RESUMEN
Interactions across frontal cortex are critical for cognition. Animal studies suggest a role for mediodorsal thalamus (MD) in these interactions, but the computations performed and direct relevance to human decision making are unclear. Here, inspired by animal work, we extended a neural model of an executive frontal-MD network and trained it on a human decision-making task for which neuroimaging data were collected. Using a biologically-plausible learning rule, we found that the model MD thalamus compressed its cortical inputs (dorsolateral prefrontal cortex, dlPFC) underlying stimulus-response representations. Through direct feedback to dlPFC, this thalamic operation efficiently partitioned cortical activity patterns and enhanced task switching across different contingencies. To account for interactions with other frontal regions, we expanded the model to compute higher-order strategy signals outside dlPFC, and found that the MD offered a more efficient route for such signals to switch dlPFC activity patterns. Human fMRI data provided evidence that the MD engaged in feedback to dlPFC, and had a role in routing orbitofrontal cortex inputs when subjects switched behavioral strategy. Collectively, our findings contribute to the emerging evidence for thalamic regulation of frontal interactions in the human brain.
Asunto(s)
Corteza Prefrontal , Tálamo , Animales , Encéfalo , Cognición/fisiología , Humanos , Aprendizaje/fisiología , Corteza Prefrontal/diagnóstico por imagen , Corteza Prefrontal/fisiología , Tálamo/diagnóstico por imagen , Tálamo/fisiologíaRESUMEN
The flexibility in adjusting the decision strategy from trial to trial is a prerequisite for learning in a probabilistic environment. Corresponding neural underpinnings remain largely unexplored. In the present study, 28 male humans were engaged in an associative learning task, in which they had to learn the changing probabilistic strengths of tactile sample stimuli. Combining functional magnetic resonance imaging with computational modeling, we show that an unchanged decision strategy over successively presented trials related to weakened functional connectivity between ventralmedial prefrontal cortex (vmPFC) and left secondary somatosensory cortex. The weaker the connection strength, the faster participants indicated their choice. If the decision strategy remained unchanged, participant's decision confidence (i.e., prior belief) was related to functional connectivity between vmPFC and right pulvinar. While adjusting the decision strategy, we instead found confidence-related connections between left orbitofrontal cortex and left thalamic mediodorsal nucleus. The stronger the participant's prior belief, the weaker the connection strengths. Together, these findings suggest that distinct thalamo-prefrontal pathways encode the confidence in keeping or changing the decision strategy during probabilistic learning. Low confidence in the decision strategy demands more thalamo-prefrontal processing resources, which is in-line with the theoretical accounts of the free-energy principle.