Functional Connectivity Profiles Research Articles

EEGminer: discovering interpretable features of brain activity with learnable filters

Objective. The patterns of brain activity associated with different brain processes can be used to identify different brain states and make behavioural predictions. However, the relevant features are not readily apparent and accessible. Our aim is to design a system for learning informative latent representations from multichannel recordings of ongoing EEG activity. Approach: We propose a novel differentiable decoding pipeline consisting of learnable filters and a pre-determined feature extraction module. Specifically, we introduce filters parameterized by generalized Gaussian functions that offer a smooth derivative for stable end-to-end model training and allow for learning interpretable features. For the feature module, we use signal magnitude and functional connectivity estimates. Main results. We demonstrate the utility of our model on a new EEG dataset of unprecedented size (i.e. 721 subjects), where we identify consistent trends of music perception and related individual differences. Furthermore, we train and apply our model in two additional datasets, specifically for emotion recognition on SEED and workload classification on simultaneous task EEG workload. The discovered features align well with previous neuroscience studies and offer new insights, such as marked differences in the functional connectivity profile between left and right temporal areas during music listening. This agrees with the specialisation of the temporal lobes regarding music perception proposed in the literature. Significance. The proposed method offers strong interpretability of learned features while reaching similar levels of accuracy achieved by black box deep learning models. This improved trustworthiness may promote the use of deep learning models in real world applications. The model code is available at https://github.com/SMLudwig/EEGminer/.

The efficacy of low frequency repetitive transcial magnetic stimulation for treating auditory verbal hallucinations in schizophrenia: Insights from functional gradient analyses

BackgroundAuditory Verbal Hallucinations (AVH) constitute a prominent feature of schizophrenia. Although low-frequency repetitive transcranial magnetic stimulation (rTMS) has demonstrated therapeutic benefits in ameliorating AVH, the underlying mechanisms of its efficacy necessitate further elucidation. ObjectiveThis study investigated the cortical gradient characteristics and their associations with clinical responses in schizophrenia patients with AVH, mediated through 1 Hz rTMS targeting the left temporoparietal junction. MethodFunctional gradient metrics were employed to examine the hierarchy patterns of cortical organization, capturing whole-brain functional connectivity profiles in patients and controls. ResultsThe 1 Hz rTMS treatment effectively ameliorated the positive symptoms in patients, specifically targeting AVH. Initial evaluations revealed expanded global gradient distribution patterns and specific principal gradient variations in certain brain regions in patients at baseline compared to a control cohort. Following treatment, these divergent global and local patterns showed signs of normalizing. Furthermore, there was observed a closer alignment in between-network dispersion among various networks after treatment, including the somatomotor, attention, and limbic networks, indicating a potential harmonization of brain functionality. ConclusionLow-frequency rTMS induces alternations in principal functional gradient patterns, may serve as imaging markers to elucidate the mechanisms underpinning the therapeutic efficacy of rTMS on AVH in schizophrenia.

Behaviour-correlated profiles of cerebellar-cerebral functional connectivity observed in independent neurodevelopmental disorder cohorts

