Somatomotor Network Research Articles

Effect of methylphenidate on functional controllability: a preliminary study in medication-naïve children with ADHD

Methylphenidate (MPH) is the recommended first-line treatment for attention-deficit/hyperactivity disorder (ADHD). While MPH’s mechanism of action as a dopamine and noradrenaline transporter blocker is well known, how this translates to ADHD-related symptom mitigation is still unclear. As functional connectivity is reliably altered in ADHD, with recent literature indicating dysfunctional connectivity dynamics as well, one possible mechanism is through altering brain network dynamics. In a double-blind, placebo-controlled MPH crossover trial, 19 medication-naïve children with ADHD underwent two functional MRI scanning sessions (one on MPH and one on placebo) that included a resting state scan and two inhibitory control tasks; 27 typically developing (TD) children completed the same protocol without medication. Network control theory, which quantifies how brain activity reacts to system inputs based on underlying connectivity, was used to assess differences in average and modal functional controllability during rest and both tasks between TD children and children with ADHD (on and off MPH) and between children with ADHD on and off MPH. Children with ADHD on placebo exhibited higher average controllability and lower modal controllability of attention, reward, and somatomotor networks than TD children. Children with ADHD on MPH were statistically indistinguishable from TD children on almost all controllability metrics. These findings suggest that MPH may stabilize functional network dynamics in children with ADHD, both reducing reactivity of brain organization and making it easier to achieve brain states necessary for cognitively demanding tasks.

Disrupted intrinsic functional brain network in patients with late-life depression: Evidence from a multi-site dataset

BackgroundLate-life depression (LLD) is a common and serious mental disorder, whose neural mechanisms are not yet fully understood. In this study, we aimed to characterize LLD-related changes in intrinsic functional brain networks using a large, multi-site sample. MethodsUsing resting-state functional magnetic resonance imaging, the edge-based functional connectivity (FC) as well as multiple topological brain network metrics at both global and nodal levels were compared between 206 LLD patients and 210 normal controls (NCs). ResultsCompared with NCs, the LLD patients had extensive alterations in the intrinsic brain FCs, especially significant decreases in FCs within the default mode network (DMN) and within the somatomotor network (SMN). The LLD patients also showed alterations in several global brain network metrics compared with NCs, including significant decreases in global efficiency, local efficiency, clustering coefficient, and small-worldness, as well as a significantly increased characteristic path length. Moreover, significant alterations in nodal network metrics (increased nodal betweenness and decreased nodal efficiency) were found in patients with LLD, which mainly involved the DMN and SMN. Post-hoc subgroup analyses indicated that the above changes in FC strengths were present in both first-episode, drug-naïve (FEDN) and non-FEDN patients, and were correlated with depression severity in the FEDN patients. Moreover, changes in FC strengths were found in both the early/late-onset (depression starts before/after the age of 50) patients, while altered topological metrics were found in only the late-onset patients. ConclusionsThese results may help to strengthen our understanding of the underlying neural mechanisms and biological heterogeneity in LLD.

Tau accumulation and degeneration differ across functional networks in atypical Alzheimer's disease phenotypes

