Functional Connectivity Analysis Research Articles

Automatically targeting the dorsolateral subthalamic nucleus for functional connectivity-guided rTMS therapy

Aim: Many resting-state functional magnetic resonance imaging (rs-fMRI) studies have provided evidence that repetitive transcranial magnetic stimulation (rTMS) exerts treatment effects via functional connectivity (FC) from a superficial stimulation target to a deep effective region. The dorsolateral subthalamic nucleus (DL-STN) is an effective target in deep brain stimulation surgery for Parkinson’s disease (PD), but its targeting highly depends on well-trained neurosurgeons and is not easily used for FC-guided rTMS. We aimed to devise a method for automatically localizing the DL-STN, and further develop a one-stop plug-in of rs-fMRI FC analysis to assist future individualized FC-guided rTMS. Methods: Based on structural and iron-sensitive MRI of 78 participants, two raters defined the DL-STN coordinates with very high reliability. The averaged coordinates in the standard Montreal Neurological Institute (MNI) space were: left DL-STN, x: -11.89 ± 0.82, y: -14.51 ± 1.00, and z: -6.40 ± 1.01 and the right DL-STN, x: 12.53 ± 0.77, y: -13.97 ± 0.86, and z: -6.57 ± 0.99. As the individual distances from the averaged coordinates were less than 3 mm (within one voxel for most rs-fMRI studies) for all 78 participants, we defined the average coordinates as AutoSTN. We then developed a one-stop plug-in named Connectivity and Coordinates Converting Assistant Toolbox (CC-CAT) and performed AutoSTN FC analysis. Results: The AutoSTN seed showed significant FC with the motor cortices in all participants. Conclusion: The AutoSTN-based rs-fMRI FC could guide future rTMS on PD. The one-stop plug-in CC-CAT can be used for any FC-guided rTMS treatment.

Network representation of multicellular activity in pancreatic islets: Technical considerations for functional connectivity analysis.

Within the islets of Langerhans, beta cells orchestrate synchronized insulin secretion, a pivotal aspect of metabolic homeostasis. Despite the inherent heterogeneity and multimodal activity of individual cells, intercellular coupling acts as a homogenizing force, enabling coordinated responses through the propagation of intercellular waves. Disruptions in this coordination are implicated in irregular insulin secretion, a hallmark of diabetes. Recently, innovative approaches, such as integrating multicellular calcium imaging with network analysis, have emerged for a quantitative assessment of the cellular activity in islets. However, different groups use distinct experimental preparations, microscopic techniques, apply different methods to process the measured signals and use various methods to derive functional connectivity patterns. This makes comparisons between findings and their integration into a bigger picture difficult and has led to disputes in functional connectivity interpretations. To address these issues, we present here a systematic analysis of how different approaches influence the network representation of islet activity. Our findings show that the choice of methods used to construct networks is not crucial, although care is needed when combining data from different islets. Conversely, the conclusions drawn from network analysis can be heavily affected by the pre-processing of the time series, the type of the oscillatory component in the signals, and by the experimental preparation. Our tutorial-like investigation aims to resolve interpretational issues, reconcile conflicting views, advance functional implications, and encourage researchers to adopt connectivity analysis. As we conclude, we outline challenges for future research, emphasizing the broader applicability of our conclusions to other tissues exhibiting complex multicellular dynamics.

Distinct roles of excitatory and inhibitory neurons in the medial prefrontal cortex in the expression and reconsolidation of methamphetamine-associated memory in male mice.

