Brain Functional Connectivity Analysis Research Articles

Neural Correlates of Theory of Mind in Autism Spectrum Disorder, Attention-Deficit/Hyperactivity Disorder, and the Comorbid Condition.

Theory of mind (ToM) or mentalizing difficulties is reported in attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), but the mechanism underpinning these apparently shared deficits is relatively unknown. Eighty-three young adult males, 19 with ASD alone, 21 with ADHD alone, 18 with dual diagnosis of ASD and ADHD, and 25 typically developing (TD) controls completed the functional magnetic resonance imaging version of the Frith-Happé animated-triangle ToM task. We compared neural function during ToM with two non-ToM conditions, random and goal directed motions, using whole-brain and region-of-interest analysis of brain activation and functional connectivity analyses. The groups showed comparable ToM task performance. All three clinical groups lacked local connectivity increase shown by TD controls during ToM in the right temporoparietal cortex, a key mentalizing region, with a differentially increased activation pattern in both ASD and comorbid groups relative to ADHD. Both ASD groups also showed reduced connectivity between right inferior lateral prefrontal and posterior cingulate cortices that could reflect an atypical information transmission to the mentalizing network. In contrast, with mentalizing both ADHD groups showed decreasing connectivity between the medial prefrontal and left temporoparietal cortices when compared to TD controls. Therefore, despite the complex pattern of atypical brain function underpinning ToM across the three disorders, some neurofunctional abnormalities during ToM are associated with ASD and appeared differentiable from those associated with ADHD, with the comorbid group displaying combined abnormalities found in each condition.

FMRI functional connectivity analysis via kernel graph in Alzheimer’s disease

Functional magnetic resonance imaging (fMRI) is an imaging tool that is used to analyze the brain’s functions. Brain functional connectivity analysis based on fMRI signals often calculated correlations among time series in different areas of the brain. For FC analysis most prior research works generate the brain graphs based on linear correlations, however, the nonlinear behavior of the brain can lower the accuracy of such graphs. Usually, the Pearson correlation coefficient is used which has limitations in revealing nonlinear relationships. One of the proper methods for nonlinear analysis is the Kernel trick. This method maps the data into a high dimensional space and calculates the linear relations in a new space that is equivalent to the nonlinear relation in primary space. Also, it does not need to know the nonlinear dependency in the initial space. In this study, after constructing weighted undirected graphs of fMRI data based on AAL atlas, different kernels have been applied to calculate the kernelized correlation in normal and Alzheimer’s subjects. The determination of parameters has been done by two statistical methods. To compare the performance of Kernel correlation analysis, the global features of graphs are computed. Also, the non-parametric permutation test shows that kernelized correlation demonstrates a more significant statistical difference between groups in comparison to the simple linear correlation. In different kernel analysis, the best performance was for the third-degree polynomial kernel. The features strength, characteristic path length, local efficiency, transitivity, modularity, and small-worldness were significantly different for P value 0.01. Besides, comparison to random graphs and further analysis in the Occipital lobe confirmed the results.

MRNA expression profiling in hippocampus of mice exposed to chronic unpredictable mild stress

Imaging methods that enable the investigation of functional networks both in human and animal brain provide important insights into mechanisms underlying pathologies including psychiatric disorders. Since the serotonergic receptor 1A (5-HT1A-R) has been strongly implicated in the pathophysiology of depressive and anxiety disorders, as well as in the action of antidepressant drugs, we investigated brain connectivity related to the 5-HT1A-R system by use of pharmacological functional magnetic resonance imaging in mice. We characterized functional connectivity elicited by activation of 5-HT1A-R and investigated how pharmacological and genetic manipulations of its function may modulate the evoked connectivity. Functional connectivity elicited by administration of the 5-HT1A-R agonist 8-OH-DPAT can be described by networks characterized by small-world attributes with nodes displaying highly concerted response patterns. Circuits identified comprised the brain structures known to be involved in stress-related disorders (e.g. prefrontal cortex, amygdala and hippocampus). The results also highlight the dorsomedial thalamus, a structure associated with fear processing, as a hub of the 5-HT1A-R functional network. Administration of a specific 5-HT1A-R antagonist or use of heterozygous 5-HT1A-R knockout mice significantly reduced functional connectivity elicited by 8-OH-DPAT. Whole brain functional connectivity analysis constitutes an attractive tool to characterize impairments in neurotransmission and the efficacy of pharmacological treatment in a comprehensive manner.

