Vulnerable brain regions in adolescent major depressive disorder:A resting-state functional magnetic resonance imaging activation likelihood estimation meta-analysis

BACKGROUND Adolescent major depressive disorder(MDD)is a significant mental health concern that often leads to recurrent depression in adulthood.Resting-state functional magnetic resonance imaging(rs-fMRI)offers unique insights into the neural mechanisms underlying this condition.However,despite previous research,the specific vulnerable brain regions affected in adolescent MDD patients have not been fully elucidated.AIM To identify consistent vulnerable brain regions in adolescent MDD patients using rs-fMRI and activation likelihood estimation(ALE)meta-analysis.METHODS We performed a comprehensive literature search through July 12,2023,for studies investigating brain functional changes in adolescent MDD patients.We utilized regional homogeneity(ReHo),amplitude of low-frequency fluctuations(ALFF)and fractional ALFF(fALFF)analyses.We compared the regions of aberrant spontaneous neural activity in adolescents with MDD vs healthy controls(HCs)using ALE.RESULTS Ten studies(369 adolescent MDD patients and 313 HCs)were included.Combining the ReHo and ALFF/fALFF data,the results revealed that the activity in the right cuneus and left precuneus was lower in the adolescent MDD patients than in the HCs(voxel size:648 mm3,P<0.05),and no brain region exhibited increased activity.Based on the ALFF data,we found decreased activity in the right cuneus and left precuneus in adolescent MDD patients(voxel size:736 mm3,P<0.05),with no regions exhibiting increased activity.CONCLUSION Through ALE meta-analysis,we consistently identified the right cuneus and left precuneus as vulnerable brain regions in adolescent MDD patients,increasing our understanding of the neuropathology of affected adolescents.

Global Functional Network Connectivity Disturbances in Parkinson’s Disease with Mild Cognitive Impairment by Resting-State Functional MRI

Examining the spontaneous BOLD activity to understand the neural mechanism of Parkinson’s disease(PD)with mild cognitive impairment(MCI)is a focus in resting-state functional MRI(rs-fMRI)studies.This study aimed to investigate the alteration of brain functional connectivity in PD with MCI in a systematical way at two levels:functional connectivity analysis within resting state networks(RSNs)and functional network connectivity(FNC)analysis.Using group independent component analysis(ICA)on rs-fMRI data acquired from 30 participants(14 healthy controls and 16 PD patients with MCI),16 RSNs were identified,and functional connectivity analysis within the RSNs and FNC analysis were carried out between groups.Compared to controls,patients with PD showed decreased functional connectivity within putamen network,thalamus network,cerebellar network,attention network,and self-referential network,and increased functional connectivity within execution network.Globally disturbed,mostly increased functional connectivity of FNC was observed in PD group,and insular network and execution network were the dominant network with extensively increased functional connectivity with other RSNs.Cerebellar network showed decreased functional connectivity with caudate network,insular network,and self-referential network.In general,decreased functional connectivity within RSNs and globally disturbed,mostly increased functional connectivity of FNC may be characteristics of PD.Increased functional connectivity within execution network may be an early marker of PD.The multi-perspective study based on RSNs may be a valuable means to assess functional changes corresponding to specific RSN,contributing to the understanding of the neural mechanism of PD.

Modified constraint-induced movement therapy enhances cortical plasticity in a rat model of traumatic brain injury:a resting-state functional MRI study

Modified constraint-induced movement therapy(mCIMT)has shown beneficial effects on motor function improvement after brain injury,but the exact mechanism remains unclear.In this study,amplitude of low frequency fluctuation(ALFF)metrics measured by resting-state functional magnetic resonance imaging was obtained to investigate the efficacy and mechanism of mCIMT in a control co rtical impact(CCI)rat model simulating traumatic brain injury.At 3 days after control co rtical impact model establishment,we found that the mean ALFF(mALFF)signals were decreased in the left motor cortex,somatosensory co rtex,insula cortex and the right motor co rtex,and were increased in the right corpus callosum.After 3 weeks of an 8-hour daily mClMT treatment,the mALFF values were significantly increased in the bilateral hemispheres compared with those at 3 days postoperatively.The mALFF signal valu es of left corpus callosum,left somatosensory cortex,right medial prefro ntal cortex,right motor co rtex,left postero dorsal hippocampus,left motor cortex,right corpus callosum,and right somatosensory cortex were increased in the mCIMT group compared with the control cortical impact group.Finally,we identified brain regions with significantly decreased mALFF valu es at 3 days postoperatively.Pearson correlation coefficients with the right forelimb sliding score indicated that the improvement in motor function of the affected upper limb was associated with an increase in mALFF values in these brain regions.Our findings suggest that functional co rtical plasticity changes after brain injury,and that mCIMT is an effective method to improve affected upper limb motor function by promoting bilateral hemispheric co rtical remodeling.mALFF values correlate with behavio ral changes and can potentially be used as biomarkers to assess dynamic cortical plasticity after traumatic brain injury.

