Novel Antidepressant Approaches for Refractory Depression

Postorivo, Danielle; Tye, Susannah J.

doi:10.1007/s40501-021-00246-y

Cited by 2 publications

(1 citation statement)

References 90 publications

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“…While many conventional treatments are available for depression, nearly one-third of patients are treatmentresistant 11 . A significant number of depressed patients do not respond to first-line medications even after multiple treatment trials 12 . Electroconvulsive therapy and transcranial magnetic stimulation are evidence-based treatments with short-term efficacy, but high rates of relapse are typical [13][14][15] .…”

Section: Main Textmentioning

confidence: 99%

Decoding Depression Severity from Intracranial Neural Activity

Xiao

Provenza

Asfouri

et al. 2022

Preprint

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Disorders of mood and cognition are prevalent, disabling, and notoriously difficult to treat. Fueling this challenge in treatment is a significant gap in our understanding of their neurophysiological basis. Here, we used intracranial neural recordings in three patients with severe depression to investigate the neural substrates of this disorder. Across prefrontal regions, we found that reduced depression severity is associated with decreased low-frequency neural activity and increased high-frequency activity. When constraining our model to decode using a single region, spectral changes in the anterior cingulate cortex best predicted depression severity in all three subjects. Relaxing this constraint revealed unique, individual-specific sets of spatio-spectral features predictive of symptom severity, reflecting the heterogeneous nature of depression. The ability to decode depression severity from neural activity increases our fundamental understanding of how depression manifests in the human brain and provides a target neural signature for personalized neuromodulation therapies.

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