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Updated: Aug 6, 2026

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
Published on: May 10, 2012
The reins of the midbrain: Task-based habenula function in healthy humans
Amat Surroca López1, Francisco Medina Osuna1, Trevor Steward2
1Department of Social Psychology and Quantitative Psychology, Institute of Neurosciences, University of Barcelona (UB), Barcelona, Spain.
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The habenula is a small epithalamic structure that animal models have characterized as a key node linking value-laden information to midbrain monoaminergic systems. Its involvement in mood disorders has driven growing interest in characterizing its function in humans, yet the healthy baseline of habenular function measured using task-based fMRI has not been systematically synthesised. Thus, we searched PubMed, Scopus, and PsycINFO and identified 34 task-based fMRI studies (37 cohorts, N = 1480) examining habenular function in healthy adults. To address the methodological challenges of habenular imaging, we appraised each study through a spatial specificity framework. Findings were synthesised across four functional domains: affective and sensory processing, computational signalling, cognitive-affective regulation, and circadian rhythms. The human habenula emerged as a multifunctional integrative node that pulls back on - or modulates - midbrain function, much like the reins from which it takes its name. It processed primary and secondary aversive stimuli, encoded the predictive value of aversive cues, and signalled negative prediction errors across reinforcer types. Research also linked habenula activity to response gating under conflict and threat, and to higher-order cognitive processes. These responses recruited distributed circuits in which cortical inputs drive habenular modulation of midbrain monoaminergic function. Based on our framework, the most rigorous findings involved action gating under threat, foraging paradigms, and Pavlovian aversive conditioning, whereas foundational findings on primary aversion and reward prediction error encoding are starting to be replicated with more appropriate protocols. We recommend systematic adoption of high-specificity protocols and the integration of laterality and sex as biological variables.

