Connectivity Of Cortical Networks Research Articles

Effects of continuous theta burst stimulation on contralateral primary motor cortex: a concurrent TMS-EEG study.

Continuous theta burst stimulation (cTBS) is a noninvasive brain stimulation technique. cTBS modulation is an effective treatment for motor dysfunction rehabilitation in post-stroke patients. However, there's currently a lack of research on the effects of cTBS stimulation on the contralesional hemisphere. To better understand the role of cTBS in motor rehabilitation, we investigated the neuroregulatory mechanisms of cTBS in the contralateral cortex using transcranial magnetic stimulation-evoked electroencephalography (TMS-EEG). In this randomized, sham-controlled, single-blind study, 18 healthy subjects received two separate stimulation conditions: cTBS or sham stimulation applied to the left primary motor cortex (M1). TMS-EEG measurements were taken before and immediately after stimulation. We investigated the TMS-evoked potentials (TEPs), evoked oscillatory responses (EOR), and phase synchronization index (PSI) of TMS-EEG. The effects of cTBS were analyzed using two-way repeated-measures analysis of variance (RMANOVA). There was a significant "cTBS condition × time" interaction effect on the theta and gamma bands of EOR, and on interhemisphere PSI (inter-PSI) and global PSI in both cTBS stimulation conditions. (theta: F = 4.526, P = 0.041; gamma: F = 5.574, P = 0.024; inter-PSI: F = 5.028, P = 0.032; global PSI: F = 5.129, P = 0.030). After real cTBS modulation, the energy in the theta and gamma frequency bands was significantly higher than before (theta: F = 5.747, P = 0.022; gamma: F = 5.545, P = 0.024). The inter-PSI and global PSI significantly increased after real cTBS modulation (inter-PSI: F = 6.209, P = 0.018; global PSI: F = 6.530, P = 0.015). cTBS modulation significantly increased EOR and PSI in contralateral brain regions, thereby enhancing cortical excitability and cortical functional connectivity throughout the brain. This provides a theoretical basis for cTBS neuromodulation in patients with stroke.NEW & NOTEWORTHY In right-handed individuals, the left hemisphere exhibits higher excitability. According to hemispheric competition theory, applying continuous theta burst stimulation (cTBS) to inhibit excitability in the left hemisphere can reduce its inhibitory effect on the right, thereby promoting neural excitability. This study applied cTBS to the left M1 of healthy individuals and, for the first time, recorded transcranial magnetic stimulation-evoked electroencephalography (TMS-EEG) from the right M1 to analyze the effects of cTBS on cortical oscillations and network connectivity in the contralateral cortex.

Mapping Motor Cortical Network Excitability and Connectivity Changes in De Novo Parkinson's Disease.

Transcranial magnetic stimulation-electroencephalography (TMS-EEG) has demonstrated decreased excitability in the primary motor cortex (M1) and increased excitability in the pre-supplementary motor area (pre-SMA) in moderate-advanced Parkinson's disease (PD). The aim was to investigate whether these abnormalities are evident from the early stages of the disease, their behavioral correlates, and relationship to cortico-subcortical connections. Twenty-eight early, drug-naive (de novo) PD patients and 28 healthy controls (HCs) underwent TMS-EEG to record TMS-evoked potentials (TEPs) from the primary motor cortex (M1) and the pre-SMA, kinematic recording of finger-tapping movements, and a 3T-MRI (magnetic resonance imaging) scan to obtain diffusion tensor imaging (DTI) reconstruction of white matter (WM) tracts connecting M1 to the ventral lateral anterior thalamic nucleus and pre-SMA to the anterior putamen. We found reduced M1 TEP P30 amplitude in de novo PD patients compared to HCs and similar pre-SMA TEP N40 amplitude between groups. PD patients exhibited smaller amplitude and slower velocity in finger-tapping movements and altered structural integrity in WM tracts of interest, although these changes did not correlate with TEPs. M1 hypoexcitability is a characteristic of PD from early phases and may be a marker of the parkinsonian state. Pre-SMA hyperexcitability is not evident in early PD and possibly emerges at later stages of the disease. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Abnormal local cortical functional connectivity due to interneuron dysmaturation after neonatal intermittent hypoxia.

