Caractérisation des traitements sensoriels dans le cortex à tonneaux du rat anesthésié.

The processing of whisker deflections by rodents barrel cortex neurons is still poorly understood. Indeed, to date, the support provided by the strict mapping of the spatial arrangement of the peripheral sensory apparatus onto the cortical surface has not been sufficient to settle on a reasonable model of whisker processing. In particular, at the moment, the linear and non-linear filtering of whisker stimulations carried in this cortical area are unclear. In order to tackle this problem, we developed a multiwhisker stimulator that allows the independent deflection of 24 whiskers, in any direction, over a wide frequency band. By combining this whisker stimulation device with electrophysiological recordings carried in the barrel cortex of anaesthetized rats, we could identify a family of linear filters common to all recorded neurons. In addition, we explored the non-linear responses of these neurons to spatio-temporal combinations of whisker deflections, and we observed two types of neuronal responses. In one side, "local" neurons responded to salient whisker deflections occurring on a single whisker and that contrasted with other whisker deflections. On the other side, "global" neurons were sensitive to the overall level of similarity between the deflections applied across stimulated whiskers. Finally, we studied the functional response of the neurons found in the layer II/III of this cortex with the help of a two-photon microscope. Using this tool, we found that local and global neuron types were strongly spatially segregated. More generally, we observed a strict mapping of the functional tuning of barrel cortex neurons onto the surface of the rat barrel cortex.Chez les rongeurs, le traitement par le cortex à tonneaux de l'information sensorielle en provenance des vibrisses est mal compris. En effet, malgré l'aide fournie par l'organisation de ce cortex en une reproduction stricte de la topographie de l'appareil sensoriel, il a été difficile jusqu'à présent d'identifier de façon indiscutable le système de filtrage linéaire et non-linéaire qu'utilisent les neurones du cortex à tonneaux durant leur traitement des scènes tactiles auxquelles ils sont exposés. Pour mieux identifier ces traitements corticaux, nous avons développé un système de stimulation vibrissale permettant d'appliquer des déflections sur un grand nombre de vibrisses indépendamment, dans toutes les directions possibles et ce à travers une vaste gamme fréquentielle. En utilisant ce dispositif de stimulation multivibrissale durant des enregistrements extracellulaires de l'activité électrique des neurones du cortex à tonneaux de rats anesthésiés, nous avons pu identifier plus précisément le filtrage linéaire des stimulations vibrissales, qui s'avère similaire pour tous les neurones que nous avons pu enregistrer. Par ailleurs, en explorant les aspects non-linéaires du traitement effectué par ces neurones, nous avons noté qu'ils se séparent en deux familles distinctes : d'un côté des neurones "locaux" qui se sont avérés sensibles à des contrastes locaux dans les déflections multivibrissales. De l'autre, des neurones "globaux" capables au contraire de détecter des situations où les déflections sont similaires pour de nombreuses vibrisses. Enfin, en effectuant d'autres enregistrements dans la couche II/III du cortex à tonneaux, cette fois à l'aide d'un microscope deux-photons, nous avons pu noter que les neurones appartenant aux familles locales et globales étaient séparés en groupes spatialement distincts et que la position spatiale des neurones était plus généralement étroitement liée à l'ensemble de leurs propriétés de filtrage des déflections vibrissales

Rich spatio-temporal stimulus dynamics unveil sensory specialization in cortical area S2.

International audienceTactile perception in rodents depends on simultaneous, multi-whisker contacts with objects. Although it is known that neurons in secondary somatosensory cortex (wS2) respond to individual deflections of many whiskers, wS2's precise function remains unknown. The convergence of information from multiple whiskers into wS2 neurons suggests that they are good candidates for integrating multi-whisker information. Here, we apply stimulation patterns with rich dynamics simultaneously to 24 macro-vibrissae of rats while recording large populations of single neurons. Varying inter-whisker correlations without changing single whisker statistics, we observe pronounced supra-linear multi-whisker integration. Using novel analysis methods, we show that continuous multi-whisker movements contribute to the firing of wS2 neurons over long temporal windows, facilitating spatio-temporal integration. In contrast, primary cortex (wS1) neurons encode fine features of whisker movements on precise temporal scales. These results provide the first description of wS2's representation during multi-whisker stimulation and outline its specialized role in parallel to wS1 tactile processing

Parvalbumin-Expressing GABAergic Neurons in Primary Motor Cortex Signal Reaching

International audienceThe control of targeted reaching is thought to be shaped by distinct subtypes of local GABAergic inhibitory neurons in primary forelimb motor cortex (M1). However, little is known about their action potential firing dynamics during reaching. To address this, we recorded the activity of parvalbumin-expressing (PV+) GABAergic neurons identified from a larger population of fast-spiking units and putative excitatory regular-spiking units in layer 5 of the mouse forelimb M1 during an M1-dependent, sensory-triggered reaching task. PV+ neurons showed short latency responses to the acoustic cue and vibrotactile trigger stimulus and an increase in firing at reaching onset that scaled with the amplitude of reaching. Unexpectedly, PV+ neurons fired before regular-spiking units at reach onset and showed high overall firing rates during both sensory-triggered and spontaneous reaches. Our data suggest that increasing M1 PV+ neuron firing rates may play a role in the initiation of voluntary reaching

Supra-barrel Distribution of Directional Tuning for Global Motion in the Mouse Somatosensory Cortex