Brain activation and inhibition after acupuncture at Taichong and Taixi: resting-state functional magnetic resonance imaging

Acupuncture can induce changes in the brain. However, the majority of studies to date have focused on a single acupoint at a time. In the present study, we observed activity changes in the brains of healthy volunteers before and after acupuncture atTaichong （LR3） andTaixi （KI3） using resting-state functional magnetic resonance imaging. Fifteen healthy volunteers underwent resting-state functional magnetic resonance imaging of the brain 15 minutes before acupuncture, then received acupuncture atTaichong andTaixi using the nail-pressing needle insertion method, after which the needle was retained in place for 30 minutes. Fifteen minutes after withdrawal of the needle, the volunteers underwent a further session of resting-state functional magnetic res-onance imaging, which revealed that the amplitude of low-frequency lfuctuation, a measure of spontaneous neuronal activity, increased mainly in the cerebral occipital lobe and middle occipital gyrus （Brodmann area 18/19）, inferior occipital gyrus （Brodmann area 18） and cuneus （Brodmann area 18）, but decreased mainly in the gyrus rectus of the frontal lobe （Brodmann area 11）, inferi-or frontal gyrus （Brodmann area 44） and the center of the posterior lobe of the cerebellum. The present ifndings indicate that acupuncture atTaichong andTaixi speciifcally promote blood lfow and activation in the brain areas related to vision, emotion and cognition, and inhibit brain areas related to emotion, attention, phonological and semantic processing, and memory.

The development of brain functional connectivity networks revealed by resting-state functional magnetic resonance imaging

Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the independent components of activation and network connectivity between brain regions, we examined brain activity status and development trends in children aged 3 and 5 years. These data could provide a reference for brain function rehabilitation in children with illness or abnormal function. We acquired functional magnetic resonance images from 15 3-year-old children and 15 5-year-old children under natural sleep cond让ions. The participants were recruited from five kindergartens in the Nanshan District of Shenzhen City, China. The parents of the participants signed an informed consent form with the premise that they had been fully informed regarding the experimental protocol. We used masked independent component analysis and BrainNet Viewer software to explore the independent components of the brain and correlation connections between brain regions. We identified seven independent components in the two groups of children, including the executive control network, the dorsal attention network, the default mode network, the left frontoparietal network, the right frontoparietal network, the salience network, and the motor network. In the default mode network, the posterior cingulate cortex, medial frontal gyrus, and inferior parietal lobule were activated in both 3- and 5-year-old children, supporting the "three-brain region theory” of the default mode network. In the frontoparietal network, the frontal and parietal gyri were activated in the two groups of children, and functional connectivity was strengthened in 5-year-olds compared with 3-year-olds, although the nodes and network connections were not yet mature. The high-correlation network connections in the default mode networks and dorsal attention networks had been significantly strengthened in 5-year-olds vs. 3-year-olds. Further, the salience network in the 3-year-old children included an activated insula/inferior frontal gyrus-anterior cingulate cortex network circu让 and an activated thalamus-parahippocampal-posterior cingulate cortex-subcortical regions network circuit. By the age of 5 years, no des and high-correlation network connections (edges) were reduced in the salience network. Overall, activation of the dorsal attention network, default mode network, left frontoparietal network, and right frontoparietal network increased (the volume of activation increased, the signals strengthened, and the high-correlation connections increased and strengthened) in 5-year-olds compared with 3-year-olds, but activation in some brain nodes weakened or disappeared in the salience network, and the network connections (edges) were reduced. Between the ages of 3 and 5 years, we observed a tendency for function in some brain regions to be strengthened and for the generalization of activation to be reduced, indicating that specialization begins to develop at this time. The study protocol was approved by the local ethics committee of the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences in China with approval No. SIAT-IRB- 131115-H0075 on November 15, 2013.

