Codage de l’information visuelle par la plasticité et la synchronisation des réponses neuronales dans le cortex visuel primaire du chat

Les systèmes sensoriels encodent l’information sur notre environnement sous la forme d’impulsions électriques qui se propagent dans des réseaux de neurones. Élucider le code neuronal – les principes par lesquels l’information est représentée dans l’activité des neurones – est une question fondamentale des neurosciences. Cette thèse constituée de 3 études (E) s’intéresse à deux types de codes, la synchronisation et l’adaptation, dans les neurones du cortex visuel primaire (V1) du chat. Au niveau de V1, les neurones sont sélectifs pour des propriétés comme l’orientation des contours, la direction et la vitesse du mouvement. Chaque neurone ayant une combinaison de propriétés pour laquelle sa réponse est maximale, l’information se retrouve distribuée dans différents neurones situés dans diverses colonnes et aires corticales. Un mécanisme potentiel pour relier l’activité de neurones répondant à des items eux-mêmes reliés (e.g. deux contours appartenant au même objet) est la synchronisation de leur activité. Cependant, le type de relations potentiellement encodées par la synchronisation n’est pas entièrement clair (E1). Une autre stratégie de codage consiste en des changements transitoires des propriétés de réponse des neurones en fonction de l’environnement (adaptation). Cette plasticité est présente chez le chat adulte, les neurones de V1 changeant d’orientation préférée après exposition à une orientation non préférée. Cependant, on ignore si des neurones spatialement proches exhibent une plasticité comparable (E2). Finalement, nous avons étudié la dynamique de la relation entre synchronisation et plasticité des propriétés de réponse (E3). Résultats principaux — (E1) Nous avons montré que deux stimuli en mouvement soit convergent soit divergent élicitent plus de synchronisation entre les neurones de V1 que deux stimuli avec la même direction. La fréquence de décharge n’était en revanche pas différente en fonction du type de stimulus. Dans ce cas, la synchronisation semble coder pour la relation de cocircularité dont le mouvement convergent (centripète) et divergent (centrifuge) sont deux cas particuliers, et ainsi pourrait jouer un rôle dans l’intégration des contours. Cela indique que la synchronisation code pour une information qui n’est pas présente dans la fréquence de décharge des neurones. (E2) Après exposition à une orientation non préférée, les neurones changent d’orientation préférée dans la même direction que leurs voisins dans 75% des cas. Plusieurs propriétés de réponse des neurones de V1 dépendent de leur localisation dans la carte fonctionnelle corticale pour l’orientation. Les comportements plus diversifiés des 25% de neurones restants sont le fait de différences fonctionnelles que nous avons observé et qui suggèrent une localisation corticale particulière, les singularités, tandis que la majorité des neurones semblent situés dans les domaines d’iso-orientation. (E3) Après adaptation, les paires de neurones dont les propriétés de réponse deviennent plus similaires montrent une synchronisation accrue. Après récupération, la synchronisation retourne à son niveau initial. Par conséquent, la synchronisation semble refléter de façon dynamique la similarité des propriétés de réponse des neurones. Conclusions — Cette thèse contribue à notre connaissance des capacités d’adaptation de notre système visuel à un environnement changeant. Nous proposons également des données originales liées au rôle potentiel de la synchronisation. En particulier, la synchronisation semble capable de coder des relations entre objets similaires ou dissimilaires, suggérant l’existence d’assemblées neuronales superposées.Sensory systems encode information about our environment into electrical impulses that propagate in networks of neurons. Understanding the neural code – the principles by which information is represented in neuronal activity – is one of the most fundamental issues in neuroscience. This thesis investigates in a series of 3 studies (S) two coding mechanisms, synchrony and adaptation, in neurons of the cat primary visual cortex (V1). In V1, neurons display selectivity for image features such as contour orientation, motion direction and velocity. Each neuron has at least one combination of features that elicits its maximum firing rate. Visual information is thus distributed among numerous neurons within and across cortical columns, modules and areas. Synchronized electrical activity between cells was proposed as a potential mechanism underlying the binding of related features to form coherent perception. However, the precise nature of the relations between image features that may elicit neuronal synchrony remains unclear (S1). In another coding strategy, sensory neurons display transient changes of their response properties following prolonged exposure to an appropriate stimulus (adaptation). In adult cat V1, orientation-selective neurons shift their preferred orientation after being exposed to a non-preferred orientation. How the adaptive behavior of a neuron is related to that of its neighbors remains unclear (S2). Finally, we investigated the relationship between synchrony and orientation tuning in neuron pairs, especially how synchrony is modulated during adaptation-induced plasticity (S3). Main results — (S1) We show that two stimuli in either convergent or divergent motion elicit significantly more synchrony in V1 neuron pairs than two stimuli with the same motion direction. Synchronization seems to encode the relation of cocircularity, of which convergent (centripetal) and divergent (centrifugal) motion are two special instances, and could thus play a role in contour integration. Our results suggest that V1 neuron pairs transmit specific information on distinct image configurations through stimulus-dependent synchrony of their action potentials. (S2) We show that after being adapted to a non-preferred orientation, cells shift their preferred orientation in the same direction as their neighbors in most cases (75%). Several response properties of V1 neurons depend on their location within the cortical orientation map. The differences we found between cell clusters that shift in the same direction and cell clusters with both attractive and repulsive shifts suggest a different cortical location, iso-orientation domains for the former and pinwheel centers for the latter. (S3) We found that after adaptation, neuron pairs that share closer tuning properties display a significant increase of synchronization. Recovery from adaptation is accompanied by a return to the initial synchrony level. Synchrony therefore seems to reflect the similarity in neurons’ response properties, and varies accordingly when these properties change. Conclusions — This thesis further advances our understanding of how visual neurons adapt to a changing environment, especially regarding cortical network dynamics. We also propose novel data about the potential role of synchrony. Especially, synchrony appears capable of binding various features, whether similar or dissimilar, suggesting superimposed neural assemblies

