An epigenetic mechanism for differential maturation of amygdala-prefrontal connectivity in childhood socio-emotional development.

Functional connectivity between the amygdala and the medial prefrontal cortex (mPFC) has been identified as a neural substrate of emotion regulation that undergoes changes throughout development, with a mature profile typically emerging at 10 years of age. Maternal bonding in childhood has been shown to buffer amygdala reactivity and to influence the trajectory of amygdala-mPFC coupling. The oxytocinergic system is critical in the development of social behavior and maternal bonding. Early-life parental care influences the methylation status of the oxytocin receptor (OXTRm) in animal models and humans, and higher OXTRm is associated with lower amygdala-PFC functional connectivity in adults. Using a neuroimaging-epigenetic approach, we investigated saliva-derived OXTRm as a biological marker of structural and functional connectivity maturation in 57 typically developing children (P < 0.05). We utilized seed-based connectivity analysis during a novel abstract movie paradigm and find that higher levels of OXTRm are associated with a more adult-like functional connectivity profile. Concurrently, more adult-like functional connectivity was associated with higher reported self-control and more diffusion streamlines between the amygdala and mPFC. OXTRm mediates the association between structural and functional connectivity with higher levels of OXTRm being associated with more streamlines. Lastly, we also find that lower OXTRm blunts the association between amygdala-mPFC connectivity and future internalizing behaviors in early adolescence. These findings implicate OXTRm as a biological marker at the interface of the social environment and amygdala-mPFC connectivity in emotional and behavioral regulation. Ultimately, identification of neurobiological markers may lead to earlier detection of children at risk for socio-emotional dysfunction.

A Nucleus Accumbens Tac1 Neural Circuit Regulates Avoidance Responses to Aversive Stimuli.

Neural circuits that control aversion are essential for motivational regulation and survival in animals. The nucleus accumbens (NAc) plays an important role in predicting aversive events and translating motivations into actions. However, the NAc circuits that mediate aversive behaviors remain elusive. Here, we report that tachykinin precursor 1 (Tac1) neurons in the NAc medial shell regulate avoidance responses to aversive stimuli. We show that NAcTac1 neurons project to the lateral hypothalamic area (LH) and that the NAcTac1→LH pathway contributes to avoidance responses. Moreover, the medial prefrontal cortex (mPFC) sends excitatory inputs to the NAc, and this circuit is involved in the regulation of avoidance responses to aversive stimuli. Overall, our study reveals a discrete NAc Tac1 circuit that senses aversive stimuli and drives avoidance behaviors.

Purpose in life promotes resilience to age-related brain burden in middle-aged adults.

BACKGROUND: Disease-modifying agents to counteract cognitive impairment in older age remain elusive. Hence, identifying modifiable factors promoting resilience, as the capacity of the brain to maintain cognition and function with aging and disease, is paramount. In Alzheimer's disease (AD), education and occupation are typical cognitive reserve proxies. However, the importance of psychological factors is being increasingly recognized, as their operating biological mechanisms are elucidated. Purpose in life (PiL), one of the pillars of psychological well-being, has previously been found to reduce the deleterious effects of AD-related pathological changes on cognition. However, whether PiL operates as a resilience factor in middle-aged individuals and what are the underlying neural mechanisms remain unknown. METHODS: Data was obtained from 624 middle-aged adults (mean age 53.71 ± 6.9; 303 women) from the Barcelona Brain Health Initiative cohort. Individuals with lower (LP; N = 146) and higher (HP; N = 100) PiL rates, according to the division of this variable into quintiles, were compared in terms of cognitive status, a measure reflecting brain burden (white matter lesions; WMLs), and resting-state functional connectivity, examining system segregation (SyS) parameters using 14 common brain circuits. RESULTS: Neuropsychological status and WMLs burden did not differ between the PiL groups. However, in the LP group, greater WMLs entailed a negative impact on executive functions. Subjects in the HP group showed lower SyS of the dorsal default-mode network (dDMN), indicating lesser segregation of this network from other brain circuits. Specifically, HP individuals had greater inter-network connectivity between specific dDMN nodes, including the frontal cortex, the hippocampal formation, the midcingulate region, and the rest of the brain. Greater functional connectivity in some of these nodes positively correlated with cognitive performance. CONCLUSION: Expanding previous findings on AD pathology and advanced age, the present results suggest that higher rates of PiL may promote resilience against brain changes already observable in middle age. Furthermore, having a purposeful life implies larger functional integration of the dDMN, which may potentially reflect greater brain reserve associated to better cognitive function.