Summary: Rodents explore their environment with an array of whiskers, inducing complex patterns of whisker deflections. Cortical neuronal networks can extract global properties of tactile scenes. In the primary somatosensory cortex, the information relative to the global direction of a spatiotemporal sequence of whisker deflections can be extracted at the single neuron level. To further understand how the cortical network integrates multi-whisker inputs, we imaged and recorded the mouse barrel cortex activity evoked by sequences of multi-whisker deflections generating global motions in different directions. A majority of barrel-related cortical columns show a direction preference for global motions with an overall preference for caudo-ventral directions. Responses to global motions being highly sublinear, the identity of the first deflected whiskers is highly salient but does not seem to determine the global direction preference. Our results further demonstrate that the global direction preference is spatially organized throughout the barrel cortex at a supra-columnar scale. : Using voltage-sensitive dye imaging of the mouse barrel cortex, Vilarchao et al. demonstrate the presence of direction selectivity to global motion generated by multi-whisker stimuli. Selectivity to global motion is spatially organized at the supra-columnar scale with an overrepresentation of selectivity to caudo-ventral directions. Keywords: tactile sensory processing, multivibrissal stimulation, primary somatosensory cortex, barrel cortex, voltage-sensitive dye imaging, mouse, extracellular electrophysiological recording

Representation of Tactile Scenes in the Rodent Barrel Cortex

International audienceAfter half a century of research, the sensory features coded by neurons of the rodent barrel cortex remain poorly understood. Still, views of the sensory representation of whisker information are increasingly shifting from a labeled line representation of single-whisker deflections to a selectivity for specific elements of the complex statistics of the multi-whisker deflection patterns that take place during spontaneous rodent behavior - so called natural tactile scenes. Here we review the current knowledge regarding the coding of patterns of whisker stimuli by barrel cortex neurons, from responses to single-whisker deflections to the representation of complex tactile scenes. A number of multi-whisker tunings have already been identified, including center-surround feature extraction, angular tuning during edge-like multi-whisker deflections, and even tuning to specific statistical properties of the tactile scene such as the level of correlation across whiskers. However, a more general model of the representation of multi-whisker information in the barrel cortex is still missing. This is in part because of the lack of a human intuition regarding the perception emerging from a whisker system, but also because in contrast to other primary sensory cortices such as the visual cortex, the spatial feature selectivity of barrel cortex neurons rests on highly nonlinear interactions that remained hidden to classical receptive field approaches

Ce que les vibrisses disent au cerveau tactile

Le système des vibrisses des rongeurs est devenu un des modèles principaux pour l’étude des propriétés fonctionnelles des neurones sensoriels. Ceci est dû, d’une part, à la structure très bien connue des voies afférentes qui relient les mécanorécepteurs à la base des vibrisses au cortex somatosensoriel primaire et, d’autre part, à l’accessibilité des senseurs tactiles permettant de contrôler l’entrée sensorielle à l’échelle du micron et de la milliseconde. L’observation de l’utilisation des vibrisses par le rongeur indique que les contacts avec des objets et des textures se font avec des dizaines de vibrisses simultanément. Nous avons exploré le codage neuronal dans le cortex à tonneaux, le cortex qui reçoit les informations depuis les vibrisses. En combinant enregistrements multi-électrodes et stimulation tactile multivibrissales avec une analyse théorique, nous avons mis en évidence que plusieurs types de réponses neuronales, semblables à celles décrites dans des aires différentes du système visuel, coexistent dans le même volume cortical. Ceci indique que des schémas de codage variés peuvent être implémentés dans le même réseau cortical et seraient mis en jeu pour analyser au mieux les stimulations tactiles diverses et changeantes auxquelles sont confrontés les rongeurs dans leur environnement naturel

Neo: a Data Model for Electrophysiological Data Representation and its Python Implementation

International audienceNeo is a hierarchical data model for the representation of intracellular and extracellular electrophysiology data with support for multi-electrodes (for example tetrodes) and EEG data.The Neo project distributes an implementation of this model with a set of input/output (IO) modules for various file formats, as an open-source, multi-platform Python package under a BSD license. It is available at http://pypi.python.org/pypi/neo.The objective of Neo is to facilitate the cooperation between independent software projects working on simulation, modeling, representation and analysis of electrophysiological signals in electroencephalography or intracellular and extracellular electrophysiology.For this, Neo provides a common representation of the core data in order to improve the reusability of the developed tools and share data between different projects. It also provides a common layer for datafile and database reading and writing through its IO modules

Neo: a Data Model for Electrophysiological Data Representation and its Python Implementation

International audienceNeo is a hierarchical data model for the representation of intracellular and extracellular electrophysiology data with support for multi-electrodes (for example tetrodes) and EEG data.The Neo project distributes an implementation of this model with a set of input/output (IO) modules for various file formats, as an open-source, multi-platform Python package under a BSD license. It is available at http://pypi.python.org/pypi/neo.The objective of Neo is to facilitate the cooperation between independent software projects working on simulation, modeling, representation and analysis of electrophysiological signals in electroencephalography or intracellular and extracellular electrophysiology.For this, Neo provides a common representation of the core data in order to improve the reusability of the developed tools and share data between different projects. It also provides a common layer for datafile and database reading and writing through its IO modules

A radial map of multi-whisker correlation selectivity in the rat barrel cortex

International audienceIn the barrel cortex, several features of single-whisker stimuli are organized in functionalmaps. The barrel cortex also encodes spatio-temporal correlation patterns of multi-whiskerinputs, but so far the cortical mapping of neurons tuned to such input statistics is unknown.Here we report that layer 2/3 of the rat barrel cortex contains an additional functional mapbased on neuronal tuning to correlated versus uncorrelated multi-whisker stimuli: neuronresponses to uncorrelated multi-whisker stimulation are strongest above barrel centres,whereas neuron responses to correlated and anti-correlated multi-whisker stimulation peakabove the barrel–septal borders, forming rings of multi-whisker synchrony-preferring cells