Synchrony between orientation-selective neurons is modulated during adaptation-induced plasticity in cat visual cortex

<p>Abstract</p> <p>Background</p> <p>Visual neurons respond essentially to luminance variations occurring within their receptive fields. In primary visual cortex, each neuron is a filter for stimulus features such as orientation, motion direction and velocity, with the appropriate combination of features eliciting maximal firing rate. Temporal correlation of spike trains was proposed as a potential code for linking the neuronal responses evoked by various features of a same object. In the present study, synchrony strength was measured between cells following an adaptation protocol (prolonged exposure to a non-preferred stimulus) which induce plasticity of neurons' orientation preference.</p> <p>Results</p> <p>Multi-unit activity from area 17 of anesthetized adult cats was recorded. Single cells were sorted out and (1) orientation tuning curves were measured before and following 12 min adaptation and 60 min after adaptation (2) pairwise synchrony was measured by an index that was normalized in relation to the cells' firing rate. We first observed that the prolonged presentation of a non-preferred stimulus produces attractive (58%) and repulsive (42%) shifts of cell's tuning curves. It follows that the adaptation-induced plasticity leads to changes in preferred orientation difference, i.e. increase or decrease in tuning properties between neurons. We report here that, after adaptation, the neuron pairs that shared closer tuning properties display a significant increase of synchronization. Recovery from adaptation was accompanied by a return to the initial synchrony level.</p> <p>Conclusion</p> <p>We conclude that synchrony reflects the similarity in neurons' response properties, and varies accordingly when these properties change.</p

Visual Cells Remember Earlier Applied Target: Plasticity of Orientation Selectivity

BACKGROUND: A canonical proposition states that, in mature brain, neurons responsive to sensory stimuli are tuned to specific properties installed shortly after birth. It is amply demonstrated that that neurons in adult visual cortex of cats are orientation-selective that is they respond with the highest firing rates to preferred oriented stimuli. METHODOLOGY/PRINCIPAL FINDINGS: In anesthetized cats, prepared in a conventional fashion for single cell recordings, the present investigation shows that presenting a stimulus uninterruptedly at a non-preferred orientation for twelve minutes induces changes in orientation preference. Across all conditions orientation tuning curves were investigated using a trial by trial method. Contrary to what has been previously reported with shorter adaptation duration, twelve minutes of adaptation induces mostly attractive shifts, i.e. toward the adapter. After a recovery period allowing neurons to restore their original orientation tuning curves, we carried out a second adaptation which produced three major results: (1) more frequent attractive shifts, (2) an increase of their magnitude, and (3) an additional enhancement of responses at the new or acquired preferred orientation. Additionally, we also show that the direction of shifts depends on the duration of the adaptation: shorter adaptation in most cases produces repulsive shifts, whereas adaptation exceeding nine minutes results in attractive shifts, in the same unit. Consequently, shifts in preferred orientation depend on the duration of adaptation. CONCLUSION/SIGNIFICANCE: The supplementary response improvements indicate that neurons in area 17 keep a memory trace of the previous stimulus properties, thereby upgrading cellular performance. It also highlights the dynamic nature of basic neuronal properties in adult cortex since repeated adaptations modified both the orientation tuning selectivity and the response strength to the preferred orientation. These enhanced neuronal responses suggest that the range of neuronal plasticity available to the visual system is broader than anticipated

Conveying facial expressions to blind and visually impaired persons through a wearable vibrotactile device

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Typical example of shift in orientation preference and response modulations.