The cerebellum, through its connectivity with the cerebral cortex, plays an integral role in regulating cognitive and affective processes, and its dysregulation can result in neurodevelopmental disorder (NDD)-related behavioural deficits. Identifying cerebellar-cerebral functional connectivity (FC) profiles in children with NDDs can provide insight into common connectivity profiles and their correlation to NDD-related behaviours. 479 participants from the Province of Ontario Neurodevelopmental Disorders (POND) network (typically developing = 93, Autism Spectrum Disorder = 172, Attention Deficit/Hyperactivity Disorder = 161, Obsessive-Compulsive Disorder = 53, mean age = 12.2) underwent resting-state functional magnetic resonance imaging and behaviour testing (Social Communication Questionnaire, Toronto Obsessive-Compulsive Scale, and Child Behaviour Checklist – Attentional Problems Subscale). FC components maximally correlated to behaviour were identified using canonical correlation analysis. Results were then validated by repeating the investigation in 556 participants from an independent NDD cohort provided from a separate consortium (Healthy Brain Network (HBN)). Replication of canonical components was quantified by correlating the feature vectors between the two cohorts. The two cerebellar-cerebral FC components that replicated to the greatest extent were correlated to, respectively, obsessive-compulsive behaviour (behaviour feature vectors, rPOND-HBN = −0.97; FC feature vectors, rPOND-HBN = −0.68) and social communication deficit contrasted against attention deficit behaviour (behaviour feature vectors, rPOND-HBN = −0.99; FC feature vectors, rPOND-HBN = −0.78). The statistically stable (|z| > 1.96) features of the FC feature vectors, measured via bootstrap re-sampling, predominantly comprised of correlations between cerebellar attentional and control network regions and cerebral attentional, default mode, and control network regions. In both cohorts, spectral clustering on FC loading values resulted in subject clusters mixed across diagnostic categories, but no cluster was significantly enriched for any given diagnosis as measured via chi-squared test (p > 0.05). Overall, two behaviour-correlated components of cerebellar-cerebral functional connectivity were observed in two independent cohorts. This suggests the existence of generalizable cerebellar network differences that span across NDD diagnostic boundaries.

Default mode network perturbations in Alzheimer's disease: an fMRI study in Klang Valley, Malaysia

The default mode network (DMN) is a large neural network that has a significant correlation with Alzheimer's disease (AD). Grey matter volume (GMV) and functional connectivity (FC) involving the regions of the DMN have been noted to differ significantly between AD and healthy older adults. Nevertheless, there is a paucity of data on the structural and functional changes in the DMN of AD patients in Malaysia. We conducted a cross-sectional study in Klang Valley, Malaysia, to evaluate AD subjects compared to healthy controls (HC) using a resting-state functional MRI (rs-fMRI) experiment. We recruited 22 subjects (AD=11, HC=11) and conducted neuropsychological tests such as the Montreal Cognitive Assessment (MoCA), Mini Mental State Examination (MMSE), and Clinical Dementia Rating (CDR). The subjects then underwent rs-fMRI scans, and subsequently, we quantitatively analysed the GMV by Voxel based Morphometry (VBM) using the structural data. We also utilised the CONN toolbox on Statistical Parametric Mapping (SPM) software to evaluate the FC and activation of the nodes of the DMN. In comparison with the HC group, the AD group demonstrated a reduction in GMV in the right and left inferior temporal gyrus, left superior frontal gyrus, right superior frontal gyrus medial segment, right gyrus rectus, right temporal lobe, left putamen, and right precuneus. Moreover, there was a significant decrease in the FC of the nodes of the DMN noted on rs-fMRI (cluster-size corrected p<0.05). In particular, the precuneus and anterior cingulate cortex had decreased FC in AD compared to HC. Hence, structural and resting-state fMRI can detect distinct imaging biomarkers of AD based on GMV and DMN functional connectivity profiles. This tool can be used as a non-invasive tool for improving the feature detection and diagnosis of AD in the Malaysian population.

Age-related differences in affective behaviors in mice: possible role of prefrontal cortical-hippocampal functional connectivity and metabolomic profiles.

The differential expression of emotional reactivity from early to late adulthood may involve maturation of prefrontal cortical responses to negative valence stimuli. In mice, age-related changes in affective behaviors have been reported, but the functional neural circuitry warrants further investigation. We assessed age variations in affective behaviors and functional connectivity in male and female C57BL6/J mice. Mice aged 10, 30 and 60 weeks (wo) were tested over 8 weeks for open field activity, sucrose preference, social interactions, fear conditioning, and functional neuroimaging. Prefrontal cortical and hippocampal tissues were excised for metabolomics. Our results indicate that young and old mice differ significantly in affective behavioral, functional connectome and prefrontal cortical-hippocampal metabolome. Young mice show a greater responsivity to novel environmental and social stimuli compared to older mice. Conversely, late middle-aged mice (60wo group) display variable patterns of fear conditioning and during re-testing in a modified context. Functional connectivity between a temporal cortical/auditory cortex network and subregions of the anterior cingulate cortex and ventral hippocampus, and a greater network modularity and assortative mixing of nodes was stronger in young versus older adult mice. Metabolome analyses identified differences in several essential amino acids between 10wo mice and the other age groups. The results support differential expression of 'emotionality' across distinct stages of the mouse lifespan involving greater prefrontal-hippocampal connectivity and neurochemistry.

