Biology subjects

Anteraper, S. A.

Publications and source records attributed to Anteraper, S. A..

3 recordsLinked to original sources

bioRxiv2021

Resting state functional connectivity in relapsing remitting multiple sclerosis with mild disability - a data driven, whole brain multivoxel pattern analysis study

BackgroundMultivoxel pattern analysis (MVPA) has emerged as a powerful unbiased approach for generating seed regions of interest (ROIs) in resting-state functional connectivity (RSFC) analysis in a data-driven manner. Studies exploring RSFC in multiple sclerosis have produced diverse and often incongruent results. ObjectivesThe aim of the present study was to investigate RSFC differences between persons with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC). MethodsWe performed a whole-brain connectome-wide MVPA in 50 RRMS patients with expanded disability status scale [≤]4 and 50 age and gender-matched HCs. ResultsSignificant group differences were noted in RSFC in three clusters distributed in the following regions; anterior cingulate gyrus, right middle frontal gyrus, and frontal medial cortex. Whole-brain seed-to-voxel RSFC characterization of these clusters as seed ROIs revealed network-specific abnormalities, specifically in the anterior cingulate cortex and the default mode network. ConclusionsThe network-wide RSFC abnormalities we report agree with the previous findings in RRMS, the cognitive and clinical implications of which are discussed herein. IMPACT STATEMENTThis study investigated resting state functional connectivity (RSFC) in relapsing remitting multiple sclerosis (RRMS) persons with mild disability (expanded disability status scale [≤]4). Whole-brain connectome-wide multivoxel pattern analysis (MVPA) was used for assessing RSFC. Compared to healthy controls (HC), we were able to identify three regions of interest for significant differences in connectivity patterns, which were then extracted as a mask for whole-brain seed-to-voxel analysis. A reduced connectivity was noted in the RRMS group, particularly in the anterior cingulate cortex and the default mode network regions, providing insights into the RSFC abnormalities in RRMS.

neuroscience↗

bioRxiv2021

Cerebello-cerebral Functional Connectivity Networks in Major Depressive Disorder: A CAN-BIND-1 Study Report

ObjectiveNeuroimaging studies have demonstrated aberrant structure and function of the "cognitive-affective cerebellum" in Major Depressive Disorder (MDD), although the specific role of the cerebello-cerebral circuitry in this population remains largely uninvestigated. The objective of this study was to delineate the role of cerebellar functional networks in depression. MethodsA total of 308 unmedicated participants completed resting-state functional magnetic resonance imaging scans, of which 247 (148 MDD; 99 Healthy Controls, HC) were suitable for this study. Seed-based resting-state functional connectivity (RsFc) analysis was performed using three cerebellar regions of interest (ROIs): ROI1 corresponded to default mode network (DMN) / inattentive processing; ROI2 corresponded to attentional networks including frontoparietal, dorsal attention, and ventral attention; ROI3 corresponded to motor processing. These ROIs were delineated based on prior functional gradient analyses of the cerebellum. A general linear model was used to perform within-group and between-group comparisons. ResultsIn comparison to HC, participants with MDD displayed increased RsFc within the cerebello-cerebral DMN (ROI1) and significantly elevated RsFc between the cerebellar ROI1 and bilateral angular gyrus at a voxel threshold (p < 0.001, two-tailed) and at a cluster level (p < 0.05, FDR-corrected). Group differences were non-significant for ROI2 and ROI3. ConclusionsThese results contribute to the development of a systems neuroscience approach to the diagnosis and treatment of MDD. Specifically, our findings confirm previously reported associations between MDD, DMN, and cerebellum, and highlight the promising role of these functional and anatomical locations for the development of novel imaging-based biomarkers and targets for neuromodulation therapies.

neuroscience↗

bioRxiv2019

Improvising at Rest: Differentiating Jazz and Classical Music Training with Resting State Functional Connectivity

Jazz improvisation offers a model for creative cognition, as it involves the real-time creation of a novel, information-rich product. Previous research has shown that when musicians improvise, they recruit regions in the Default Mode Network (DMN) and Executive Control Network (ECN). Here, we ask whether these findings from task-fMRI studies might extend to intrinsic differences in resting state functional connectivity. We compared Improvising musicians, Classical musicians, and Minimally Musically Trained (MMT) controls in seed-based functional connectivity and network analyses in resting state functional MRI. We also examined the functional correlates of behavioral performance in musical improvisation and divergent thinking. Seed-based analysis consistently showed higher connectivity in ventral DMN (vDMN) and bilateral ECN in both groups of musically trained individuals as compared to MMT controls, with additional group differences in primary visual network, precuneus network, and posterior salience network. In particular, primary visual network connectivity to DMN and ECN was highest in Improvisational musicians, whereas within-network connectivity of vDMN and precuneus network was higher in both Improvisational and Classical musicians than in MMT controls; in contrast, connectivity between posterior salience network and superior parietal lobule was highest in Classical musicians. Furthermore, graph-theoretical analysis indicated heightened betweenness centrality, clustering, and local efficiency in Classical musicians. Taken together, results suggest that heightened functional connectivity among musicians can be explained by higher within-network connectivity (more tight-knit cortical networks) in Classical musicians, as opposed to more disperse, globally-connected cortical networks in Improvisational musicians.\n\nHighlightsO_LIMusic training is associated with higher resting state connectivity\nC_LIO_LIHigher connectivity in Improvisational musicians from visual network to ECN and DMN\nC_LIO_LIClassical musicians show higher vDMN and Precuneus within-network connectivity\nC_LIO_LIImprovisation and divergent thinking performance correlate with similar connectivity patterns\nC_LI

neuroscience↗