Ryan S. Smith

This paper shows that interoceptive training improves heartbeat perception accuracy and reduces anxiety, with computational models explaining the underlying changes in signal precision and noise parameters.

This study evaluates the responsiveness of DNA methylation aging biomarkers across 51 longevity interventions, identifying factors influencing their response and highlighting the utility of explainable clocks.

This study uses computational models to show that psilocybin increases reward acquisition in rats by enhancing task engagement through altered forgetting rates and reduced loss aversion.

This study investigates neural responses to gastrointestinal sensations using a vibrating capsule, showing improved perceptual accuracy and correlated neural activity.

This study examines the effects of shearing frequency on Australian Merino sheep, identifying epigenetic markers and physiological changes associated with different shearing treatments.

This paper presents a neurocomputational model based on Active Inference to address limitations in the global neuronal workspace theory, demonstrating its ability to reproduce experimental findings and extend the GNW taxonomy.

This paper introduces an active inference framework for modeling structure learning, using concept learning as an example, and demonstrates its ability to generalize and reduce model complexity.

The paper replicates previous findings showing healthy individuals adjust prior expectations and interoceptive precision estimates based on task context using an active inference approach.

This paper presents an Active Inference model to simulate emotional state inference and emotion concept learning, showing it can acquire emotion concepts and their learning depends on early experiences and attention patterns.

This paper develops a computational model to understand factors influencing antidepressant non-adherence by simulating decision-making processes.

This paper develops a deep active inference model to simulate neurocomputational mechanisms of emotional awareness and identifies potential clinical implications for personalized interventions.