A distinctive subcortical functional connectivity pattern linking negative affect and treatment outcome in major depressive disorder

Major depressive disorder (MDD) is associated with functional disturbances in subcortical regions. In this naturalistic prospective study (NCT03294525), we aimed to investigate relationships among subcortical functional connectivity (FC), mood symptom profiles and treatment outcome in MDD using multivariate methods. Medication-free participants with MDD (n = 135) underwent a functional magnetic resonance imaging scan at baseline and completed posttreatment clinical assessment after 8 weeks of antidepressant monotherapy. We used partial least squares (PLS) correlation analysis to explore the association between subcortical FC and mood symptom profiles. FC score, reflecting the weighted representation of each individual in this association, was computed. Replication analysis was undertaken in an independent sample (n = 74). We also investigated the relationship between FC score and treatment outcome in the main sample. A distinctive subcortical connectivity pattern was found to be associated with negative affect. In general, higher FC between the caudate, putamen and thalamus was associated with greater negative affect. This association was partly replicated in the independent sample (similarity between the two samples: r = 0.66 for subcortical connectivity, r = 0.75 for mood symptom profile). Lower FC score predicted both remission and response to treatment after 8 weeks of antidepressant monotherapy. The emphasis here on the role of dorsal striatum and thalamus consolidates prior work of subcortical connectivity in MDD. The findings provide insight into the pathogenesis of MDD, linking subcortical FC with negative affect. However, while the FC score significantly predicted treatment outcome, the low odds ratio suggests that finding predictive biomarkers for depression remains an aspiration.

Mapping the functional and structural connectivity of the scene network.

The recognition and perception of places has been linked to a network of scene-selective regions in the human brain. While previous studies have focussed on functional connectivity between scene-selective regions themselves, less is known about their connectivity with other cortical and subcortical regions in the brain. Here, we determine the functional and structural connectivity profile of the scene network. We used fMRI to examine functional connectivity between scene regions and across the whole brain during rest and movie-watching. Connectivity within the scene network revealed a bias between posterior and anterior scene regions implicated in perceptual and mnemonic aspects of scene perception respectively. Differences between posterior and anterior scene regions were also evident in the connectivity with cortical and subcortical regions across the brain. For example, the Occipital Place Area (OPA) and posterior Parahippocampal Place Area (PPA) showed greater connectivity with visual and dorsal attention networks, whileanterior PPA and Retrosplenial Complex showed preferential connectivity with default mode and frontoparietal control networks and the hippocampus. We further measured the structural connectivity of the scene network using diffusion tractography. This indicated both similarities and differences with the functional connectivity, highlighting biases between posterior and anterior regions, but also between ventral and dorsal scene regions. Finally, we quantified the structural connectivity between the scene network and major white matter tracts throughout the brain. These findings provide a map of the functional and structural connectivity of scene-selective regions to each other and the rest of the brain.

Distinct resting-state functional connectivity of the anterior cingulate cortex subregions in first-episode schizophrenia.