Premature infants often experience frequent hypoxic episodes due to immaturity of respiratory control that may result in disturbances of gray and white matter development and long-term cognitive and behavioral abnormalities. We hypothesize that neonatal intermittent hypoxia alters cortical maturation of excitatory and inhibitory circuits that can be detected early with functional MRI. C57BL/6 mouse pups were exposed to an intermittent hypoxia (IH) regimen consisting of 12 to 20 daily hypoxic episodes of 5% oxygen exposure for 2 min at 37C from P3 to P7, followed by MRI at P12 and electrophysiological recordings in cortical slices and in vivo at several time points between P7 and P13. Behavioral tests were conducted at P41-P50 to assess animal activity and motor learning. Adult mice after neonatal IH exhibited hyperactivity in open field test and impaired motor learning in complex wheel tasks. Patch clamp and evoked field potential electrophysiology revealed increased glutamatergic transmission accompanied by elevation of tonic inhibition. A decreased synaptic inhibitory drive was evidenced by miniature IPSC frequency on pyramidal cells, multi-unit activity recording in vivo in the motor cortex with selective GABA A receptor inhibitor picrotoxin injection, as well as by the decreased interneuron density at P13. There was also an increased tonic depolarizing effect of picrotoxin after IH on principal cells' membrane potential on patch clamp and direct current potential in extracellular recordings. The amplitude of low-frequency fluctuation on resting-state fMRI was larger, with a larger increase after picrotoxin injection in the IH group. Increased excitatory glutamatergic transmission, decreased numbers, and activity of inhibitory interneurons after neonatal IH may affect the maturation of connectivity in cortical networks, resulting in long-term cognitive and behavioral changes, including impaired motor learning and hyperactivity. Functional MRI reveals increased intrinsic connectivity in the sensorimotor cortex, suggesting neuronal dysfunction in cortical maturation after neonatal IH. The increased tonic inhibition, presumably due to tonic extrasynaptic GABA receptor drive, may be compensatory to the elevated excitatory glutamatergic transmission.

Development of the Fetal Brain Corticocortical Structural Network during the Second-to-Third Trimester Based on Diffusion MRI.

During the second-to-third trimester, the neuronal pathways of the fetal brain experience rapid development, resulting in the complex architecture of the interwired network at birth. While diffusion MRI-based tractography has been employed to study the prenatal development of structural connectivity network (SCN) in preterm neonatal and postmortem fetal brains, the in utero development of SCN in the normal fetal brain remains largely unknown. In this study, we utilized in utero dMRI data from human fetuses of both sexes between 26 and 38 gestational weeks to investigate the developmental trajectories of the fetal brain SCN, focusing on intrahemispheric connections. Our analysis revealed significant increases in global efficiency, mean local efficiency, and clustering coefficient, along with significant decrease in shortest path length, while small-worldness persisted during the studied period, revealing balanced network integration and segregation. Widespread short-ranged connectivity strengthened significantly. The nodal strength developed in a posterior-to-anterior and medial-to-lateral order, reflecting a spatiotemporal gradient in cortical network connectivity development. Moreover, we observed distinct lateralization patterns in the fetal brain SCN. Globally, there was a leftward lateralization in network efficiency, clustering coefficient, and small-worldness. The regional lateralization patterns in most language, motor, and visual-related areas were consistent with prior knowledge, except for Wernicke's area, indicating lateralized brain wiring is an innate property of the human brain starting from the fetal period. Our findings provided a comprehensive view of the development of the fetal brain SCN and its lateralization, as a normative template that may be used to characterize atypical development.

Altered Cortical Activity during a Finger Tap in People with Stroke.