Methamphetamine, a commonly abused drug, is known for its high relapse rate. The persistence of addictive memories associated with methamphetamine poses a significant challenge in preventing relapse. Memory retrieval and subsequent reconsolidation provide an opportunity to disrupt addictive memories. However, the key node in the brain network involved in methamphetamine-associated memory retrieval has not been clearly defined. In this study, using the conditioned place preference in male mice, whole brain c-FOS mapping and functional connectivity analysis, together with chemogenetic manipulations of neural circuits, we identified the medial prefrontal cortex (mPFC) as a critical hub that integrates inputs from the retrosplenial cortex and the ventral tegmental area to support both the expression and reconsolidation of methamphetamine-associated memory during its retrieval. Surprisingly, with further cell-type specific analysis and manipulation, we also observed that methamphetamine-associated memory retrieval activated inhibitory neurons in the mPFC to facilitate memory reconsolidation, while suppressing excitatory neurons to aid memory expression. These findings provide novel insights into the neural circuits and cellular mechanisms involved in the retrieval process of addictive memories. They suggest that targeting the balance between excitation and inhibition in the mPFC during memory retrieval could be a promising treatment strategy to prevent relapse in methamphetamine addiction.

Functional connectivity alterations in the thalamus among patients with bronchial asthma

ObjectiveBronchial Asthma (BA) is a common chronic respiratory disease worldwide. Earlier research has demonstrated abnormal functional connectivity (FC) in multiple cognition-related cortices in asthma patients. The thalamus (Thal) serves as a relay center for transmitting sensory signals, yet the modifications in the thalamic FC among individuals with asthma remain uncertain. This research employed the resting-state functional connectivity (rsFC) approach to explore alterations in thalamic functional connectivity among individuals with BA.Patients and methodsAfter excluding participants who did not meet the criteria, this study finally included 31 patients with BA, with a gender distribution of 16 males and 15 females. Subsequently, we recruited 31 healthy control participants (HC) matched for age, gender, and educational background. All participants underwent the Montreal Cognitive Assessment (MoCA) and the Hamilton Depression Rating Scale (HAMD) assessment. Following this, both groups underwent head magnetic resonance imaging scans, and resting-state functional magnetic resonance imaging (rs-fMRI) data was collected. Based on the AAL (Automated Anatomical Labeling) template, the bilateral thalamic regions were used as seed points (ROI) for subsequent rsFC research. Pearson correlation analysis was used to explore the relationship between thalamic functional connectivity and neuropsychological scales in both groups. After controlling for potential confounding factors such as age, gender, intelligence, and emotional level, a two-sample t-test was further used to explore differences in thalamic functional connectivity between the two groups of participants.ResultCompared to the HC group, the BA group demonstrated heightened functional connectivity (FC) between the left thalamus and the left cerebellar posterior lobe (CPL), left postcentral gyrus (PCG), and right superior frontal gyrus (SFG). Concurrently, there was a decrease in FC with both the Lentiform Nucleus (LN) and the left corpus callosum (CC). Performing FC analysis with the right thalamus as the Region of Interest (ROI) revealed an increase in FC between the right thalamus and the right SFG as well as the left CPL. Conversely, a decrease in FC was observed between the right thalamus and the right LN as well as the left CC.ConclusionIn our study, we have verified the presence of aberrant FC patterns in the thalamus of BA patients. When compared to HCs, BA patients exhibit aberrant alterations in FC between the thalamus and various brain areas connected to vision, hearing, emotional regulation, cognitive control, somatic sensations, and wakefulness. This provides further confirmation of the substantial role played by the thalamus in the advancement of BA.

The vmPFC-IPL functional connectivity as the neural basis of future self-continuity impacted procrastination: the mediating role of anticipated positive outcomes