The effect of fatigue on brain connectivity networks

In the fatigue state, the neural response characteristics of the brain might be different from those in the normal state. Brain functional connectivity analysis is an effective tool for distinguishing between different brain states. For example, comparative studies on the brain functional connectivity have the potential to reveal the functional differences in different mental states. The purpose of this study was to explore the relationship between human mental states and brain control abilities by analyzing the effect of fatigue on the brain response connectivity. In particular, the phase‐scrambling method was used to generate images with two noise levels, while the N‐back working memory task was used to induce the fatigue state in subjects. The paradigm of rapid serial visual presentation (RSVP) was used to present visual stimuli. The analysis of brain connections in the normal and fatigue states was conducted using the open‐source eConnectome toolbox. The results demonstrated that the control areas of neural responses were mainly distributed in the parietal region in both the normal and fatigue states. Compared to the normal state, the brain connectivity power in the parietal region was significantly weakened under the fatigue state, which indicates that the control ability of the brain is reduced in the fatigue state.

Neurobiological influence of comorbid conditions in young patients diagnosed with gaming disorder: A whole-brain functional connectivity study based on a data driven method.

Gaming disorder, which is characterized by multiple cognitive and behavioral symptoms, often has comorbid psychiatric conditions such as depression and attention-deficit hyperactivity disorder. Neurobiological effects of the comorbid disorders so far reported are not converging, exhibiting positive and negative alterations of the connectivity in brain networks. In this study, we conducted resting-state functional magnetic-resonance imaging and whole brain functional connectivity analyses for young participants consisting of 40 patients diagnosed with the gaming disorder, with and without comorbid conditions, and 29 healthy controls. Compared to healthy controls, the gaming disorder-alone patients had partially diminished connectivities in the reward system and executive control network, within which there existed central nodes that served as a hub of diminished connections. In the gaming disorder patients who had comorbidity of autism spectrum disorder, the diminished connections were enlarged, with alteration of the hub nodes, to the entire brain areas involved in the reward system including cortical, subcortical and limbic areas that are crucial for reward processing, and to the whole cortical areas composing the executive control network. These observations suggest that the neurodevelopmental condition coexisting with the gaming disorder induced substantial impairment of the neural organizations associated with executive/cognitive and emotional functions, which are plausibly causal to the behavioral addiction, by rearranging and diminishing functional connectivities in the network.

The Long-Term Effects of Acupuncture on Hippocampal Functional Connectivity in aMCI with Hippocampal Atrophy: A Randomized Longitudinal fMRI Study