Functional connectivity changes during working memory in autism spectrum disorder: A two-year longitudinal MEG study.

Working memory impairments have been reported in adults with autism spectrum disorder (ASD) and associated with functional outcomes and social difficulties. However, little is known about the developmental trajectory of working memory in youth with ASD. The current magnetoencephalography (MEG) study is the first to examine the longitudinal development over two years of working memory networks in youth with ASD. We analysed MEG data from 32 children and adolescents with and without ASD (64 datasets; 7-14 years), all tested twice at a two-year interval, during a visual n-back task, with two loads (1- and 2-back). We performed a whole-brain functional connectivity analysis to examine the networks during the successful recognition of visual stimuli. We demonstrate that youth with ASD show decreased connectivity in the theta frequency (4-7 Hz) in the higher memory load (2-back) condition compared to typically developing (TD) controls. This hypo-connected theta network was anchored in primary visual areas with connections to frontal, parietal and limbic regions. These network differences were found despite similar task performance between ASD and TD groups. Within the TD group, we found an increase in alpha (8-14 Hz) connectivity at Time 2 compared to Time 1 in both the 1- and 2-back conditions. These findings demonstrate the continued development of working memory mechanisms over middle childhood, which were not apparent in youth with ASD. Together, our findings support a network-based approach to understanding atypical neural functioning in ASD and the developmental trajectories of working memory processes over middle childhood.

Atypical functional connectivity of temporal cortex with precuneus and visual regions may be an early-age signature of ASD.

BACKGROUND: Social and language abilities are closely intertwined during early typical development. In autism spectrum disorder (ASD), however, deficits in social and language development are early-age core symptoms. We previously reported that superior temporal cortex, a well-established social and language region, shows reduced activation to social affective speech in ASD toddlers; however, the atypical cortical connectivity that accompanies this deviance remains unknown. METHODS: We collected clinical, eye tracking, and resting-state fMRI data from 86 ASD and non-ASD subjects (mean age 2.3 ± 0.7 years). Functional connectivity of left and right superior temporal regions with other cortical regions and correlations between this connectivity and each child's social and language abilities were examined. RESULTS: While there was no group difference in functional connectivity, the connectivity between superior temporal cortex and frontal and parietal regions was significantly correlated with language, communication, and social abilities in non-ASD subjects, but these effects were absent in ASD subjects. Instead, ASD subjects, regardless of different social or nonsocial visual preferences, showed atypical correlations between temporal-visual region connectivity and communication ability (r(49) = 0.55, p < 0.001) and between temporal-precuneus connectivity and expressive language ability (r(49) = 0.58, p < 0.001). LIMITATIONS: The distinct connectivity-behavior correlation patterns may be related to different developmental stages in ASD and non-ASD subjects. The use of a prior 2-year-old template for spatial normalization may not be optimal for a few subjects beyond this age range. CONCLUSIONS: Superior temporal cortex is known to have reduced activation to social affective speech in ASD at early ages, and here we find in ASD toddlers that it also has atypical connectivity with visual and precuneus cortices that is correlated with communication and language ability, a pattern not seen in non-ASD toddlers. This atypicality may be an early-age signature of ASD that also explains why the disorder has deviant early language and social development. Given that these atypical connectivity patterns are also present in older individuals with ASD, we conclude these atypical connectivity patterns persist across age and may explain why successful interventions targeting language and social skills at all ages in ASD are so difficult to achieve.

Molecular and spatial profiling of the paraventricular nucleus of the thalamus.