This study describes electroencephalography (EEG) measurements during a simple finger movement in people with stroke to understand how temporal patterns of cortical activation and network connectivity align with prolonged muscle contraction at the end of a task. We investigated changes in the EEG temporal patterns in the beta band (13-26Hz) of people with chronic stroke (N = 10, 7F/3M) and controls (N = 10, 7F/3M), during and after a cued movement of the index finger. We quantified the change in beta band EEG power relative to baseline as activation at each electrode and the change in task-based phase-locking value (tbPLV) and beta band task-based coherence (tbCoh) relative to baseline coherence as connectivity between EEG electrodes. Finger movements were associated with a decrease in beta power (event related desynchronization (ERD)) followed by an increase in beta power (event related resynchronization (ERS)). The ERS in the post task period was lower in the stroke group (7%), compared to controls (44%) (p < 0.001) and the transition from ERD to ERS was delayed in the stroke group (1.43s) compared to controls (0.90s) in the C3 electrode (p = 0.007). In the same post movement period, the stroke group maintained a heightened tbPLV (p = 0.030 for time to baseline of the C3:Fz electrode pair) and did not show the decrease in connectivity in electrode pair C3:Fz that was observed in controls (tbPLV: p = 0.006; tbCoh: p = 0.023). Our results suggest that delays in cortical deactivation patterns following movement coupled with changes in the time course of connectivity between the sensorimotor and frontal cortices in the stroke group might explain clinical observations of prolonged muscle activation in people with stroke. This prolonged activation might be attributed to the combination of cortical reorganization and changes to sensory feedback post-stroke.

TEMPORARY REMOVAL: Pro-inflammatory markers are related to cortical network connectivity in women exposed to interpersonal trauma with PTSD

Exposure to interpersonal violence affects a significant number of individuals each year and further increases the risk for developing Posttraumatic Stress Disorder (PTSD). A growing body of research suggests that immune system dysfunction, in particular elevated inflammation, may contribute to the pathophysiology of PTSD. However, few studies have examined the neurobiological correlates of inflammation in women with PTSD using resting-state fMRI. The present study explored the relationship between pro-inflammatory cytokine levels, C-reactive protein (CRP), tumor necrosis factor alpha TNF-alpha), and interleukin-6 (IL-6), and resting-state functional connectivity patterns in three major cortical networks (default mode network (DMN), central executive network (CEN), and salience network (SN)) in a sample of women (N=18) exposed to interpersonal violence with PTSD. Results indicated that higher CRP levels were associated with stronger functional connectivity between the SN and visual areas, but weaker functional connectivity between the CEN and visual areas. These findings suggest that pro-inflammatory markers are related to connectivity of task-positive networks in women with PTSD. Further, our results provide evidence for potential neurobiological markers of inflammation in PTSD.

Resting-state networks and their relationship with MoCA performance in PD patients.

Although mild cognitive impairment is a common non-motor symptom experienced by individuals with Parkinson's Disease, the changes in intrinsic resting-state networks associated with its onset in Parkinson's remain underexamined. To address the issue, our study sought to examine resting-state network alterations and their association with total performance in the Montreal Cognitive Assessment and its cognitive domains in Parkinson's by means of functional magnetic resonance imaging of 29 Parkinson's patients with normal cognition, 25 Parkinson's patients with mild cognitive impairment, and 13 healthy controls. To contrast the Parkinson's groups with each other and the controls, the images were used to estimate the Z-score coefficient between the regions of interest from the default mode network, the salience network and the central executive network. Our first finding was that default mode and salience network connectivity decreased significantly in Parkinson's patients regardless of their cognitive status. Additionally, default mode network nodes had a negative and salience network nodes a positive correlation with the global assessment in Parkinson's with normal cognition; this inverse relationship of both networks to total score was not found in the group with cognitive impairment. Finally, a positive correlation was found between executive scores and anterior and posterior cortical network connectivity and, in the group with cognitive impairment, between language scores and salience network connectivity. Our results suggest that specific resting-state networks of Parkinson's patients with cognitive impairment differ from those of Parkinson's patients with normal cognition, supporting the evidence that cognitive impairment in Parkinson's Disease displays a differentiated neurodegenerative pattern.

