Neural Field Model of VSD Optical Imaging Signals

In this report we propose a solution to the direct problem of VSD optical imaging based on a neural field model of a cortical area and reproduce optical signals observed in various mammals cortices. We first present a biophysical approach to neural fields and show that these easily integrate the biological knowledge on cortical structure, especially horizontal and vertical connectivity patterns. After having introduced the reader to VSD optical imaging, we propose a biophysical formula expressing the optical imaging signal in terms of the activity of the field. Then, we simulate optical signals that have been observed by experimentalists. We have chosen two experimental sets: the line-motion illusion in the visual cortex of mammals (jancke, chavane, et al. 2004} and the spread of activity in the rat barrel cortex (petersen, grinvald, et al. 2003). We begin with a structural description of both areas, with a focus on horizontal connectivity. Finally we simulate the corresponding neural field equations and extract the optical signal using the direct problem formula developed in the preceding sections. We have been able to reproduce the main experimental results with these models

Decoding cortical activity evoked by artificial retinal implants

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Processing various motion features and measuring RGCs pairwise correlations with a 2D retinal model

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25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Like a clock in the rabbit's visual cortex

International audienceThree rules govern the connectivity between neurons in the thalamus and inhibitory neurons in the visual cortex of rabbits

Effects of GABAA kinetics on cortical population activity: computational studies and physiological confirmations

International audienceVoltage-sensitive dye (VSD) imaging produces an unprecedented real-time and high-resolution mesoscopic signal to measure the cortical population activity. We have previously shown that the neuronal compartments contributions to the signal are dynamic and stimulus-dependent (Chemla S, Chavane F. Neuroimage 53: 420 – 438, 2010). Moreover, the VSD signal can also be strongly affected by the network state, such as in anesthetized vs. awake preparations. Here, we investigated the impact of the network state, through GABA A receptors modulation, on the VSD signal using a computational approach. We therefore systematically measured the effect of the GABA A-mediated inhibitory post-synaptic potentials (IPSPs) decay time constant (G) on our modeled VSD response to an input stimulus of increasing strength. Our simulations suggest that G strongly modulates the dynamics of the VSD signal, affecting the amplitude, input response function, and the transient balance of excitation and inhibition. We confirmed these predictions experimentally on awake and anesthetized monkeys, comparing VSD responses to drifting gratings stimuli of various contrasts. Lastly, one in vitro study has suggested that GAB

Neural field model to reconcile structure with function in primary visual cortex

International audienceVoltage-sensitive dye imaging experiments in primary visual cortex (V1) have shown that local, oriented visual stimuli elicit stable orientation-selective activation within the stimulus retinotopic footprint. The cortical activation dynamically extends far beyond the retinotopic footprint, but the peripheral spread stays non-selective-a surprising finding given a number of anatomo-functional studies showing the orientation specificity of long-range connections. Here we use a computational model to investigate this apparent discrepancy by studying the expected population response using known published anatomical constraints. The dynamics of input-driven localized states were simulated in a planar neural field model with multiple sub-populations encoding orientation. The realistic connectivity profile has parameters controlling the clustering of long-range connections and their orientation bias. We found substantial overlap between the anatomically relevant parameter range and a steep decay in orientation selective activation that is consistent with the imaging experiments. In this way our study reconciles the reported orientation bias of long-range connections with the functional expression of orientation selective neural activity. Our results demonstrate this sharp decay is contingent on three factors, that long-range connections are sufficiently diffuse, that the orientation bias of these connections is in an intermediate range (consistent with anatomy) and that excitation is sufficiently balanced by inhibition. Conversely, our modelling results predict that, for reduced inhibition strength, spurious orientation selective activation could be generated through long-range lateral connections. Furthermore, if the orientation bias of lateral connections is very strong, or if inhibition is particularly weak, the network operates close to an instability leading to unbounded cortical activation. Author Summary Optical imaging techniques can reveal the dynamical patterns of cortical activation that encode low-level visual features like position and orientation, which are shaped by both feed-forward projections, recurrent and long-range intra-cortical connections. Anatomical studies have characterized intra-cortical connections, however, it is non-trivial to predict from this data how evoked activity might spread across cortex. Indeed, there remains PLOS Computational Biology | https://doi