Background. Acupuncture has been used to treat amnestic mild cognitive impairment (aMCI) for many years in China. However, the long-term effects of continuous acupuncture treatment remained unclear. Objective. We aimed to explore the long-term effects of continuous acupuncture treatment on hippocampal functional connectivity (FC) in aMCI. Methods. Fifty healthy control (HC) participants and 28 aMCI patients were recruited for resting-state functional magnetic resonance imaging (fMRI) at baseline. The 28 aMCI patients were then divided into the aMCI acupuncture group, which received acupuncture treatment for 6 months, and the aMCI control group, which received no intervention. All aMCI patients completed the second resting-state fMRI scanning after 6 months of acupuncture treatment. Analysis based on the region of interest and two-way analysis of covariance were both used to explore the long-term effects of acupuncture on cognition change and hippocampal FC in aMCI. Results. Compared to HC, aMCI showed decreased right hippocampal FC with the right inferior/middle temporal gyrus (ITG/MTG), left amygdala, and the right fusiform and increased FC with bilateral caudates at baseline. After acupuncture treatment, the right hippocampal FC with right ITG/MTG enhanced significantly in the aMCI acupuncture group, but continued to decrease in the aMCI control group. Whole brain FC analysis showed enhanced right hippocampal FC with the right ITG and the left MTG in the aMCI acupuncture group relative to the aMCI control group. Furthermore, FC strength of the right hippocampus with right ITG at baseline was negatively correlated with the changes in memory scores of aMCI acupuncture patients. Conclusion. Acupuncture treatment could alleviate the progression of cognitive decline and could enhance hippocampal FC with ITG and MTG in aMCI that may be associated with resilience to resistant against neurodegeneration. The findings provided a better understanding of the long-term effects of acupuncture treatment and confirmed the therapeutic role of acupuncture in aMCI.

A Novel Adaptive Fading Kalman Filter-Based Approach to Time-Varying Brain Spectral/Connectivity Analyses of Event-Related EEG Signals

This paper proposes a novel adaptive fading Kalman filter (AF-KF)-based approach to time-varying brain spectral and functional connectivity analyses of event-related multi-channel electroencephalogram (EEG) signals. By modeling the EEG signals as a time-varying (TV) multivariate autoregressive (MVAR) process, a new AF-KF with variable number of measurements (AF-KF-VNM) is proposed for estimating the spectra of the EEG signals and identifying their functional connectivity. The proposed AF-KF-VNM algorithm uses a new adaptive fading method to adaptively update the model parameters of the KF for improved state estimation and utilizes multiple measurements for better adaptation to the nonstationary signal observations. Experimental results on a simulated data for modeling the TV directed interactions in multivariate neural data show that the proposed AF-KF-VNM method yields better tracking performance than other approaches tested. The proposed algorithm is then integrated into a novel methodology for combined functional Magnetic Resonance Imaging (fMRI) activation maps and EEG spectrum analyses for quantifying the differences in spectrum contents and information flows between the target and standard conditions in a visual oddball paradigm. The results and findings show that the proposed methodology agrees well with the literature and is capable of revealing significant frequency components and information flow involved as well as their time variations.

Multi-Hypergraph Learning-Based Brain Functional Connectivity Analysis in fMRI Data.

Recently, a hypergraph constructed from functional magnetic resonance imaging (fMRI) was utilized to explore brain functional connectivity networks (FCNs) for the classification of neurodegenerative diseases. Each edge of a hypergraph (called hyperedge) can connect any number of brain regions-of-interest (ROIs) instead of only two ROIs, and thus characterizes high-order relations among multiple ROIs that cannot be uncovered by a simple graph in the traditional graph based FCN construction methods. Unlike the existing hypergraph based methods where all hyperedges are assumed to have equal weights and only certain topological features are extracted from the hypergraphs, we propose a hypergraph learning based method for FCN construction in this paper. Specifically, we first generate hyperedges from fMRI time series based on sparse representation, then employ hypergraph learning to adaptively learn hyperedge weights, and finally define a hypergraph similarity matrix to represent the FCN. In our proposed method, weighting hyperedges results in better discriminative FCNs across subjects, and the defined hypergraph similarity matrix can better reveal the overall structure of brain network than using those hypergraph topological features. Moreover, we propose a multi-hypergraph learning based method by integrating multi-paradigm fMRI data, where the hyperedge weights associated with each fMRI paradigm are jointly learned and then a unified hypergraph similarity matrix is computed to represent the FCN. We validate the effectiveness of the proposed method on the Philadelphia Neurodevelopmental Cohort dataset for the classification of individuals' learning ability from three paradigms of fMRI data. Experimental results demonstrate that our proposed approach outperforms the traditional graph based methods (i.e., Pearson's correlation and partial correlation with the graphical Lasso) and the existing unweighted hypergraph based methods, which sheds light on how to optimize estimation of FCNs for cognitive and behavioral study.