Alteration of functional connectivity in patients with Alzheimer’s disease revealed by resting-state functional magnetic resonance imaging

The main symptom of patients with Alzheimer’s disease is cognitive dysfunction. Alzheimer’s disease is mainly diagnosed based on changes in brain structure. Functional connectivity reflects the synchrony of functional activities between non-adjacent brain regions, and changes in functional connectivity appear earlier than those in brain structure. In this study, we detected resting-state functional connectivity changes in patients with Alzheimer’s disease to provide reference evidence for disease prediction. Functional magnetic resonance imaging data from patients with Alzheimer’s disease were used to show whether particular white and gray matter areas had certain functional connectivity patterns and if these patterns changed with disease severity. In nine white and corresponding gray matter regions, correlations of normal cognition, early mild cognitive impairment, and late mild cognitive impairment with blood oxygen level-dependent signal time series were detected. Average correlation coefficient analysis indicated functional connectivity patterns between white and gray matter in the resting state of patients with Alzheimer’s disease. Functional connectivity pattern variation correlated with disease severity, with some regions having relatively strong or weak correlations. We found that the correlation coefficients of five regions were 0.3–0.5 in patients with normal cognition and 0–0.2 in those developing Alzheimer’s disease. Moreover, in the other four regions, the range increased to 0.45–0.7 with increasing cognitive impairment. In some white and gray matter areas, there were specific connectivity patterns. Changes in regional white and gray matter connectivity patterns may be used to predict Alzheimer’s disease;however, detailed information on specific connectivity patterns is needed. All study data were obtained from the Alzheimer’s Disease Neuroimaging Initiative Library of the Image and Data Archive Database.

Small-worldness of brain networks after brachial plexus injury: a resting-state functional magnetic resonance imaging study

Research on brain function after brachial plexus injury focuses on local cortical functional reorganization,and few studies have focused on brain networks after brachial plexus injury.Changes in brain networks may help understanding of brain plasticity at the global level.We hypothesized that topology of the global cerebral resting-state functional network changes after unilateral brachial plexus injury.Thus,in this cross-sectional study,we recruited eight male patients with unilateral brachial plexus injury（right handedness,mean age of 27.9±5.4years old）and eight male healthy controls（right handedness,mean age of 28.6±3.2）.After acquiring and preprocessing resting-state magnetic resonance imaging data,the cerebrum was divided into 90 regions and Pearson’s correlation coefficient calculated between regions.These correlation matrices were then converted into a binary matrix with affixed sparsity values of 0.1–0.46.Under sparsity conditions,both groups satisfied this small-world property.The clustering coefficient was markedly lower,while average shortest path remarkably higher in patients compared with healthy controls.These findings confirm that cerebral functional networks in patients still show smallworld characteristics,which are highly effective in information transmission in the brain,as well as normal controls.Alternatively,varied small-worldness suggests that capacity of information transmission and integration in different brain regions in brachial plexus injury patients is damaged.

Resting-state functional connectivity abnormalities in first-onset unmedicated depression

Depression is closely linked to the morphology and functional abnormalities of multiple brain regions; however, its topological structure throughout the whole brain remains unclear. We col- lected resting-state functional MRI data from 36 first-onset unmedicated depression patients and 27 healthy controls. The resting-state functional connectivity was constructed using the Auto- mated Anatomical Labeling template with a partial correlation method. The metrics calculation and statistical analysis were performed using complex network theory. The results showed that both depressive patients and healthy controls presented typical small-world attributes. Compared with healthy controls, characteristic path length was significantly shorter in depressive patients, suggesting development toward randomization. Patients with depression showed apparently abnormal node attributes at key areas in cortical-striatal-pallidal-thalamic circuits. In addition, right hippocampus and right thalamus were closely linked with the severity of depression. We se- lected 270 local attributes as the classification features and their P values were regarded as criteria for statistically significant differences. An artificial neural network algorithm was applied for classification research. The results showed that brain network metrics could be used as an effec- tive feature in machine learning research, which brings about a reasonable application prospect for brain network metrics. The present study also highlighted a significant positive correlation between the importance of the attributes and the intergroup differences; that is, the more sig- nificant the differences in node attributes, the stronger their contribution to the classification. Experimental findings indicate that statistical significance is an effective quantitative indicator of the selection of brain network metrics and can assist the clinical diagnosis of depression.