The paraventricular nucleus of the thalamus (PVT) is known to regulate various cognitive and behavioral processes. However, while functional diversity among PVT circuits has often been linked to cellular differences, the molecular identity and spatial distribution of PVT cell types remain unclear. To address this gap, here we used single nucleus RNA sequencing (snRNA-seq) and identified five molecularly distinct PVT neuronal subtypes in the mouse brain. Additionally, multiplex fluorescent in situ hybridization of top marker genes revealed that PVT subtypes are organized by a combination of previously unidentified molecular gradients. Lastly, comparing our dataset with a recently published single-cell sequencing atlas of the thalamus yielded novel insight into the PVT's connectivity with the cortex, including unexpected innervation of auditory and visual areas. This comparison also revealed that our data contains a largely non-overlapping transcriptomic map of multiple midline thalamic nuclei. Collectively, our findings uncover previously unknown features of the molecular diversity and anatomical organization of the PVT and provide a valuable resource for future investigations.

Propofol disrupts alpha dynamics in functionally distinct thalamocortical networks during loss of consciousness.

During propofol-induced general anesthesia, alpha rhythms measured using electroencephalography undergo a striking shift from posterior to anterior, termed anteriorization, where the ubiquitous waking alpha is lost and a frontal alpha emerges. The functional significance of alpha anteriorization and the precise brain regions contributing to the phenomenon are a mystery. While posterior alpha is thought to be generated by thalamocortical circuits connecting nuclei of the sensory thalamus with their cortical partners, the thalamic origins of the propofol-induced alpha remain poorly understood. Here, we used human intracranial recordings to identify regions in sensory cortices where propofol attenuates a coherent alpha network, distinct from those in the frontal cortex where it amplifies coherent alpha and beta activities. We then performed diffusion tractography between these identified regions and individual thalamic nuclei to show that the opposing dynamics of anteriorization occur within two distinct thalamocortical networks. We found that propofol disrupted a posterior alpha network structurally connected with nuclei in the sensory and sensory associational regions of the thalamus. At the same time, propofol induced a coherent alpha oscillation within prefrontal cortical areas that were connected with thalamic nuclei involved in cognition, such as the mediodorsal nucleus. The cortical and thalamic anatomy involved, as well as their known functional roles, suggests multiple means by which propofol dismantles sensory and cognitive processes to achieve loss of consciousness.

Mecanismos neurológicos involucrados en la escoliosis idiopática. Revisión sistemática de la literatura / Neurological mechanisms involved in idiopathic scoliosis. Systematic review of the literature

La literatura que explica los mecanismos neurológicos que subyacen al desarrollo o a la compensación de la escoliosis idiopática es limitada. El objetivo del presente artículo es describir e integrar los mecanismos y las vías nerviosas por medio de las cuales se compensa y/o se desarrolla la escoliosis idiopática. Se realizó una revisión sistemática narrativa en diferentes bases de datos sobre los estudios publicados entre el 1 de enero 1967 y el 1 de abril de 2021, empleando los siguientes términos: «scoliosis», «vision», «ocular», «vestibule», «labyrinth», «posture», «balance», «eye movements», «cerebellum», «proprioception» y «physiological adaptation». En la búsqueda se identificaron 1.112 referencias, de las cuales al final se incluyeron 50: 46 estudios clínicos observacionales analítico-descriptivos (entre cohortes, reporte y serie de casos) y 4 estudios experimentales. En la respuesta neurológica a la escoliosis idiopática, la integración sensitivo-cortical de las aferencias visual-oculomotor-vestibular-propioceptiva permite realizar modificaciones a nivel postural con el fin de lograr una compensación inicial sobre el balance sagital y el centro de masa; sin embargo, con el tiempo dicho mecanismo de compensación puede agotarse y causar progresión de la deformidad inicial. (AU)