Resting-state functional connectivity alterations in periventricular nodular heterotopia related epilepsy

Periventricular nodular heterotopia (PNH) is a neural migration disorder which often presents clinically with seizures. However, the underlying functional neural basis of PNH is still unclear. We aimed to explore the underlying pathological mechanism of PNH by combining both whole brain functional connectivity (FC) and seed-based FC analyses. We utilized resting-state fMRI to measure functional connectivity strength (FCS) in 38 patients with PNH-related epilepsy and 38 control subjects. The regions with FCS alterations were selected as seeds in the following FC analyses. Pearson correlation analyses were performed to explore associations between these functional neural correlates and clinical features. In comparison with controls, PNH patients showed lower FCS in bilateral insula (P < 0.05, family wise error (FWE) correction), higher FC in the default mode network and lower FC in the fronto-limbic-cerebellar circuits (P < 0.05, FWE correction). Pearson correlation analyses revealed that FCS in bilateral insula was negatively correlated with the epilepsy duration (P < 0.05); medial prefronto-insular connectivity was negatively correlated with Hamilton Anxiety Scale (P < 0.05) and cerebellar-insular connectivity was also negatively correlated with Hamilton Depression Scale (P < 0.05). Using the resting-state FCS analytical approach, we identified significant insular hypoactivation in PNH patients, which suggests that the insula might represent the cortical hub of the whole-brain networks in this condition. Additionally, disruption of resting state FC in large-scale neural networks pointed to a connectivity-based neuropathological process in PNH.

From State-to-Trait Meditation: Reconfiguration of Central Executive and Default Mode Networks.

While brain default mode network (DMN) activation in human subjects has been associated with mind wandering, meditation practice has been found to suppress it and to increase psychological well-being. In addition to DMN activity reduction, experienced meditators (EMs) during meditation practice show an increased connectivity between the DMN and the central executive network (CEN). However, the gradual change between DMN and CEN configuration from pre-meditation, during meditation, and post-meditation is unknown. Here, we investigated the change in DMN and CEN configuration by means of brain activity and functional connectivity (FC) analyses in EMs across three back-to-back functional magnetic resonance imaging (fMRI) scans: pre-meditation baseline (trait), meditation (state), and post-meditation (state-to-trait). Pre-meditation baseline group comparison was also performed between EMs and healthy controls (HCs). Meditation trait was characterized by a significant reduction in activity and FC within DMN and increased anticorrelations between DMN and CEN. Conversely, meditation state and meditation state-to-trait periods showed increased activity and FC within the DMN and between DMN and CEN. However, the latter anticorrelations were only present in EMs with limited practice. The interactions between networks during these states by means of positive diametric activity (PDA) of the fractional amplitude of low-frequency fluctuations (fALFFs) defined as [Formula: see text] revealed no trait differences but significant increases during meditation state that persisted in meditation state-to-trait. The gradual reconfiguration in DMN and CEN suggest a neural mechanism by which the CEN negatively regulates the DMN and is probably responsible for the long-term trait changes seen in meditators and reported psychological well-being.

Resting-state functional magnetic resonance imaging of supramarginal gyrus-cerebellum circuit in obsessive-compulsive disorder