Procrastination is universally acknowledged as a problematic behavior with wide-ranging consequences impacting various facets of individuals’ lives, including academic achievement, social accomplishments, and mental health. Although previous research has indicated that future self-continuity is robustly negatively correlated with procrastination, it remains unknown about the neural mechanisms underlying the impact of future self-continuity on procrastination. To address this issue, we employed a free construction approach to collect individuals’ episodic future thinking (EFT) thoughts regarding specific procrastination tasks. Next, we conducted voxel-based morphometry (VBM) and resting-state functional connectivity (RSFC) analysis to explore the neural substrates underlying future self-continuity. Behavior results revealed that future self-continuity was significantly negatively correlated with procrastination, and positively correlated with anticipated positive outcome. The VBM analysis showed a positive association between future self-continuity and gray matter volumes in the right ventromedial prefrontal cortex (vmPFC). Furthermore, the RSFC results indicated that the functional connectivity between the right vmPFC and the left inferior parietal lobule (IPL) was positively correlated with future self-continuity. More importantly, the mediation analysis demonstrated that anticipated positive outcome can completely mediate the relationship between the vmPFC-IPL functional connectivity and procrastination. These findings suggested that vmPFC-IPL functional connectivity might prompt anticipated positive outcome about the task and thereby reduce procrastination, which provides a new perspective to understand the relationship between future self-continuity and procrastination.

Targeting thalamocortical circuits for closed-loop stimulation in Lennox-Gastaut syndrome

Abstract This paper outlines the therapeutic rationale and neurosurgical targeting technique for bilateral, closed-loop, thalamocortical stimulation in Lennox-Gastaut syndrome, a severe form of childhood-onset epilepsy. Thalamic stimulation can be an effective treatment for Lennox-Gastaut syndrome, but complete seizure control is rarely achieved. Outcomes may be improved by stimulating areas beyond the thalamus, including cortex, but the optimal targets are unknown. We aimed to identify a cortical target by synthesizing prior neuroimaging studies, and to use this knowledge to advance a dual thalamic (centromedian) and cortical (frontal) approach for closed-loop stimulation. Multi-modal brain network maps from 3 group-level studies of Lennox-Gastaut syndrome were averaged to define the area of peak overlap: simultaneous EEG-functional MRI of generalized paroxysmal fast activity, [18F]fluorodeoxyglucose PET of cortical hypometabolism, and diffusion MRI structural connectivity associated with clinical efficacy in a previous trial of thalamic deep brain stimulation. The resulting “hotspot” was used as a seed in a normative functional MRI connectivity analysis to identify connected networks. Intracranial electrophysiology was reviewed in the first two trial patients undergoing bilateral implantations guided by this hotspot. Simultaneous recordings from cortex and thalamus were analyzed for presence and synchrony of epileptiform activity. The peak overlap was in bilateral premotor cortex/caudal middle frontal gyrus. Functional connectivity of this hotspot revealed a distributed network of frontoparietal cortex resembling the diffuse abnormalities seen on EEG-functional MRI and PET. Intracranial electrophysiology showed characteristic epileptiform activity of Lennox-Gastaut syndrome in both the cortical hotspot and thalamus; most detected events occurred first in the cortex before appearing in the thalamus. Premotor frontal cortex shows peak involvement in Lennox-Gastaut syndrome and functional connectivity of this region resembles the wider epileptic brain network. Thus, it may be an optimal target for a range of neuromodulation therapies, including thalamocortical stimulation and emerging non-invasive treatments like focused ultrasound or transcranial magnetic stimulation. Compared to thalamus-only approaches, the addition of this cortical target may allow more rapid detections of seizures, more diverse stimulation paradigms, and broader modulation of the epileptic network. A prospective, multi-center trial of closed-loop thalamocortical stimulation for Lennox-Gastaut syndrome is currently underway.

Pseudo-resting-state functional MRI derived from dynamic susceptibility contrast perfusion MRI can predict cognitive impairment in glioma.