The literature that explains the neurological mechanisms underlying the development or compensation of idiopathic scoliosis is limited. The objective of the article is to describe and integrate the mechanisms and nerve pathways through which idiopathic scoliosis is compensated and/or developed. A narrative systematic review in different databases of the studies published between January 1, 1967 and April 1, 2021 was performed, using the following terms: «scoliosis», «vision», «eye», «vestibule», «labyrinth», «posture», «balance», «eye movements», «cerebellum», «proprioception», and «physiological adaptation». In the search, 1112 references were identified, of which 50 were finally included: 46 observational analytical clinical studies-descriptive (between cohorts, report and series of cases) and 4 experimental studies. In the neurological response to idiopathic scoliosis, the sensory-cortical integration of the afferences in the visual-oculomotor-vestibular-proprioceptive systems, allows modifications at the postural level in order to achieve an initial compensation on the sagittal balance and the centre of body mass; however, over time these compensation mechanisms may be exhausted causing progression of the initial deformity. (AU)

Proteomics-based synapse characterization: From proteins to circuits.

The highly heterogeneous nature of neuronal cell types and their connections presents a major challenge to the characterization of neural circuits at the protein level. New approaches now enable an increasingly sophisticated dissection of cell type- and cellular compartment-specific proteomes, as well as the profiling of the protein composition of specific synaptic connections. Here, we provide an overview of these approaches and discuss how they hold considerable promise toward unravelling the molecular mechanisms of neural circuit formation and function. Finally, we provide an outlook of technological developments that may bring the characterization of synaptic proteomes at the single-synapse level within reach.

Internet gaming disorder and tobacco use disorder share neural connectivity patterns between the subcortical and the motor network.

Internet gaming disorder (IGD) and tobacco use disorder (TUD) are globally common, non-substance-related disorders and substance-related disorders worldwide, respectively. Recognizing the commonalities between IGD and TUD will deepen understanding of the underlying mechanisms of addictive behavior and excessive online gaming. Using node strength, 141 resting-state data were collected in this study to compute network homogeneity. The participants included participants with IGD (PIGD: n = 34, male = 29, age: 15-25 years), participants with TUD (PTUD: n = 33, male = 33, age: 19-42 years), and matched healthy controls (control-for-IGD: n = 41, male = 38, age: 17-32 years; control-for-TUD: n = 33, age: 21-27 years). PIGD and PTUD exhibited common enhanced node strength between the subcortical and motor networks. Additionally, a common enhanced resting-state functional connectivity (RSFC) was found between the right thalamus and right postcentral gyrus in PIGD and PTUD. Node strength and RSFC were used to distinguish PIGD and PTUD from their respective healthy controls. Interestingly, models trained on PIGD versus controls could classify PTUD versus controls and vice versa, suggesting that these disorders share common neurological patterns. Enhanced connectivity may indicate a greater association between rewards and behaviors, inducing addiction behaviors without flexible and complex regulation. This study discovered that the connectivity between the subcortical and motor networks is a potential biological target for developing addiction treatment in the future.

Lifespan differences in visual short-term memory load-modulated functional connectivity.

Working memory is critical to higher-order executive processes and declines throughout the adult lifespan. However, our understanding of the neural mechanisms underlying this decline is limited. Recent work suggests that functional connectivity between frontal control and posterior visual regions may be critical, but examinations of age differences therein have been limited to a small set of brain regions and extreme group designs (i.e., comparing young and older adults). In this study, we build on previous research by using a lifespan cohort and a whole-brain approach to investigate working memory load-modulated functional connectivity in relation to age and performance. The article reports on analysis of the Cambridge center for Ageing and Neuroscience (Cam-CAN) data. Participants from a population-based lifespan cohort (N = 101, age 23-86) performed a visual short-term memory task during functional magnetic resonance imaging. Visual short-term memory was measured with a delayed recall task for visual motion with three different loads. Whole-brain load-modulated functional connectivity was estimated using psychophysiological interactions in a hundred regions of interest, sorted into seven networks (Schaefer et al., 2018, Yeo et al., 2011). Results showed that load-modulated functional connectivity was strongest within the dorsal attention and visual networks during encoding and maintenance. With increasing age, load-modulated functional connectivity strength decreased throughout the cortex. Whole-brain analyses for the relation between connectivity and behavior were non-significant. Our results give additional support to the sensory recruitment model of working memory. We also demonstrate the widespread negative impact of age on the modulation of functional connectivity by working memory load. Older adults might already be close to ceiling in terms of their neural resources at the lowest load and therefore less able to further increase connectivity with increasing task demands.