Objective Regional homogeneity (ReHo) and functional connectivity (FC) were used to study obsessive-compulsive disorder(OCD), and to explore the mechanism of OCD in resting state. Method Resting-state functional magnetic resonance imaging (RS-fMRI) was performed in 55 patients with OCD(OCD group) and 50 normal controls (control group) matched by sex, age, nationality and education.The data and screening abnormal brain areas were analyzed and compared by DPARSFA2.3 and Rest software in OCD group.Whole brain FC analysis was performed with abnormal brain areas as seed points. Result Compared with the control group, ReHo in right thalamus (MNI: x=9, y=-24, z=6, t=4.3217) and left superior marginal gyrus (MNI: x=-45, y=-30, z=27, t=3.6320) increased and ReHo in right caudate nucleus (MNI: x=3, y=15, z=9, t=-3.1687) decreased in obsessive-compulsive disorder group, and the difference was statistically significant(P<0.05). Using left superior marginal gyrus, right thalamus and right caudate nucleus as seed voxels, the whole brain FC analysis showed that there were abnormal functional connections between bilateral cerebellar foot 1/2 area and left supramarginal gyrus, right thalamus and right caudate nucleus (P<0.05) and the left supramarginal gyrus-bilateral cerebellum feet 1 area-right thalamic circuit and left supramarginal gyrus-bilateral cerebellum feet 1, 2-right caudate nucleus-right thalamic circuit existed in OCD group. Conclusion The left supramarginal gyrus-bilateral cerebellum feet 1 area-right thalamic circuit and left supramarginal gyrus-bilateral cerebellum feet 1, 2-right caudate nucleus-right thalamic circuit may play an important role in the mechanism of OCD. Key words: Obsessive compulsive disorder; Regional homogeneity; Functional connection; Supramarginal gyrus-cerebellum circuit

Estrogen regulates local protein synthesis in the female hippocampus

Imaging methods that enable the investigation of functional networks both in human and animal brain provide important insights into mechanisms underlying pathologies including psychiatric disorders. Since the serotonergic receptor 1A (5-HT1A-R) has been strongly implicated in the pathophysiology of depressive and anxiety disorders, as well as in the action of antidepressant drugs, we investigated brain connectivity related to the 5-HT1A-R system by use of pharmacological functional magnetic resonance imaging in mice. We characterized functional connectivity elicited by activation of 5-HT1A-R and investigated how pharmacological and genetic manipulations of its function may modulate the evoked connectivity. Functional connectivity elicited by administration of the 5-HT1A-R agonist 8-OH-DPAT can be described by networks characterized by small-world attributes with nodes displaying highly concerted response patterns. Circuits identified comprised the brain structures known to be involved in stress-related disorders (e.g. prefrontal cortex, amygdala and hippocampus). The results also highlight the dorsomedial thalamus, a structure associated with fear processing, as a hub of the 5-HT1A-R functional network. Administration of a specific 5-HT1A-R antagonist or use of heterozygous 5-HT1A-R knockout mice significantly reduced functional connectivity elicited by 8-OH-DPAT. Whole brain functional connectivity analysis constitutes an attractive tool to characterize impairments in neurotransmission and the efficacy of pharmacological treatment in a comprehensive manner.

The right thalamic glutamate level correlates with functional connectivity with right dorsal anterior cingulate cortex/middle occipital gyrus in unmedicated obsessive-compulsive disorder: A combined fMRI and 1H-MRS study.

The imbalance in neurotransmitter and neuronal metabolite concentration within cortico-striato-thalamo-cortical (CSTC) circuit contributes to obsessive-compulsive disorder's (OCD) onset. Previous studies showed that glutamate mediated upregulation of resting-state activity in healthy people. However, there have been few studies investigating the correlational features between functional and neurochemical alterations in OCD. We utilize a combined resting-state functional magnetic resonance imaging (rs-fMRI) and proton magnetic resonance spectroscopy (1H-MRS) approach to investigate the altered functional connectivity (FC) in association with glutamatergic dysfunction in OCD pathophysiology. Three regions of interest are investigated, i.e., medial prefrontal cortex and bilateral thalamus, for seed-based whole-brain FC analysis as well as MRS data acquisition. There are 23 unmedicated adult OCD patients and 23 healthy controls recruited for brain FC analysis. Among them, 12 OCD and 8 controls are performed MRS data acquisition. Besides abnormal FC within CSTC circuit, we also find altered FCs in large-scale networks outside CSTC circuit, including occipital area and limbic and motor systems. The decreased FC between right thalamus and right middle occipital gyrus (MOG) is correlated with glutamatergic signal within right thalamus in OCD patients. Moreover, the FC between right thalamus and right dorsal anterior cingulate cortex (dACC) is associated with glutamate level in right thalamus, specifically in patient's group. Finally, the FC between right thalamus and right MOG is correlated with patient's Yale-Brown Obsessive Compulsive Scale (YBOCS) compulsion and total scores, while the right thalamic glutamatergic signal is associated with YBOCS-compulsion score. Our findings showed that the coupled intrinsic functional-biochemical alterations existed both within CSTC circuit and from CSTC to occipital lobe in OCD pathophysiology.

