The Hidden Brain: Uncovering Previously Overlooked Brain Regions by Employing Novel Preclinical Unbiased Network Approaches.
fMRI
graph theory
iDISCO
iDISCO+
immunohistochemistry
modularity
network neuroscience
Journal
Frontiers in systems neuroscience
ISSN: 1662-5137
Titre abrégé: Front Syst Neurosci
Pays: Switzerland
ID NLM: 101477946
Informations de publication
Date de publication:
2021
2021
Historique:
received:
16
08
2020
accepted:
26
03
2021
entrez:
10
5
2021
pubmed:
11
5
2021
medline:
11
5
2021
Statut:
epublish
Résumé
A large focus of modern neuroscience has revolved around preselected brain regions of interest based on prior studies. While there are reasons to focus on brain regions implicated in prior work, the result has been a biased assessment of brain function. Thus, many brain regions that may prove crucial in a wide range of neurobiological problems, including neurodegenerative diseases and neuropsychiatric disorders, have been neglected. Advances in neuroimaging and computational neuroscience have made it possible to make unbiased assessments of whole-brain function and identify previously overlooked regions of the brain. This review will discuss the tools that have been developed to advance neuroscience and network-based computational approaches used to further analyze the interconnectivity of the brain. Furthermore, it will survey examples of neural network approaches that assess connectivity in clinical (i.e., human) and preclinical (i.e., animal model) studies and discuss how preclinical studies of neurodegenerative diseases and neuropsychiatric disorders can greatly benefit from the unbiased nature of whole-brain imaging and network neuroscience.
Identifiants
pubmed: 33967705
doi: 10.3389/fnsys.2021.595507
pmc: PMC8097000
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
595507Subventions
Organisme : NIAAA NIH HHS
ID : P60 AA006420
Pays : United States
Organisme : NIAAA NIH HHS
ID : R00 AA027301
Pays : United States
Organisme : NIAAA NIH HHS
ID : R01 AA026081
Pays : United States
Informations de copyright
Copyright © 2021 Simpson, Chen, Wellmeyer, Smith, Aragon Montes, George and Kimbrough.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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