Modulation of prefrontal couplings by prior belief-related responses in ventromedial prefrontal cortex

Humans and other animals can maintain constant payoffs in an uncertain environment by steadily re-evaluating and flexibly adjusting current strategy, which largely depends on the interactions between the prefrontal cortex (PFC) and mediodorsal thalamus (MD). While the ventromedial PFC (vmPFC) represents the level of uncertainty (i.e., prior belief about external states), it remains unclear how the brain recruits the PFC-MD network to re-evaluate decision strategy based on the uncertainty. Here, we leverage non-linear dynamic causal modeling on fMRI data to test how prior belief-dependent activity in vmPFC gates the information flow in the PFC-MD network when individuals switch their decision strategy. We show that the prior belief-related responses in vmPFC had a modulatory influence on the connections from dorsolateral PFC (dlPFC) to both, lateral orbitofrontal (lOFC) and MD. Bayesian parameter averaging revealed that only the connection from the dlPFC to lOFC surpassed the significant threshold, which indicates that the weaker the prior belief, the less was the inhibitory influence of the vmPFC on the strength of effective connections from dlPFC to lOFC. These findings suggest that the vmPFC acts as a gatekeeper for the recruitment of processing resources to re-evaluate the decision strategy in situations of high uncertainty

Understanding the role of striosomes in learning a decision-making task

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2020Cataloged from student-submitted PDF of thesis.Includes bibliographical references (pages 74-77).Learning to approach for rewards and avoid for costs is a necessary skill for species survival. In this thesis, I investigate the role of the striosomal compartment of the rodent basal ganglia while learning a cost-benefit decision making task. I analyze data from animals of different age groups and animals with expressive Huntington's disease (HD) gene. My goal is to understand the computational role of striosomes in learning, and how aging and Huntington's disorder affect the anatomical structure of striosomes and thus the ability to learn. By analyzing Ca⁺⁺ (Calcium) neuron population recordings, behavior recordings, and histological brain slice images of mice, I find that: 1) the activity of spiny projection neurons (SPNs) in striosomes correlate with learning ability; 2) an animal's attentiveness to the task is critical for learning; 3) anatomical circuit disassembly, specifically reduced connectivity of inhibitory Parvalbumin (PV) interneurons on SPNs, is found in animal groups with lower learning ability. These results help elucidate the unclear role of striosomes in learning and provide ideas for future research directions that could inspire neurological treatments for neuro-degradation in aging and disorder.by Sabrina Mariel Drammis.M. Eng.M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienc

Thalamic regulation of frontal interactions in human cognitive flexibility

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.</jats:p

Brain regions related to the Strategy Switching (<i>Switching</i> > <i>Staying</i>) (p < 0.001, uncorrected).

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Selective dlPFC sensory representations in the MD intact neural model.

A. We identified model dlPFC cells that were cue-responsive in one of the two behavioral contexts selectively and cells that were cue-responsive in both contexts non-selectively, using logistic regression. We found the most significant difference between the MD intact and MD lesioned models was an increase in non-selective cells with MD lesioning (Mann-Whitney U test, two-tailed, both contexts p-value 0.003, match-selective p = 0.210, non-match selective p = 0.449). Bars represent means ±SEM B. Schematic shows cartoon of cells that were cue-responsive only in one of the behavioral contexts, and the connections to the appropriate output cell (left). These cells had their weights to the appropriate output neuron increase coherently in the corresponding behavioral context and remain dormant out of context (right). C. In comparison, cells that responded to the same cue in either context showed impaired learning with forgetting of previous learning after each experimental block, as rewarded behavioral responses reversed. We show weight averages from the population of dlPFC cells encoding on of the input cues, as identified by logistic regression, to the appropriate output neuron, with shaded areas representing ±SD.</p

Striosomes Mediate Value-Based Learning Vulnerable in Age and a Huntington’s Disease Model

© 2020 Elsevier Inc. Friedman et al. find that specialized regions of the striatum, a key part of the brain's movement and motivation control system, are essential for learning about the values of good and bad outcomes of decisions. The learning signals in striosomes scale according to subjective value and are vulnerable to decline with aging and in neurodegenerative disorders