Resting-state functional MRI (rs-fMRI) can be used to estimate functional connectivity (FC) between different brain regions, which may be of value for identifying cognitive impairment in patients with brain tumors. Unfortunately, neither rs-fMRI nor neurocognitive assessments are routinely assessed clinically, mostly due to limitations in exam time and cost. Since DSC perfusion MRI is often used clinically to assess tumor vascularity and similarly uses a gradient echo-EPI sequence for T2*sensitivity, we theorized a "pseudo-rs-fMRI" signal could be derived from DSC perfusion to simultaneously quantify FC and perfusion metrics, and these metrics can be used to estimate cognitive impairment in patients with brain tumors. N=24 consecutive patients with gliomas were enrolled in a prospective study that included DSC perfusion MRI, rs-fMRI, and neurocognitive assessment. Voxel-wise modeling of contrast bolus dynamics during DSC acquisition was performed and then subtracted from the original signal to generate a residual "pseudo-rs-fMRI" signal. Following the pre-processing of pseudo-rs-fMRI, full rs-fMRI, and a truncated version of the full rs-fMRI (first 100 timepoints) data, the default mode, motor, and language network maps were generated with atlas-based ROIs. Dice scores were calculated for the resting-state network maps from pseudo-rs-fMRI and truncated rs-fMRI using the full rs-fMRI maps as reference. Seed-to-voxel and ROI-to-ROI analyses were performed to assess FC differences between cognitively impaired and non-impaired patients. Dice scores for the group-level and patient-level (mean±SD) default mode, motor, and language network maps using pseudo-rs-fMRI were 0.905/0.689±0.118 (group/patient), 0.973/0.730±0.124, and 0.935/0.665±0.142, respectively. There was no significant difference in Dice scores between pseudo-rs-fMRI and the truncated rs-fMRI default mode (P=0.97) or language networks (P=0.30), but there was a difference in motor networks (P=0.02). A multiple logistic regression classifier applied to ROI-to-ROI FC networks using pseudo-rs-fMRI could identify cognitively impaired patients (Sensitivity=84.6%, Specificity=63.6%, ROC AUC=0.7762±0.0954 (SE), P=0.0221) and performance was not significantly different than full rs-fMRI predictions (AUC=0.8881±0.0733 (SE), P=0.0013, P=0.29 compared to pseudo-rs-fMRI). DSC perfusion MRI-derived pseudo-rs-fMRI data can be used to perform typical rs-fMRI FC analyses that may identify cognitive decline in patients with brain tumors while still simultaneously performing perfusion analyses.ABBREVIATIONS: AUC = Area under curve; BOLD = Blood oxygenation level dependent; FC = Functional connectivity; MNI = Montreal Neurological Institute; ROC = Receiver operating characteristic; Rs-fMRI = Resting-state functional MRI.

Altered static and dynamic cerebellar-cerebral functional connectivity in acute pontine infarction.

This study investigates abnormalities in cerebellar-cerebral static and dynamic functional connectivity among patients with acute pontine infarction, examining the relationship between these connectivity changes and behavioral dysfunction. Resting-state functional magnetic resonance imaging was utilized to collect data from 45 patients within seven days post-pontine infarction and 34 normal controls. Seed-based static and dynamic functional connectivity analyses identified divergences in cerebellar-cerebral connectivity features between pontine infarction patients and normal controls. Correlations between abnormal functional connectivity features and behavioral scores were explored. Compared to normal controls, left pontine infarction patients exhibited significantly increased static functional connectivity within the executive, affective-limbic, and motor networks. Conversely, right pontine infarction patients demonstrated decreased static functional connectivity in the executive, affective-limbic, and default mode networks, alongside an increase in the executive and motor networks. Decreased temporal variability of dynamic functional connectivity was observed in the executive and default mode networks among left pontine infarction patients. Furthermore, abnormalities in static and dynamic functional connectivity within the executive network correlated with motor and working memory performance in patients. These findings suggest that alterations in cerebellar-cerebral static and dynamic functional connectivity could underpin the behavioral dysfunctions observed in acute pontine infarction patients.

Oscillation-specific nodal differences in Parkinson's disease patients with anxiety.

