Dataset Information

Inter-individual body mass variations relate to fractionated functional brain hierarchies.

ABSTRACT: Variations in body mass index (BMI) have been suggested to relate to atypical brain organization, yet connectome-level substrates of BMI and their neurobiological underpinnings remain unclear. Studying 325 healthy young adults, we examined associations between functional connectivity and inter-individual BMI variations. We utilized non-linear connectome manifold learning techniques to represent macroscale functional organization along continuous hierarchical axes that dissociate low level and higher order brain systems. We observed an increased differentiation between unimodal and heteromodal association networks in individuals with higher BMI, indicative of a disrupted modular architecture and hierarchy of the brain. Transcriptomic decoding and gene enrichment analyses identified genes previously implicated in genome-wide associations to BMI and specific cortical, striatal, and cerebellar cell types. These findings illustrate functional connectome substrates of BMI variations in healthy young adults and point to potential molecular associations.

SUBMITTER: Park BY

PROVIDER: S-EPMC8203627 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Inter-individual body mass variations relate to fractionated functional brain hierarchies.

Park Bo-Yong BY Park Hyunjin H Morys Filip F Kim Mansu M Byeon Kyoungseob K Lee Hyebin H Kim Se-Hong SH Valk Sofie L SL Dagher Alain A Bernhardt Boris C BC

Communications biology 20210614 1

Variations in body mass index (BMI) have been suggested to relate to atypical brain organization, yet connectome-level substrates of BMI and their neurobiological underpinnings remain unclear. Studying 325 healthy young adults, we examined associations between functional connectivity and inter-individual BMI variations. We utilized non-linear connectome manifold learning techniques to represent macroscale functional organization along continuous hierarchical axes that dissociate low level and hi ...[more]

PMID: 34127795

Similar Datasets

Project description:Current evidence suggests that two spatially distinct neuroanatomical networks, the dorsal attention network (DAN) and the default mode network (DMN), support externally and internally oriented cognition, respectively, and are functionally regulated by a third, frontoparietal control network (FPC). Interactions among these networks contribute to normal variations in cognitive functioning and to the aberrant affective profiles present in certain clinical conditions, such as major depression. Nevertheless, their links to non-clinical variations in affective functioning are still poorly understood. To address this issue, we used fMRI to measure the intrinsic functional interactions among these networks in a sample of predominantly younger women (N=162) from the Human Connectome Project. Consistent with the previously documented dichotomous motivational orientations (i.e., withdrawal versus approach) associated with sadness versus anger, we hypothesized that greater sadness would predict greater DMN (rather than DAN) functional dominance, whereas greater anger would predict the opposite. Overall, there was evidence of greater DAN (rather than DMN) functional dominance, but this pattern was modulated by current experience of specific negative emotions, as well as subclinical depressive and anxiety symptoms. Thus, greater levels of currently experienced sadness and subclinical depression independently predicted weaker DAN functional dominance (i.e., weaker DAN-FPC functional connectivity), likely reflecting reduced goal-directed attention towards the external perceptual environment. Complementarily, greater levels of currently experienced anger and subclinical anxiety predicted greater DAN functional dominance (i.e., greater DAN-FPC functional connectivity and, for anxiety only, also weaker DMN-FPC coupling). Our findings suggest that distinct affective states and subclinical mood symptoms have dissociable neural signatures, reflective of the symbiotic relationship between cognitive processes and emotional states.

Project description:BACKGROUND: Dental microwear analyses are commonly used to deduce the diet of extinct mammals. Conventional methods rely on the user identifying features within a 2D image. However, recent interdisciplinary research has lead to the development of an advanced methodology that is free of observer error, based on the automated quantification of 3D surfaces by combining confocal microscopy with scale-sensitive fractal analysis. This method has already proved to be very efficient in detecting dietary differences between species. Focusing on a finer, intra-specific scale of analysis, the aim of this study is to test this method's ability to track such differences between individuals from a single population. METHODOLOGY/PRINCIPAL FINDINGS: For the purposes of this study, the 3D molar microwear of 78 individuals from a well-known population of extant roe deer (Capreolus caprelous) is quantified. Multivariate statistical analyses indicate significant seasonal and sexual differences in individual dental microwear design. These are probably the consequence of seasonal variations in fruit, seed and leaf availability, as well as differences in feeding preference between males and females due to distinct energy requirements during periods of rutting, gestation or giving birth. Nevertheless, further investigations using two-block Partial Least-Squares analysis show no strong relationship between individual stomach contents and microwear texture. This is an expected result, assuming that stomach contents are composed of food items ingested during the last few hours whereas dental microwear texture records the physical properties of items eaten over periods of days or weeks. CONCLUSIONS/SIGNIFICANCE: Microwear 3D scale-sensitive fractal analysis does detect differences in diet ranging from the inter-feeding styles scale to the intra-population between-season and between-sex scales. It is therefore a possible tool, to be used with caution, in the further exploration of the feeding biology and ecology of extinct mammals.

Project description:Cognitive abilities, such as working memory, differ among people; however, individuals also vary in their own day-to-day cognitive performance. One potential source of cognitive variability may be fluctuations in the functional organization of neural systems. The degree to which the organization of these functional networks is optimized may relate to the effective cognitive functioning of the individual. Here we specifically examine how changes in the organization of large-scale networks measured via resting state functional connectivity MRI and graph theory track changes in working memory capacity.Twenty-two participants performed a test of working memory capacity and then underwent resting-state fMRI. Seventeen subjects repeated the protocol three weeks later. We applied graph theoretic techniques to measure network organization on 34 brain regions of interest (ROI). Network modularity, which measures the level of integration and segregation across sub-networks, and small-worldness, which measures global network connection efficiency, both predicted individual differences in memory capacity; however, only modularity predicted intra-individual variation across the two sessions. Partial correlations controlling for the component of working memory that was stable across sessions revealed that modularity was almost entirely associated with the variability of working memory at each session. Analyses of specific sub-networks and individual circuits were unable to consistently account for working memory capacity variability.The results suggest that the intrinsic functional organization of an a priori defined cognitive control network measured at rest provides substantial information about actual cognitive performance. The association of network modularity to the variability in an individual's working memory capacity suggests that the organization of this network into high connectivity within modules and sparse connections between modules may reflect effective signaling across brain regions, perhaps through the modulation of signal or the suppression of the propagation of noise.

Dataset Information

Inter-individual body mass variations relate to fractionated functional brain hierarchies.

Publications

Inter-individual body mass variations relate to fractionated functional brain hierarchies.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets