A habenula-insular circuit encodes the willingness to act
Open accessAbstract
The decision that it is worth doing something rather than nothing is a core yet understudied feature of voluntary behaviour. Here we study “willingness to act”, the probability of making a response given the context. Human volunteers encountered opportunities to make effortful actions in order to receive rewards, while watching a movie inside a 7 T MRI scanner. Reward and other context features determined willingness-to-act. Activity in the habenula tracked trial-by-trial variation in participants’ willingness-to-act. The anterior insula encoded individual environment features that determined this willingness. We identify a multi-layered network in which contextual information is encoded in the anterior insula, converges on the habenula, and is then transmitted to the supplementary motor area, where the decision is made to either act or refrain from acting via the nigrostriatal pathway.
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We used high-resolution (1-mm isotropic), rapid-repetition-time (1.378 s), accelerated ultrahigh-field (7T) fMRI to measure activity simultaneously across all five neuromodulatory nuclei and two interconnected cortical regions (AI and ACC).
“Here we exploit high-resolution (1-mm isotropic), rapid-repetition-time (1.378 s), accelerated ultrahigh-field (7T) functional magnetic resonance imaging (fMRI)27,28 to measure activity simultaneously across all five neuromodulatory nuclei and two interconnected cortical regions that project to them: the anterior insula (AI) and anterior cingulate cortex (ACC)3,22,29–33.”
From Interpretable abstractions of artificial neural networks predict behavior and neural activity during human information gathering (2026) · cites this paper as [28]
AI and activity in dopaminergic midbrain areas such as SN have been reported when people evaluate whether and when to initiate an action.
“AI and activity in dopaminergic midbrain areas such as SN have been reported when people evaluate whether and when to initiate an action28,41.”
From Interpretable abstractions of artificial neural networks predict behavior and neural activity during human information gathering (2026) · cites this paper as [28]
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- Authors
- Khalighinejad, N., Garrett, N., Priestley, L., Lockwood, P., & Rushworth, M. F. S.
- Affiliations
- University of Oxford (GB)
- University of East Anglia (GB)
- Corresponding author
- Khalighinejad, Nima
- Venue
- Nature Communications
- Published
- 2021-11-03
- Volume
- 12
- Issue
- 1
- Pages
- 6329-6329
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC8566457
- OpenAlex
- W3209609691
- Cited by
- 32
- References
- 54
- Citations by year
- 2026: 9 · 2025: 10 · 2024: 4 · 2023: 5 · 2022: 3 · 2021: 1
- FWCI
- 1.71
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UEA Digital Repository (University of East Anglia) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion, cc-by)
- Funders
- Wellcome Trust (WT101092MA, WT100973AIA, 203139/Z/16/Z)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- willingness to act, habenula, anterior insula, supplementary motor area, nigrostriatal pathway, contextual encoding
- MeSH terms
- Adolescent, Adult, Animals, Behavior, Brain, Cerebral Cortex, Decision Making, Female, Humans, Magnetic Resonance Imaging, Male, Probability, Reward, Habenula, Young Adult
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