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

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.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 la 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 echelle 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

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

Le jeu de l'asthme et la BPCO (construction et évaluation d'un outil pédagogique à l'attention de l'équipe officinale)

PARIS-BIUP (751062107) / 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

Biophysical cortical column model for optical signal analysis

International audienceWe propose a biological cortical column model, at a some mesoscopic scale, in order to better understand and start to interpret biological sources of voltagesensitive dye imaging signal. The mesoscopic scale, corresponding to a micro-column, is about 50 ,m. Simulations are done thanks to the NEURON and NEURONCONSTRUCT software. This model suggests that the OI signal is the result of an average from multiple components whose proportion changes with levels of activity and shows surprisingly that inhibitory cells, spiking activity and deep layers may well participate more to the signal than initially though

Cortical propagating waves: amplifying and suppressive?

International audienceIn this commentary, we would like to revisit a recent publication by Davis et al. (2020) showing that propagating waves in cerebral cortex could serve to boost the response to visual stimuli and gate perception. It seems therefore interesting to us to relate these observations to the suppressive traveling waves previously observed in the awake monkey (Chemla et al., 2019). We would like to overview these two results, clarifying that they are compatible and suggest that they may represent different facets of the same phenomenon. Consistent with this, we propose that the mechanism of suppressive waves (also called “suppression mechanism” thereafter) modulates the response to visual stimuli and, ultimately, their detection

Revealing α oscillatory activity using voltage-sensitive dye imaging in monkey V1

The relevance of α oscillations (7-12Hz) in neural processing, although recognized long ago, remains a major research question in the field. While intensively studied in humans, α oscillations appear much less often investigated (and observed) in monkeys. Here we wish to provide data from non-human primates on stimulus-related α rhythm. Indeed, in humans, EEG α is enhanced in response to non-periodic dynamic visual stimulation (“perceptual echoes” or to a static stimulus (“flickering wheel illusion”). Do the same visual patterns induce an oscillatory response in monkey V1? We record voltage-sensitive dye signals from three anesthetized monkeys to investigate the population-based oscillatory neural response that is not resulting from attention-related feedback signals. We revealed α oscillations in monkey V1 which, when they occur, react in a manner comparable to human studies

Anticipatory responses along motion trajectories in awake monkey area V1

What are the neural mechanisms underlying motion integration of translating objects? Visual motion integration is generally conceived of as a feedforward, hierarchical, information processing. However, feedforward models fail to account for many contextual effects revealed using natural moving stimuli. In particular, a translating object evokes a sequence of transient feedforward responses in the primary visual cortex but also propagations of activity through horizontal and feedback pathways. We investigated how these pathways shape the representation of a translating bar in monkey V1. We show that, for long trajectories, spiking activity builds-up hundreds of milliseconds before the bar enters the neurons’ receptive fields. Using VSDI and LFP recordings guided by a phenomenological model of propagation dynamics, we demonstrate that this anticipatory response arises from the interplay between horizontal and feedback networks driving V1 neurons well ahead of their feedforward inputs. This mechanism could subtend several perceptual contextual effects observed with translating objects