The anterior cingulate cortex (ACC) is a heterogeneous region of the brain's limbic system that regulates cognitive and emotional processing, and is frequently implicated in schizophrenia. This study aims to characterize resting-state functional connectivity (rsFC) profiles of three subregions of ACC in patients with first-episode schizophrenia and healthy controls. Resting-state functional magnetic resonance imaging (rs-fMRI) scans were collected from 60 first-episode schizophrenia (FES) patients and 60 healthy controls (HC), and the subgenual ACC (sgACC), pregenual ACC (pgACC), and dorsal ACC (dACC) were selected as seed regions from the newest automated anatomical labeling atlas 3 (AAL3). Seed-based rsFC maps for each ACC subregion were generated and compared between the two groups. The results revealed that compared to the HC group, the FES group showed higher rsFC between the pgACC and bilateral lateral orbitofrontal cortex (lOFC), and lower rsFC between the dACC and right posterior OFC (pOFC), the medial prefrontal gyrus (MPFC), and the precuneus cortex (PCu). These findings point to a selective functional dysconnectivity of pgACC and dACC in schizophrenia and provide more accurate information about the functional role of the ACC in this disorder.

Dysconnectivity of the brain functional network and abnormally expressed peripheral transcriptional profiles in patients with anxious depression

BackgroundMajor depressive disorder (MDD) is a heterogeneous mental disorder, and accompanying anxiety symptoms, known as anxious depression (AD), are the most common subtype. However, the pathophysiology of AD may be distinct in depressed patients without anxiety (NAD) and remains unknown. This study aimed to investigate the relationship between functional connectivity and peripheral transcriptional profiles in patients with AD and NAD. MethodsFunctional imaging data were collected to identify differences in functional networks among patients with AD (n = 66), patients with NAD (n = 115), and healthy controls (HC, n = 200). The peripheral transcriptional data were clustered as co-expression modules, and their associations with AD, AND, and HC were analyzed. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses of the genes in the significant module were performed. Correlation analysis was performed to identify functional network-associated gene co-expression modules. ResultsA network was identified which consisted of 23 nodes and 28 edges that were significantly different among three sample groups. The regions of the network were located in temporal and occipital lobe. Two gene co-expression modules were shown to be associated with NAD, and one of which was correlated with the disrupted network in the AD group. The biological function of this module was enriched in immune regulation pathways. ConclusionThe results suggested that immune-related mechanisms were associated with functional networks in AD.

Abnormal functional connectivity within the prefrontal cortex is associated with multiple plasma lipid species in major depressive disorder

BackgroundAbnormalities in functional connectivity (FC) in major depressive disorder (MDD) have been widely reported. Analysis of the relationship between FC and plasma lipid profiles would be meaningful in the exploration of pathophysiological mechanisms and helpful for the identification of biomarkers for MDD. MethodsPatients with MDD (n = 49) and healthy controls (HC, n = 87) were recruited. Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected for FC construction. The plasma lipid profiles were acquired using ultra-performance liquid chromatography (UPLC) and mass spectrometry (MS) analysis and clustered as co-expression modules. The differential FC and lipid modules between HCs and patients with MDD were identified, and then the association between FC and lipid co-expression modules was analyzed using correlation analysis. The modules associated molecular function was explored using metabolite set enrichment analysis (MSEA). ResultsMDD-associated FC and lipid co-expression modules were identified. One module was associated with FC values between the right orbital part of the middle frontal gyrus and the opercular part of the left inferior frontal gyrus, which was enriched in lipid sets of diacylglycerols and fatty alcohols; another module was associated with FC values between the right middle frontal gyrus and the right anterior cingulate and paracingulate gyri, which was enriched in lipid sets of glycerophosphocholines and glycerophosphoethanolamines. ConclusionOur results indicated that abnormal FC in the prefrontal cortex is associated with multiple plasma lipid species, which may provide novel clues for exploring the pathophysiology of MDD.

Higher Fat-Related Body Composition Measurement and Lower Resting-State Inter-Network Functional Connectivity of APOE ε4 Carrier in Mild Cognitive Impairment Patients With Aβ Deposition.

