Biology subjects

Quetu, T.

Publications and source records attributed to Quetu, T..

3 recordsLinked to original sources

bioRxiv2025

A cortical code emerges in Layer5a of S1 through temporal integration of thalamic inputs

Tactile representations in the barrel field of the primary somatosensory cortex (wS1) receive input from two thalamic nuclei: ventro-posterior-medial (VPM) and posterior-medial complex (POm). However, how these inputs generate distinct cortical representations remains unclear. Previous work revealed a sweep-stick code in rat wS1 using novel velocity-white noise whisker stimulus. Sticks are high-velocity single-whisker bumps; sweeps are large multi-whisker displacements with extended temporal profiles. We hypothesized that cortex neurons inherit 'stick' responses from VPM and 'sweep' responses from first order POm. We tested this by studying coding strategies in both thalamic nuclei and wS1 in mice, determining where the cortical sweep and stick codes originate. We found a stratified wS1 representation of sweep and stick classes, whereas in our recordings VPM and POm mostly contained stick-responding neurons. Layer 4 'stick' responses are delayed versions of VPM responses, and layer 5b 'sweep' responses come from first order POm. Notably, layer 5a 'sweep' responses arise from temporal integration of 'stick' information from VPM and first order POm. Thus, contrary to our initial hypothesis, sweep responses are not inherited from the VPM or first order POm but are constructed within the cortex. In contrast, higher order POm presented only 'sweep' responses inherited from layer 5b of cortex, with a latency similar to that in layer 5a. Our findings reveal a circuit where fast VPM-encoded 'sticks' allow fine-tuned texture processing, complemented by cortically constructed sweep responses that integrate multi-whisker information.

neuroscience↗

bioRxiv2025

Accurate spatiotemporal retinal responses require a color intensity balance fine-tuned to natural conditions

Color vision is vital for animal survival, essential for foraging and predator detection. In mice, as in other mammals, color vision originates in the retina, where photoreceptor signals are processed by neural circuits. However, retinal responses to stimuli involving multiple colors are still not well understood. One possible explanation of this knowledge gap is that previous studies have not thoroughly examined how neuronal activity adapts to a 30 seconds to a few minutes timescale when exposed to multiple color sources. To address this, we systematically varied the UV-to-green light balance with a custom-built stimulator targeting mice opsins spectra while recording retinal ganglion cell responses across the dorso-ventral axis of the retina using multielectrode arrays. Responses to full-field chirp and checkerboard stimulations with alternating UV and green light revealed that more than one order of magnitude of intensity difference favoring green M-opsin over UV S-opsin is needed for a balanced reliability in retinal ganglion cell responses in the ventral retina. An incorrect balance, with slightly increased UV light, silenced responses to green illumination. To determine if these values are consistent with natural conditions, we analyzed isomerisation rates in the mouse retina across different times of the day. We found that the M- to S-opsin activation ratio remains constant through the mesopic-photopic range, and that our empirically determined values in the ventral retina align well with these natural conditions. These lie far from a simple equalization of M- and S-opsin isomerisation rates, which we found only balances ganglion cell responses in the dorsal retina. In conclusion, a finely tuned color intensity balance matching natural light spectrum is essential for accurately measuring both fast temporal responses and detailed spatial receptive fields in the ventral retina.

neuroscience↗

bioRxiv2024

Nonlinear spatial integration allows the retina to detect the sign of defocus in natural scenes

Eye growth is regulated by the visual input. Many studies suggest that the retina can detect if a visual image is focused in front or behind the back of the eye, and modulate eye growth to bring it back to focus. How can the retina distinguish between these two types of defocus? Here we simulated how eye optics transform natural images and recorded how the isolated retina responds to different types of simulated defocus. We found that some ganglion cell types could distinguish between an image focussed in front or behind the retina, by estimating spatial contrast. Aberrations in the eye optics made spatial contrast, but not luminance, a reliable cue to distinguish these two types of defocus. Our results suggest a mechanism for how the retina can estimate the sign of defocus and provide an explanation for several results aiming at mitigating strong myopia by slowing down eye growth.

neuroscience↗