High noise correlation between the functionally connected neurons in emergent V1 microcircuits

Abstract : Neural correlations (noise correlations and cross-correlograms) are widely studied to infer functional connectivity between neurons. High noise correlations (Rsc) between neurons have been reported to increase the encoding accuracy of a neuronal population; however, low noise correlations have also been documented to play a critical role in cortical microcircuits. Therefore, the role of noise correlations in neural encoding is highly debated. To this aim, through multi-electrodes, we recorded neuronal ensembles in the primary visual cortex of anesthetized cats. By computing cross-correlograms (CCGs), we divulged the functional network (microcircuit) between neurons within an ensemble in relation to a specific orientation. We show that functionally connected neurons systematically exhibit higher noise correlations than functionally unconnected neurons in a microcircuit that is activated in response to a particular orientation. Furthermore, the mean strength of noise correlations for the connected neurons increases steeply than the unconnected neurons as a function of the resolution-window used to calculate noise correlations. We suggest that, neurons that display high noise correlations in emergent microcircuits feature functional connections which are inevitable for information encoding in the primary visual cortex

Summation of connectivity strengths in the visual cortex reveals stability of neuronal microcircuits after plasticity

Abstract : Background: Within sensory systems, neurons are continuously affected by environmental stimulation. Recently, we showed that, on cell-pair basis, visual adaptation modulates the connectivity strength between similarly tuned neurons to orientation and we suggested that, on a larger scale, the connectivity strength between neurons forming sub-networks could be maintained after adaptation-induced-plasticity. In the present paper, based on the summation of the connectivity strengths, we sought to examine how, within cell-assemblies, functional connectivity is regulated during an exposure-based adaptation. Results: Using intrinsic optical imaging combined with electrophysiological recordings following the reconfiguration of the maps of the primary visual cortex by long stimulus exposure, we found that within functionally connected cells, the summed connectivity strengths remain almost equal although connections among individual pairs are modified. Neuronal selectivity appears to be strongly associated with neuronal connectivity in a “homeodynamic” manner which maintains the stability of cortical functional relationships after experience-dependent plasticity. Conclusions: Our results support the “homeostatic plasticity concept” giving new perspectives on how the summation in visual cortex leads to the stability within labile neuronal ensembles, depending on the newly acquired properties by neurons

Synergistic activity between primary visual neurons

Abstract : Cortical microcircuitry plays a pivotal role in encoding sensory information reaching the cortex. However, the fundamental knowledge concerning the mechanisms that govern feature-encoding by these sub-networks is still sparse. Here, we show through multi electrode recordings in V1 of conventionally prepared anesthetized cats, that an avalanche of synergistic neural activity occurs between functionally connected neurons in a cell assembly in response to the presented stimulus. The results specifically show that once the reference neuron spikes in a connected neuron-pair, it facilitates the response of its companion (target) neuron for 50 ms and, thereafter, the excitability of the target neuron declines. On the other hand, the functionally unconnected neurons do not facilitate each other’s activity within the 50 ms time-window. The added excitation (facilitation) of connected neurons is almost four times the responsiveness of unconnected neurons. This suggests that connectedness confers the added excitability to neurons; consequently leading to feature-encoding within the emergent 50 ms-period. Furthermore, the facilitation significantly decreases as a function of orientation selectivity spread

Comparative effects of adaptation on layer II-III and layer V-VI neurons in cat V1

Abstract: V1 is fundamentally grouped into columns that descend from layers II–III to V–VI. Neurons inherent to visual cortex are capable of adapting to changes in the incoming stimuli that drive the cortical plasticity. A principle feature called orientation selectivity can be altered by the presentation of non‐optimal stimulus called ‘adapter’. When triggered, LGN cells impinge upon layer IV and further relay the information to deeper layers via layers II–III. Using different adaptation protocols, neuronal plasticity can be investigated. Superficial neurons in area V1 are well acknowledged to exhibit attraction and repulsion by shifting their tuning peaks when challenged by a non‐optimal stimulus called ‘adapter’. Layers V–VI neurons in spite of partnering layers II–III neurons in cortical computation have not been explored simultaneously toward adaptation. We believe that adaptation not only affects cells specific to a layer but modifies the entire column. In this study, through simultaneous multiunit recordings in anesthetized cats using a multichannel depth electrode, we show for the first time how layers V–VI neurons (1000–1200 μm) along with layers II–III neurons (300–500 μm) exhibit plasticity in response to adaptation. Our results demonstrate that superficial and deeper layer neurons react synonymously toward adapter by exhibiting similar behavioral properties. The neurons displayed similar amplitude of shift and maintained equivalent sharpness of Gaussian tuning peaks before and the following adaptation. It appears that a similar mechanism, belonging to all layers, is responsible for the analog outcome of the neurons’ experience with adapter