Abnormal resting-state functional network centrality in patients with high myopia： evidence from a voxel-wise degree centrality analysis

AIM： To investigate the functional networks underlying the brain-activity changes of patients with high myopia using the voxel-wise degree centrality（DC） method.METHODS： In total, 38 patients with high myopia（HM）（17 males and 21 females）, whose binocular refractive diopter were-6.00 to-7.00 D, and 38 healthy controls（17 males and 21 females）, closely matched in age, sex, and education levels, participated in the study. Spontaneous brain activities were evaluated using the voxel-wise DC method. The receiver operating characteristic curve was measured to distinguish patients with HM from healthy controls. Correlation analysis was used to explore the relationship between the observed mean DC values of the different brain areas and the behavioral performance.RESULTS： Compared with healthy controls, HM patients had significantly decreased DC values in the right inferior frontal gyrus/insula, right middle frontal gyrus, and right supramarginal/inferior parietal lobule（P〈0.05）. In contrast, HM patients had significantly increased DC values in the right cerebellum posterior lobe, left precentral gyrus/postcentral gyrus, and right middle cingulate gyrus（P〈0.05）. However, no relationship was found between the observed mean DC values of the different brain areas and the behavioral performance（P〉0.05）.CONCLUSION： HM is associated with abnormalities in many brain regions, which may indicate the neural mechanisms of HM. The altered DC values may be used as a useful biomarker for the brain activity changes in HM patients.

Analgesic effects of balanced acupuncture versus body acupuncture in low-back and leg pain patients with lumbar disc herniation, as assessed by resting-state functional magnetic resonance imaging

Balanced acupuncture, a single-acupoint balance therapy, regulates the balance of the cerebral center, and is characterized by exerting quick effects and a short treatment course. A total of 20 low-back and leg pain patients with lumbar disc herniation were treated with balanced acupuncture or body acupuncture. Central mechanisms of vaded acupunctures were compared using resting-state functional MRI. Patients from both groups received functional MRI before and after acupuncture. Functional connectivity in brain regions that were strongly associated with the bilatera amygdala was analyzed utilizing AFNI software. Visual analogue scale scores were greater in the balanced acupuncture group compared with the body acupuncture group. Function of the endogenous pain regulation network was enhanced in patients in the balanced acupuncture group, but was not changed in the body acupuncture group. This result indicates that the analgesic effects of body acupuncture do not work through the central nervous system. These data suggest that balanced acupuncture exerts analgesic effects on low-back and leg pain patients with lumbar disc herniation by regulating the function of the endogenous pain regulation network.

Human Mirror Neuron System (hMNS) Specific Differences in Resting-State Functional Connectivity in Self-Reported Democrats and Republicans: A Pilot Study

In light of ever-present partisan division in the US political system, it is critical that researchers gain a better under-standing of potential biological differences that exist between self-professed Democrats and Republicans. In the current pilot experiment, we examined differences within the human mirror neuron system (hMNS), a network linked to a host of social and emotional abilities, in a small group of self-identified Republicans and Democrats. We found clear differences between these two groups with respect to resting-state brain connectivity within the hMNS. These neural differences were not systematically related to differences in empathy. Our findings are consistent with the idea that other factors, such as one’s preferential type of social connectivity (broad vs. tight), may have driven the reported findings. These data provide novel insights regarding our knowledge of the biological basis of party identification, and suggest specific directions for future research.