<p>A: The first 12 min adaptation displaces the preferred orientation of the cell by 15.5° toward the adapting stimulus. The head arrow indicates the non-preferred adapting stimulus. Following a recovery period of 60 min, the cell recovered its control preferred orientation at 9.0°. Adaptation II produces an identical attractive shift of 15.1°. B, C and D: Histograms shows the response modulations at the control preferred orientation, the new preferred orientation after adaptations and the baseline level (θ = 90°), respectively. At the control preferred orientation, the mean firing rate of cell decrease after adaptation I (<i>t</i>-test, p<0.001) and returned to control level in 60 min. In parallel, the mean firing rate increase by 27% at the new preferred orientation (<i>t</i>-test, p<0.0001). Following recovery, the firing rate further increases: 48% in comparison to adaptation I (<i>t</i>-test, p<0.0001). Baseline level remains unchanged across conditions. E and F: Peri-stimulus time histograms (PSTH) are illustrated for the neuron responding to orientations in C and D, respectively. Blue curves; control condition, red curves; adaptation I, black curves; adaptation II.</p

Adaptation-induced plasticity of orientation tuning in a population of 69 neurons.

<p>A: Scatter plot showing the amplitude of shifts in preferred orientation after adaptation as a function of the absolute difference between the control preferred orientation and the adapting orientation. Black dots represent shifts orientation preference following adaptation I and gray dots following adaptation II. Positive values designate attractive shifts and negative values designate repulsive shifts. The majority of cells 80% (55/69) displayed significant shifts in orientation preference. Dashed lines represent the significance level. Adaptation I induced mostly significant attractive shifts 74% (41/55) and 26% of significant repulsive shifts (14/55). Overall, the mean attractive shift is 15.7°±1.8°, while the average repulsive shifts is 15.6°±2.9° (red dots; errors bars are SEM). Adaptation II induced more attractive shifts 84% (46/55) than repulsive ones 16% (11/55). The magnitude of the attractive shifts significantly increased to 19.5°±1.3° (Mann Whitney test p<0.01) whereas the mean repulsive shits slightly diminished to 13.6°±2.0° (amber dots; errors bars are SEM). B: Neurons displaying significant (<i>t</i>-test, p<0.05) and non-significant (<i>t</i>-test, p>0.05) changes in orientation preference are compared regardless of shifts direction (shifts pooled). The mean shift amplitude of orientation is 15.4°+/−1.3° whereas non-significant shifts average 2.6°+/−0.4°. Insert: The jitter in preferred orientations is unchanged following adaptation, prior to adaptation: 2.2°+/−0.02°; following adaptation: 2.4°+/−0.02° I (errors bars are SEM). The histograms suggest that the peak orientation is almost invariant.</p

(A) Schematic example of raw tuning curves showing the data points (broken lines) for which the synchrony was measured

In this example the preferred orientation difference is 22.5°. CCHs were computed for the initial preferred orientation of each cell and for the adapting orientation. (B) Example of cross-correlation histogram (CCH) where cells had identical preferred orientation (0°). Synchrony index (SI) measured at 0 time lag, SI value was 0.041. Confidence intervals at 99.9% levels are indicated by green lines. (C) Example of CCH where the preferred orientation difference is 45°. In that case, the SI is lower (0.027). (D) Example of CCH where the difference extends to 90° (rare in our sample). The height of the central peak is clearly not significant being below the upper confidence interval, and the SI value was 0.004. Orientation differences from curves fits measurements was 4.0°, 40.0° and 84.1° in B, C and D, respectively. Pairs comprising neurons with distinct preferred orientations (e.g. in C and D) produced 2 CCHs, only one is shown for sake of clarity.<p><b>Copyright information:</b></p><p>Taken from "Synchrony between orientation-selective neurons is modulated during adaptation-induced plasticity in cat visual cortex"</p><p>http://www.biomedcentral.com/1471-2202/9/60</p><p>BMC Neuroscience 2008;9():60-60.</p><p>Published online 3 Jul 2008</p><p>PMCID:PMC2481260.</p><p></p