We aimed to evaluate the impact of interaction between APOE ε4 carrier status and body composition measurements on intra- and inter-regional functional connectivity (FC) in mild cognitive impairment (MCI) patients with Aβ deposition. MCI patients with and without APOE ε4 allele (carrier, n=86; non-carrier, n=95) underwent neuropsychological battery, resting-state functional magnetic resonance imaging scans, positron emission tomography scans with [18F]flutemetamol, and bioelectrical impedance analysis for measuring body composition. We employed a priori defined regions of interest to investigate the intra- and inter-network FC profiles of default mode network (DMN), central executive network (CEN), and salience network. There was a significant interaction of APOE ε4 carrier status with body fat mass index, visceral fat area, and waist-hip circumference ratio for inter-network FC between DMN and CEN, contributing higher fat-related body composition measurements in the APOE ε4 carrier with lower DMN-CEN FC. The present results highlight the detrimental effect of APOE ε4 carrier status on the associations between the fat-related body composition measurements and FC in the MCI patients with Aβ accumulation.

Static and dynamic functional connectome reveals reconfiguration profiles of whole-brain network across cognitive states.

Assessment of functional connectivity (FC) has revealed a great deal of knowledge about the macroscale spatiotemporal organization of the brain network. Recent studies found task-versus-rest network reconfigurations were crucial for cognitive functioning. However, brain network reconfiguration remains unclear among different cognitive states, considering both aggregate and time-resolved FC profiles. The current study utilized static FC (sFC, i.e., long timescale aggregate FC) and sliding window-based dynamic FC (dFC, i.e., short timescale time-varying FC) approaches to investigate the similarity and alterations of edge weights and network topology at different cognitive loads, particularly their relationships with specific cognitive process. Both dFC/sFC networks showed subtle but significant reconfigurations that correlated with task performance. At higher cognitive load, brain network reconfiguration displayed increased functional integration in the sFC-based aggregate network, but faster and larger variability of modular reorganization in the dFC-based time-varying network, suggesting difficult tasks require more integrated and flexible network reconfigurations. Moreover, sFC-based network reconfigurations mainly linked with the sensorimotor and low-order cognitive processes, but dFC-based network reconfigurations mainly linked with the high-order cognitive process. Our findings suggest that reconfiguration profiles of sFC/dFC networks provide specific information about cognitive functioning, which could potentially be used to study brain function and disorders.

Functional connectivity and network analysis in adolescents with major depressive disorder showing suicidal behavior

BackgroundThis study aimed to gather a homogeneous sample of adolescent patients to analyze the differences in functional connectivity and brain network parameters between suicidal and non-suicidal major depressive disorder (MDD) patients using a data-driven whole-brain approach. MethodsPatients recruited at the psychiatry department of Korea University Guro Hospital from November 2014 to March 2020 were diagnosed with MDD, were 13–18 years old, had IQ scores >80, had no family history of psychotic or personality disorders, had no smoking or alcohol consumption history, and were drug-naïve to psychotropic medication. Depressive symptoms were assessed using the Hamilton Depression Rating Scale and the Children's Depression Inventory. Structural and functional MRI scans were conducted and analyzed using the CONN toolbox. ResultsOf 74 enrolled patients, 62 were analyzed. Regions of interest (ROIs) showing higher betweenness centrality in non-suicidal patients were the left superior temporal gyrus and left supramarginal gyrus. ROIs showing higher betweenness centrality in suicidal patients were the right hippocampus, left intracalcarine cortex, right inferior temporal gyrus, and the lateral visual network. Suicidal patients also showed different resting state functional connectivity profiles from non-suicidal patients. LimitationsSmall sample size. ConclusionSuicidal patients may overthink and overvalue future risks while having a more negatively biased autobiographical memory. Social cognition and the ability to overcome egocentricity bias seem to weaken. Such features can disrupt cognitive recovery and resilience, leading to more suicidal behaviors. Therefore, increased suicidality is not acquired, but is an innate trait.