Anger provocation increases limbic and decreases medial prefrontal cortex connectivity with the left amygdala in reactive aggressive violent offenders

Neurobiological models propose reactive aggression as a failure in emotion regulation, caused by an imbalance between prefrontal cortical control and excessive bottom-up signals of negative affect by limbic regions, including the amygdala. Therefore, we hypothesize a negative correlation between PFC and amygdala activity (pre/post resting-state scans) in violent offenders. In this study resting-state fMRI was administered before and after an emotion (anger and happiness) provocation or engagement task within 18 male violent offenders scoring high on reactive aggression, and 18 male non-offender controls. Research in emotional pre/post resting-state showed altered connectivity by task performance. Therefore, bilateral amygdala region of interest (ROI) whole brain functional connectivity analysis tested dynamic change differences between pre and post resting-state connectivity between groups. Self-reported anger showed a positive significant relationship with medial prefrontal cortex activity in the pre-task scan and significantly increased during the emotion task in both the violent and control group. Imaging results showed a significant decrease in amygdala – medial prefrontal functional connectivity in the violent offenders and an increase in the non-offender controls after the emotion task. The opposite pattern was found for amygdala connectivity with the (para) limbic regions: violent offenders showed increased connectivity and non-offender controls showed decreased connectivity. The present results indicate that reactive aggression might stem from a focus on emotion processing, as indicated by an increase in limbic functional connectivity. The combination of a focus on emotion, along with a lack of medial prefrontal cortex regulation, has the potential to grow out of control e.g. in reactive aggression.

Binarized Brain Connectivity: A Novel Autocorrelation-Based Iterative Synchronization Technique

The brain is a highly interconnected neurobiological system. Network-level characterization is thus largely performed to understand brain functioning. Brain activity can be captured through modalities like functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG). Brain networks are then estimated through pairwise relationships between brain regions using brain connectivity. Functional connectivity, which measures the degree of coactivation between two brain regions, is estimated from pairwise EEG (or fMRI) time series using a measure of synchronization like Pearson's correlation. However, all such measures suffer from the fact that they are continuous variables, with values often lying in the ambiguous range (say 0.3–0.7) wherein it is difficult to infer whether the two time series are actually synchronized or not. This makes the interpretation of findings challenging. Synchronization measures are also largely corrupted by noise. In this paper, a novel autocorrelation-based iterative synchronization (ABIS) technique is proposed, which provides binary synchronization values (0 = not synchronized, 1 = synchronized). It is entirely data driven with no assumptions, input parameters, or arbitrary choices. We demonstrate that ABIS resolves ambiguous synchronizations and provides reliable, robust, and neurobiologically meaningful binary synchronization values. ABIS also performs better than conventional synchronization on all these faculties. This technique has tremendous applications in brain functional connectivity analysis. Complex network modeling of the brain using graph theoretic techniques largely require binary connectivity matrices, which are often obtained by arbitrarily thresholding continuous connectivity matrices. Such practice usually sophisticates the analysis or yields unreliable results. The use of ABIS could entirely eliminate these issues since it provides binary connectivity matrices in a single step, without assumptions or arbitrary choices. Additionally, it resolves ambiguous connectivities to provide a set of sure-connections and sure no-connections, which improves the interpretability of connectivity results and enhances noise robustness (which plagues connectivity analysis). This study has potential applications in network modeling of the brain, and graph-theoretic analysis in general.

