ArticleFrontiers in human neuroscience2021
Distributed Subnetworks of Depression Defined by Direct Intracranial Neurophysiology.
Article in Frontiers in human neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Phase synchronization alterations of EEG oscillations during emotional video processing in depression and anxiety: a transdiagnostic study.European archives of psychiatry and clinical neuroscience · 2026Article
- Measuring Arousal: Promises and Pitfalls.Affective science · 2025Review
- Conflicting Interests and New Frontiers: A Role for Virtue Ethics in Cutting Edge Brain Research with Humans.Neuroethics · 2025Article
- High-level cognition is supported by information-rich but compressible brain activity patterns.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Elevated phase amplitude coupling as a depression biomarker in epilepsy.Epilepsy & behavior : E&B · 2024Article
- The Neurostimulationist will see you now: prescribing direct electrical stimulation therapies for the human brain in epilepsy and beyond.Frontiers in human neuroscience · 2024Review
- New and emerging approaches to treat psychiatric disorders.Nature medicine · 2023Review
- Network targets for therapeutic brain stimulation: towards personalized therapy for pain.Frontiers in pain research (Lausanne, Switzerland) · 2023Article
- Integrating biobehavioral information to predict mood disorder suicide risk.Brain, behavior, & immunity - health · 2022Review
- Wiring up the brain to beat depression.Nature · 2022Article
- A Gaussian Process Model of Human Electrocorticographic Data.Cerebral cortex (New York, N.Y. : 1991) · 2020Article
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10 authors.
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Abstract
Major depressive disorder is a common and disabling disorder with high rates of treatment resistance. Evidence suggests it is characterized by distributed network dysfunction that may be variable across patients, challenging the identification of quantitative biological substrates. We carried out this study to determine whether application of a novel computational approach to a large sample of high spatiotemporal resolution direct neural recordings in humans could unlock the functional organization and coordinated activity patterns of depression networks. This group level analysis of depression networks from heterogenous intracranial recordings was possible due to application of a correlational model-based method for inferring whole-brain neural activity. We then applied a network framework to discover brain dynamics across this model that could classify depression. We found a highly distributed pattern of neural activity and connectivity across cortical and subcortical structures that was present in the majority of depressed subjects. Furthermore, we found that this depression signature consisted of two subnetworks across individuals. The first was characterized by left temporal lobe hypoconnectivity and pathological beta activity. The second was characterized by a hypoactive, but hyperconnected left frontal cortex. These findings have applications toward personalization of therapy.
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