Parkinson's disease (PD) is a common neurodegenerative disorder that is predominantly known for its motor symptoms but is also accompanied by non-motor symptoms, including anxiety. The underlying neurobiological substrates and brain network changes associated with comorbid anxiety in PD require further exploration. An analysis of oscillation-specific nodal properties in patients with and without anxiety was conducted using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory. We used a band-pass filtering approach to differentiate oscillatory frequency bands for subsequent functional connectivity (FC) and graph analyses. The study included 68 non-anxiety PD (naPD) patients, 62 anxiety PD (aPD) patients, and 64 healthy controls (NC). Analyses of nodal betweenness centrality (BC), degree centrality (DC), and efficiency were conducted across multiple frequency bands. The findings indicated no significant differences in BC among naPD, aPD, and NC within the 0.01-0.08 Hz frequency range. However, we observed a specific reduction in BC at narrower frequency ranges in aPD patients, as well as differing patterns of change in DC and efficiency, which are believed to reflect the neurophysiological bases of anxiety symptoms in PD. Differential oscillation-specific nodal characteristics have been identified in PD patients with anxiety, suggesting potential dysregulations in brain network dynamics. These findings emphasize the complexity of brain network alterations in anxiety-associated PD and identify oscillatory frequencies as potential biomarkers. The study highlights the importance of considering oscillatory frequency bands in the analysis of brain network changes.

Effects of maternal supplementation with DHA and/or egg yolk powder on monoamine homeostasis in the perinatal piglet brain

ABSTRACT Objectives Reports indicate that children of mothers who received docosahexaenoic acid (DHA) or egg yolk supplements during pregnancy have improved performance on cognitive tasks and brain growth; their combination has recently been demonstrated to modulate functional neuronal network connectivity in the human-relevant piglet brain. To expand upon this functional connectivity analysis, neurochemical evaluation to determine how dietary supplementation with one or both of these nutrients during the last trimester of pregnancy alters monoamine homeostasis in selected brain regions of piglets was done. Methods Beginning gestation days 60–69 through weaning, pregnant sows were fed either control diet or diets supplemented with egg yolk powder, DHA, or both. Brains were then collected, and monoamine neurotransmitters and their metabolites were quantified from various brain regions with HPLC-ECD. Results Relative to controls, egg yolk supplementation increased serotonin metabolite (5-HIAA) levels in the cerebellum, while DHA supplementation decreased serotonin (5-HT) levels in the prefrontal cortex; combined supplementation increased norepinephrine metabolite (MHPG) levels in the prefrontal cortex and cerebellum, but decreased 5-HT levels in the posterior hippocampus. Notably, all diets increased serotonin, dopamine, and their respective metabolite levels in the substantia nigra. Disscussion This suggests both overlapping and specific effects of DHA and components of egg yolk in the context of maternal supplementation during pregnancy and lactation that might facilitate optimal neurodevelopment, with the nigrostriatal pathway being particularly sensitive. Such supplementations might impact brain function and facilitate development later in life through modulating monoamine homeostasis.

Perceived stress and brain connectivity in subthreshold depression: Insights from eyes-closed and eyes-open states

Perceived stress is an acknowledged risk factor for subthreshold depression (StD), and fluctuations in perceived stress are thought to disrupt the harmony of brain networks essential for emotional and cognitive functioning. This study aimed to elucidate the relationship between eye-open (EO) and eye-closed (EC) states, perceived stress, and StD. We recruited 27 individuals with StD and 33 healthy controls, collecting resting state fMRI data under both EC and EO conditions. We combined intrinsic connectivity and seed-based functional connectivity analyses to construct the functional network and explore differences between EC and EO conditions. Graph theory analysis revealed weakened connectivity strength in the right superior frontal gyrus (SFG) and right median cingulate and paracingulate gyrus (MCC) among participants with StD, suggesting an important role for these regions in the stress-related emotions dysregulation. Notably, altered SFG connectivity was observed to significantly relate to perceived stress levels in StD, and the SFG connection emerges as a neural mediator potentially influencing the relationship between perceived stress and StD. These findings highlight the role of SFG and MCC in perceived stress and suggest that understanding EC and EO states in relation to these regions is important in the neurobiological framework of StD. This may offer valuable perspectives for early prevention and intervention strategies in mental health disorders.