Rapid fluctuations in functional connectivity of cortical networks encode spontaneous behavior.

Experimental work across species has demonstrated that spontaneously generated behaviors are robustly coupled to variations in neural activity within the cerebral cortex. Functional magnetic resonance imaging data suggest that temporal correlations in cortical networks vary across distinct behavioral states, providing for the dynamic reorganization of patterned activity. However, these data generally lack the temporal resolution to establish links between cortical signals and the continuously varying fluctuations in spontaneous behavior observed in awake animals. Here, we used wide-field mesoscopic calcium imaging to monitor cortical dynamics in awake mice and developed an approach to quantify rapidly time-varying functional connectivity. We show that spontaneous behaviors are represented by fast changes in both the magnitude and correlational structure of cortical network activity. Combining mesoscopic imaging with simultaneous cellular-resolution two-photon microscopy demonstrated that correlations among neighboring neurons and between local and large-scale networks also encode behavior. Finally, the dynamic functional connectivity of mesoscale signals revealed subnetworks not predicted by traditional anatomical atlas-based parcellation of the cortex. These results provide new insights into how behavioral information is represented across the neocortex and demonstrate an analytical framework for investigating time-varying functional connectivity in neural networks.

Acute alcohol induces greater dose-dependent increase in the lateral cortical network functional connectivity in adult than adolescent rats

Alcohol misuse and, particularly adolescent drinking, is a major public health concern. While evidence suggests that adolescent alcohol use affects frontal brain regions that are important for cognitive control over behavior, little is known about how acute alcohol exposure alters large-scale brain networks and how sex and age may moderate such effects. Here, we employ a recently developed functional magnetic resonance imaging (fMRI) protocol to acquire rat brain functional connectivity data and use an established analytical pipeline to examine the effect of sex, age, and alcohol dose on connectivity within and between three major rodent brain networks: default mode, salience, and lateral cortical network. We identify the intra- and inter-network connectivity differences and establish moderation models to reveal significant influences of age on acute alcohol-induced lateral cortical network connectivity. Through this work, we make brain-wide isotropic fMRI data with acute alcohol challenge publicly available, with the hope to facilitate future discovery of brain regions/circuits that are causally relevant to the impact of acute alcohol use.

Functional connectivity of cortical-cerebellar networks in relation to sensorimotor behavior and clinical features in autism spectrum disorder.

Sensorimotor issues are present in the majority of individuals with autism spectrum disorder (ASD) and are associated with core symptoms. The neural systems associated with these impairments remain unclear. Using a visually guided precision gripping task during functional magnetic resonance imaging, we characterized task-based connectivity and activation of cortical, subcortical, and cerebellar visuomotor networks. Participants with ASD (n = 19; ages 10-33) and age- and sex-matched neurotypical controls (n = 18) completed a visuomotor task at low and high force levels. Relative to controls, individuals with ASD showed reduced functional connectivity of right primary motor-anterior cingulate cortex and left anterior intraparietal lobule (aIPL)-right Crus I at high force only. At low force, increased caudate, and cerebellar activation each were associated with sensorimotor behavior in controls, but not in ASD. Reduced left aIPL-right Crus I connectivity was associated with more severe clinically rated ASD symptoms. These findings suggest that sensorimotor problems in ASD, particularly at high force levels, involve deficits in the integration of multimodal sensory feedback and reduced reliance on error-monitoring processes. Adding to literature positing that cerebellar dysfunction contributes to multiple developmental issues in ASD, our data implicate parietal-cerebellar connectivity as a key neural marker underlying both core and comorbid features of ASD.

Distinctively different human neurobiological responses after trauma exposure and implications for posttraumatic stress disorder subtyping.