AbstractBackgroundRecent models of Alzheimer's disease (AD) posit that pathogenic tau propagates through interconnected structural networks, suggesting amnestic and non‐amnestic AD (aAD & naAD) phenotypes could reflect differential involvement of functional networks. We tested this hypothesis by contrasting longitudinal grey matter (GM) atrophy and tau accumulation across AD clinical phenotypes in 7 canonical functional networks.MethodsWe analyzed longitudinal 3‐Tesla T1‐weighted MRI from 122 patients [aAD=49; logopenic primary progressive aphasia (lvPPA)=31; posterior cortical atrophy (PCA)=23; behavioral/dysexecutive AD (bvAD)=6; corticobasal syndrome (CBS)=6; mixed naAD=4] with autopsy or CSF evidence of AD pathology and 91 cognitively normal controls (Table 1). Thirty‐one patients (aAD=9; lvPPA=7; PCA=9; bvAD=2; CBS=3; naAD=1) had longitudinal flortaucipir PET (FTP‐PET) data. We computed baseline values and annualized change for GM volume and FTP‐PET standardized uptake value ratios (SUVRs) in the 100‐label, 7‐network parcellation of Schaefer et al. (2018). Linear mixed effects models (α=0.05, corrected) adjusting for MMSE assessed group differences in atrophy and tau accumulation.ResultsAll groups exhibited significant baseline and longitudinal atrophy vs. controls in multiple networks (Figs. 1‐2). Differences in longitudinal atrophy rate (Fig. 2) were observed in the dorsal attention network [PCA>lvPPA, t(371)=3.1, p<0.04], salience network [PCA>aAD, t(371)=3.1, p<0.04], and limbic network [CBS>aAD, t(371)=3.3, p<0.02; CBS>bvAD, t(371)=3.7, p<0.006]. PCA patients exhibited FTP‐PET SUVR increases in all networks (all p<0.02), while aAD patients displayed increases in all networks except visual and limbic (all others p<0.0001). LvPPA patients exhibited net SUVR increases only in the somatomotor network [t(97)=3.5, p<0.001]. At baseline, lvPPA patients had left > right atrophy in all networks [all t>3.7, p<0.0002]; right > left atrophy was observed in the visual network for PCA and CBS; the salience network for PCA and bvAD; and in the dorsal attention, frontoparietal control, and default mode networks for bvAD [all t>3.0, p<0.03]. In longitudinal analyses, no hemispheric differences were found in rates of GM volume loss or FTP‐PET change.ConclusionAD clinical variants exhibited GM atrophy and tau accumulation in partially overlapping networks. Investigating early‐stage disease will be crucial for assessing whether disease spread through canonical functional networks can explain anatomic differences in aAD and naAD phenotypes.

Elevated integration within the reward network underlies vulnerability to distress.

Distress tolerance (DT), the capability to persist under negative circumstances, underlies a range of psychopathologies. It has been proposed that DT may originate from the activity and connectivity in diverse neural networks integrated by the reward system. To test this hypothesis, we examined the link between DT and integration and segregation in the reward network as derived from resting-state functional connectivity data. DT was measured in 147 participants from a large community sample using the Behavioral Indicator of Resiliency to Distress task. Prior to DT evaluation, participants underwent a resting-state functional magnetic resonance imaging scan. For each participant, we constructed a whole-brain functional connectivity network and calculated the degree of reward network integration and segregation based on the extent to which reward network nodes showed functional connections within and outside their network. We found that distress-intolerant participants demonstrated heightened reward network integration relative to the distress-tolerant participants. In addition, these differences in integration were higher relative to the rest of the brain and, more specifically, the somatomotor network, which has been implicated in impulsive behavior. These findings support the notion that increased integration in large-scale brain networks may constitute a risk for distress intolerance and its psychopathological correlates.

Differences in resting state functional connectivity underlie visuomotor performance declines in older adults with a genetic risk (APOE ε4) for Alzheimer's disease.

Non-standard visuomotor integration requires the interaction of large networks in the brain. Previous findings have shown that non-standard visuomotor performance is impaired in individuals with specific dementia risk factors (family history of dementia and presence of the APOE ε4 allele) in advance of any cognitive impairments. These findings suggest that visuomotor impairments are associated with early dementia-related brain changes. The current study examined the underlying resting state functional connectivity (RSFC) associated with impaired non-standard visuomotor performance, as well as the impacts of dementia family history, sex, and APOE status. Cognitively healthy older adults (n = 48) were tested on four visuomotor tasks where reach and gaze were increasingly spatially dissociated. Participants who had a family history of dementia or the APOE ε4 allele were considered to be at an increased risk for AD. To quantify RSFC within networks of interest, an EPI sequence sensitive to BOLD contrast was collected. The networks of interest were the default mode network (DMN), somatomotor network (SMN), dorsal attention network (DAN), ventral attention network (VAN), and frontoparietal control network (FPN). Individuals with the ε4 allele showed abnormalities in RSFC between posterior DMN nodes that predicted poorer non-standard visuomotor performance. Specifically, multiple linear regression analyses revealed lower RSFC between the precuneus/posterior cingulate cortex and the left inferior parietal lobule as well as the left parahippocampal cortex. Presence of the APOE ε4 allele also modified the relationship between mean DAN RSFC and visuomotor control, where lower mean RSFC in the DAN predicted worse non-standard visuomotor performance only in APOE ε4 carriers. There were otherwise no effects of family history, APOE ε4 status, or sex on the relationship between RSFC and visuomotor performance for any of the other resting networks. The preliminary findings provide insight into the impact of APOE ε4-related genetic risk on neural networks underlying complex visuomotor transformations, and demonstrate that the non-standard visuomotor task paradigm discussed in this study may be used as a non-invasive, easily accessible assessment tool for dementia risk.