Autism spectrum disorder diagnosis using fractal and non-fractal-based functional connectivity analysis and machine learning methods

Autism spectrum disorder diagnosis using fractal and non-fractal-based functional connectivity analysis and machine learning methods

Multimodal 7T imaging reveals enhanced functional coupling between salience and frontoparietal networks in young adult tobacco cigarette smokers.

Tobacco cigarette smoking is associated with disrupted brain network dynamics in resting brain networks including the Salience (SN) and Fronto parietal (FPN). Unified multimodal methods [Resting state connectivity analysis, Diffusion Tensor Imaging (DTI), neurite orientation dispersion and density imaging (NODDI), and cortical thickness analysis] were employed to test the hypothesis that the impact of cigarette smoking on the balance among these networks is due to alterations in white matter connectivity, microstructural architecture, functional connectivity and cortical thickness (CT) and that these metrics define fundamental differences between people who smoke and nonsmokers. Multimodal analyses of previously collected 7 Tesla MRI data via the Human Connectome Project were performed on 22 people who smoke (average number of daily cigarettes was 10 ± 5) and 22 age- and sex-matched nonsmoking controls. First, functional connectivity analysis was used to examine SN-FPN-DMN interactions between people who smoke and nonsmokers. The anatomy of these networks was then assessed using DTI and CT analyses while microstructural architecture of WM was analyzed using the NODDI toolbox. Seed-based connectivity analysis revealed significantly enhanced within network [p = 0.001 FDR corrected] and between network functional coupling of the salience and R-frontoparietal networks in people who smoke [p = 0.004 FDR corrected]. The network connectivity was lateralized to the right hemisphere. Whole brain diffusion analysis revealed no significant differences between people who smoke and nonsmokers in Fractional Anisotropy, Mean diffusivity and in neurite orienting and density. There were also no significant differences in CT in the hubs of these networks. Our results demonstrate that tobacco cigarette smoking is associated with enhanced functional connectivity, but anatomy is largely intact in young adults. Whether this enhanced connectivity is pre-existing, transient or permanent is not known. The observed enhanced connectivity in resting state networks may contribute to the maintenance of smoking frequency.

Difficulty sensitivity replaces reward sensitivity during adolescence: Task-related fMRI and functional connectivity during self-regulative learning choices

AimWe examined age-related differences in valuation and cognitive control circuits during value-based decision-making. Methods13-year-olds (N = 25) and 17-year-olds (N = 22) made a metacognitive choice to be tested or not on an upcoming learning task, based on reward and difficulty associated with word-pairs. To investigate whether these determinants of subjective value are differently processed at different ages, we performed region-of-interest(ROI)-based analyses of task-related and functional connectivity data.Results: We observed age-related differences in responsiveness of valuation structures (amygdala, ventral striatum, ventromedial prefrontal cortex) and caudate nucleus, with activity modulated by reward in 13-year-olds, while in 17-year-olds activity being responsive to difficulty. These accompanied age-related differences in functional connectivity between medial prefrontal and striatal/amygdala seeds. DiscussionThese results are in line with current views that sensitivity changes for reward and difficulty during adolescence are the result of a maturational switch in effort-related signalling in the cognitive control circuit, which increasingly regulates value-signalling structures.

Altered Functional Connectivity of the Multisensory Vestibular Cortex in Patients with Chronic Unilateral Vestibulopathy.