Trauma elicits various adaptive and maladaptive responses among all exposed people. There may be distinctively different patterns of adaptation/maladaptation or types according to neurobiological predisposition. The present study aims to dissect the heterogeneity of posttraumatic conditions in order to identify clinically meaningful subtypes in recently traumatized individuals and evaluate their neurobiological correlates and long-term prognosis. We implemented a data-driven classification approach in both discovery (n = 480) and replication (n = 220) datasets of trauma-exposed and trauma-unexposed individuals based on the clinical data across a wide range of assessments. Subtype-specific patterns of functional connectivity in higher-order cortical networks, longitudinal clinical outcomes, and changes in functional connectivity were also evaluated. We identified four distinct and replicable subtypes for trauma-exposed individuals according to posttraumatic stress symptoms. Each subtype was distinct in clinical characteristics, brain functional organization, and long-term trajectories for posttraumatic symptoms. These findings help enhance current understanding of mechanisms underlying the human-specific heterogeneous responses to trauma. Furthermore, this study contributes data towards the development of improved interventions, including targeting of subtype-specific characteristics, for trauma-exposed individuals and those with PTSD.

Relating local connectivity and global dynamics in recurrent excitatory-inhibitory networks.

How the connectivity of cortical networks determines the neural dynamics and the resulting computations is one of the key questions in neuroscience. Previous works have pursued two complementary approaches to quantify the structure in connectivity. One approach starts from the perspective of biological experiments where only the local statistics of connectivity motifs between small groups of neurons are accessible. Another approach is based instead on the perspective of artificial neural networks where the global connectivity matrix is known, and in particular its low-rank structure can be used to determine the resulting low-dimensional dynamics. A direct relationship between these two approaches is however currently missing. Specifically, it remains to be clarified how local connectivity statistics and the global low-rank connectivity structure are inter-related and shape the low-dimensional activity. To bridge this gap, here we develop a method for mapping local connectivity statistics onto an approximate global low-rank structure. Our method rests on approximating the global connectivity matrix using dominant eigenvectors, which we compute using perturbation theory for random matrices. We demonstrate that multi-population networks defined from local connectivity statistics for which the central limit theorem holds can be approximated by low-rank connectivity with Gaussian-mixture statistics. We specifically apply this method to excitatory-inhibitory networks with reciprocal motifs, and show that it yields reliable predictions for both the low-dimensional dynamics, and statistics of population activity. Importantly, it analytically accounts for the activity heterogeneity of individual neurons in specific realizations of local connectivity. Altogether, our approach allows us to disentangle the effects of mean connectivity and reciprocal motifs on the global recurrent feedback, and provides an intuitive picture of how local connectivity shapes global network dynamics.

Study on the diversity of mental states and neuroplasticity of the brain during human-machine interaction.

With the increasing demand for human-machine collaboration systems, more and more attention has been paid to the influence of human factors on the performance and security of the entire system. Especially in high-risk, high-precision, and difficult special tasks (such as space station maintenance tasks, anti-terrorist EOD tasks, surgical robot teleoperation tasks, etc.), there are higher requirements for the operator's perception and cognitive level. However, as the human brain is a complex and open giant system, the perception ability and cognitive level of the human are dynamically variable, so that it will seriously affect the performance and security of the whole system. The method proposed in this paper innovatively explained this phenomenon from two dimensions of brain space and time and attributed the dynamic changes of perception, cognitive level, and operational skills to the mental state diversity and the brain neuroplasticity. In terms of the mental state diversity, the mental states evoked paradigm and the functional brain network analysis method during work were proposed. In terms of neuroplasticity, the cognitive training intervention paradigm and the functional brain network analysis method were proposed. Twenty-six subjects participated in the mental state evoked experiment and the cognitive training intervention experiment. The results showed that (1) the mental state of the subjects during work had the characteristics of dynamic change, and due to the influence of stimulus conditions and task patterns, the mental state showed diversity. There were significant differences between functional brain networks in different mental states, the information processing efficiency and the mechanism of brain area response had changed significantly. (2) The small-world attributes of the functional brain network of the subjects before and after the cognitive training experiment were significantly different. The brain had adjusted the distribution of information flow and resources, reducing costs and increasing efficiency as a whole. It was demonstrated that the global topology of the cortical connectivity network was reconfigured and neuroplasticity was altered through cognitive training intervention. In summary, this paper revealed that mental state and neuroplasticity could change the information processing efficiency and the response mechanism of brain area, thus causing the change of perception, cognitive level and operational skills, which provided a theoretical basis for studying the relationship between neural information processing and behavior.

