Mood and anxiety disorders are complex heterogeneous syndromes that manifest in dysfunctions across multiple brain regions, cell types, and circuits. Biomarkers using brain-wide activity patterns in humans have proven useful in distinguishing between disorder subtypes and identifying effective treatments. In order to improve biomarker identification, it is crucial to understand the basic circuitry underpinning brain-wide activity patterns. Leveraging a large repertoire of techniques, animal studies have examined roles of specific cell types and circuits in driving maladaptive behavior. Recent advances in multiregion recording techniques, data-driven analysis approaches, and machine-learning-based behavioral analysis tools can further push the boundary of animal studies and bridge the gap with human studies, to assess how brain-wide activity patterns encode and drive emotional behavior. Together, these efforts will allow identifying more precise biomarkers to enhance diagnosis and treatment. Distributed Neural Circuits Underly Mood and Anxiety Disorders Mood and anxiety disorders disrupt basic functions of individuals' lives, and are among the leading causes of disability [1]. In the USA, it is estimated that at a given timepoint, 10-20% of adults are impacted, and 20-30% of adults will experience a mood or anxiety disorder at some point in their lives (https://www.hcp.med.harvard.edu/ncs). However, most existing treatments are not effective [2,3]; largely due to a lack of clear understanding of disease etiology. The search for effective treatment is further complicated by the fact that mood and anxiety disorders are heterogeneous syndromes with various subtypes, where patients present diverse symptoms even for the same disorder, and often respond differently to the same treatment [4-7]. Highlights Mood and anxiety disorders are complex neural-circuit-based conditions that arise from dysfunctions across multiple cell types, brain regions, and circuits. Recent efforts in identifying circuit-based biomarkers using brain-wide activity patterns have shown promising results in stratifying disorder subtypes and identifying effective treatments for patients with mood and anxiety disorders.