Rôle fonctionnel des interactions latérales dans l'intégration du mouvement visuel (étude en imagerie optique au niveau du cortex visuel primaire du singe éveillé)

La thématique principale de nos travaux est l'étude de l'intégration du mouvement au niveau de la population du cortex visuel primaire du singe éveillé : de l'identification des circuits corticaux impliqués dans le traitement du mouvement,jusqu'à l'identification et l'émergence d'un signal de mouvement. Nous avons ainsi principalement utilisé deux protocoles (mouvement réel ou apparent).La réponse neuronale de population à l'entrée du système (V1) a été comparée à une réponse comportementale en sortie, la réponse de suivi oculaire réflexe (OFR).L'activité de population dans le cortex visuel primaire est enregistrée par imagerie optique de composés sensible au potentiel.Nous avons alors montré que la réponse au contraste dans V1 est contrôlée par un bassin de normalisation dynamique qui évolue lentement via un recrutement progressif et polysynaptique des circuits récurrents locaux. Ce bassin reçoit des afférents horizontaux liés au contraste qui suppriment graduellement le gain au contraste et à la réponse neuronale.Ensuite, en comparant l'activité de population de V1 avec la réponse de suivi oculaire réflexe avec un stimulus dont l'échelle intermédiaire active à la fois l'entrée et la sortie du système, nous avons identifié deux mécanismes distincts, impliqués dans les interactions contextuelles étudiées : un mécanisme précoce et rapide agissant sur les entrées fortes provenant majoritairement de MT et un mécanisme lent et soutenu plus visible sur les entrées faibles provenant majoritairement de V1.Finalement, en étudiant l'intégration et la représentation du mouvement apparent à la surface de V1, nous avons observé que la dynamique de l'activité corticale générée par des stimuli de mouvement apparent induit une suppression non-linéaire à la surface du cortex qui permet à la population de V1 de ne représenter qu'un seul stimulus à la fois, et ferait donc émerger un signal de mouvement non-ambigu.Pour conclure, nos expériences montrent que les interactions non-linéaires entre et parmi les aires corticales entraînent la normalisation, la modulation et l'émergence de différents signaux de mouvement.Our goal is to study motion integration at population level in V1 in the awake behaving onkey. We compare V1population recorded with optical imaging of voltage sensitive dyes with ocular following response.We have shown that contrast response function in V1 is controlled by a dynamic normalization pool. Then we identified two distinct mechanisms involved in contextual modulations: a fast transient one originating from MT and a show and sustained one, originating from V1. Finally, we have observed that cortical activity dynamics in presponse to apparent motion can induce a suppression wave at acortical surface.AIX-MARSEILLE2-Bib.electronique (130559901) / SudocSudocFranceF

Un modèle biophysique de colonne corticale pour l'analyse du signal d'imagerie optique