Modulation of functional connectivity following visual adaptation: homeostasis in V1

Abstract: Sensory neurons exhibit remarkable adaptability in acquiring new optimal selectivity to unfamiliar features when a new stimulus becomes prevalent in the environment. In conventionally prepared adult anesthetized cats, we used visual adaptation to change the preferred orientation selectivity in V1 neurons. Cortical circuits are dominated by complex and intricate connections between neurons. Cross-correlation of cellular spike-trains discloses the putative functional connection between two neurons. We sought to investigate changes in these links following a twelve minute uninterrupted application of a specific, usually non-preferred, orientation. We report that visual adaptation, mimicking training, modulates the magnitude of cross-correlograms suggesting that the strength of inter-neuronal relationships is modified. While individual cell-pairs exhibit changes in their response correlation strength, the average correlation of the recorded cell cluster remains unchanged. Hence, visual adaptation induces plastic changes that impact the connectivity between neurons

Network-selectivity and stimulus-discrimination in the primary visual cortex : cell-assembly dynamics

Abstract : Visual neurons coordinate their responses in relation to the stimulus; however, the complex interplay between a stimulus and the functional dynamics of an assembly still eludes neuroscientists. To this aim, we recorded cell assemblies from multi-electrodes in the primary visual cortex of anaesthetized cats in response to randomly presented sine-wave drifting gratings whose orientation tilted in 22.5° steps. Cross-correlograms divulged the functional connections at all the tested orientations. We show that a cell-assembly discriminates between orientations by recruiting a ‘salient’ functional network at every presented orientation, wherein, the connections and their strengths (peak-probabilities in the cross-correlogram) change from one orientation to another. Within these assemblies, closely tuned neurons exhibited increased connectivity and connection-strengths than differently tuned neurons. Minimal connectivity between untuned neurons suggests the significance of neuronal selectivity in assemblies. This study reflects upon the dynamics of functional connectivity, and brings to the fore the importance of a ‘signature’ functional network in an assembly that is strictly related to a specific stimulus. Apparently, it points to the fact that an assembly is the major ‘functional unit’ of information processing in cortical circuits, rather than the individual neurons

Reprogramming of orientation columns in visual cortex : a domino effect

Abstract : Cortical organization rests upon the fundamental principle that neurons sharing similar properties are co-located. In the visual cortex, neurons are organized into orientation columns. In a column, most neurons respond optimally to the same axis of an oriented edge, that is, the preferred orientation. This orientation selectivity is believed to be absolute in adulthood. However, in a fully mature brain, it has been established that neurons change their selectivity following sensory experience or visual adaptation. Here, we show that after applying an adapter away from the tested cells, neurons whose receptive fields were located remotely from the adapted site also exhibit a novel selectivity in spite of the fact that they were not adapted. These results indicate a robust reconfiguration and remapping of the orientation domains with respect to each other thus removing the possibility of an orientation hole in the new hypercolumn. These data suggest that orientation columns transcend anatomy, and are almost strictly functionally dynamic

Plasticité du cortex visuel: «homéodynamie» des connexions neuronales et modèle d’effets d’antidépresseurs

