Biology subjects

Ego-Stengel, V.

Publications and source records attributed to Ego-Stengel, V..

5 recordsLinked to original sources

bioRxiv2026

Specific targeting of layer 4 for direct cortical stimulation is not necessary to induce reliable perception

The primary somatosensory cortex (S1) processes tactile inputs through microcircuits involving connections between and within layers. In particular, layer 4 is the main first cortical target of tactile inputs. However, the need for the initial activation of layer 4 neurons in order to generate a tactile percept has not been studied yet. Here, we investigated whether optogenetic activation of layer 4 neurons first is necessary to induce perception, or whether stimulation of neurons in other layers may suffice. To achieve this, we generated mouse profiles expressing a light-sensitive opsin in excitatory neurons in different combinations of cortical layers, including or excluding layer 4. We generated these profiles by combining transgenic mouse lines and peripheral injections of PHP.eB adeno-associated viruses. After providing proof-of-concept for neuronal optogenetic control in vivo with PHP.eB viruses, we trained mice in a task involving the discrimination of moving optogenetic stimuli projected onto the whisker S1 area, thanks to patterned photostimulation. Mice learned to track the position of a light bar in order to obtain rewards. Direct activation of layer 4 was sufficient for the mice to learn the task, but not necessary. Indeed, activation of all layers but layer 4 induced learning. Moreover, the simultaneous direct activation of all layers accelerated learning. These findings contribute to a better understanding of the cortical mechanisms underlying somatosensory perception. They could also help to optimize artificial sensory stimuli to provide efficient feedback in cortical neuroprostheses.

neuroscience↗

bioRxiv2025

Cortical control of a forelimb prosthesis in mice

Robotic upper-limb prostheses aim to restore the autonomy of paralyzed patients and amputees. So far, advances in this field have relied on monkey pre-clinical and human clinical research. Here, we report on the direct brain control by mice of a miniature mouse forelimb prosthesis. We show that mice implanted with a cortical, microelectrode-based brain-machine interface can learn to control the prosthesis via neuronal operant conditioning, and solve a water collection task in a 2-dimensional and up to a 3-dimensional space. As they learned this task, the mice shaped increasingly consistent prosthesis movements that led to rewards, thanks to coordinated patterns of neuronal activity across the several control dimensions. Beyond the demonstration of unexpected cognitive and motor control abilities in mice, we anticipate that this preclinical model of upper-limb prosthesis control will be a tool to address several of the most pressing issues in prosthetics controlled by brain-machine interfaces.

neuroscience↗

bioRxiv2024

Operant conditioning of cortical waves through a brain-machine interface

At the surface of the cerebral cortex, the dynamics of brain activity at the mesoscopic scale are characterized by waves of synchronized neuronal activity. These waves have been shown to impact the processing of sensory information, but can they be actively shaped by the subject in a goal directed manner? To address this question, we designed a fast widefield optical brain-machine interface for mice that can detect and reinforce individual traveling waves, which follow a specific displacement at the surface of the somatosensory cortex. Trained mice learned to generate these Conditioned Waves, which became progressively more stereotyped. The Conditioned Waves resulted from a reshaping of the cortical activity associated with limb movements, which included a sharp pre-movement cortical suppression that emerged with learning. Our work demonstrates that traveling cortical waves of neuronal activity can be subject to operant control. It provides evidence for the plasticity and functional relevance of large-scale cortical dynamics, and establishes a new paradigm for manipulating mesoscale brain activity.

neuroscience↗

bioRxiv2021

Continuity within somatosensory cortical map shapes the integration of optogenetic input

The topographic organization of sensory cortices is a prominent feature, but its functional role remains unclear. Particularly, how activity is integrated within a cortical area depending on its topography is unknown. Here, we trained mice expressing channelrhodopsin in cortical excitatory neurons to track a bar photostimulation that rotated smoothly over the primary somatosensory cortex (S1). When photostimulation was aimed at vS1, the area which contains a contiguous representation of the whisker array at the periphery, mice could learn to discriminate angular positions of the bar to obtain a reward. In contrast, they could not learn the task when the photostimulation was aimed at the representation of the trunk and legs in S1, where neighboring zones represent distant peripheral body parts, introducing discontinuities. Mice demonstrated anticipation of reward availability, specifically when cortical topography enabled to predict future sensory activation. These results are particularly helpful for designing efficient cortical sensory neuroprostheses. TeaserOptogenetic stimulation sweeping the cortical surface: A way to provide precise sensory information and guide behaviour.

neuroscience↗

bioRxiv2019

Sensorimotor neuronal learning requires cortical topography

Neuroprosthetics offer great hope for motor-impaired patients. One obstacle is that fine motor control requires near-instantaneous, rich somatosensory feedback. Such distributed feedback may be recreated in a brain-machine interface using distributed artificial stimulation across the cortical surface. Here, we hypothesized that neuronal stimulation must be contiguous in its spatiotemporal dynamics in order to be efficiently integrated by sensorimotor circuits. Using a closed-loop brain-machine interface, we trained head-fixed mice to control a virtual cursor by modulating the activity of motor cortex neurons. We provided artificial feedback in real time with distributed optogenetic stimulation patterns in the primary somatosensory cortex. Mice developed a specific motor strategy and succeeded to learn the task only when the optogenetic feedback pattern was spatially and temporally contiguous while it moved across the topography of the somatosensory cortex. These results reveal new properties of sensorimotor cortical integration and set new constraints on the design of neuroprosthetics. TeaserTargeting a brain-machine interface feedback to a cortical map reveals unexpected constraints.

neuroscience↗