Opportunities and Challenges for Psychiatry in the Connectomic Era
Abstract
Most major psychiatric disorders arise from disturbances of anatomically distributed neural systems rather than isolated dysfunction of circumscribed brain regions. The past decade has witnessed rapid advances in our capacity to measure, map, and model neural connectivity in diverse species and at different resolution scales, from the level of individual neurons and synapses to large-scale systems spanning the entire brain. In this review, we consider how these techniques, when grounded in the theory and methods of network science, can contribute to a biological understanding of mental illness. We focus in particular on attempts to accurately map brain network disturbances in clinical populations and to model the mechanistic causes of these changes. This work suggests that pathology within highly connected hub regions is a consistent finding across a broad array of phenotypically diverse disorders, and that disparate changes in brain network organization can sometimes be explained by a surprisingly small and simple set of mechanisms.
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Thresholding weak edges implicitly assumes a correlation between reconstructed edge strength and validity, which can be violated.
“This strategy implicitly assumes a correlation between the strength of a reconstructed edge and its validity, which can be violated in a range of ways due to the errors produced by streamlines tractography not being simply random variance.”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Fornito et al., 2016
For scalar values interpreted as inversely related to connectivity strength, such as RD, MD, or maps reflecting extracellular or isotropic/free water components, a transformation of the connectivity matrix using the reciprocal or log function may be performed prior to subsequent connectivity analysis.
“For scalar values that are interpreted as inversely related to connectivity “strength,” such as RD, MD, or maps reflecting extracellular or isotropic/free water components of the signal, a transformation of the connectivity matrix may be performed using the reciprocal or the log function prior to any subsequent connectivity analysis (Fornito et al., 2016).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Fornito et al., 2016
Graph measures can be classified by resolution or scope into local, mesoscale, and global measures.
“Graph measures can be classified based on their resolution or scope—from local measures that quantify properties of individual ROIs (nodes), to mesoscale measures describing clusters of interconnected ROIs, to global measures that describe whole-brain connectivity properties (Betzel and Bassett, 2017; Fornito et al., 2016) such as network communication in the brain (Graham et al., 2020) (Fig. 4b).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Fornito et al., 2016
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References 154 · Cited by 74
- Authors
- Fornito, A., Bullmore, E. T., & Zalesky, A.
- Affiliations
- Melbourne Health (AU)
- GlaxoSmithKline (United Kingdom) (GB)
- The University of Melbourne (AU)
- Corresponding author
- Fornito, Alex
- Venue
- Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
- Publisher
- Elsevier BV
- Published
- 2017-01
- Volume
- 2
- Issue
- 1
- Pages
- 9-19
- ISSN
- 2451-9022 (ISSN-L)
- OpenAlex
- W2478419804
- Cited by
- 74
- References
- 154
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 8 · 2023: 6 · 2022: 10 · 2021: 13 · 2020: 5 · 2019: 12 · 2018: 6 · 2017: 6
- FWCI
- 0.84
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biological Psychiatry Cognitive Neuroscience and Neuroimaging (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Australian Research Council (FT130100589)
- National Health and Medical Research Council (1050504, 1066779, 1047648, 1103252)
- Wellcome Trust
- National Institute of Health Research
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- connectomics, mental illness, network science, hub regions, neuronal connectivity, network modeling
- MeSH terms
- Brain, Humans, Nerve Net, Neural Pathways, Neurons, Psychiatry, Connectome
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