Dynamic dopamine signaling, prediction error, and microcircuit mechanisms in stress-induced depression-like behaviors.

Authors

Ashraf Mahmud, Ljupcho Efremov

Published in

Frontiers in cell and developmental biology. Volume 14. Pages 1948686. Epub Oct 12, 2026.

Abstract

Chronic stress contributes to major depressive disorder (MDD) phenotypes by disrupting coordinated neuromodulatory systems and their corresponding computational frameworks. In this review, we explore how the dynamic interplay of ventral tegmental area dopamine (DA) signaling, microcircuit gating, and prediction error mechanics orchestrates stress-induced depressive behaviors, such as anhedonia and amotivation. Rather than acting as the sole driver of depression, pathway-specific neuroadaptations across mesolimbic ( $\text{VTA}\to \text{NAc}$ ) and mesocortical ( $\text{VTA}\to \text{PFC}$ ) dopaminergic projections operate within a broader multi-transmitter landscape, interacting with serotonergic, noradrenergic, cholinergic, and glutamatergic/GABAergic systems. These signaling anomalies often translate into computational deficits in reinforcement learning, manifesting as blunted striatal reward prediction error (RPE) signals that scale directly with anhedonia severity. Chronic stress also disrupts cortical microcircuit gating governed by dopamine $D_1$ and $D_2$ receptors, inducing cellular senescence and collapsing ensemble synchrony within the prefrontal cortex and interconnected networks. Furthermore, specialized subcortical loops, including inputs from the nucleus accumbens (NAc), ventral hippocampus (vHIPP), lateral habenula (LHb), and locus coeruleus (LC), recalibrate overall susceptibility versus resilience by altering DA firing dynamics and population activity pools, often in a sex-specific manner. By bridging synaptic dopamine dynamics, subcortical prediction errors, and cortical ensemble synchrony, we propose a unified, multi-level framework demonstrating how stress-induced depressive behaviors result from a progressive breakdown in the brain's predictive coding and adaptive coping networks.

PMID:
42928939
Bibliographic data and abstract were imported from PubMed on 26 Oct 2026.

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