| Summary: | Toby Wise,1 Anthony J Cleare,1 Andrés Herane,1,2 Allan H Young,1 Danilo Arnone1 1King’s College London, Institute of Psychiatry, Department of Psychological Medicine, Centre for Affective Disorders, London, United Kingdom; 2Clínica Psiquiátrica Universitaria, Universidad de Chile, Santiago, Chile Abstract: A growing number of studies have used neuroimaging to further our understanding of how brain structure and function are altered in major depression. More recently, these techniques have begun to show promise for the diagnosis and treatment of depression, both as aids to conventional methods and as methods in their own right. In this review, we describe recent neuroimaging findings in the field that might aid diagnosis and improve treatment accuracy. Overall, major depression is associated with numerous structural and functional differences in neural systems involved in emotion processing and mood regulation. Furthermore, several studies have shown that the structure and function of these systems is changed by pharmacological and psychological treatments of the condition and that these changes in candidate brain regions might predict clinical response. More recently, “machine learning” methods have used neuroimaging data to categorize individual patients according to their diagnostic status and predict treatment response. Despite being mostly limited to group-level comparisons at present, with the introduction of new methods and more naturalistic studies, neuroimaging has the potential to become part of the clinical armamentarium and may improve diagnostic accuracy and inform treatment choice at the patient level. Keywords: depression, mood disorder, neuroimaging, diagnosis, treatment
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