Linking connectivity of deep brain stimulation of nucleus accumbens area with clinical depression improvements: a retrospective longitudinal case series

Treatment-resistant depression is a severe form of major depressive disorder and deep brain stimulation is currently an investigational treatment. The stimulation’s therapeutic effect may be explained through the functional and structural connectivities between the stimulated area and other brain regions, or to depression-associated networks. In this longitudinal, retrospective study, four female patients with treatment-resistant depression were implanted for stimulation in the nucleus accumbens area at our center. We analyzed the structural and functional connectivity of the stimulation area: the structural connectivity was investigated with probabilistic tractography; the functional connectivity was estimated by combining patient-specific stimulation volumes and a normative functional connectome. These structural and functional connectivity profiles were then related to four clinical outcome scores. At 1-year follow-up, the remission rate was 66%. We observed a consistent structural connectivity to Brodmann area 25 in the patient with the longest remission phase. The functional connectivity analysis resulted in patient-specific R-maps describing brain areas significantly correlated with symptom improvement in this patient, notably the prefrontal cortex. But the connectivity analysis was mixed across patients, calling for confirmation in a larger cohort and over longer time periods.

Neuroimaging anomalies in asymptomatic middle cerebral artery steno-occlusive disease with normal-appearing white matter.

Asymptomatic chronic cerebrovascular steno-occlusive disease is common, but the cognitive function and alterations in the brain's structural and functional profiles have not been well studied. This study aimed to reveal whether and how patients with asymptomatic middle cerebral artery (MCA) steno-occlusive disease and normal-appearing white matter differ in brain structural and functional profiles from normal controls and their correlations with cognitive function. In all, 26 patients with asymptomatic MCA steno-occlusive disease and 22 healthy controls were compared for neurobehavioral assessments, brain volume, cortical thickness, fiber connectivity density (FiCD) value, and resting-state functional connectivity (FC) using multimodal MRI. We also investigated the associations between abnormal cortical thicknesses, FiCD values, and functional connectivities with the neurobehavioral assessments. Patients performed worse on memory tasks (Auditory Verbal Learning Test-Huashan version) compared with healthy controls. Patients were divided into two groups: the right group (patients with right MCA steno-occlusive disease) and the left group (patients with left MCA steno-occlusive disease). The left group showed significant cortical thinning in the left superior parietal lobule, while the right group showed significant cortical thinning in the right superior parietal lobule and caudal portion of the right middle frontal gyrus. Increased FiCD values in the superior frontal region of the left hemisphere were observed in the left group. In addition, a set of interhemispheric and intrahemispheric FC showed a significant decrease or increase in both the left and right groups. Many functional connectivity profiles were positively correlated with cognitive scores. No correlation was found between cortical thickness, FiCD values, and cognitive scores. Even if the patients with MCA steno-occlusive disease were asymptomatic and had normal-appearing white matter, their cognitive function and structural and functional profiles had changed, especially the FC. Alterations in FC may be an important mechanism underlying the neurodegenerative process in patients with asymptomatic MCA steno-occlusive disease before structural changes occur, so FC assessment may promote the detection of network alterations, which may be used as a biomarker of disease progression and therapeutic efficacy evaluation in these patients.

Nucleus accumbens deep brain stimulation improves depressive-like behaviors through BDNF-mediated alterations in brain functional connectivity of dopaminergic pathway