Functional connectivity of cortical resting-state networks is differentially affected by rest conditions

Optimal conditions for resting-state functional magnetic resonance imaging (rs-fMRI) are still highly debated. Here, we comprehensively assessed the effects of various rest conditions on all cortical resting-state networks (RSNs) defined by an established atlas. Twenty-two healthy college students (22 ± 4 years old, 12 females) were scanned on a GE 3T MRI scanner. Rs-fMRI datasets were collected under four different conditions for each subject: (1) eyes open in dim light (Eyes-Open), (2) eyes closed and awake (Eyes-Closed), (3) eyes closed while remembering four numbers through the scan session (Eyes-Closed-Number) and (4) asked to watch a movie (Movie). We completed a thorough examination of the 17 functional RSNs defined by Yeo and colleagues. Importantly, the movie led to changes in global connectivity and should be avoided as a rest condition. Conversely, there were no significant connectivity differences between conditions within the frontoparietal control and limbic networks and the following subnetworks as defined by Yeo et al.: default-B, dorsal-attention-B and salience/ventral-attention-B. These were not even significant when compared to the highly stimulative Movie condition. A significant difference was not found between Eyes-Closed and Eyes-Closed-Number conditions in whole-brain, within-network and between-network comparisons. When considering other rest conditions, however, we observed connectivity changes in some subnetworks, including those of the default-mode network. Overall, we found conditions with more external stimulation led to more changes in functional connectivity during rs-fMRI. In conclusion, the comprehensive results of our study can aid in choosing rest conditions for the study of overall and specific functional networks.

Effective Connectivity in Cortical Networks During Deception: A Lie Detection Study Based on EEG.

Thus far, when deception behaviors occur, the connectivity patterns and the communication between different brain areas remain largely unclear. In this study, the most important information flows (MIIFs) between different brain cortices during deception were explored. First, the guilty knowledge test protocol was employed, and 64 electrodes' electroencephalogram (EEG) signals were recorded from 30 subjects (15 guilty and 15 innocent). Cortical current density waveforms were then estimated on the 24 regions of interest (ROIs). Next, partial directed coherence (PDC), an effective connectivity (EC) analysis was applied in the cortical waveforms to obtain the brain EC networks for four bands: delta (1-4 Hz), theta (4-8 Hz), alpha (8-13 Hz) and beta (13-30 Hz). Furthermore, using the graph theoretical analysis, the network parameters with significant differences in the EC network were extracted as features to identify the two groups. The high classification accuracy of the four bands demonstrated that the proposed method was suitable for lie detection. In addition, based on the optimal features in the classification mode, the brain "hub" regions were identified, and the MIIFs were significantly different between the guilty and innocent groups. Moreover, the fronto-parietal network was found to be most prominent among all MIIFs at the four bands. Furthermore, combining the neurophysiology significance of the four frequency bands, the roles of all MIIFs were analyzed, which could help us to uncover the underlying cognitive processes and mechanisms of deception.