Neural substrates underlying effortful control deficit in autism spectrum disorder: a meta-analysis of fMRI studies

Effortful control comprises attentional control, inhibitory control, and cognitive flexibility subprocesses. Effortful control is impaired in individuals with autism spectrum disorder, yet its neural underpinnings remain elusive. By conducting a coordinate-based meta-analysis, this study compared the brain activation patterns between autism and typically developing individuals and examined the effect of age on brain activation in each effortful control subprocesses. Meta-analytic results from 22 studies revealed that, individuals with autism showed hypoactivation in the default mode network for tasks tapping inhibitory control functioning (threshold-free cluster enhancement p < 0.001). When these individuals perform tasks tapping attentional control and cognitive flexibility, they exhibited aberrant activation in various brain networks including default mode network, dorsal attention, frontoparietal, visual and somatomotor networks (uncorrected ps < 0.005). Meta-regression analyses revealed that brain regions within the default mode network showed a significant decreasing trend in activation with increasing age (uncorrected p < 0.05). In summary, individuals with autism showed aberrant activation patterns across multiple brain functional networks during all cognitive tasks supporting effortful control, with some regions showing a decrease in activation with increasing age.

Sensory stimulation for upper limb amputations modulates adaptability of cortical large-scale systems and combination of somatosensory and visual inputs

Touch-like phantom limb sensations can be elicited through targeted transcutaneous electrical nerve stimulation (tTENS) in individuals with upper limb amputation. The corresponding impact of sensory stimulation on cortical activity remains an open question. Brain network research shows that sensorimotor cortical activity is supported by dynamic changes in functional connections between relevant brain regions. These groups of interconnected regions are functional modules whose architecture enables specialized function and related neural processing supporting individual task needs. Using electroencephalographic (EEG) signals to analyze modular functional connectivity, we investigated changes in the modular architecture of cortical large-scale systems when participants with upper limb amputations performed phantom hand movements before, during, and after they received tTENS. We discovered that tTENS substantially decreased the flexibility of the default mode network (DMN). Furthermore, we found increased interconnectivity (measured by a graph theoretic integration metric) between the DMN, the somatomotor network (SMN) and the visual network (VN) in the individual with extensive tTENS experience. While for individuals with less tTENS experience, we found increased integration between DMN and the attention network. Our results provide insights into how sensory stimulation promotes cortical processing of combined somatosensory and visual inputs and help develop future tools to evaluate sensory combination for individuals with amputations.

Functional reconfiguration of task-active frontoparietal control network facilitates abstract reasoning.

While the brain's functional network architecture is largely conserved between resting and task states, small but significant changes in functional connectivity support complex cognition. In this study, we used a modified Raven's Progressive Matrices Task to examine symbolic and perceptual reasoning in human participants undergoing fMRI scanning. Previously, studies have focused predominantly on discrete symbolic versions of matrix reasoning, even though the first few trials of the Raven's Advanced Progressive Matrices task consist of continuous perceptual stimuli. Our analysis examined the activation patterns and functional reconfiguration of brain networks associated with resting state and both symbolic and perceptual reasoning. We found that frontoparietal networks, including the cognitive control and dorsal attention networks, were significantly activated during abstract reasoning. We determined that these same task-active regions exhibited flexibly-reconfigured functional connectivity when transitioning from resting state to the abstract reasoning task. Conversely, we showed that a stable network core of regions in default and somatomotor networks was maintained across both resting and task states. We propose that these regionally-specific changes in the functional connectivity of frontoparietal networks puts the brain in a "task-ready" state, facilitating efficient task-based activation.

