Cargando…

Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to IQ and Gender

During the last years, it has been established that the prefrontal and posterior parietal brain lobes, which are mostly related to intelligence, have many connections to cerebellum. However, there is a limited research investigating cerebellum's relationship with cognitive processes. In this st...

Descripción completa

Detalles Bibliográficos
Autores principales: Pezoulas, Vasileios C., Zervakis, Michalis, Michelogiannis, Sifis, Klados, Manousos A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5405083/
https://www.ncbi.nlm.nih.gov/pubmed/28491028
http://dx.doi.org/10.3389/fnhum.2017.00189
_version_ 1783231698435047424
author Pezoulas, Vasileios C.
Zervakis, Michalis
Michelogiannis, Sifis
Klados, Manousos A.
author_facet Pezoulas, Vasileios C.
Zervakis, Michalis
Michelogiannis, Sifis
Klados, Manousos A.
author_sort Pezoulas, Vasileios C.
collection PubMed
description During the last years, it has been established that the prefrontal and posterior parietal brain lobes, which are mostly related to intelligence, have many connections to cerebellum. However, there is a limited research investigating cerebellum's relationship with cognitive processes. In this study, the network of cerebellum was analyzed in order to investigate its overall organization in individuals with low and high fluid Intelligence Quotient (IQ). Functional magnetic resonance imaging (fMRI) data were selected from 136 subjects in resting-state from the Human Connectome Project (HCP) database and were further separated into two IQ groups composed of 69 low-IQ and 67 high-IQ subjects. Cerebellum was parcellated into 28 lobules/ROIs (per subject) using a standard cerebellum anatomical atlas. Thereafter, correlation matrices were constructed by computing Pearson's correlation coefficients between the average BOLD time-series for each pair of ROIs inside the cerebellum. By computing conventional graph metrics, small-world network properties were verified using the weighted clustering coefficient and the characteristic path length for estimating the trade-off between segregation and integration. In addition, a connectivity metric was computed for extracting the average cost per network. The concept of the Minimum Spanning Tree (MST) was adopted and implemented in order to avoid methodological biases in graph comparisons and retain only the strongest connections per network. Subsequently, six global and three local metrics were calculated in order to retrieve useful features concerning the characteristics of each MST. Moreover, the local metrics of degree and betweenness centrality were used to detect hubs, i.e., nodes with high importance. The computed set of metrics gave rise to extensive statistical analysis in order to examine differences between low and high-IQ groups, as well as between all possible gender-based group combinations. Our results reveal that both male and female networks have small-world properties with differences in females (especially in higher IQ females) indicative of higher neural efficiency in cerebellum. There is a trend toward the same direction in men, but without significant differences. Finally, three lobules showed maximum correlation with the median response time in low-IQ individuals, implying that there is an increased effort dedicated locally by this population in cognitive tasks.
format Online
Article
Text
id pubmed-5405083
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-54050832017-05-10 Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to IQ and Gender Pezoulas, Vasileios C. Zervakis, Michalis Michelogiannis, Sifis Klados, Manousos A. Front Hum Neurosci Neuroscience During the last years, it has been established that the prefrontal and posterior parietal brain lobes, which are mostly related to intelligence, have many connections to cerebellum. However, there is a limited research investigating cerebellum's relationship with cognitive processes. In this study, the network of cerebellum was analyzed in order to investigate its overall organization in individuals with low and high fluid Intelligence Quotient (IQ). Functional magnetic resonance imaging (fMRI) data were selected from 136 subjects in resting-state from the Human Connectome Project (HCP) database and were further separated into two IQ groups composed of 69 low-IQ and 67 high-IQ subjects. Cerebellum was parcellated into 28 lobules/ROIs (per subject) using a standard cerebellum anatomical atlas. Thereafter, correlation matrices were constructed by computing Pearson's correlation coefficients between the average BOLD time-series for each pair of ROIs inside the cerebellum. By computing conventional graph metrics, small-world network properties were verified using the weighted clustering coefficient and the characteristic path length for estimating the trade-off between segregation and integration. In addition, a connectivity metric was computed for extracting the average cost per network. The concept of the Minimum Spanning Tree (MST) was adopted and implemented in order to avoid methodological biases in graph comparisons and retain only the strongest connections per network. Subsequently, six global and three local metrics were calculated in order to retrieve useful features concerning the characteristics of each MST. Moreover, the local metrics of degree and betweenness centrality were used to detect hubs, i.e., nodes with high importance. The computed set of metrics gave rise to extensive statistical analysis in order to examine differences between low and high-IQ groups, as well as between all possible gender-based group combinations. Our results reveal that both male and female networks have small-world properties with differences in females (especially in higher IQ females) indicative of higher neural efficiency in cerebellum. There is a trend toward the same direction in men, but without significant differences. Finally, three lobules showed maximum correlation with the median response time in low-IQ individuals, implying that there is an increased effort dedicated locally by this population in cognitive tasks. Frontiers Media S.A. 2017-04-26 /pmc/articles/PMC5405083/ /pubmed/28491028 http://dx.doi.org/10.3389/fnhum.2017.00189 Text en Copyright © 2017 Pezoulas, Zervakis, Michelogiannis and Klados. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Pezoulas, Vasileios C.
Zervakis, Michalis
Michelogiannis, Sifis
Klados, Manousos A.
Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to IQ and Gender
title Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to IQ and Gender
title_full Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to IQ and Gender
title_fullStr Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to IQ and Gender
title_full_unstemmed Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to IQ and Gender
title_short Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to IQ and Gender
title_sort resting-state functional connectivity and network analysis of cerebellum with respect to iq and gender
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5405083/
https://www.ncbi.nlm.nih.gov/pubmed/28491028
http://dx.doi.org/10.3389/fnhum.2017.00189
work_keys_str_mv AT pezoulasvasileiosc restingstatefunctionalconnectivityandnetworkanalysisofcerebellumwithrespecttoiqandgender
AT zervakismichalis restingstatefunctionalconnectivityandnetworkanalysisofcerebellumwithrespecttoiqandgender
AT michelogiannissifis restingstatefunctionalconnectivityandnetworkanalysisofcerebellumwithrespecttoiqandgender
AT kladosmanousosa restingstatefunctionalconnectivityandnetworkanalysisofcerebellumwithrespecttoiqandgender