Psilocybin induces spatially constrained alterations in thalamic functional organizaton and connectivity

BackgroundClassic psychedelics, such as psilocybin and LSD, and other serotonin 2A receptor (5-HT2AR) agonists evoke acute alterations in perception and cognition. Altered thalamocortical connectivity has been hypothesized to underlie these effects, which is supported by some functional MRI (fMRI) studies. These studies have treated the thalamus as a unitary structure, despite known differential 5-HT2AR expression and functional specificity of different intrathalamic nuclei. Independent Component Analysis (ICA) has been previously used to identify reliable group-level functional subdivisions of the thalamus from resting-state fMRI (rsfMRI) data. We build on these efforts with a novel data-maximizing ICA-based approach to examine psilocybin-induced changes in intrathalamic functional organization and thalamocortical connectivity in individual participants. MethodsBaseline rsfMRI data (n=38) from healthy individuals with a long-term meditation practice was utilized to generate a statistical template of thalamic functional subdivisions. This template was then applied in a novel ICA-based analysis of the acute effects of psilocybin on intra- and extra-thalamic functional organization and connectivity in follow-up scans from a subset of the same individuals (n=18). We examined correlations with subjective reports of drug effect and compared with a previously reported analytic approach (treating the thalamus as a single functional unit). ResultsSeveral intrathalamic components showed significant psilocybin-induced alterations in spatial organization, with effects of psilocybin largely localized to the mediodorsal and pulvinar nuclei. The magnitude of changes in individual participants correlated with reported subjective effects. These components demonstrated predominant decreases in thalamocortical connectivity, largely with visual and default mode networks. Analysis in which the thalamus is treated as a singular unitary structure showed an overall numerical increase in thalamocortical connectivity, consistent with previous literature using this approach, but this increase did not reach statistical significance. ConclusionsWe utilized a novel analytic approach to discover psilocybin-induced changes in intra- and extra-thalamic functional organization and connectivity of intrathalamic nuclei and cortical networks known to express the 5-HT2AR. These changes were not observed using whole-thalamus analyses, suggesting that psilocybin may cause widespread but modest increases in thalamocortical connectivity that are offset by strong focal decreases in functionally relevant intrathalamic nuclei.

Large-Scale Exploration of Whole-Brain Structural Connectivity in Anorexia Nervosa: Alterations in the Connectivity of Frontal and Subcortical Networks

BackgroundAnorexia nervosa (AN) is characterized by disturbances in cognition and behavior surrounding eating and weight. The severity of AN combined with the absence of localized brain abnormalities suggests distributed, systemic underpinnings that may be identified using diffusion-weighted magnetic resonance imaging and tractography to reconstruct white matter pathways. MethodsDiffusion-weighted magnetic resonance imaging data acquired from female patients with AN (n= 147) and female healthy control (HC) participants (n = 119), ages 12 to 40 years, were combined across 5 studies. Probabilistic tractography was completed, and full-cortex connectomes describing streamline counts between 84 brain regions were generated and harmonized. Graph theory methods were used to describe alterations in network organization in AN. The network-based statistic tested between-group differences in brain subnetwork connectivity. The metrics strength and efficiency indexed the connectivity of brain regions (network nodes) and were compared between groups using multiple linear regression. ResultsIndividuals with AN, relative to HC peers, had reduced connectivity in a network comprising subcortical regions and greater connectivity between frontal cortical regions (p < .05, familywise error corrected). Node-based analyses indicated reduced connectivity of the left hippocampus in patients relative to HC peers (p < .05, permutation corrected). Severity of illness, assessed by body mass index, was associated with subcortical connectivity (p < .05, uncorrected). ConclusionsAnalyses identified reduced structural connectivity of subcortical networks and regions, and stronger cortical network connectivity, among individuals with AN relative to HC peers. These findings are consistent with alterations in feeding, emotion, and executive control circuits in AN, and may direct hypothesis-driven research into mechanisms of persistent restrictive eating behavior.

Examining the Role of Socioeconomic Status and Maternal Sensitivity in Predicting Functional Brain Network Connectivity in 5-Month-Old Infants.

Infancy is a sensitive period of human brain development that is plastically shaped by environmental factors. Both proximal factors, such as sensitive parenting, and distal factors, such as socioeconomic status (SES), are known predictors of individual differences in structural and functional brain systems across the lifespan, yet it is unclear how these familial and contextual factors work together to shape functional brain development during infancy, particularly during the first months of life. In the current study, we examined pre-registered hypotheses regarding the interplay between these factors to assess how maternal sensitivity, within the broader context of socioeconomic variation, relates to the development of functional connectivity in long-range cortical brain networks. Specifically, we measured resting-state functional connectivity in three cortical brain networks (fronto-parietal network, default mode network, homologous-interhemispheric connectivity) using functional near-infrared spectroscopy (fNIRS), and examined the associations between maternal sensitivity, SES, and functional connectivity in a sample of 5-month-old infants and their mothers (N = 50 dyads). Results showed that all three networks were detectable during a passive viewing task, and that maternal sensitivity was positively associated with functional connectivity in the default mode network, such that infants with more sensitive mothers exhibited enhanced functional connectivity in this network. Contrary to hypotheses, we did not observe any associations of SES with functional connectivity in the brain networks assessed in this study. This suggests that at 5 months of age, maternal sensitivity is an important proximal environmental factor associated with individual differences in functional connectivity in a long-range cortical brain network implicated in a host of emotional and social-cognitive brain processes.

Still Wanting to Win: Reward System Stability in Healthy Aging.

Healthy aging is accompanied by multi-faceted changes. Especially within the brain, healthy aging exerts substantial impetus on core parts of cognitive and motivational networks. Rewards comprise basic needs, such as food, sleep, and social contact. Thus, a functionally intact reward system remains indispensable for elderly people to cope with everyday life and adapt to their changing environment. Research shows that reward system function is better preserved in the elderly than most cognitive functions. To investigate the compensatory mechanisms providing reward system stability in aging, we employed a well-established reward paradigm (Monetary Incentive Delay Task) in groups of young and old participants while undergoing EEG measurement. As a new approach, we applied EEG connectivity analyses to assess cortical reward-related network connectivity. At the behavioral level, our results confirm that the function of the reward system is preserved in old age. The mechanisms identified for maintaining reward system function in old age do not fit into previously described models of cognitive aging. Overall, older adults exhibit lower reward-related connectivity modulation, higher reliance on posterior and right-lateralized brain areas than younger adults, and connectivity modulation in the opposite direction than younger adults, with usually greater connectivity during non-reward compared to reward conditions. We believe that the reward system has unique compensatory mechanisms distinct from other cognitive functions, probably due to its etymologically very early origin. In summary, this study provides important new insights into cortical reward network connectivity in healthy aging.

Revealing directed effective connectivity of cortical neuronal networks from measurements.

In the study of biological networks, one of the major challenges is to understand the relationships between network structure and dynamics. In this paper, we model in vitro cortical neuronal cultures as stochastic dynamical systems and apply a method that reconstructs directed networks from dynamics [Ching and Tam, Phys. Rev. E 95, 010301(R) (2017)2470-004510.1103/PhysRevE.95.010301] to reveal directed effective connectivity, namely, the directed links and synaptic weights, of the neuronal cultures from voltage measurements recorded by a multielectrode array. The effective connectivity so obtained reproduces several features of cortical regions in rats and monkeys and has similar network properties as the synaptic network of the nematode Caenorhabditis elegans, whose entire nervous system has been mapped out. The distribution of the incoming degree is bimodal and the distributions of the average incoming and outgoing synaptic strength are non-Gaussian with long tails. The effective connectivity captures different information from the commonly studied functional connectivity, estimated using statistical correlation between spiking activities. The average synaptic strengths of excitatory incoming and outgoing links are found to increase with the spiking activity in the estimated effective connectivity but not in the functional connectivity estimated using the same sets of voltage measurements. These results thus demonstrate that the reconstructed effective connectivity can capture the general properties of synaptic connections and better reveal relationships between network structure and dynamics.