Genuine high-order interactions in brain networks and neurodegeneration

Brain functional networks have been traditionally studied considering only interactions between pairs of regions, neglecting the richer information encoded in higher orders of interactions. In consequence, most of the connectivity studies in neurodegeneration and dementia use standard pairwise metrics. Here, we developed a genuine high-order functional connectivity (HOFC) approach that captures interactions between 3 or more regions across spatiotemporal scales, delivering a more biologically plausible characterization of the pathophysiology of neurodegeneration. We applied HOFC to multimodal (electroencephalography [EEG], and functional magnetic resonance imaging [fMRI]) data from patients diagnosed with behavioral variant of frontotemporal dementia (bvFTD), Alzheimer's disease (AD), and healthy controls. HOFC revealed large effect sizes, which, in comparison to standard pairwise metrics, provided a more accurate and parsimonious characterization of neurodegeneration. The multimodal characterization of neurodegeneration revealed hypo and hyperconnectivity on medium to large-scale brain networks, with a larger contribution of the former. Regions as the amygdala, the insula, and frontal gyrus were associated with both effects, suggesting potential compensatory processes in hub regions. fMRI revealed hypoconnectivity in AD between regions of the default mode, salience, visual, and auditory networks, while in bvFTD between regions of the default mode, salience, and somatomotor networks. EEG revealed hypoconnectivity in the γ band between frontal, limbic, and sensory regions in AD, and in the δ band between frontal, temporal, parietal and posterior areas in bvFTD, suggesting additional pathophysiological processes that fMRI alone can not capture. Classification accuracy was comparable with standard biomarkers and robust against confounders such as sample size, age, education, and motor artifacts (from fMRI and EEG). We conclude that high-order interactions provide a detailed, EEG- and fMRI compatible, biologically plausible, and psychopathological-specific characterization of different neurodegenerative conditions.

Investigation of white matter functional networks underlying different behavioral profiles in attention-deficit/hyperactivity disorder.

Cortical functional network alterations have been widely accepted as the neural basis of attention-deficit/hyperactivity disorder (ADHD). Recently, white matter has also been recognized as a novel neuroimaging marker of psychopathology and has been used as a complement to cortical functional networks to investigate brain-behavior relationships. However, disorder-specific features of white matter functional networks (WMFNs) are less well understood than those of gray matter functional networks. In the current study, we constructed WMFNs using a new strategy to characterize behavior-related network features in ADHD. We recruited 46 drug-naïve boys with ADHD and 46 typically developing (TD) boys, and used clustering analysis on resting-state functional magnetic resonance imaging data to generate WMFNs in each group. Intrinsic activity within each network was extracted, and the associations between network activity and behavior measures were assessed using correlation analysis. Nine WMFNs were identified for both ADHD and TD participants. However, boys with ADHD showed a splitting of the inferior corticospinal-cerebellar network and lacked a cognitive control network. In addition, boys with ADHD showed increased activity in the dorsal attention network and somatomotor network, which correlated positively with attention problems and hyperactivity symptom scores, respectively, while they presented decreased activity in the frontoparietal network and frontostriatal network in association with poorer performance in response inhibition, working memory, and verbal fluency. We discovered a dual pattern of white matter network activity in drug-naïve ADHD boys, with hyperactive symptom-related networks and hypoactive cognitive networks. These findings characterize two distinct types of WMFN in ADHD psychopathology.

Cerebro-cerebellar Dysconnectivity in Children and Adolescents With Attention-Deficit/Hyperactivity Disorder.

Abnormal cerebellar development has been implicated in attention-deficit/hyperactivity disorder (ADHD), although cerebro-cerebellar functional connectivity (FC) has yet to be examined in ADHD. Our objective is to investigate the disturbed cerebro-cerebellar FC in children and adolescents with ADHD. We analyzed a dataset of 106 individuals with ADHD (68 children, 38 adolescents) and 62 healthy comparison individuals (34 children, 28 adolescents) from the publicly available ADHD-200 dataset. We identified 7 cerebellar subregions based on cerebro-cerebellar FC and subsequently obtained the FC maps of cerebro-cerebellar networks. The main effects of ADHD and age and their interaction were examined using 2-way analysis of variance. Compared to comparisons, ADHD showed higher cerebro-cerebellar FC in the superior temporal gyrus within the somatomotor network. Interactions of diagnosis and age were identified in the supplementary motor area and postcentral gyrus within the somatomotor network and middle temporal gyrus within the ventral attention network. Follow-up Pearson correlation analysis revealed decreased cerebro-cerebellar FC in these regions with increasing age in comparisons, whereas the opposite pattern of increased cerebro-cerebellar FC occurred in ADHD. Increased cerebro-cerebellar FC in the superior temporal gyrus within the somatomotor network could underlie impairments in cognitive control and somatic motor function in ADHD. In addition, increasing cerebro-cerebellar FC in older participants with ADHD suggests that enhanced cerebellar involvement may compensate for dysfunctions of the cerebral cortex in ADHD.

