{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T12:07:51Z","timestamp":1788782871179,"version":"build-2803163510"},"reference-count":108,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T00:00:00Z","timestamp":1788739200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Psychol."],"abstract":"<jats:p>Major depressive disorder (MDD) remains challenging to treat due to the lack of objective biomarkers for monitoring treatment response and predicting outcomes. Traditional treatment response evaluation rely heavily on subjective assessments, creating a pressing need for objective biomarkers to monitor therapeutic efficacy. Functional near-infrared spectroscopy (fNIRS), a non-invasive, portable, and high-temporal-resolution brain imaging technique, can indirectly reflect brain function by monitoring metrics such as oxy-hemoglobin. This review systematically synthesizes research from 2021\u20132026 to detail the application of fNIRS in evaluating various depression interventions, including pharmacotherapy, physical therapies, psychological interventions, integrated interventions, and combined East\u2013West medicine approaches. Evidence indicates that fNIRS can precisely capture hemodynamic and functional connectivity changes in key brain regions like the prefrontal and temporal cortices across different treatments, which correlate closely with clinical symptom improvement. This positions fNIRS as a promising biomarker for treatment efficacy assessment and a potential tool for predicting therapeutic response. Current limitations, such as small sample sizes and a lack of standardized protocols, are also discussed. Future directions include promoting multimodal integration, establishing standardized procedures, and building machine learning models to advance personalized and precise treatment monitoring for depression.<\/jats:p>","DOI":"10.3389\/fpsyg.2026.1934277","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T11:14:45Z","timestamp":1788779685000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Application of functional near-infrared spectroscopy in evaluating antidepressant treatment efficacy: a review of recent evidence (2021\u20132026)"],"prefix":"10.3389","volume":"17","author":[{"given":"Mao-liang","family":"Ma","sequence":"first","affiliation":[{"name":"Department of Clinical Psychology, Tianjin Medical University General Hospital Airport Hospital","place":["Tianjin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiang","family":"Cao","sequence":"additional","affiliation":[{"name":"Department of Clinical Psychology, Tianjin Medical University General Hospital","place":["Tianjin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian-li","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Clinical Psychology, Tianjin Medical University General Hospital","place":["Tianjin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,7]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"2154","DOI":"10.3390\/healthcare13172154","article-title":"Explainable AI in clinical decision support systems: a meta-analysis of methods, applications, and usability challenges","volume":"13","author":"Abbas","year":"2025","journal-title":"Healthcare"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1111\/pcn.13488","article-title":"Prognostic factors in major depressive disorder: comparing responders and non-responders to repetitive transcranial magnetic stimulation (rTMS), a naturalistic retrospective chart review","volume":"77","author":"Abo Aoun","year":"2023","journal-title":"Psychiatry Clin. 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