Survivors of COVID-19 exhibit altered amplitudes of low frequency fluctuation in the brain: a resting-state functional magnetic resonance imaging study at 1-year follow-up

Although some short-term follow-up studies have found that individuals recovering from coronavirus disease 2019(COVID-19)exhibit anxiety,depression,and altered brain microstructure,their long-term physical problems,neuropsychiatric sequelae,and changes in brain function remain unknown.This observational cohort study collected 1-year follow-up data from 22 patients who had been hospitalized with COVID-19(8 males and 11 females,aged 54.2±8.7 years).Fatigue and myalgia were persistent symptoms at the 1-year follow-up.The resting state functional magnetic resonance imaging revealed that compared with 29 healthy controls(7 males and 18 females,aged 50.5±11.6 years),COVID-19 survivors had greatly increased amplitude of low-frequency fluctuation(ALFF)values in the left precentral gyrus,middle frontal gyrus,inferior frontal gyrus of operculum,inferior frontal gyrus of triangle,insula,hippocampus,parahippocampal gyrus,fusiform gyrus,postcentral gyrus,inferior parietal angular gyrus,supramarginal gyrus,angular gyrus,thalamus,middle temporal gyrus,inferior temporal gyrus,caudate,and putamen.ALFF values in the left caudate of the COVID-19 survivors were positively correlated with their Athens Insomnia Scale scores,and those in the left precentral gyrus were positively correlated with neutrophil count during hospitalization.The long-term follow-up results suggest that the ALFF in brain regions related to mood and sleep regulation were altered in COVID-19 survivors.This can help us understand the neurobiological mechanisms of COVID-19-related neuropsychiatric sequelae.This study was approved by the Ethics Committee of the Second Xiangya Hospital of Central South University(approval No.2020 S004)on March 19,2020.

Connectivity differences between adult male and female patients with attention deficit hyperactivity disorder according to resting-state functional MRI

Attention deficit hyperactivity disorder（ADHD） is a pervasive psychiatric disorder that affects both children and adults. Adult male and female patients with ADHD are differentially affected, but few studies have explored the differences. The purpose of this study was to quantify differences between adult male and female patients with ADHD based on neuroimaging and connectivity analysis. Resting-state functional magnetic resonance imaging scans were obtained and preprocessed in 82 patients. Group-wise differences between male and female patients were quantified using degree centrality for different brain regions. The medial-, middle-, and inferior-frontal gyrus, superior parietal lobule, precuneus, supramarginal gyrus, superior- and middle-temporal gyrus, middle occipital gyrus, and cuneus were identified as regions with significant group-wise differences. The identified regions were correlated with clinical scores reflecting depression and anxiety and significant correlations were found. Adult ADHD patients exhibit different levels of depression and anxiety depending on sex, and our study provides insight into how changes in brain circuitry might differentially impact male and female ADHD patients.

Age-related changes in resting-state functional connectivity in older adults

Age-related changes in the brain connectivity of healthy older adults have been widely studied in recent years,with some differences in the obtained results.Most of these studies showed decreases in general functional connectivity,but they also found increases in some particular regions and areas.Frequently,these studies compared young individuals with older subjects,but few studies compared different age groups only in older populations.The purpose of this study is to analyze whole-brain functional connectivity in healthy older adult groups and its network characteristics through functional segregation.A total of 114 individuals,48 to 89 years old,were scanned using resting-state functional magnetic resonance imaging in a resting state paradigm and were divided into six different age groups(<60,60–64,65–69,70–74,75–79,≥80 years old).A partial correlation analysis,a pooled correlation analysis and a study of 3-cycle regions with prominent connectivity were conducted.Our results showed progressive diminution in the functional connectivity among different age groups and this was particularly pronounced between 75 and 79 years old.The oldest group(≥80 years old)showed a slight increase in functional connectivity compared to the other groups.This occurred possibly because of compensatory mechanism in brain functioning.This study provides information on the brain functional characteristics of every age group,with more specific information on the functional progressive decline,and supplies methodological tools to study functional connectivity characteristics.Approval for the study was obtained from the ethics committee of the Comision de Bioetica de la Universidad de Barcelona(approval No.PSI2012-38257)on June 5,2012,and from the ethics committee of the Barcelona’s Hospital Clinic(approval No.2009-5306 and 2011-6604)on October 22,2009 and April 7,2011 respectively.

