ArticleNature communications2025
Biomimetic model of corticostriatal micro-assemblies discovers a neural code.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Mechanistic corticostriatal circuit model predicts learning-dependent fMRI dynamics and individual reward bias in humans.bioRxiv : the preprint server for biology · 2026Article
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9 authors.
Funding
Abstract
Although computational models have deepened our understanding of neuroscience, it is still highly challenging to link actual low-level physiological activity (spiking, field potentials) and biochemistry (transmitters and receptors) directly with high-level cognitive abilities (decision-making, working memory) and associated disorders. Here, we introduce a mechanistically accurate multi-scale model directly generating simulated physiology from which extended neural and cognitive phenomena emerge. The model produces spiking, fields, phase synchronies, and synaptic change, directly generating working memory, decisions, and categorization. These were then validated on extensive experimental macaque data from which the model received no prior training of any kind. Moreover, the simulation uncovered a previously unknown neural code ("incongruent neurons") that specifically predicts upcoming erroneous behaviors, also subsequently confirmed in empirical data. The biomimetic model thus directly and predictively links decision and reinforcement signals, of computational interest, with spiking and field codes, of neurobiological importance.
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