Background: Chronic unilateral vestibulopathy (CUVP) is a common chronic vestibular syndrome; the mechanisms of central vestibular compensation in CUVP are rarely studied. Methods: This study analyzed the data of 18 patients with CUVP and 18 healthy controls (HCs) and used seed-based functional connectivity (FC) and voxel-mirrored homotopic connectivity (VMHC) analyses to explore the FC alterations. Results: Compared with HCs, patients with CUVP showed decreased FC between the left dorsolateral superior frontal gyrus and the right hippocampus; the left middle frontal gyrus and the right posterior cingulate gyrus, the right hippocampus, the right parahippocampal gyrus. There is also a reduction in FC betweenthe left and right insula. There was enhanced FC between the left supplementary motor area (SMA) and the bilateral superior occipital gyrus, the left hippocampus and the left posterior cingulate gyrus, as wellas a the left middle temporal gyrus (p = 0.03). Additionally,VMHC was decreased betweenthe bilateral medial superior frontal gyrus, the bilateral precentral gyrus, and the bilateral postcentral gyrus (p = 0.001). The zVMHC values in the bilateral superior frontal gyrus and the precentral gyrus were both negatively corrected with the Dizziness Handicap Inventory (DHI) score.wellas Conclusions: Altered FC in regions of bilateral multisensory vestibular cortex existed in patients with CUVP. Decreased FC and VMHC in the bilateral multisensory vestibular cortex may affect vestibular information integration, thus affecting self-motion perception, spatial orientation, and postural control.

A Comprehensive and Broad Approach to Resting-State Functional Connectivity in Adult Patients with Mild Traumatic Brain Injury.

Several recent works using resting-state fMRI suggest possible alterations of resting-state functional connectivity after mild traumatic brain injury. However, the literature is plagued by various analysis approaches and small study cohorts, resulting in an inconsistent array of reported findings. In this study, we aimed to investigate differences in whole-brain resting-state functional connectivity between adult patients with mild traumatic brain injury within 1 month of injury and healthy control subjects using several comprehensive resting-state functional connectivity measurement methods and analyses. A total of 123 subjects (72 patients with mild traumatic brain injury and 51 healthy controls) were included. A standard fMRI preprocessing pipeline was used. ROI/seed-based analyses were conducted using 4 standard brain parcellation methods, and the independent component analysis method was applied to measure resting-state functional connectivity. The fractional amplitude of low-frequency fluctuations was also measured. Group comparisons were performed on all measurements with appropriate whole-brain multilevel statistical analysis and correction. There were no significant differences in age, sex, education, and hand preference between groups as well as no significant correlation between all measurements and these potential confounders. We found that each resting-state functional connectivity measurement revealed various regions or connections that were different between groups. However, after we corrected for multiple comparisons, the results showed no statistically significant differences between groups in terms of resting-state functional connectivity across methods and analyses. Although previous studies point to multiple regions and networks as possible mild traumatic brain injury biomarkers, this study shows that the effect of mild injury on brain resting-state functional connectivity has not survived after rigorous statistical correction. A further study using subject-level connectivity analyses may be necessary due to both subtle and variable effects of mild traumatic brain injury on brain functional connectivity across individuals.

A primary sensory cortical interareal feedforward inhibitory circuit for tacto-visual integration

Tactile sensation and vision are often both utilized for the exploration of objects that are within reach though it is not known whether or how these two distinct sensory systems combine such information. Here in mice, we used a combination of stereo photogrammetry for 3D reconstruction of the whisker array, brain-wide anatomical tracing and functional connectivity analysis to explore the possibility of tacto-visual convergence in sensory space and within the circuitry of the primary visual cortex (VISp). Strikingly, we find that stimulation of the contralateral whisker array suppresses visually evoked activity in a tacto-visual sub-region of VISp whose visual space representation closely overlaps with the whisker search space. This suppression is mediated by local fast-spiking interneurons that receive a direct cortico-cortical input predominantly from layer 6 neurons located in the posterior primary somatosensory barrel cortex (SSp-bfd). These data demonstrate functional convergence within and between two primary sensory cortical areas for multisensory object detection and recognition.

Resting-state functional connectivity of the primary visual cortex in children with anisometropia amblyopia.