Altered language network in benign childhood epilepsy patients with spikes from non-dominant side: A resting-state fMRI study

Benign childhood epilepsy with centrotemporal spikes (BECTS) is one of the most common childhood epilepsy syndromes, and language deficits associated with BECTS have become a hot topic. This study investigated alterations of the language network in BECTS children with spikes from the non-dominant side in comparison with healthy controls. Twenty-three children with BECTS and 20 age-matched healthy controls were enrolled. Region of interest −based whole brain functional connectivity analysis was used to identify the potential differences in the functional connectivity of the Broca’s area between the two groups. Increased positive functional connectivity within the Broca’s region was detected mainly at the left superior frontal gyrus (Brodmann area 8), bilateral insula, and anterior and posterior cingulate in the BECTS group. No regions showed significantly decreased connection in the BECTS patients compared to the controls. This study suggested alterations in the language network that was related with the Broca’s area in children with BECTS from the non-dominant side. Further studies with longitudinal assessments from the perceptive of functional neuroimaging are needed to illustrate the dynamic course of language development and corresponding neuroimaging evidence.

Brain Activity in Response to Trauma-specific, Negative, and Neutral Stimuli. A fMRI Study of Recent Road Traffic Accident Survivors.

Most studies of neuro-functional patterns in trauma-exposed individuals have been conducted considerable time after the traumatic event. Hence little is known about neuro-functional processing shortly after trauma-exposure. We investigated brain activity patterns in response to trauma reminders as well as neutral and negative stimuli in individuals who had recently (within 3 weeks) been involved in a road traffic accident (RTA). Twenty-three RTA survivors and 17 non-trauma-exposed healthy controls (HCs) underwent functional MRI while viewing Trauma-specific, Negative, and Neutral pictures. Data were analyzed from four a priori regions of interest, including bilateral amygdala, subcallosal cortex, and medial prefrontal cortex. In addition, we performed a whole brain analysis and functional connectivity analysis during stimulus presentation. For both groups, Negative stimuli elicited more activity in the amygdala bilaterally than did Neutral and Trauma-specific stimuli. The whole brain analysis revealed higher activation in sensory processing related areas (bilateral occipital and temporal cortices and thalamus) as well as frontal and superior parietal areas, for the RTA group compared to HC, for Trauma-specific stimuli contrasted with Neutral stimuli. We also observed higher functional connectivity for Trauma-specific stimuli, between bilateral amygdala and somatosensory areas, for the RTA group compared to controls, when contrasted with Neutral stimuli. We argue that these results might indicate an attentional sensory processing bias toward Trauma-specific stimuli for trauma exposed individuals, a result in line with findings from the post-traumatic stress disorder literature.

How feedback, motor imagery, and reward influence brain self-regulation using real-time fMRI.

The learning process involved in achieving brain self-regulation is presumed to be related to several factors, such as type of feedback, reward, mental imagery, duration of training, among others. Explicitly instructing participants to use mental imagery and monetary reward are common practices in real-time fMRI (rtfMRI) neurofeedback (NF), under the assumption that they will enhance and accelerate the learning process. However, it is still not clear what the optimal strategy is for improving volitional control. We investigated the differential effect of feedback, explicit instructions and monetary reward while training healthy individuals to up-regulate the blood-oxygen-level dependent (BOLD) signal in the supplementary motor area (SMA). Four groups were trained in a two-day rtfMRI-NF protocol: GF with NF only, GF,I with NF + explicit instructions (motor imagery), GF,R with NF + monetary reward, and GF,I,R with NF + explicit instructions (motor imagery) + monetary reward. Our results showed that GF increased significantly their BOLD self-regulation from day-1 to day-2 and GF,R showed the highest BOLD signal amplitude in SMA during the training. The two groups who were instructed to use motor imagery did not show a significant learning effect over the 2 days. The additional factors, namely motor imagery and reward, tended to increase the intersubject variability in the SMA during the course of training. Whole brain univariate and functional connectivity analyses showed common as well as distinct patterns in the four groups, representing the varied influences of feedback, reward, and instructions on the brain. Hum Brain Mapp 37:3153-3171, 2016. © 2016 Wiley Periodicals, Inc.