Major depressive disorder (MDD), a common psychiatric condition, adversely affects patients’ moods and quality of life. Despite the development of various treatments, many patients with MDD remain vulnerable and inadequately controlled. Since anhedonia is a feature of depression and there is evidence of leading to metabolic disorder, deep brain stimulation (DBS) to the nucleus accumbens (NAc) might be promising in modulating the dopaminergic pathway. To determine whether NAc-DBS alters glucose metabolism via mitochondrial alteration and neurogenesis and whether these changes increase neural plasticity that improves behavioral functions in a chronic social defeat stress (CSDS) mouse model. The Lab-designed MR-compatible neural probes were implanted in the bilateral NAc of C57BL/6 mice with and without CSDS, followed by DBS or sham stimulation. All animals underwent open-field and sucrose preference testing, and brain resting-state functional MRI analysis. Meanwhile, we checked the placement of neural probes in each mouse by T2 images. By confirming the placement location, mice with incorrect probe placement (the negative control group) showed no significant therapeutic effects in behavioral performance and functional connectivity (FC) after receiving electrical stimulation and were excluded from further analysis. Western blotting, seahorse metabolic analysis, and electron microscopy were further applied for the investigation of NAc-DBS. We found NAc-DBS restored emotional deficits in CSDS-subjected mice. Concurrent with behavioral amelioration, the CSDS DBS-on group exhibited enhanced FC in the dopaminergic pathway with increased expression of BDNF- and NeuN-positive cells increased dopamine D1 receptor, dopamine D2 receptors, and TH in the medial prefrontal cortex, NAc, ventral hippocampus, ventral tegmental area, and amygdala. Increased pAMPK/total AMPK and PGC-1α levels, functions of oxidative phosphorylation, and mitochondrial biogenesis were also observed after NAc-DBS treatment. Our findings demonstrate that NAc-DBS can promote BDNF expression, which alters FC and metabolic profile in the dopaminergic pathway, suggesting a potential strategy for ameliorating emotional processes in individuals with MDD.

Altered functional connectivity in anterior cingulate cortex subregions in treatment-resistant schizophrenia patients

BackgroundThe anterior cingulate cortex (ACC) plays a key role in motor control, attention, and cognitive control. It is well established that schizophrenia is associated with impaired functional connectivity (FC) of the ACC pathway. So far, however, there has been little discussion about the ACC subregions function in patients with treatment-resistant schizophrenia (TRS). AimThis study aims to characterize resting-state functional connectivity (rs-FC) profiles of ACC subregions in patients with TRS. The association between these FC and clinical symptoms, neurocognitive function, and grey matter volume (GMV) was studied as well. MethodsA total of 81 patients with schizophrenia (40 patients with TRS = 40, 41 patients with non-treatment-resistant schizophrenia (NTRS)) and 39 age- and gender-matched healthy controls (HC) were enrolled, and underwent structural magnetic resonance imaging (MRI), resting-state functional MRI (rs-fMRI), clinical evaluation. The ACC subregions, including subgenual ACC (sgACC), pregenual ACC (pgACC), and dorsal ACC (dACC), were selected as seed regions from the automated anatomical labelling atlas 3 (AAL3). The GMV of the ACC subregions were calculated and seed-based FC maps for all ACC subregions were generated and compared between the TRS and NTRS, HC group. Additionally, correlations between altered FC and clinical symptoms, GMV, and neurocognitive functions in the TRS patients were explored. ResultCompared with HC, increased FC was observed in TRS and NTRS groups between bilateral sgACC and left cuneus, right cuneus, and left lingual gyrus, while decreased FC was found between bilateral dACC and thalamic. Additionally, compared with NTRS, the TRS group showed increased FC between bilateral dACC and right cuneus and decreased FC between bilateral dACC and thalamic. The TRS group showed decreased GMV in all ACC subregions than the HC group, and there is no significant difference between the TRS group and the NTRS group. ConclusionThe findings in this study suggest that disrupted FC of subregional ACC has the potential as a marker for TRS. The dysconnectivity of bilateral dACC- right cuneus and bilateral dACC-thalamus, are likely to be the unique FC profiles of TRS. These findings further our understanding of the neurobiological impairments in TRS.

Striatonigrostriatal connectivity-based cross-species parcellation of human and macaque substantia nigra.

