Biology subjects

Rousseau, C. V.

Publications and source records attributed to Rousseau, C. V..

3 recordsLinked to original sources

bioRxiv2023

Coexistence of state, choice, and sensory integration coding in barrel cortex LII/III

During perceptually guided decisions, correlates of choice are found as upstream as in the primary sensory areas. However, how well these choice signals align with early sensory representations, a prerequisite for their interpretation as feedforward substrates of perception, remains an open question. We designed a two alternative forced choice task (2AFC) in which mice compared stimulation frequencies applied to two adjacent vibrissae. The optogenetic silencing of individual columns in the primary somatosensory cortex (wS1) resulted in predicted shifts of psychometric functions, demonstrating that perception depends on focal, early sensory representations. Functional imaging of layer II/III single neurons revealed sensory, choice and engagement coding. From trial to trial, these three varied substantially, but independently from one another. Thus, coding of sensory and non-sensory variables co-exist in orthogonal subspace of the population activity, suggesting that perceptual variability does not originate from wS1 but rather from state or choice fluctuations in downstream areas.

neuroscience↗

bioRxiv2021

Tools for accurate post hoc determination of marker location within whole-brain microscopy images

To interpret in vivo experiments designed to understand brain function, high-resolution whole-brain microscopy provides a means for post hoc determination of the location of implanted devices and recorded cells in three dimensional brain space that is a critical step for data interrogation. Here we have developed Python-based tools (brainreg and brainreg-segment) to accurately map, in a common coordinate space, the position of dye-labelled probe tracks and two-photon imaged cell populations expressing fluorescent protein. The precise location of probes and cells were validated using physiological recordings and human raters that indicate accuracy levels to less than 70{micro}m. These flexible, open-source methodologies are expected to further evolve with need and to deliver the anatomical precision that is necessary for understanding the functional architecture of the brain.

neuroscience↗

bioRxiv2020

A deep learning algorithm for 3D cell detection in whole mouse brain image datasets

Understanding the function of the nervous system necessitates mapping the spatial distributions of its constituent cells defined by function, anatomy or gene expression. Recently, developments in tissue preparation and microscopy allow cellular populations to be imaged throughout the entire rodent brain. How-ever, mapping these neurons manually is prone to bias and is often impractically time consuming. Here we present an opensource algorithm for fully automated 3D detection of neuronal somata in mouse whole-brain microscopy images using standard desktop computer hardware. We demonstrate the applicability and power of our approach by mapping the brain-wide locations of large populations of cells labeled with cytoplasmic fluorescent proteins expressed via retrograde trans-synaptic viral infection.

neuroscience↗