L'imagerie optique extrinsèque basée sur l'utilisation de colorants sensibles aux potentiels (VSD) est actuellement la seule technique de neuroimagerie offrant la possibilité d'observer l'activité d'une large population de neurones avec une forte résolution spatiale et temporelle. Dans cette thèse, notre but est d'étudier les origines biologiques du signal d'imagerie optique (signal VSD), étant donné que cette question reste sans réponse claire dans littérature. Identifier l'origine du signal VSD est difficile au niveau physiologique car les molécules de colorant reflètent la dynamique du potentiel de membrane de toutes les membranes du tissu cortical, incluant toutes les couches corticales, tous les types de cellules (excitatrices, inhibitrices, gliales) et tous les compartiments neuronaux (somas, axons, dendrites). Pour répondre à cette question, nous proposons dans cette thèse d'utiliser un modèle biophysique de colonne corticale, à une échelle mésoscopique, prenant en compte les paramètres neuronaux biologiques connus de la structure corticale. Le modèle est basé sur un microcircuit cortical à six populations de neurones interconnectés: une population excitatrice et une population inhibitrice dans chacune des trois principales couches du cortex. Chaque neurone est représenté par une structure morphologique réduite à compartiments avec une dynamique de type Hodgkin-Huxley. Le modèle est alimenté par une activité spontanée, des connexions latérales et une entrée thalamique d'intensité croissante. Les neurones isolés et le comportement en réseau ont été ajustés pour correspondre à des données publiées dans la littérature. Le modèle ainsi ajusté offre ainsi la possibilité de calculer le signal VSD avec une formule linéaire. Nous avons validé le modèle en comparant le signal VSD simulé et le signal VSD mesuré expérimentalement. Grâce à la construction compartimentale de ce modèle, nous confirmons et quantifions le fait que le signal VSD est le résultat d'une moyenne de plusieurs composantes, avec comme contribution majeure, l'activité dendritique des neurones excitateurs des couches superficielles du cortex. Le modèle suggère également que les neurones inhibiteurs, l'activité supraliminaire et les couches profondes participent également au signal, et ce de manière dépendante du temps et de la force de la réponse. Nous arrivons à la conclusion que le signal VSD possède une origine multicomposante dynamique et proposons un nouveau formalisme pour l'interpréter.Voltage-sensitive dye imaging (VSDI) is a powerful modern neuroimaging technique whose application is expanding worldwide because it offers the possibility to monitor the neuronal activation of a large population with high spatial and temporal resolution. In this thesis, we investigate the biological sources of the voltage-sensitive dye signal (VSD signal), since this question remains unresolved in the literature.What does the voltage-sensitive dye imaging signal measures? This question is difficult to resolve at the physiological level as the signal is multi-component: The dye reflects the dynamics of the membrane potential of all membranes in the neuronal tissue, including all layers of the circuitry, all cell types (excitatory, inhibitory, glial) and all neuronal compartments (somas, axons, dendrites). To answer this question, we propose to use a biophysical cortical column model, at a mesoscopic scale, taking into account biological and electrical neural parameters of the laminar cortical structure. The model is based on a cortical microcircuit, whose synaptic connections are made between six specific populations of neurons, excitatory and inhibitory neurons in three main layers. Each neuron is represented by a reduced compartmental description with conductance-based Hodgkin-Huxley neuron model. The model is fed by a thalamic input with increasing activity, background activity and lateral connections. Isolated neurons and network behavior have been adjusted to fit data published in the literature. The so-calibrated model offers the possibility to compute the VSD signal with a linear formula. We validated the model by comparing the simulated and the measured VSD signal.Thanks to the compartmental construction of this model, we confirm and quantify the fact that the VSD signal is the result of an average from multiple components, with excitatory dendritic activity of superficial layers as the main contribution. It also suggests that inhibitory cells, spiking activity and deep layers are contributing differentially to the signal dependently on time and response strength. We conclude that the VSD signal has a dynamic multi-component origin and propose a new framework for interpreting VSD data.NICE-BU Sciences (060882101) / SudocSudocFranceF

Dependence of operating region on thresholds.

<p>Colormaps as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005821#pcbi.1005821.g007" target="_blank">Fig 7A–7C</a> with additional contours. <b>A:</b> Decreasing the threshold for normalized selective area to 0.95 would still give a reasonable operating region. <b>B:</b> Similarly for a marginal increase, to say 87.5%, in the proportion of correction orientation threshold. <b>C:</b> Similarly for an increase in the exponent ratio to, say, <i>n</i>_Sel/<i>n</i>_Act = 1.45.</p