Characteristic cortico-cortical connection profile of human precuneus revealed by probabilistic tractography.

It is generally hypothesized that functional connectivity (FC) reflects the underlying structural connectivity (SC). The precuneus is associated with highly integrated cognitive functions. However, our understanding of the structural connections that could underlie them is limited. This study aimed to characterize the cortico-cortical connections by probabilistic tractography. The precuneus corresponds to the five cortical areas (7Am, PCV, 7Pm, 7m, POS2) on the HCP MMP atlas. We first conducted the atlas-based probabilistic tractography. The anterior part (7Am) was strongly connected to the sensorimotor region. The dorsal part (7Am, 7Pm) was highly connected with the adjacent parietal and temporal cortex, while the ventral part (PCV, 7m) showed strong connections with the adjacent posterior cingulate and medial prefrontal cortex. The most posterior part (POS2) was explicitly connected to the visual cortex. In addition, there was a correlation between SC and resting-state fMRI connectivity (Spearman's rank correlation coefficient = 0.322 ± 0.019, p < 0.05 corrected at subject level). Collectively, the current study revealed the characteristic connectional profile of precuneus, which could shed light on the structural heterogeneity for the future functional analyses.

The Basolateral Amygdala Sends a Mixed (GABAergic and Glutamatergic) Projection to the Mediodorsal Thalamic Nucleus.

The medial prefrontal cortex receives converging inputs from the mediodorsal thalamic nucleus (MD) and basolateral amygdala (BLA). Although many studies reported that the BLA also projects to MD, there is conflicting evidence regarding this projection, with some data suggesting that it originates from GABAergic or glutamatergic neurons. Therefore, the present study aimed to determine the neurotransmitter used by MD-projecting BLA cells in male and female rats. We first examined whether BLA cells retrogradely labeled by Fast Blue infusions in MD are immunopositive for multiple established markers of BLA interneurons. A minority of MD-projecting BLA cells expressed somatostatin (∼22%) or calretinin (∼11%) but not other interneuronal markers, suggesting that BLA neurons projecting to MD not only include glutamatergic cells, but also long-range GABAergic neurons. Second, we examined the responses of MD cells to optogenetic activation of BLA axons using whole-cell recordings in vitro Consistent with our immunohistochemical findings, among responsive MD cells, light stimuli typically elicited isolated EPSPs (73%) or IPSPs (27%) as well as coincident EPSPs and IPSPs (11%). Indicating that these IPSPs were monosynaptic, light-evoked EPSPs and IPSPs had the same latency and the IPSPs persisted in the presence of ionotropic glutamate receptor antagonists. Overall, our results indicate that the BLA sends a mixed, glutamatergic-GABAergic projection to MD, which likely influences coordination of activity between BLA, MD, and medial prefrontal cortex. An important challenge for future studies will be to examine the connections formed by MD-projecting glutamatergic and GABAergic BLA cells with each other and other populations of BLA cells.SIGNIFICANCE STATEMENT The mediodorsal thalamic nucleus (MD) and basolateral amygdala (BLA) send convergent projections to the medial prefrontal cortex. Although many studies reported that the BLA also projects to MD, there is conflicting evidence as to whether this projection is glutamatergic or GABAergic. By combining tract tracing, immunohistochemistry, optogenetics, and patch clamp recordings in vitro, we found that BLA neurons projecting to MD not only include glutamatergic cells, but also long-range GABAergic neurons. Differential recruitment of these two contingents of cells likely influences coordination of activity between the BLA, MD, and medial prefrontal cortex.

Altered electroencephalography resting state network coherence in remitted MDD.

