Exploring resting-state functional connectivity invariants across the lifespan in healthy people by means of a recently proposed graph theoretical model
In this paper we investigate the changes in the functional connectivity intensity, and some related properties, in healthy people, across the life span and at resting state. For the explicit computation of the functional connectivity we exploit a recently proposed model, that bases not only on the c...
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Published in | PloS one Vol. 13; no. 11; p. e0206567 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
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United States
Public Library of Science
08.11.2018
Public Library of Science (PLoS) |
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Online Access | Get full text |
ISSN | 1932-6203 1932-6203 |
DOI | 10.1371/journal.pone.0206567 |
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Abstract | In this paper we investigate the changes in the functional connectivity intensity, and some related properties, in healthy people, across the life span and at resting state. For the explicit computation of the functional connectivity we exploit a recently proposed model, that bases not only on the correlations data provided by the acquisition equipment, but also on different parameters, such as the anatomical distances between nodes and their degrees. The leading purpose of the paper is to show that the proposed approach is able to recover the main aspects of resting state condition known from the available literature, as well as to suggest new insights, perspectives and speculations from a neurobiological point of view. Our study involves 133 subjects, both males and females of different ages, with no evidence of neurological diseases or systemic disorders. First, we show how the model applies to the sample, where the subjects are grouped into 28 different groups (14 of males and 14 of females), according to their age. This leads to the construction of two graphs (one for males and one for females), that can be realistically interpreted as representative of the neural network during the resting state. Second, following the idea that the brain network is better understood by focusing on specific nodes having a kind of centrality, we refine the two output graphs by introducing a new metric that favours the selection of nodes having higher degrees. As a third step, we extensively comment and discuss the obtained results. In particular, it is remarkable that, despite a great overlapping exists between the outcomes concerning males and females, some intriguing differences appear. This motivates a deeper local investigation, which represents the fourth part of the paper, carried out through a thorough statistical analysis. As a result, we are enabled to support that, for two special age groups, a few links contribute in differentiating the behaviour of males and females. In addition, we performed an average-based comparison between the proposed model and the traditional statistical correlation-based approach, then discussing and commenting the main outlined discrepancies. |
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AbstractList | In this paper we investigate the changes in the functional connectivity intensity, and some related properties, in healthy people, across the life span and at resting state. For the explicit computation of the functional connectivity we exploit a recently proposed model, that bases not only on the correlations data provided by the acquisition equipment, but also on different parameters, such as the anatomical distances between nodes and their degrees. The leading purpose of the paper is to show that the proposed approach is able to recover the main aspects of resting state condition known from the available literature, as well as to suggest new insights, perspectives and speculations from a neurobiological point of view. Our study involves 133 subjects, both males and females of different ages, with no evidence of neurological diseases or systemic disorders. First, we show how the model applies to the sample, where the subjects are grouped into 28 different groups (14 of males and 14 of females), according to their age. This leads to the construction of two graphs (one for males and one for females), that can be realistically interpreted as representative of the neural network during the resting state. Second, following the idea that the brain network is better understood by focusing on specific nodes having a kind of centrality, we refine the two output graphs by introducing a new metric that favours the selection of nodes having higher degrees. As a third step, we extensively comment and discuss the obtained results. In particular, it is remarkable that, despite a great overlapping exists between the outcomes concerning males and females, some intriguing differences appear. This motivates a deeper local investigation, which represents the fourth part of the paper, carried out through a thorough statistical analysis. As a result, we are enabled to support that, for two special age groups, a few links contribute in differentiating the behaviour of males and females. In addition, we performed an average-based comparison between the proposed model and the traditional statistical correlation-based approach, then discussing and commenting the main outlined discrepancies. In this paper we investigate the changes in the functional connectivity intensity, and some related properties, in healthy people, across the life span and at resting state. For the explicit computation of the functional connectivity we exploit a recently proposed model, that bases not only on the correlations data provided by the acquisition equipment, but also on different parameters, such as the anatomical distances between nodes and their degrees. The leading purpose of the paper is to show that the proposed approach is able to recover the main aspects of resting state condition known from the available literature, as well as to suggest new insights, perspectives and speculations from a neurobiological point of view. Our study involves 133 subjects, both males and females of different ages, with no evidence of neurological diseases or systemic disorders. First, we show how the model applies to the sample, where