Biology subjects

Perets, I.

Publications and source records attributed to Perets, I..

3 recordsLinked to original sources

bioRxiv2026

Thalamo-insular basis for updating physiological needs

Physiological needs, such as thirst and hunger, produce powerful motivation for behaviors that are essential for survival. Yet, how the brain estimates these needs remains unknown. It is unclear whether the brain continuously monitors bodily signals to create real-time representations, or if existing internal representations are only updated when meaningful changes occur. To address this question, we manipulated thalamic internal sensory inputs to the interoceptive insular cortex. We found that inhibiting internal sensory inputs prevents the updating of insular cortex representations of thirst and hunger, thereby keeping its activity closer to its initial physiological need state. Consequently, cued feeding and drinking, as well as free consumption of food and water, persist beyond the current physiological need. We further show that insular cortex activity normally represents both predictions and sensory information. However, violating learned expectations evokes widespread need-specific prediction error signals. Our results thus reveal a thalamo-cortical basis for updating physiological needs in the brain.

neuroscience↗

bioRxiv2025

Insular cortex predictions regulate glucose homeostasis

Brain-body interactions are essential for physical and emotional homeostasis. The brain uses information from the external world to predict upcoming bodily changes. This process involves interoceptive predictions, which are thought to play a central role in brain-body interactions. Yet there is little direct experimental evidence causally linking interoceptive predictions to regulation of bodily physiology. Here we address this by focusing on insular cortex and glucose homeostasis. We find that just before the onset of a meal, insular cortex exhibits a transient burst of activity, reflecting a prediction of the future metabolic state. This transient predictive burst of activity is essential for anticipatory insulin release, subsequent post-meal insulin release, post-meal glucose and lipid homeostasis, and post-meal metabolism signaling in the liver. Our results highlight that insular cortex predictive computations are essential for anticipatory physiological control and for subsequently maintaining metabolic homeostasis.

neuroscience↗

bioRxiv2024

Continuous structural neuroplasticity during motor learning - a diffusion MRI study

How does our brain transform when we encounter a new task? To fully answer this question, comparing brain states before and after learning may not be enough, but rather an on-going, continuous monitoring of brain changes during learning is required. While such continuous examinations of functional learning-induced changes are widely available using functional magnetic resonance imaging (fMRI), a continuous investigation of microstructural brain modifications during learning is yet to be reported. Here, we continuously acquire diffusion MRI images during task performance. We then compute the mean diffusivity (MD) using a sliding-window approach, resulting in a continuous measure of microstructural changes throughout learning. We demonstrate the utility of this method on a motor sequence learning (finger tapping) task (n=58). MD decrease was detected in task-related brain regions, including the parahippocampal gyrus, hippocampus, inferior temporal gyrus, and cerebellum. Analysis of the temporal patterns of decrease revealed a rapid MD reduction in the right temporal gyrus after 11 minutes of learning, with additional decrease in the right parahippocampal gyrus and left cerebellum after 22 minutes. We further computed "neuroplasticity networks" of brain areas showing similar change patterns and detected similarities between these networks and canonical functional connectivity networks. Our findings offer novel insights on the spatio-temporal dynamics of microstructural neuroplasticity by demonstrating continuous modifications during the encoding phase of learning itself, rather than comparing pre- and post-learning states.

neuroscience↗