated the neural mechanisms by which social context alters sense of agency. Participants made costly actions to stop inflating a balloon before it burst. On "social" trials, another player could act in their stead, but we analyzed only trials in which the other player remained passive. We hypothesized that mentalizing processes during social trials would affect decision-making fluency and lead to a decreased sense of agency. In line with this hypothesis, we found increased activity in the bilateral temporo-parietal junction (TPJ), precuneus, and middle frontal gyrus during social trials compared with nonsocial trials. Activity in the precuneus was, in turn, negatively related to sense of agency at a single-trial level. We further found a double dissociation between TPJ and angular gyrus (AG): activity in the left AG was not sensitive to social context but was negatively related to sense of agency. In contrast, activity in the TPJ was modulated by social context but was not sensitive to sense of agency.

The left frontal cortex supports reserve in aging by enhancing functional network efficiency

Background

Recent evidence derived from functional magnetic resonance imaging (fMRI) studies suggests that functional hubs (i.e., highly connected brain regions) are important for mental health. We found recently that global connectivity of a hub in the left frontal cortex (LFC connectivity) is associated with relatively preserved memory abilities and higher levels of protective factors (education, IQ) in normal aging and Alzheimer’s disease. These results suggest that LFC connectivity supports reserve capacity, alleviating memory decline. An open question, however, is why LFC connectivity is beneficial and supports memory function in the face of neurodegeneration. We hypothesized that higher LFC connectivity is associated with enhanced efficiency in connected major networks involved in episodic memory. We further hypothesized that higher LFC-related network efficiency predicts higher memory abilities.

Methods

We assessed fMRI during a face-name association learning task performed by 26 healthy, cognitively normal elderly participants. Using beta-series correlation analysis, we computed task-related LFC connectivity to key memory networks, including the default mode network (DMN) and dorsal attention network (DAN). Network efficiency within the DMN and DAN was estimated by the graph theoretical small-worldness statistic. We applied linear regression analyses to test the association between LFC connectivity with the DMN/DAN and small-worldness of these networks. Mediation analysis was applied to test LFC connectivity to the DMN and DAN as a mediator of the association between education and higher DMN and DAN small-worldness. Last, we tested network small-worldness as a predictor of memory performance.

Results

We found that higher LFC connectivity to the DMN and DAN during successful memory encoding and recognition was associated with higher small-worldness of those networks. Higher task-related LFC connectivity mediated the association between education and higher small-worldness in the DMN and DAN. Further, higher small-worldness of these networks predicted better performance in the memory task.

Conclusions

The present results suggest that higher education-related LFC connectivity to key memory networks during a memory task is associated with higher network efficiency and thus enhanced reserve of memory abilities in aging.

Electronic supplementary material

The online version of this article (10.1186/s13195-018-0358-y) contains supplementary material, which is available to authorized users.

Neural Correlates of Racial Ingroup Bias in Observing Computer-Animated Social Encounters

Despite evidence for the role of group membership in the neural correlates of social cognition, the mechanisms associated with processing non-verbal behaviors displayed by racially ingroup vs. outgroup members remain unclear. Here, 20 Caucasian participants underwent fMRI recording while observing social encounters with ingroup and outgroup characters displaying dynamic and static non-verbal behaviors. Dynamic behaviors included approach and avoidance behaviors, preceded or not by a handshake; both dynamic and static behaviors were followed by participants’ ratings. Behaviorally, participants showed bias toward their ingroup members, demonstrated by faster/slower reaction times for evaluating ingroup static/approach behaviors, respectively. At the neural level, despite overall similar responses in the action observation network to ingroup and outgroup encounters, the medial prefrontal cortex showed dissociable activation, possibly reflecting spontaneous processing of ingroup static behaviors and positive evaluations of ingroup approach behaviors. The anterior cingulate and superior frontal cortices also showed sensitivity to race, reflected in coordinated and reduced activation for observing ingroup static behaviors. Finally, the posterior superior temporal sulcus showed uniquely increased activity to observing ingroup handshakes. These findings shed light on the mechanisms of racial ingroup bias in observing social encounters, and have implications for understanding factors related to successful interactions with individuals from diverse backgrounds.

Neural bases of ingroup altruistic motivation in soccer fans

Humans have a strong need to belong to social groups and a natural inclination to benefit ingroup members. Although the psychological mechanisms behind human prosociality have extensively been studied, the specific neural systems bridging group belongingness and altruistic motivation remain to be identified. Here, we used soccer fandom as an ecological framing of group membership to investigate the neural mechanisms underlying ingroup altruistic behaviour in male fans using event-related functional magnetic resonance. We designed an effort measure based on handgrip strength to assess the motivation to earn money (i) for oneself, (ii) for anonymous ingroup fans, or (iii) for a neutral group of anonymous non-fans. While overlapping valuation signals in the medial orbitofrontal cortex (mOFC) were observed for the three conditions, the subgenual cingulate cortex (SCC) exhibited increased functional connectivity with the mOFC as well as stronger hemodynamic responses for ingroup versus outgroup decisions. These findings indicate a key role for the SCC, a region previously implicated in altruistic decisions and group affiliation, in dovetailing altruistic motivations with neural valuation systems in real-life ingroup behaviour.

Decreased sleep duration is associated with increased fMRI responses to emotional faces in children

In adults and children, sleep loss is associated with affective dysregulation and increased responsivity to negative stimuli. Adult functional neuroimaging (fMRI) studies have demonstrated associations between restricted sleep and neural alterations in the amygdala and reward circuitry when viewing emotional picture and face stimuli. Despite this, few studies have examined the associations between short sleep duration and emotional responsivity in typically developing children, and no studies have investigated this relationship using fMRI. The current study examined the relationship between sleep duration and fMRI activation to emotional facial expressions in 15 male children (ages 7-11 years). During fMRI scanning, subjects viewed and made perceptual judgments regarding negative, neutral, and positive emotional faces. Maternal reported child sleep duration was negatively associated with (a) activation in the bilateral amygdala, left insula, and left temporal pole activation when viewing negative (i.e., fearful, disgust) vs. neutral faces, (b) right orbitofrontal and bilateral prefrontal activation when viewing disgust vs. neutral faces, and (c) bilateral orbitofrontal, right anterior cingulate, and left amygdala activation when viewing happy vs. neutral faces. Consistent with our prediction, we also noted that emotion-dependent functional connectivity between the bilateral amygdala and prefrontal cortex, cingulate, fusiform, and occipital cortex was positively associated with sleep duration. Paralleling similar studies in adults, these findings collectively suggest that decreased sleep duration in school-aged children may contribute to enhanced reactivity of brain regions involved in emotion and reward processing, as well as decreased emotion-dependent functional connectivity between the amygdala and brain regions associated with emotion regulation.