Altered controllability of white matter networks and related brain function changes in first-episode drug-naive schizophrenia.

Understanding how structural connectivity alterations affect aberrant dynamic function using network control theory will provide new mechanistic insights into the pathophysiology of schizophrenia. The study included 140 drug-naive schizophrenia patients and 119 healthy controls (HCs). The average controllability (AC) quantifying capacity of brain regions/networks to shift the system into easy-to-reach states was calculated based on white matter connectivity and was compared between patients and HCs as well as functional network topological and dynamic properties. The correlation analysis between AC and duration of untreated psychosis (DUP) were conducted to characterize the controllability progression pattern without treatment effects. Relative to HCs, patients exhibited reduced AC in multiple nodes, mainly distributed in default mode network (DMN), visual network (VN), and subcortical regions, and increased AC in somatomotor network. These networks also had impaired functional topology and increased temporal variability in dynamic functional connectivity analysis. Longer DUP was related to greater reductions of AC in VN and DMN. The current study highlighted potential structural substrates underlying altered functional dynamics in schizophrenia, providing a novel understanding of the relationship of anatomic and functional network alterations.

Low glutamate diet improves working memory and contributes to altering BOLD response and functional connectivity within working memory networks in Gulf War Illness

Gulf War Illness is a chronic multi-symptom disorder with severe cognitive impairments which may be related to glutamate excitotoxicity and central nervous system dysfunction. The low glutamate diet has been proposed as a comprehensive intervention for Gulf War Illness. We examined the effects of the low glutamate diet on verbal working memory using a fMRI N-back task. Accuracy, whole-brain blood oxygen level dependency (BOLD) response, and task-based functional connectivity were assessed at baseline and after 1 month on the diet (N = 24). Multi-voxel pattern analysis identified regions of whole-brain BOLD pattern differences after the diet to be used as seeds for subsequent seed-to-voxel functional connectivity analyses. Verbal working memory accuracy improved after the diet (+ 13%; p = 0.006). Whole-brain BOLD signal changes were observed, revealing lower activation within regions of the frontoparietal network and default mode network after the low glutamate diet. Multi-voxel pattern analysis resulted in 3 clusters comprising parts of the frontoparietal network (clusters 1 and 2) and ventral attention network (cluster 3). The seed-to-voxel analyses identified significant functional connectivity changes post-diet for clusters 1 and 2 (peak p < 0.001, cluster FDR p < 0.05). Relative to baseline, clusters 1 and 2 had decreased functional connectivity with regions in the ventral attention and somatomotor networks. Cluster 2 also had increased functional connectivity with regions of the default mode and frontoparietal networks. These findings suggest that among veterans with Gulf War Illness, the low glutamate diet improves verbal working memory accuracy, alters BOLD response, and alters functional connectivity within two networks central to working memory.

Structural-functional connectivity bandwidth of the human brain

BackgroundThe human brain is a complex network that seamlessly manifests behaviour and cognition. This network comprises neurons that directly, or indirectly mediate communication between brain regions. Here, we show how multilayer/multiplex network analysis provides a suitable framework to uncover the throughput of structural connectivity (SC) to mediate information transfer—giving rise to functional connectivity (FC). MethodWe implemented a novel method to reconcile SC and FC using diffusion and resting-state functional MRI connectivity data from 484 subjects (272 females, 212 males; age = 29.15 ± 3.47) from the Human Connectome Project. First, we counted the number of direct and indirect structural paths that mediate FC. FC nodes with indirect SC paths were then weighted according to their least restrictive SC path. We refer to this as SC-FC Bandwidth. We then mapped paths with the highest SC-FC Bandwidth across 7 canonical resting-state networks. FindingsWe found that most pairs of FC nodes were connected by SC paths of length two and three (SC paths of length >5 were virtually non-existent). Direct SC-FC connections accounted for only 10% of all SC-FC connections. The majority of FC nodes without a direct SC path were mediated by a proportion of two (44%) or three SC path lengths (39%). Only a small proportion of FC nodes were mediated by SC path lengths of four (5%). We found high-bandwidth direct SC-FC connections show dense intra- and sparse inter-network connectivity, with a bilateral, anteroposterior distribution. High bandwidth SC-FC triangles have a right superomedial distribution within the somatomotor network. High-bandwidth SC-FC quads have a superoposterior distribution within the default mode network. ConclusionOur method allows the measurement of indirect SC-FC using undirected, weighted graphs derived from multimodal MRI data in order to map the location and throughput of SC to mediate FC. An extension of this work may be to explore how SC-FC Bandwidth changes over time, relates to cognition/behavior, and if this measure reflects a marker of neurological injury or psychiatric disorders.

