Evidence map›Paper›PMID 42421731›Full record

ReviewFrontiers in psychology2026

Guided Imagery and Music modulates neural circuits in mood disorders: a systematic review of mechanisms and clinical efficacy.

Tianyi Wang, Xin Zhao, Han Wang, Ying Li, Qitong Jiang, Yuan Feng, Gang Wang, Jing Du

Abstract readReview
In one paragraph

Review in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Tianyi WangThe National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Xin ZhaoThe National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Han WangThe National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Ying LiThe National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Qitong JiangThe National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Yuan FengThe National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Gang WangThe National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Jing DuThe National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Guided Imagery and Music (GIM), as an emerging therapeutic approach, is widely applied in the treatment of Mood disorders (MDs). However, its efficacy and underlying neural mechanisms remain unclear at present. MDs represent one of the leading causes of disability worldwide. Conventional pharmacological treatments, which primarily target single biological pathways, are frequently limited by side effects and demonstrate inconsistent therapeutic efficacy. GIM is a multimodal psychotherapeutic intervention that utilizes music-evoked imagery to facilitate emotional and cognitive processing. By engaging cognitive and emotional processing networks, GIM is regarded as one of the approaches for neuropsychological rehabilitation in mood disorders. However, the underlying neural circuit mechanisms of this approach remain insufficiently systematized and warrant further investigation. Methods: We conducted a systematic review following PRISMA guidelines. A comprehensive literature search was performed in PubMed and Web of Science (2000-2024) to examine the neural mechanisms and clinical efficacy of GIM for MDs, with emphasis on randomized controlled trials (RCTs) and neuroimaging studies. Results: GIM modulates four key neural circuits implicated in MDs: (1) regulates amygdala hyperactivity while enhancing prefrontal-amygdala connectivity; (2) promotes hippocampal neuroplasticity via auditory-driven theta synchronization; (3) reorganizes prefrontal network coordination by strengthening dorsolateral prefrontal connectivity and reducing ventromedial default mode network (DMN) hyperconnectivity; and (4) activates the nucleus accumbens dopaminergic reward pathway to mitigate anhedonia. Clinically, GIM demonstrates significant efficacy in alleviating depressive symptoms, improving cognitive function, and reducing somatic complaints across diverse populations. Conclusion: This study proposes an integrated neural circuit-targeted model for GIM in MDs, bridging multimodal neural modulation with clinical outcomes. The findings establish a neuroscientific basis for GIM as a promising non-pharmacological intervention and support its integration into standard mood disorder treatment protocols. This review presents an integrative neural circuit framework for GIM in MDs, synthesizing existing neuroimaging and clinical evidence, and laying the groundwork for future mechanistic and clinical research.

Indexed as

emotional cognitionGuided Imagery and Musicmood disordersneural circuitsneuroplasticitynon-pharmacological interventionreward system

Identifiers

PMID42421731
PMCPMC13341468

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.