Evidence map›Paper›PMID 42831145›Full record

ReviewiScience2026

Deep brain stimulation mechanisms in comorbid pain and emotional dysregulation from animal models.

Tian-En Si, Hao Han, Ying-Ying Zhang, Zhen Zhou, Zhi-Xiao Li, Jing Cao, Wei Dong Zang

Abstract readReview
In one paragraph

Review in iScience, 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

7 authors.

Tian-En SiDepartment of Anatomy, Basic Medical College, Zhengzhou University, Zhengzhou 450001, China.
Hao HanThe First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Ying-Ying ZhangDepartment of Anatomy, Basic Medical College, Zhengzhou University, Zhengzhou 450001, China.
Zhen ZhouThe First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Zhi-Xiao LiDepartment of Anatomy, Basic Medical College, Zhengzhou University, Zhengzhou 450001, China.
Jing CaoDepartment of Anatomy, Basic Medical College, Zhengzhou University, Zhengzhou 450001, China.
Wei Dong ZangDepartment of Anatomy, Basic Medical College, Zhengzhou University, Zhengzhou 450001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deep brain stimulation (DBS) is a potent neuromodulatory intervention for chronic pain and comorbid affective disorders. This review synthesizes preclinical evidence detailing the neural circuits and molecular cascades engaged by DBS in models of pain and emotional dysregulation. We delineate how DBS-targeting regions like the prefrontal cortex (PFC), thalamus, and nucleus accumbens (NAc) recruit the prefrontal-midbrain-spinal axis to facilitate endogenous opioid release and modulate neurotransmission, thereby attenuating nociception. Concurrently, stimulating the ventromedial PFC (vmPFC) or lateral habenula (LHb) ameliorates affective deficits by restoring serotonergic (5-HT) and dopaminergic (DA) tone and stabilizing circuit dynamics. By mapping these convergent and divergent mechanisms, we highlight how DBS fine-tunes reward, anti-reward, and descending antinociceptive pathways. This mechanism-based framework outlines a translational roadmap for personalized neuromodulation, guiding symptom-specific target selection and the development of biomarker-driven, closed-loop DBS systems to concurrently treat pain and affective pathologies.

Indexed as

circuitsdeep brain stimulationdepresssionmolecular pathwayspain

Identifiers

PMID42831145
PMCPMC13634358

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.