Identification of Focal Epileptogenic Networks in Generalized Epilepsy Using Brain Functional Connectivity Analysis of Bilateral Intracranial EEG Signals.

Simultaneous bilateral onset and bi-synchrony epileptiform discharges in electroencephalogram (EEG) remain hallmarks for generalized seizures. However, the possibility of an epileptogenic focus triggering rapidly generalized epileptiform discharges has been documented in several studies. Previously, a new multi-stage surgical procedure using bilateral intracranial EEG (iEEG) prior to and post complete corpus callosotomy (CC) was developed to uncover seizure focus in non-lateralizing focal epilepsy. Five patients with drug-resistant generalized epilepsy who underwent this procedure were included in the study. Their bilateral iEEG findings prior to complete CC showed generalized epileptiform discharges with no clear lateralization. Nonetheless, the bilateral ictal iEEG findings post complete CC indicated lateralized or localized seizure onset. This study hypothesized that brain functional connectivity analysis, applied to the pre CC bilateral iEEG recordings, could help identify focal epileptogenic networks in generalized epilepsy. The results indicated that despite diffuse epileptiform discharges, focal features can still be observed in apparent generalized seizures through brain connectivity analysis. The seizure onset localization/lateralization from connectivity analysis demonstrated a good agreement with the bilateral iEEG findings post complete CC and final surgical outcomes. Our study supports the role of focal epileptic networks in generalized seizures.

Decreased Functional Connectivity of Homotopic Brain Regions in Chronic Stroke Patients: A Resting State fMRI Study.

The recovery of motor functions is accompanied by brain reorganization, and identifying the inter-hemispheric interaction post stroke will conduce to more targeted treatments. However, the alterations of bi-hemispheric coordination pattern between homologous areas in the whole brain for chronic stroke patients were still unclear. The present study focuses on the functional connectivity (FC) of mirror regions of the whole brain to investigate the inter-hemispheric interaction using a new fMRI method named voxel-mirrored homotopic connectivity (VMHC). Thirty left subcortical chronic stroke patients with pure motor deficits and 37 well-matched healthy controls (HCs) underwent resting-state fMRI scans. We employed a VMHC analysis to determine the brain areas showed significant differences between groups in FC between homologous regions, and we explored the relationships between the mean VMHC of each survived area and clinical tests within patient group using Pearson correlation. In addition, the brain areas showed significant correlations between the mean VMHC and clinical tests were defined as the seed regions for whole brain FC analysis. Relative to HCs, patients group displayed lower VMHC in the precentral gyrus, postcentral gyrus, inferior frontal gyrus, middle temporal gyrus, calcarine gyrus, thalamus, cerebellum anterior lobe, and cerebellum posterior lobe (CPL). Moreover, the VMHC of CPL was positively correlated with the Fugl–Meyer Score of hand (FMA-H), while a negative correlation between illness duration and the VMHC of this region was also detected. Furthermore, we found that when compared with HCs, the right CPL exhibited reduced FC with the left precentral gyrus, inferior frontal gyrus, inferior parietal lobule, middle temporal gyrus, thalamus and hippocampus. Our results suggest that the functional coordination across hemispheres is impaired in chronic stroke patients, and increased VMHC of the CPL is significantly associated with higher FMA-H scores. These findings may be helpful in understanding the mechanism of hand deficit after stroke, and the CPL may serve as a target region for hand rehabilitation following stroke.