Les informations sensorielles sont traitées dans le cortex par des réseaux de neurones co-activés qui forment des assemblées neuronales fonctionnelles. Le traitement visuel dans le cortex est régit par différents aspects des caractéristiques neuronales tels que l’aspect anatomique, électrophysiologique et moléculaire. Au sein du cortex visuel primaire, les neurones sont sélectifs à divers attributs des stimuli tels que l’orientation, la direction, le mouvement et la fréquence spatiale. Chacun de ces attributs conduit à une activité de décharge maximale pour une population neuronale spécifique. Les neurones du cortex visuel ont cependant la capacité de changer leur sélectivité en réponse à une exposition prolongée d’un stimulus approprié appelée apprentissage visuel ou adaptation visuelle à un stimulus non préférentiel. De ce fait, l’objectif principal de cette thèse est d’investiguer les mécanismes neuronaux qui régissent le traitement visuel durant une plasticité induite par adaptation chez des animaux adultes. Ces mécanismes sont traités sous différents aspects : la connectivité neuronale, la sélectivité neuronale, les propriétés électrophysiologiques des neurones et les effets des drogues (sérotonine et fluoxétine). Le modèle testé se base sur les colonnes d’orientation du cortex visuel primaire. La présente thèse est subdivisée en quatre principaux chapitres. Le premier chapitre (A) traite de la réorganisation du cortex visuel primaire suite à une plasticité induite par adaptation visuelle. Le second chapitre (B) examine la connectivité neuronale fonctionnelle en se basant sur des corrélations croisées entre paires neuronales ainsi que sur des corrélations d’activités de populations neuronales. Le troisième chapitre (C) met en liaison les aspects cités précédemment (les effets de l’adaptation visuelle et la connectivité fonctionnelle) aux propriétés électrophysiologiques des neurones (deux classes de neurones sont traitées : les neurones à décharge régulière et les neurones à décharge rapide ou burst). Enfin, le dernier chapitre (D) a pour objectif l’étude de l’effet du couplage de l’adaptation visuelle à l’administration de certaines drogues, notamment la sérotonine et la fluoxétine (inhibiteur sélectif de recapture de la sérotonine). Méthodes En utilisant des enregistrements extracellulaires d’activités neuronales dans le cortex visuel primaire (V1) combinés à un processus d’imagerie cérébrale optique intrinsèque, nous enregistrons l’activité de décharge de populations neuronales et nous examinons l’activité de neurones individuels extraite des signaux multi-unitaires. L’analyse de l’activité cérébrale se base sur différents algorithmes : la distinction des propriétés électrophysiologiques des neurones se fait par calcul de l’intervalle de temps entre la vallée et le pic maximal du potentiel d’action (largeur du potentiel d’action), la sélectivité des neurones est basée sur leur taux de décharge à différents stimuli, et la connectivité fonctionnelle utilise des calculs de corrélations croisées. L’utilisation des drogues se fait par administration locale sur la surface du cortex (après une craniotomie et une durotomie). Résultats et conclusions Dans le premier chapitre, nous démontrons la capacité des neurones à modifier leur sélectivité après une période d’adaptation visuelle à un stimulus particulier, ces changements aboutissent à une réorganisation des cartes corticales suivant un patron spécifique. Nous attribuons ce résultat à la flexibilité de groupes fonctionnels de neurones qui étaient longtemps considérés comme des unités anatomiques rigides. En effet, nous observons une restructuration extensive des domaines d’orientation dans le but de remodeler les colonnes d’orientation où chaque stimulus est représenté de façon égale. Ceci est d’autant plus confirmé dans le second chapitre où dans ce cas, les cartes de connectivité fonctionnelle sont investiguées. En accord avec les résultats énumérés précédemment, les cartes de connectivité montrent également une restructuration massive mais de façon intéressante, les neurones utilisent une stratégie de sommation afin de stabiliser leurs poids de connectivité totaux. Ces dynamiques de connectivité sont examinées dans le troisième chapitre en relation avec les propriétés électrophysiologiques des neurones. En effet, deux modes de décharge neuronale permettent la distinction entre deux classes neuronales. Leurs dynamiques de corrélations distinctes suggèrent que ces deux classes jouent des rôles clés différents dans l’encodage et l’intégration des stimuli visuels au sein d’une population neuronale. Enfin, dans le dernier chapitre, l’adaptation visuelle est combinée avec l’administration de certaines substances, notamment la sérotonine (neurotransmetteur) et la fluoxétine (inhibiteur sélectif de recapture de la sérotonine). Ces deux substances produisent un effet similaire en facilitant l’acquisition des stimuli imposés par adaptation. Lorsqu’un