Comparing resting-state connectivity of working memory networks in U.S. Service members with mild traumatic brain injury and posttraumatic stress disorder

Mild traumatic brain injury (mTBI) and posttraumatic stress disorder (PTSD) are prevalent among military populations, and both have been associated with working memory (WM) impairments. Previous resting-state functional connectivity (rsFC) research conducted separately in PTSD and mTBI populations suggests that there may be similar and distinct abnormalities in WM-related networks. However, no studies have compared rsFC of WM brain regions in participants with mTBI versus PTSD. We used resting-state fMRI to investigate rsFC of WM networks in U.S. Service Members (n = 127; ages 18–59) with mTBI only (n = 46), PTSD only (n = 24), and an orthopedically injured (OI) control group (n = 57). We conducted voxelwise rsFC analyses with WM brain regions to test for differences in WM network connectivity in mTBI versus PTSD. Results revealed reduced rsFC between ventrolateral prefrontal cortex (vlPFC), lateral premotor cortex, and dorsolateral prefrontal cortex (dlPFC) WM regions and brain regions in the dorsal attention and somatomotor networks in both mTBI and PTSD groups versus controls. When compared to those with mTBI, individuals with PTSD had lower rsFC between both the lateral premotor WM seed region and middle occipital gyrus as well as between the dlPFC WM seed region and paracentral lobule. Interestingly, only vlPFC connectivity was significantly associated with WM performance across the samples. In conclusion, we found primarily overlapping patterns of reduced rsFC in WM brain regions in both mTBI and PTSD groups. Our finding of decreased vlPFC connectivity associated with WM is consistent with previous clinical and neuroimaging studies. Overall, these results provide support for shared neural substrates of WM in individuals with either mTBI or PTSD.

Alterations of static and dynamic functional network connectivity in acute ischemic brainstem stroke.

Prior studies have shown abnormal brain functional network changes in patients with acute ischemic stroke. However, the alterations of dynamic functional network connectivity (FNC) in brainstem strokes have not been elucidated. To assess alterations of static and dynamic FNCs and determine the relationships between these and upper limb movement performance in patients with acute brainstem ischemic stroke. In total, 50 patients with acute brainstem ischemic stroke and 50 age- and sex-matched healthy controls were enrolled in the present study and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Independent component analysis was conducted to assess static and dynamic FNC patterns based on seven resting-state networks, namely, the default mode network (DMN), executive control network (ECN), attention network (AN), somatomotor network (SMN), visual network (VN), auditory network (AUN), and cerebellum network (CN). Compared with controls, patients with acute brainstem ischemic stroke exhibited wide aberrations of static FNC, including increased FNC in DMN-ECN, DMN-VN, ECN-VN, ECN-AN and AN-AUN pairs. Patients with acute brainstem ischemic stroke showed aberrant dynamic FNC in State 1, involving increased FNC aberrance in the DMN with AN, DMN with ECN, and reduced FNC in SMN-VN pairs. In State 5, patients with acute brainstem ischemic stroke showed increased FNC in DMN-VN and AN-AUN, and decreased FNC in AN-SMN pairs. This study suggests that static and dynamic FNC impairment and aberrant connections exist in acute brainstem ischemic stroke, which expands what is known regarding the relationship between stroke and FNC from static and dynamic perspectives.

Carotenoids improve the development of cerebral cortical networks in formula-fed infant macaques

Nutrition during the first years of life has a significant impact on brain development. This study characterized differences in brain maturation from birth to 6 months of life in infant macaques fed formulas differing in content of lutein, β-carotene, and other carotenoids using Magnetic Resonance Imaging to measure functional connectivity. We observed differences in functional connectivity based on the interaction of diet, age and brain networks. Post hoc analysis revealed significant diet-specific differences between insular-opercular and somatomotor networks at 2 months of age, dorsal attention and somatomotor at 4 months of age, and within somatomotor and between somatomotor-visual and auditory-dorsal attention networks at 6 months of age. Overall, we found a larger divergence in connectivity from the breastfeeding group in infant macaques fed formula containing no supplemental carotenoids in comparison to those fed formula supplemented with carotenoids. These findings suggest that carotenoid formula supplementation influences functional brain development.