This study aimed to explore the functional connectivity of the primary visual cortex (V1) in children with anisometropic amblyopia by using the resting-state functional connectivity (RSFC) analysis method and determine whether anisometropic amblyopia is associated with changes in brain function. Functional magnetic resonance imaging (fMRI) data were obtained from 16 children with anisometropia amblyopia (CAA group) and 12 healthy children (HC group) during the resting state. The Brodmann area 17 (BA17) was used as the region of interest (ROI), and the functional connection (FC) of V1 was analyzed in both groups. A two-sample t-test was used to analyze the FC value between the two groups. Pearson's correlation was used to analyze the correlation between the mean FC value in the brain function change area of the CAA group and the best corrected visual acuity (BCVA) of amblyopia. P<0.05 was considered statistically significant. There were no significant differences in age and sex between the CAA and HC groups (p > 0.05). Compared to the HC group, the CAA group showed lower FC values in BA17 and the left medial frontal gyrus, as well as BA17 and the left triangle inferior frontal gyrus. Conversely, the CAA group showed higher FC values in BA17 and the left central posterior gyrus. Notably, BCVA in amblyopia did not correlate with the area of change in mean FC in the brain function of the CAA group. Resting-state fMRI-based functional connectivity analysis indicates a significant alteration in V1 of children with anisometropic amblyopia. These findings contribute additional insights into the neuropathological mechanisms underlying visual impairment in anisometropic amblyopia.

Dysconnectivity of the Nucleus Accumbens and Amygdala in Youths with Thought Problems: A Dimensional Approach.

Background: Youths with thought problems (TP) are at risk to develop psychosis and obsessive-compulsive disorder (OCD). Yet, the pathophysiological mechanisms underpinning TP are still unclear. Functional magnetic resonance imaging (fMRI) studies have shown that striatal and limbic alterations are associated with psychosis-like and obsessive-like symptoms in individuals at clinical risk for psychosis, schizophrenia, and OCD. More specifically, nucleus accumbens (NAcc) and amygdala are mainly involved in these associations. The current study aims to investigate the neural correlates of TP in youth populations using a dimensional approach and explore potential cognitive functions and neurotransmitters associated with it. Methods: Seed-to-voxels functional connectivity analyses using NAcc and amygdala as regions-of-interest were conducted with resting-state fMRI data obtained from 1360 young individuals, and potential confounders related to TP such as anxiety and cognitive functions were included as covariates in multiple regression analyses. Replicability was tested in using an adult cohort. In addition, functional decoding and neurochemical correlation analyses were performed to identify the associated cognitive functions and neurotransmitters. Results: The altered functional connectivities between the right NAcc and posterior parahippocampal gyrus, between the right amygdala and lateral prefrontal cortex, and between the left amygdala and the secondary visual area were the best predictors of TP in multiple regression model. These functional connections are mainly involved in social cognition and reward processing. Conclusions: The results show that alterations in the functional connectivity of the NAcc and the amygdala in neural pathways involved in social cognition and reward processing are associated with severity of TP in youths.

Dynamic graph transformer network via dual-view connectivity for autism spectrum disorder identification

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that requires objective and accurate identification methods for effective early intervention. Previous population-based methods via functional connectivity (FC) analysis ignore the differences between positive and negative FCs, which provide the potential information complementarity. And they also require additional information to construct a pre-defined graph. Meanwhile, two challenging demand attentions are the imbalance of performance caused by the class distribution and the inherent heterogeneity of multi-site data. In this paper, we propose a novel dynamic graph Transformer network based on dual-view connectivity for ASD Identification. It is based on the Autoencoders, which regard the input feature as individual feature and without any inductive bias. First, a dual-view feature extractor is designed to extract individual and complementary information from positive and negative connectivity. Then Graph Transformer network is innovated with a hot plugging K-Nearest Neighbor (KNN) algorithm module which constructs a dynamic population graph without any additional information. Additionally, we introduce the PolyLoss function and the Vrex method to address the class imbalance and improve the model's generalizability. The evaluation experiment on 1102 subjects from the ABIDE I dataset demonstrates our method can achieve superior performance over several state-of-the-art methods and satisfying generalizability for ASD identification.