stimulus non optimal est présenté en présence de l’une des deux substances, nous observons une augmentation du taux de décharge des neurones en présentant ce stimulus. Nous présentons un modèle neuronal basé sur cette recherche afin d’expliquer les fluctuations du taux de décharge neuronale en présence ou en absence des drogues. Cette thèse présente de nouvelles perspectives quant à la compréhension de l’adaptation des neurones du cortex visuel primaire adulte dans le but de changer leur sélectivité dans un environnement d’apprentissage. Nous montrons qu’il y a un parfait équilibre entre leurs habiletés plastiques et leur dynamique d’homéostasie.Sensory informations are computed in the cortex by networks of co-activated neurons forming functional ensembles. Visual processing in the cortex underlies several aspects of neuronal characteristics such as anatomical, electrophysiological and molecular. In the primary visual cortex, neurons display selectivity for stimulus features such as orientation, motion direction and spatial frequency. Each stimulus property elicits a maximal firing rate of specific neuronal populations. Visual neurons display transient modifications of their response properties following prolonged exposure to an appropriate stimulus using visual learning or visual adaptation to a non-preferred stimulus. The main objective of this thesis is to investigate the neuronal mechanisms underlying the visual processing during adaptation-induced plasticity in adult animals. These mechanisms are examined through different aspects: the neuronal connectivity, the neuronal selectivity, the electrical properties of neurons, and the effects of drugs (serotonin and fluoxetine). The tested model is the orientation columns of the primary visual cortex. The present thesis is divided into four main chapters. The first chapter (A) focuses on the cortical reorganization following visual adaptation. The second chapter (B) examines the neuronal connectivity using pair-wise correlations and populational correlations of neuronal activities. The third chapter (C) further relate the previous aspects, i.e. the adaptation effects and the functional connectivity to the properties of neurons (two classes: regular-spiking and fast-spiking neurons). Finally, the fourth chapter (D) investigates the coupling of visual adaptation with the local administration of drugs (serotonin and fluoxetine). Methodology Using in vivo extracellular recordings of the neural activity in the primary visual cortex (V1) combined with intrinsic optical brain imaging, we record the spiking activity of neuronal populations and examine, from the multi-unit activity, the activity of individual neurons. The analysis of brain activity uses different algorithms: the electrophysiological distinctions between neurons are based on the trough-to-peak time of each spike (spike-width), the selectivity of neurons is based on the firing rate at different stimuli, and the functional connectivity uses a crosscorrelation computation. The usage of drugs is performed locally on the visual cortex (after craniotomy and removing of the dura). Results and conclusions In the first chapter, we demonstrate the ability of neurons to modify their selectivity to the presented stimuli following visual adaptation, exhibiting a well-organized reprogramming of the orientation columns; we attribute this result to a flexibility of functional units rather than rigid anatomical structures. Indeed, we observe an extensive restructuring of the complete orientation domain in order to refine the columnar organization where every stimulus is equally represented. This is further confirmed in the second chapter where in this case, the connectivity maps are investigated. In concordance with the previous results, the connectivity maps also exhibit restructuring but interestingly, neurons use a summative strategy to stabilize their total connectivity weights. These connectivity dynamics are examined in the third chapter in relation to electrophysiological properties of neurons. Indeed, two differently firing modes dissociate between two classes of neurons. Their distinct correlation dynamics point to the fact that they play different key roles in stimulus encoding within a neuronal population. Finally, in the last chapter, visual adaptation is coupled with the administration of serotonin and fluoxetine. Both drugs produce similar effects by facilitating the acquisition of the imposed stimulus. The non-preferred stimulus when adapted with the presence of the drug results in an increased firing rate of neurons at this particular stimulus. We present a neuronal model based on our findings to explain the fluctuations of firing with and without the drug. This thesis provides new insights into how visual neurons adapt to change their selectivity in the interplay between their plastic ability and their homeostatic dynamic

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