Individuals with remitted depression are at greater risk for subsequent depression and therefore may provide a unique opportunity to understand the neurophysiological correlates underlying the risk of depression. Research has identified abnormal resting-state electroencephalography (EEG) power metrics and functional connectivity patterns associated with major depression, however little is known about these neural signatures in individuals with remitted depression. We investigate the spectral dynamics of 64-channel EEG surface power and source-estimated network connectivity during resting states in 37 individuals with depression, 56 with remitted depression, and 49 healthy adults that did not differ on age, education, and cognitive ability across theta, alpha, and beta frequencies. Average reference spectral EEG surface power analyses identified greater left and midfrontal theta in remitted depression compared to healthy adults. Using Network Based Statistics, we also demonstrate within and between network alterations in LORETA transformed EEG source-space coherence across the default mode, fronto-parietal, and salience networks where individuals with remitted depression exhibited enhanced coherence compared to those with depression, and healthy adults. This work builds upon our currently limited understanding of resting EEG connectivity in depression, and helps bridge the gap between aberrant EEG power and brain network connectivity dynamics in this disorder. Further, our unique examination of remitted depression relative to both healthy and depressed adults may be key to identifying brain-based biomarkers for those at high risk for future, or subsequent depression.

Functional connectivity based machine learning approach for autism detection in young children using MEG signals.

Objective.Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder, and identifying early autism biomarkers plays a vital role in improving detection and subsequent life outcomes. This study aims to reveal hidden biomarkers in the patterns of functional brain connectivity as recorded by the neuro-magnetic brain responses in children with ASD.Approach.We recorded resting-state magnetoencephalogram signals from thirty children with ASD (4-7 years) and thirty age and gender-matched typically developing (TD) children. We used a complex coherency-based functional connectivity analysis to understand the interactions between different brain regions of the neural system. The work characterizes the large-scale neural activity at different brain oscillations using functional connectivity analysis and assesses the classification performance of coherence-based (COH) measures for autism detection in young children. A comparative study has also been carried out on COH-based connectivity networks both region-wise and sensor-wise to understand frequency-band-specific connectivity patterns and their connections with autism symptomatology. We used artificial neural network (ANN) and support vector machine (SVM) classifiers in the machine learning framework with a five-fold CV technique.Main results.To classify ASD from TD children, the COH connectivity feature yields the highest classification accuracy of 91.66% in the high gamma (50-100 Hz) frequency band. In region-wise connectivity analysis, the second highest performance is in the delta band (1-4 Hz) after the gamma band. Combining the delta and gamma band features, we achieved a classification accuracy of 95.03% and 93.33% in the ANN and SVM classifiers, respectively. Using classification performance metrics and further statistical analysis, we show that ASD children demonstrate significant hyperconnectivity.Significance.Our findings support the weak central coherency theory in autism detection. Further, despite its lower complexity, we show that region-wise COH analysis outperforms the sensor-wise connectivity analysis. Altogether, these results demonstrate the functional brain connectivity patterns as an appropriate biomarker of autism in young children.

Exploring neural activity in inflammatory bowel diseases using functional connectivity and DKI-fMRI fusion.

Although MRI has made considerable progress in Inflammatory bowel disease (IBD), most studies have concentrated on data information from a single modality, and a better understanding of the interplay between brain function and structure, as well as appropriate clinical aids to diagnosis, is required. We calculated functional connectivity through fMRI time series using resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion kurtosis imaging (DKI) data from 27 IBD patients and 29 healthy controls. Through the DKI data of each subject, its unique structure map is obtained, and the relevant indicators are projected onto the structure map corresponding to each subject by using the graph Fourier transform in the grasp signal processing (GSP) technology. After the features are optimized, a classical support vector machine is used to classify the features. IBD patients have altered functional connectivity in the default mode network (DMN) and subcortical network (SCN). At the same time, compared with the traditional brain network analysis, in the test of some indicators, the average classification accuracy produced by the framework method is 12.73% higher than that of the traditional analysis method. This paper found that the brain network structure of IBD patients in DMN and SCN has changed. Simultaneously, the application of GSP technology to fuse functional information and structural information is superior to the traditional framework in classification, providing a new perspective for subsequent clinical auxiliary diagnosis.

Interactions across emotional, cognitive and subcortical motor networks underlying freezing of gait.