An abnormal resting-state functional brain network indicates progression towards Alzheimer's disease

Brain structure and cognitive function change in the temporal lobe, hippocampus, and prefrontal cortex of patients with mild cognitive impairment and Alzheimer＇s disease, and brain network-connection strength, network efficiency, and nodal attributes are abnormal. However, existing research has only analyzed the differences between these patients and normal controls. In this study, we constructed brain networks using resting-state functional MRI data that was extracted from four populations （nor- mal controls, patients with early mild cognitive impairment, patients with late mild cognitive impairment, and patients with Alzheimer＇s disease） using the Alzheimer＇s Disease Neuroimaging Initiative data set. The aim was to analyze the characteristics of resting-state functional neural networks, and to observe mild cognitive impairment at different stages before the transformation to Alzheimer＇s disease. Results showed that as cognitive deficits increased across the four groups, the shortest path in the rest- ing-state functional network gradually increased, while clustering coefficients gradually decreased. This evidence indicates that dementia is associated with a decline of brain network efficiency. In addi- tion, the changes in functional networks revealed the progressive deterioration of network function across brain regions from healthy elderly adults to those with mild cognitive impairment and AIz- heimer＇s disease. The alterations of node attributes in brain regions may reflect the cognitive functions in brain regions, and we speculate that early impairments in memory, hearing, and language function can eventually lead to diffuse brain injury and other cognitive impairments.

Age-related connectivity differences between attention deficit and hyperactivity disorder patients and typically developing subjects：a resting-state functional MRI study

Attention deficit and hyperactivity disorder（ADHD） is a disorder characterized by behavioral symptoms including hyperactivity/impulsivity among children,adolescents,and adults.These ADHD related symptoms are influenced by the complex interaction of brain networks which were under explored.We explored age-related brain network differences between ADHD patients and typically developing（TD） subjects using resting state f MRI（rs-f MRI） for three age groups of children,adolescents,and adults.We collected rs-f MRI data from 184 individuals（27 ADHD children and 31 TD children;32 ADHD adolescents and 32 TD adolescents;and 31 ADHD adults and 31 TD adults）.The Brainnetome Atlas was used to define nodes in the network analysis.We compared three age groups of ADHD and TD subjects to identify the distinct regions that could explain age-related brain network differences based on degree centrality,a well-known measure of nodal centrality.The left middle temporal gyrus showed significant interaction effects between disease status（i.e.,ADHD or TD） and age（i.e.,child,adolescent,or adult）（P 0.001）.Additional regions were identified at a relaxed threshold（P 0.05）.Many of the identified regions（the left inferior frontal gyrus,the left middle temporal gyrus,and the left insular gyrus） were related to cognitive function.The results of our study suggest that aberrant development in cognitive brain regions might be associated with age-related brain network changes in ADHD patients.These findings contribute to better understand how brain function influences the symptoms of ADHD.

Altered spontaneous brain activity in patients with diabetic optic neuropathy:A resting-state functional magnetic resonance imaging study using regional homogeneity

BACKGROUND Diabetes is a common chronic disease.Given the increasing incidence of diabetes,more individuals are affected by diabetic optic neuropathy(DON),which results in decreased vision.Whether DON leads to abnormalities of other visual systems,including the eye,the visual cortex,and other brain regions,remains unknown.AIM To investigate the local characteristics of spontaneous brain activity using regional homogeneity(ReHo)in patients with DON.METHODS We matched 22 patients with DON with 22 healthy controls(HCs).All subjects underwent resting-state functional magnetic resonance imaging.The ReHo technique was used to record spontaneous changes in brain activity.Receiver operating characteristic(ROC)curves were applied to differentiate between ReHo values for patients with DON and HCs.We also assessed the correlation between Hospital Anxiety and Depression Scale scores and ReHo values in DON patients using Pearson correlation analysis.RESULTS ReHo values of the right middle frontal gyrus(RMFG),left anterior cingulate(LAC),and superior frontal gyrus(SFG)/left frontal superior orbital gyrus(LFSO)were significantly lower in DON patients compared to HCs.Among these,the greatest difference was observed in the RMFG.The result of the ROC curves suggest that ReHo values in altered brain regions may help diagnose DON,and the RMFG and LAC ReHo values are more clinically relevant than SFG/LFSO.We also found that anxiety and depression scores of the DON group were extremely negatively correlated with the LAC ReHo values(r=-0.9336,P<0.0001 and r=-0.8453,P<0.0001,respectively).CONCLUSION Three different brain regions show ReHo changes in DON patients,and these changes could serve as diagnostic and/or prognostic biomarkers to further guide the prevention and treatment of DON patients.

