Summary
This narrative review examines how circuit-level biomarkers derived from brain-wide activity patterns can improve diagnosis and treatment selection for mood and anxiety disorders. The authors synthesise advances in multiregion recording techniques, data-driven analysis, and machine-learning tools, arguing that integration of animal circuit studies with human neuroimaging will enhance precision biomarker identification and clinical application.
Regional applicability
The findings are relevant to UK neuroscience research and clinical practice by informing development of objective, circuit-based diagnostic tools for mood and anxiety disorders. However, the review does not address UK-specific healthcare systems, NHS implementation barriers, or population-level applicability.
Key measures
Multiregion brain recordings; brain-wide activity patterns; machine-learning-based behavioural analysis; neuroimaging biomarkers for mood and anxiety disorders
Outcomes reported
The paper reviews how brain-wide activity patterns across multiple regions and cell types can serve as biomarkers to distinguish mood and anxiety disorder subtypes and identify effective treatments. It synthesises evidence from animal studies and human neuroimaging to characterise the circuit-level mechanisms underlying emotional dysfunction.
Topic tags
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