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Understanding brain networks and brain organization
Open accessAbstract
What is the relationship between brain and behavior? The answer to this question necessitates characterizing the mapping between structure and function. The aim of this paper is to discuss broad issues surrounding the link between structure and function in the brain that will motivate a network perspective to understanding this question. However, as others in the past, I argue that a network perspective should supplant the common strategy of understanding the brain in terms of individual regions. Whereas this perspective is needed for a fuller characterization of the mind-brain, it should not be viewed as panacea. For one, the challenges posed by the many-to-many mapping between regions and functions is not dissolved by the network perspective. Although the problem is ameliorated, one should not anticipate a one-to-one mapping when the network approach is adopted. Furthermore, decomposition of the brain network in terms of meaningful clusters of regions, such as the ones generated by community-finding algorithms, does not by itself reveal "true" subnetworks. Given the hierarchical and multi-relational relationship between regions, multiple decompositions will offer different "slices" of a broader landscape of networks within the brain. Finally, I described how the function of brain regions can be characterized in a multidimensional manner via the idea of diversity profiles. The concept can also be used to describe the way different brain regions participate in networks.
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“multiple structural network configurations can theoretically give rise to the same apparent aberrations in function – this is essentially the ‘many-to-many mappings’ problem very nicely described in (Pessoa, 2014).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Pessoa, 2014
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“There are numerous lines of evidence to suggest that brain-behavior relationships are not simply one-to-one (Pessoa, 2014).”
From Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders (2019) · cites this paper as Pessoa, 2014
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“The network perspective maybe opens a new avenue to further understand the function properties of human brain, especially in large scale (Pessoa 2014).”
BackgroundSilva, L. L. S. O. E. (2019) · UCL Discovery (University College London)
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Glas, G. G. (2019) · Algemeen Nederlands Tijdschrift voor Wijsbegeerte · doi:10.5117/antw2019.3.009.glas
Cognition as a Mediated, Self-Organized, and Dynamic Activity
Damasceno, B. P. (2020) · Springer eBooks · doi:10.1007/978-3-030-57267-9_6
Leichner, J. (2020) · doi:10.25148/etd.fidc009178
“However, due to the multi-relational interactions between regions on numerous hierarchical scales, any decomposition of the brain network will fundamentally offer an incomplete perspective of the true landscape of the brain (Pessoa, 2014).”
BackgroundTraining Sparse Neural Network by Constraining Synaptic Weight on Unit Lp SpherePreprint
Li, W., Yang, X., Li, C., Lü, R., & Xie, X. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.16013
Salience neural network: another tribute to fashion or the key to all doors?
Dubatova, I. V., & Antsyborov, A. V. (2021) · Interactive science · doi:10.21661/r-554291
Zaquine, F., Coutsiers, E. E., Oliveira, D. M. D. S., Fink, J., & Caro, R. (2021) · Editora Poisson eBooks · doi:10.36229/978-65-5866-147-4.cap.12
Smulders, T. V. (2020) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.736647594.793579140
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Stothers, M. E., & Cardy, J. O. (2016) · IGI Global eBooks · doi:10.4018/978-1-5225-0034-6.ch068
Stebnicki, M. A. (2020) · Wiley eBooks · doi:10.1002/9781119783527.ch4
Guedes, K., de Macedo, C. A., Fenerich, F. C., & Ferreira, M. A. M. (2021) · Editora Poisson eBooks · doi:10.36229/978-65-5866-147-4.cap.23
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Schumann, J. H. (2017) · Language learning and language teaching · doi:10.1075/lllt.48.4sch
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Metadata
- Authors
- Pessoa, L.
- Affiliations
- University of Maryland, College Park (US)
- Corresponding author
- Pessoa, Luiz
- ORCID
- Pessoa, Luiz
- Venue
- Physics of Life Reviews
- Publisher
- Elsevier BV
- Published
- 2014-09
- Volume
- 11
- Issue
- 3
- Pages
- 400-435
- ISSN
- 1571-0645 (ISSN-L)
- PMC
- PMC4157099
- OpenAlex
- W2031461126
- Cited by
- 464
- References
- 156
- Citations by year
- 2026: 31 · 2025: 48 · 2024: 47 · 2023: 59 · 2022: 45 · 2021: 37 · 2020: 31 · 2019: 30 · 2018: 26 · 2017: 35 · 2016: 39 · 2015: 19 · 2014: 16
- FWCI
- 3.52
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Physics of Life Reviews (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Institute of Mental Health (R01MH071589)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- brain networks, brain organization, structure-function mapping, brain-behavior relationship, network perspective, many-to-many mapping, community detection, subnetworks, hierarchical brain organization, brain regions
- MeSH terms
- Algorithms, Animals, Brain, Brain Mapping, Humans, Nerve Net
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