Sex Differences in Reconstructed Resting-State Functional Brain Networks for Children

Neuroscience studies have demonstrated that functional differences in human brains between males and females might result in their cognitive and psychological distinctions. To investigate sex differences in resting-state functional networks for children, the functional brain networks of two groups including boys and girls were reconstructed by functional connectivity with significant between-group differences respectively based on two brain atlases, and then the reconstructed functional networks were compared from the viewpoint of small-world properties. The functional brain networks of the two groups both displayed topological properties of the small-world network based on different brain atlases but exhibited some sex differences in certain measures. Specifically, for the automated anatomical labeling atlas, compared with girls, boys showed stronger small-world properties and higher ability of local information processing in brain networks;for the Harvard Oxford Atlas, the shortest path length of boys increased, indicating poorer performance in both global information transmission and resistance to the random attack.

Potential Biomarkers of Schizophrenia from MEG Resting-State Functional Connectivity Networks: Preliminary Data

Previous studies examining coherence and connectivity deviations in schizophrenia patients relied on standard coherence measures between recording sites (at the sensor level). A coherence source imaging (CSI) methodology where coherence is assessed within imaged brain structures (at the source level) was developed recently by our group and applied successfully for detecting coherent areas in the cortical networks of patients with epilepsy. We applied this Magnetoencephalography (MEG)-CSI technique to measure normal and pathological patterns of brain oscillations (biomarkers) in normal subjects and patients diagnosed with schizophrenia. Twelve patients diagnosed with schizophrenia and twelve healthy control subjects were studied. A ten-minute resting state MEG brain scan was performed with eyes open. MEG-CSI analysis was performed to identify the cortical areas that interacted strongly within the 3 - 50 Hz frequency range. Statistically significant increased regions of coherence were detected in schizophrenia patients compared to controls in the right inferior frontal gyrus (BA 47—pars orbitalis), left superior frontal gyrus (BA9— dorsolateral prefrontal cortex), right middle frontal gyrus (BA 10—anterior prefrontal cortex & BA 46—dorsolateral prefrontal cortex), and right cingulate gyrus (BA 24—ventral anterior cingulate cortex). These areas are involved in language, memory, decision making, empathy, executive and, higher cognitive functioning. We conclude that MEG-CSI can detect imaging biomarkers from resting state brain activity in schizophrenia patients that deviates from normal control subjects in several behaviorally salient brain regions. Analysis with MEG-CSI can provide biomarkers of abnormalities in the resting-state. The findings and procedures described can be used to probe the pathophysiology of schizophrenia and possibly detect subtypes.

Predicting Resting-state Functional Connectivity With Efficient Structural Connectivity

The complex relationship between structural connectivity(SC) and functional connectivity(FC) of human brain networks is still a critical problem in neuroscience. In order to investigate the role of SC in shaping resting-state FC, numerous models have been proposed. Here, we use a simple dynamic model based on the susceptible-infected-susceptible(SIS) model along the shortest paths to predict FC from SC. Unlike the previous dynamic model based on SIS theory, we focus on the shortest paths as the principal routes to transmit signals rather than the empirical structural brain network. We first simplify the structurally connected network into an efficient propagation network according to the shortest paths and then combine SIS infection theory with the efficient network to simulate the dynamic process of human brain activity. Finally, we perform an extensive comparison study between the dynamic models embedded in the efficient network, the dynamic model embedded in the structurally connected network and dynamic mean field(DMF) model predicting FC from SC. Extensive experiments on two different resolution datasets indicate that i) the dynamic model simulated on the shortest paths can predict FC among both structurally connected and unconnected node pairs; ii) though there are fewer links in the efficient propagation network, the predictive power of FC derived from the efficient propagation network is better than the dynamic model simulated on a structural brain network; iii) in comparison with the DMF model,the dynamic model embedded in the shortest paths is found to perform better to predict FC.