Anatomical and functional heterogeneous substantia nigra (SN) has been extensively studied in humans and animals like rhesus monkeys given its crucial role in modulating a broad range of behaviors. Increasingly important cross-species research of SN may require connectionally homogeneous and homologous subregions of SN as objective and stable starting points from which the evolutionary characteristics of brain could be inspected. However, existing atlases of SN were all inaccurate mappings as a cross-species connectome atlas due to inadequate homology constraint during their constructions, and arbitrary paired use of these atlases might cause unreliable findings. In this study, a reliable blind-source cross-species parcellation of SN was developed based on the following rationale: striatonigrostriatal circuits form major structure of nigral connectivity; different nigral components have unique striatonigrostriatal connectivity; and inter-species corresponding human and macaque nigral components have similar striatonigrostriatal connectivity. Specifically, all voxels in human and macaque SN were grouped together and then classified based on inter-species identically characterized striatonigrostriatal connectivity attributes. Our results delineated a pars compacta-pars reticulate-like parcellation and further demonstrated its reliability by illustrating best-matched whole-brain structural and functional connectivity profiles of inter-species corresponding nigral subregions. Detailed inter-species and inter-regional differences in multi-aspect connectivities of these nigral subregions were inspected. It is expected that this cross-species connectome atlas of SN can offer biologically reliable cornerstones and important information to facilitate future cross-species research.

Brain hubs defined in the group do not overlap with regions of high inter-individual variability

Connector ‘hubs’ are brain regions with links to multiple networks. These regions are hypothesized to play a critical role in brain function. While hubs are often identified based on group-average functional magnetic resonance imaging (fMRI) data, there is considerable inter-subject variation in the functional connectivity profiles of the brain, especially in association regions where hubs tend to be located. Here we investigated how group hubs are related to locations of inter-individual variability. To answer this question, we examined inter-individual variation at group-level hubs in both the Midnight Scan Club and Human Connectome Project datasets. The top group hubs defined based on the participation coefficient did not overlap strongly with the most prominent regions of inter-individual variation (termed ‘variants’ in prior work). These hubs have relatively strong similarity across participants and consistent cross-network profiles, similar to what was seen for many other areas of cortex. Consistency across participants was further improved when these hubs were allowed to shift slightly in local position. Thus, our results demonstrate that the top group hubs defined with the participation coefficient are generally consistent across people, suggesting they may represent conserved cross-network bridges. More caution is warranted with alternative hub measures, such as community density (which are based on spatial proximity to network borders) and intermediate hub regions which show higher correspondence to locations of individual variability.

Effects of ambient fine particulates, nitrogen dioxide, and ozone on maturation of functional brain networks across early adolescence

BackgroundAir pollution is linked to neurodevelopmental delays, but its association with longitudinal changes in brain network development has yet to be investigated. We aimed to characterize the effect of PM2.5, O3, and NO2 exposure at ages 9–10 years on changes in functional connectivity (FC) over a 2-year follow-up period, with a focus on the salience (SN), frontoparietal (FPN), and default-mode (DMN) brain networks as well as the amygdala and hippocampus given their importance in emotional and cognitive functioning. MethodsA sample of children (N = 9,497; with 1–2 scans each for a total of 13,824 scans; 45.6% with two brain scans) from the Adolescent Brain Cognitive Development (ABCD) Study® were included. Annual averages of pollutant concentrations were assigned to the child’s primary residential address using an ensemble-based exposure modeling approach. Resting-state functional MRI was collected on 3T MRI scanners. First, developmental linear mixed-effect models were performed to characterize typical FC development within our sample. Next, single- and multi-pollutant linear mixed-effect models were constructed to examine the association between exposure and intra-network, inter-network, and subcortical-to-network FC change over time, adjusting for sex, race/ethnicity, income, parental education, handedness, scanner type, and motion. ResultsDevelopmental profiles of FC over the 2-year follow-up included intra-network integration within the DMN and FPN as well as inter-network integration between the SN-FPN; along with intra-network segregation in the SN as well as subcortical-to-network segregation more broadly. Higher PM2.5 exposure resulted in greater inter-network and subcortical-to-network FC over time. In contrast, higher O3 concentrations resulted in greater intra-network, but less subcortical-to-network FC over time. Lastly, higher NO2 exposure led to less inter-network and subcortical-to-network FC over the 2-year follow-up period. ConclusionTaken together, PM2.5, O3, and NO2 exposure in childhood relate to distinct changes in patterns of network maturation over time. This is the first study to show outdoor ambient air pollution during childhood is linked to longitudinal changes in brain network connectivity development.