the subjects are grouped into 28 different groups (14 of males and 14 of females), according to their age. This leads to the construction of two graphs (one for males and one for females), that can be realistically interpreted as representative of the neural network during the resting state. Second, following the idea that the brain network is better understood by focusing on specific nodes having a kind of centrality, we refine the two output graphs by introducing a new metric that favours the selection of nodes having higher degrees. As a third step, we extensively comment and discuss the obtained results. In particular, it is remarkable that, despite a great overlapping exists between the outcomes concerning males and females, some intriguing differences appear. This motivates a deeper local investigation, which represents the fourth part of the paper, carried out through a thorough statistical analysis. As a result, we are enabled to support that, for two special age groups, a few links contribute in differentiating the behaviour of males and females. In addition, we performed an average-based comparison between the proposed model and the traditional statistical correlation-based approach, then discussing and commenting the main outlined discrepancies.In this paper we investigate the changes in the functional connectivity intensity, and some related properties, in healthy people, across the life span and at resting state. For the explicit computation of the functional connectivity we exploit a recently proposed model, that bases not only on the correlations data provided by the acquisition equipment, but also on different parameters, such as the anatomical distances between nodes and their degrees. The leading purpose of the paper is to show that the proposed approach is able to recover the main aspects of resting state condition known from the available literature, as well as to suggest new insights, perspectives and speculations from a neurobiological point of view. Our study involves 133 subjects, both males and females of different ages, with no evidence of neurological diseases or systemic disorders. First, we show how the model applies to the sample, where the subjects are grouped into 28 different groups (14 of males and 14 of females), according to their age. This leads to the construction of two graphs (one for males and one for females), that can be realistically interpreted as representative of the neural network during the resting state. Second, following the idea that the brain network is better understood by focusing on specific nodes having a kind of centrality, we refine the two output graphs by introducing a new metric that favours the selection of nodes having higher degrees. As a third step, we extensively comment and discuss the obtained results. In particular, it is remarkable that, despite a great overlapping exists between the outcomes concerning males and females, some intriguing differences appear. This motivates a deeper local investigation, which represents the fourth part of the paper, carried out through a thorough statistical analysis. As a result, we are enabled to support that, for two special age groups, a few links contribute in differentiating the behaviour of males and females. In addition, we performed an average-based comparison between the proposed model and the traditional statistical correlation-based approach, then discussing and commenting the main outlined discrepancies. |
Author | Cercignani, Mara Baglio, Francesca Costantini, Isa Finotelli, Paolo Pini, Alessia Dulio, Paolo Dipasquale, Ottavia Baselli, Giuseppe |
AuthorAffiliation | 2 MRI Lab, IRCCS, Fondazione Don Carlo Gnocchi, Milan, Italy 1 Department of Mathematics, Politecnico di Milano, Milan, Italy 3 Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy South-Central University for Nationalities, CHINA 4 Neuroimaging Laboratory, Santa Lucia Foundation, Rome, Italy |
AuthorAffiliation_xml | – name: South-Central University for Nationalities, CHINA – name: 2 MRI Lab, IRCCS, Fondazione Don Carlo Gnocchi, Milan, Italy – name: 3 Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy – name: 4 Neuroimaging Laboratory, Santa Lucia Foundation, Rome, Italy – name: 1 Department of Mathematics, Politecnico di Milano, Milan, Italy |
Author_xml | – sequence: 1 givenname: Paolo orcidid: 0000-0002-8529-4321 surname: Finotelli fullname: Finotelli, Paolo – sequence: 2 givenname: Ottavia surname: Dipasquale fullname: Dipasquale, Ottavia – sequence: 3 givenname: Isa surname: Costantini fullname: Costantini, Isa – sequence: 4 givenname: Alessia surname: Pini fullname: Pini, Alessia – sequence: 5 givenname: Francesca surname: Baglio fullname: Baglio, Francesca – sequence: 6 givenname: Giuseppe surname: Baselli fullname: Baselli, Giuseppe – sequence: 7 givenname: Paolo surname: Dulio fullname: Dulio, Paolo – sequence: 8 givenname: Mara surname: Cercignani fullname: Cercignani, Mara |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30408067$$D View this record in MEDLINE/PubMed |
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Copyright | 2018 Finotelli et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2018 Finotelli et al 2018 Finotelli et al |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: The authors have declared that no competing interests exist. Current address: King's College London, London, United Kingdom Current address: University of Nice Sophia Antipolis, Nice, France Current address: Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Falmer, United Kingdom Current address: Università Cattolica del Sacro Cuore, Milan, Italy |
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SubjectTerms | Biology and Life Sciences Brain Cognition & reasoning Computer and Information Sciences Correlation Females Graphs Life span Males Mathematical models Mathematics Medicine and Health Sciences Neural networks Neurological diseases NMR Nodes Nuclear magnetic resonance People and Places Physical Sciences Research and Analysis Methods Statistical analysis Statistical correlation Theory |
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Title | Exploring resting-state functional connectivity invariants across the lifespan in healthy people by means of a recently proposed graph theoretical model |
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