Freezing of gait (FOG) is a gait disorder affecting patients with Parkinson's disease (PD) and related disorders. The pathophysiology of FOG is unclear because of its phenomenological complexity involving motor, cognitive, and emotional aspects of behavior. Here we used resting-state functional MRI to retrieve functional connectivity (FC) correlated with the New FOG questionnaire (NFOGQ) reflecting severity of FOG in 67 patients with PD. NFOGQ scores were correlated with FCs in the extended basal ganglia network (BGN) involving the striatum and amygdala, and in the extra-cerebellum network (CBLN) involving the frontoparietal network (FPN). These FCs represented interactions across the emotional (amygdala), subcortical motor (BGN and CBLN), and cognitive networks (FPN). Using these FCs as features, we constructed statistical models that explained 40% of the inter-individual variances of FOG severity and that discriminated between PD patients with and without FOG. The amygdala, which connects to the subcortical motor (BGN and CBLN) and cognitive (FPN) networks, may have a pivotal role in interactions across the emotional, cognitive, and subcortical motor networks. Future refinement of the machine learning-based classifier using FCs may clarify the complex pathophysiology of FOG further and help diagnose and evaluate FOG in clinical settings.

Pre- and post-task resting-state differs in clinical populations.

Resting-state functional connectivity has generated great hopes as a potential brain biomarker for improving prevention, diagnosis, and treatment in psychiatry. This neuroimaging protocol can routinely be performed by patients and does not depend on the specificities of a task. Thus, it seems ideal for big data approaches that require aggregating data across multiple studies and sites. However, technical variability, diverging data analysis approaches, and differences in data acquisition protocols introduce heterogeneity to the aggregated data. Besides these technical aspects, a prior task that changes the psychological state of participants might also contribute to heterogeneity. In healthy participants, studies have shown that behavioral tasks can influence resting-state measures, but such effects have not yet been reported in clinical populations. Here, we fill this knowledge gap by comparing resting-state functional connectivity before and after clinically relevant tasks in two clinical conditions, namely substance use disorders and phobias. The tasks consisted of viewing craving-inducing and spider anxiety provoking pictures that are frequently used in cue-reactivity studies and exposure therapy. We found distinct pre- vs post-task resting-state connectivity differences in each group, as well as decreased thalamo-cortical and increased intra-thalamic connectivity which might be associated with decreased vigilance in both groups. Our results confirm that resting-state measures can be strongly influenced by prior emotion-inducing tasks that need to be taken into account when pooling resting-state scans for clinical biomarker detection. This demands that resting-state datasets should include a complete description of the experimental design, especially when a task preceded data collection.

Functional connectivity of sub-cortical brain regions: disparities and similarities.

Sub-cortical grey matter structures, such as the putamen, pallidum, caudate, thalamus, amygdala and hippocampus, play substantial roles in both simple and complex brain functions, including regulation of pleasure and emotions; control of movements; learning; decision-making; language development; and sensory, cognitive, social and other higher-order functions. Most of these regions act as information hubs for the nervous system, relaying and controlling the flow of information to various portions of the brain. To further understand the complex neurophysiological characteristics of sub-cortical areas, the aim of this study was to investigate the functional integrations of six sub-cortical areas to different major functional brain networks. One hundred ninety-eight healthy individuals were examined using resting-state functional MRI. The seeds identified in this study were six sub-cortical deep grey matter regions, namely putamen, pallidum, caudate, thalamus, amygdala and hippocampus. The analysis indicated that the link between the sub-cortical regions and some functional brain networks was similar in some aspects, but there were disparities in the mechanism underlying such a link and in the existence of functional connections between these regions and networks. Despite the substantial functional connectivity linkages between the sub-cortical regions, discrepancies were still noted. On the basis of the connections to the majority of the major brain networks, this study demonstrated the essential functional roles and involvements of the sub-cortical regions. This finding is consistent with an earlier report that revealed a substantial role of the sub-cortical regions in several brain functions.

Identification of overlapping and interacting networks reveals intrinsic spatiotemporal organization of the human brain.

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.