Biology subjects

Mousavi, S. N.

Publications and source records attributed to Mousavi, S. N..

2 recordsLinked to original sources

bioRxiv2025

Retinal Origins of Circadian Photoregulation's Specialized Dynamic Range and Temporal Integration

The day-night cycle drives profound environmental changes, which animals anticipate using the circadian clock. The clock synchronizes with this cycle by extracting features of light that indicate solar elevation. It uses a specialized dynamic range to sense relevant photon rates and precise, extended temporal integration to encode total photon counts. This feature selectivity is distinct from that of visual perception and is thought to arise in the brain. We have found it within the retina's M1 melanopsin photoreceptors, which signal light to the clock. M1s have heterogeneous intrinsic and synaptic drives, and collectively account for the dynamic range of circadian photoregulation. Both individually and as a population, M1s approach the level of temporal integration observed behaviorally. M1s and behavior match closely when the pupillary light reflex, another M1-driven function, dynamically shapes retinal illumination. Thus, the earliest steps of photoreception are tuned to signifiers of Earth's rotation.

neuroscience↗

bioRxiv2022

Exploiting Color Space Geometry for Visual Stimulus Design across Animals

Color vision represents a vital aspect of perception that ultimately enables a wide variety of species to thrive in the natural world. However, unified methods for constructing chromatic visual stimuli in a laboratory setting are lacking. Here, we present stimulus design methods and an accompanying programming package to efficiently probe the color space of any species in which the photoreceptor spectral sensitivities are known. Our hardware-agnostic approach incorporates photoreceptor models within the framework of the principle of univariance. This enables experimenters to identify the most effective way to combine multiple light sources to create desired distributions of light, and thus easily construct relevant stimuli for mapping the color space of an organism. We include methodology to handle uncertainty of photoreceptor spectral sensitivity as well as to optimally reconstruct hyperspectral images given recent hardware advances. Our methods support broad applications in color vision science and provide a framework for uniform stimulus designs across experimental systems.

neuroscience↗