Biology subjects

Gozel, O.

Publications and source records attributed to Gozel, O..

5 recordsLinked to original sources

bioRxiv2026

Convergence of Cortical and Thalamic Origins of Free Behavior Modulation of Mouse Primary Visual Cortex

The quality of sensory information flow in the brain may be affected by uninstructed free animal behavior. However, the specific circuit pathways that merge sensory and free behavior remain obscure. In mouse primary visual cortex (V1), we combine two-photon calcium imaging of cortical neurons and thalamo-cortical LGN (lateral geniculate nucleus) boutons with simultaneous measurements of facial movements. When controlling for spurious time-structured nonsense correlations, we observed representations of both eye movements and non-ocular facial movement features in both LGN bouton and V1 cortical neuron activity during grating input stimulation. Further, the correlation between V1 neurons and facial movement is larger for grating stimulation compared to blank stimulation, likely due to the integration of LGN inputs and modulation of V1 from higher brain centers during grating stimulation. Together, our results suggest a convergence of uninstructed non-visual signals from a persistent top-down pathway and a stimulus-gated bottom-up pathway in primary visual cortex.

neuroscience↗

bioRxiv2025

Circuit-Based Understanding of Fine Spatial Scale Clustering of Orientation Tuning in Mouse Visual Cortex

In sensory cortex of brain it is often the case that neurons are spatially organized by their functional properties. A hallmark of primary visual cortex (V1) in higher mammals is a columnar functional map, where neurons tuned to different stimuli features are regularly organized in space. However, rodent visual cortex is at odds with this rule and lacks any spatially ordered functional architecture, and rather neuron feature preference is haphazardly organized in patterns termed salt-and-pepper. This sharp contrast in feature organization between the visual cortices of rodents and higher mammals has been a persistent mystery, fueled in part by abundant evidence of conserved cortical physiology between species. In this work, we applied a novel GCaMP indicator that are localized in the nucleus of neurons during two-photon imaging in mouse V1, which enabled us to overcome most spurious spatially correlated activity due to fluorescence contamination, and to ensure a faithful observation of functional organization over space. We found that the orientation tuning properties of distant neuron pairs (> 20 {micro}m) are irregularly and randomly organized, while neuron pairs that are extremely close (< 20 {micro}m) have strongly correlated orientation tuning, indicating a narrow yet strong spatially clustered organization of orientation preference, which we term micro-clustered organization. Exploring a circuit-based model of recurrently coupled mouse V1 we derived two key predictions for the micro-cluster: spatially localized recurrent connections over a comparable narrow spatial scale, and common relative spatial spreads of balanced excitation and inhibition in the network over broad spatial scales. These predictions are validated by both anatomical and optogenetic-based physiological circuit mapping experiments. Altogether, our work takes an important step in building a circuit-based theory of visual processing in mouse V1 over spatial scales that are often ignored, yet contain powerful synaptic interactions.

neuroscience↗

bioRxiv2022

Between-area communication through the lens of within-area neuronal dynamics

A core problem in systems and circuits neuroscience is deciphering the origin of shared dynamics in neuronal activity: do they emerge through local network interactions, or are they inherited from external sources? We explore this question with large-scale networks of spatially ordered spiking neuron models where a downstream network receives input from an upstream sender network. We show that linear measures of the communication between the sender and receiver networks can discriminate between emergent or inherited population dynamics. Faithful communication requires a match in the dimensionality of the sender and receiver population activities, along with an alignment of their shared fluctuations. However, a nonlinear mapping between the sender - receiver activity or downstream emergent population-wide fluctuations can impair linear communication. Our work exposes the benefits and limitations of linear measures when analyzing between-area communication in circuits with rich population-wide neuronal dynamics.

neuroscience↗

bioRxiv2021

An Oscillatory Mechanism for Multi-level Storage in Short-term Memory

Oscillatory activity is commonly observed during the maintenance of information in short-term memory, but its role remains unclear. Non-oscillatory models of short-term memory storage are able to encode stimulus identity through their spatial patterns of activity, but are typically limited to either an all-or-none representation of stimulus amplitude or exhibit a biologically implausible exact-tuning condition. Here, we demonstrate a simple phase-locking mechanism by which oscillatory input enables a circuit to generate persistent or sequential activity patterns that encode information not only in their location but also in their discretely graded amplitudes. SignificanceA core observation in many memory systems and tasks is the presence of oscillations during memory maintenance. Here, we demonstrate a mechanism for the accumulation and storage of information in short-term memory in which oscillatory activity enables a solution to long-standing challenges in modeling the persistent neural activity underlying working memory. These challenges include the ability to encode information with low firing rates, multi-level storage of stimulus amplitude without extreme fine tuning, and multi-level storage of information in sequential activity. Altogether, this work proposes a new class of models for the storage of information in working memory, a new potential role for brain oscillations, and a novel dynamical mechanism for multi-stability.

neuroscience↗

bioRxiv2019

Adult dentate gyrus neurogenesis: A functional model

In adult dentate gyrus neurogenesis, the link between maturation of newborn neurons and their function, such as behavioral pattern separation, has remained puzzling. By analyzing a theoretical model, we show that the switch from excitation to inhibition of the GABAergic input onto maturing newborn cells is crucial for their proper functional integration. When the GABAergic input is excitatory, cooperativity drives the growth of synapses such that newborn cells become sensitive to stimuli similar to those that activate mature cells. When GABAergic input switches to inhibitory, competition pushes the configuration of synapses onto newborn cells towards stimuli that are different from previously stored ones. This enables the maturing newborn cells to code for concepts that are novel, yet similar to familiar ones. Our theory of newborn cell maturation explains both how adult-born dentate granule cells integrate into the preexisting network and why they promote separation of similar but not distinct patterns.

neuroscience↗