Schwinn, S. | bioRxiv Science

bioRxiv2024

Sensorimotor integration enhances temperature stimulus processing

Animals optimize behavior by integrating sensory input with motor actions. We hypothe-sized that coupling thermosensory information with motor output enhances the brains capacity to process temperature changes, leading to more precise and adaptive behaviors. To test this, we developed a virtual "thermal plaid" environment where zebrafish either actively controlled temperature changes (sensorimotor feedback) or passively experienced the same thermal fluctuations. Our findings demonstrate that sensorimotor feedback amplifies the influence of thermal stimuli on swim initiation, resulting in more structured and organized motor output. We show that previously identified mixed-selectivity neurons that simultaneously encode thermal cues and motor activity enable the integration of sensory and motor feedback to optimize behavior. These results highlight the role of sensorimotor integration in refining thermosensory processing, revealing critical neural mechanisms underlying flexible thermoregulatory behavior. Our study offers new insights into how animals adaptively process environmental stimuli and adjust their actions, contributing to a deeper understanding of the neural circuits driving goal-directed behavior in dynamic environments.

neuroscience↗

bioRxiv2022

A model-free approach to link neural activity to behavioral tasks

Brains are not engineered solutions to a well-defined problem but arose through selective pressure acting on random variation. It is therefore unclear how well a model chosen by an experimenter can relate neural activity to experimental conditions. Here we developed "Model identification of neural encoding (MINE)." MINE is an accessible framework using convolutional neural networks (CNN) to discover and characterize a model that relates aspects of tasks to neural activity . Although flexible, CNNs are difficult to interpret. We use Taylor decomposition approaches to understand the discovered model and how it maps task features to activity. We apply MINE to a published cortical dataset as well as experiments designed to probe thermoregulatory circuits in zebrafish. MINE allowed us to characterize neurons according to their receptive field and computational complexity, features which anatomically segregate in the brain. We also identified a new class of neurons that integrate thermosensory and behavioral information which eluded us previously when using traditional clustering and regression-based approaches.

neuroscience↗