Brain functional connectivity mirrors genetic pleiotropy in psychiatric conditions.

Pleiotropy occurs when a genetic variant influences more than one trait. This is a key property of the genomic architecture of psychiatric disorders and has been observed for rare and common genomic variants. It is reasonable to hypothesize that the microscale genetic overlap (pleiotropy) across psychiatric conditions and cognitive traits may lead to similar overlaps at the macroscale brain level such as large-scale brain functional networks. We took advantage of brain connectivity, measured by resting-state functional MRI to measure the effects of pleiotropy on large-scale brain networks, a putative step from genes to behaviour. We processed nine resting-state functional MRI datasets including 32 726 individuals and computed connectome-wide profiles of seven neuropsychiatric copy-number-variants, five polygenic scores, neuroticism and fluid intelligence as well as four idiopathic psychiatric conditions. Nine out of 19 pairs of conditions and traits showed significant functional connectivity correlations (rFunctional connectivity), which could be explained by previously published levels of genomic (rGenetic) and transcriptomic (rTranscriptomic) correlations with moderate to high concordance: rGenetic-rFunctional connectivity = 0.71 [0.40-0.87] and rTranscriptomic-rFunctional connectivity = 0.83 [0.52; 0.94]. Extending this analysis to functional connectivity profiles associated with rare and common genetic risk showed that 30 out of 136 pairs of connectivity profiles were correlated above chance. These similarities between genetic risks and psychiatric disorders at the connectivity level were mainly driven by the overconnectivity of the thalamus and the somatomotor networks. Our findings suggest a substantial genetic component for shared connectivity profiles across conditions and traits, opening avenues to delineate general mechanisms-amenable to intervention-across psychiatric conditions and genetic risks.

Revisiting sex differences in the acquisition and extinction of threat conditioning in humans.

Findings pertaining to sex differences in the acquisition and extinction of threat conditioning, a paradigm widely used to study emotional homeostasis, remain inconsistent, particularly in humans. This inconsistency is likely due to multiple factors, one of which is sample size. Here, we pooled functional magnetic resonance imaging (fMRI) and skin conductance response (SCR) data from multiple studies in healthy humans to examine sex differences during threat conditioning, extinction learning, and extinction memory recall. We observed increased functional activation in males, relative to females, in multiple parietal and frontal (medial and lateral) cortical regions during acquisition of threat conditioning and extinction learning. Females mainly exhibited higher amygdala activation during extinction memory recall to the extinguished conditioned stimulus and also while responding to the unconditioned stimulus (presentation of the shock) during threat conditioning. Whole-brain functional connectivity analyses revealed that females showed increased connectivity across multiple networks including visual, ventral attention, and somatomotor networks during late extinction learning. At the psychophysiological level, a sex difference was only observed during shock delivery, with males exhibiting higher unconditioned responses relative to females. Our findings point to minimal to no sex differences in the expression of conditioned responses during acquisition and extinction of such responses. Functional MRI findings, however, show some distinct functional activations and connectivities between the sexes. These data suggest that males and females might use different neural mechanisms, mainly related to cognitive processing, to achieve comparable levels of acquired conditioned responses to threating cues.

State-dependent tDCS modulation of the somatomotor network: A MEG study

ObjectiveTranscranial direct current stimulation (tDCS) is a non-invasive technique widely used to investigate brain excitability and activity. However, the variability in both brain and behavioral responses to tDCS limits its application for clinical purposes.This study aims to shed light on state-dependency, a phenomenon that contributes to the variability of tDCS. MethodsTo this aim, we investigated changes in spectral activity and functional connectivity in somatomotor regions after Real and Sham tDCS using generalized additive mixed models (GAMMs), which allowed us to investigate how modulation depends on the initial state of the brain. ResultsResults showed that changes in spectral activity, but not connectivity, in the somatomotor regions depend on the initial state of the brain, confirming state-dependent effects. Specifically, we found a non-linear interaction between stimulation conditions (Real vs Sham) and initial state: a reduction of alpha and beta power was observed only in participants that had higher alpha and beta power before Real tDCS. ConclusionsThis study highlights the importance of considering state-dependency to tDCS and shows how it can be taken into account with appropriate statistical models. SignificanceOur findings bear insight into tDCS mechanisms, potentially leading to discriminate between tDCS responders and non-responders.