The Role of Thalamic Population Synchrony in the Emergence of Cortical Feature Selectivity

In a wide range of studies, the emergence of orientation selectivity in primary visual cortex has been attributed to a complex interaction between feed-forward thalamic input and inhibitory mechanisms at the level of cortex. Although it is well known that layer 4 cortical neurons are highly sensitive to the timing of thalamic inputs, the role of the stimulus-driven timing of thalamic inputs in cortical orientation selectivity is not well understood. Here we show that the synchronization of thalamic firing contributes directly to the orientation tuned responses of primary visual cortex in a way that optimizes the stimulus information per cortical spike. From the recorded responses of geniculate X-cells in the anesthetized cat, we synthesized thalamic sub-populations that would likely serve as the synaptic input to a common layer 4 cortical neuron based on anatomical constraints. We used this synchronized input as the driving input to an integrate-and-fire model of cortical responses and demonstrated that the tuning properties match closely to those measured in primary visual cortex. By modulating the overall level of synchronization at the preferred orientation, we show that efficiency of information transmission in the cortex is maximized for levels of synchronization which match those reported in thalamic recordings in response to naturalistic stimuli, a property which is relatively invariant to the orientation tuning width. These findings indicate evidence for a more prominent role of the feed-forward thalamic input in cortical feature selectivity based on thalamic synchronization

Correlated Activity and Corticothalamic Cell Function in the Early Mouse Visual System

Vision has long been the model for understanding cortical function. Great progress has been made in understanding the transformations that occur within some primary visual cortex (V1) layers, like the emergence of orientation selectivity in layer 4. Less is known about other V1 circuit elements, like the shaping of V1 input via corticothalamic projections, or the population structure of the cortico-cortical output in layer 2/3. Here, we use the mouse early visual system to investigate the structure and function of circuit elements in V1. We use two approaches: comparative physiology and optogenetics. We measured the structure of pairwise correlations in the output layer 2/3 using extracellular recordings. We find that despite a lack of organization in mouse V1 seen in other species, the specificity of connections preserves a correlation structure on multiple timescales. To investigate the role of corticogeniculate projections, we utilize a transgenic mouse line to specifically and reversibly manipulate these projections with millisecond precision. We find that activity of these cells results a mix of inhibition and excitation in the thalamus, is not spatiotemporally specific, and can affect correlated activity. Finally, we classify mouse thalamic cells according to stimuli used for cell classification in primates and cats, finding some, but not complete, homology to the processing streams of primate thalamus and further highlighting fundamentals of mammalian visual system organization

Linking Visual Development and Learning to Information Processing: Preattentive and Attentive Brain Dynamics

National Science Foundation (SBE-0354378); Office of Naval Research (N00014-95-1-0657

Towards building a more complex view of the lateral geniculate nucleus: Recent advances in understanding its role

The lateral geniculate nucleus (LGN) has often been treated in the past as a linear filter that adds little to retinal processing of visual inputs. Here we review anatomical, neurophysiological, brain imaging, and modeling studies that have in recent years built up a much more complex view of LGN . These include effects related to nonlinear dendritic processing, cortical feedback, synchrony and oscillations across LGN populations, as well as involvement of LGN in higher level cognitive processing. Although recent studies have provided valuable insights into early visual processing including the role of LGN, a unified model of LGN responses to real-world objects has not yet been developed. In the light of recent data, we suggest that the role of LGN deserves more careful consideration in developing models of high-level visual processing

Effects of Adaptation on Discrimination of Whisker Deflection Velocity and Angular Direction in a Model of the Barrel Cortex

Two important stimulus features represented within the rodent barrel cortex are velocity and angular direction of whisker deflection. Each cortical barrel receives information from thalamocortical (TC) cells that relay information from a single whisker, and TC input is decoded by barrel regular-spiking (RS) cells through a feedforward inhibitory architecture (with inhibition delivered by cortical fast-spiking or FS cells). TC cells encode deflection velocity through population synchrony, while deflection direction is encoded through the distribution of spike counts across the TC population. Barrel RS cells encode both deflection direction and velocity with spike rate, and are divided into functional domains by direction preference. Following repetitive whisker stimulation, system adaptation causes a weakening of synaptic inputs to RS cells and diminishes RS cell spike responses, though evidence suggests that stimulus discrimination may improve following adaptation. In this work, I construct a model of the TC, FS, and RS cells comprising a single barrel system the model incorporates realistic synaptic connectivity and dynamics and simulates both angular direction (through the spatial pattern of |C activation) and velocity (through synchrony of the TC population spikes) of a deflection of the primary whisker, and I use the model to examine direction and velocity selectivity of barrel RS cells before and after adaptation. I find that velocity and direction selectivity of individual RS cells (measured over multiple trials) sharpens following adaptation, but stimulus discrimination using a simple linear classifier by the RS population response during a single trial (a more biologically meaningful measure than single cell discrimination over multiple trials) exhibits strikingly different behavior velocity discrimination is similar both before and after adaptation, while direction classification improves substantially following adaptation. This is the first model, to my knowledge, that simulates both whisker deflection velocity and angular direction and examines the ability of the RS population response to pinpoint both stimulus features within the context of adaptation

Neural population coding: combining insights from microscopic and mass signals

Behavior relies on the distributed and coordinated activity of neural populations. Population activity can be measured using multi-neuron recordings and neuroimaging. Neural recordings reveal how the heterogeneity, sparseness, timing, and correlation of population activity shape information processing in local networks, whereas neuroimaging shows how long-range coupling and brain states impact on local activity and perception. To obtain an integrated perspective on neural information processing we need to combine knowledge from both levels of investigation. We review recent progress of how neural recordings, neuroimaging, and computational approaches begin to elucidate how interactions between local neural population activity and large-scale dynamics shape the structure and coding capacity of local information representations, make them state-dependent, and control distributed populations that collectively shape behavior

Investigating the encoding of visual stimuli by forming neural circuits in the cat primary visual cortex

Contexte La connectomique, ou la cartographie des connexions neuronales, est un champ de recherche des neurosciences évoluant rapidement, promettant des avancées majeures en ce qui concerne la compréhension du fonctionnement cérébral. La formation de circuits neuronaux en réponse à des stimuli environnementaux est une propriété émergente du cerveau. Cependant, la connaissance que nous avons de la nature précise de ces réseaux est encore limitée. Au niveau du cortex visuel, qui est l’aire cérébrale la plus étudiée, la manière dont les informations se transmettent de neurone en neurone est une question qui reste encore inexplorée. Cela nous invite à étudier l’émergence des microcircuits en réponse aux stimuli visuels. Autrement dit, comment l’interaction entre un stimulus et une assemblée cellulaire est-elle mise en place et modulée? Méthodes En réponse à la présentation de grilles sinusoïdales en mouvement, des ensembles neuronaux ont été enregistrés dans la couche II/III (aire 17) du cortex visuel primaire de chats anesthésiés, à l’aide de multi-électrodes en tungstène. Des corrélations croisées ont été effectuées entre l’activité de chacun des neurones enregistrés simultanément pour mettre en évidence les liens fonctionnels de quasi-synchronie (fenêtre de ± 5 ms sur les corrélogrammes croisés corrigés). Ces liens fonctionnels dévoilés indiquent des connexions synaptiques putatives entre les neurones. Par la suite, les histogrammes peri-stimulus (PSTH) des neurones ont été comparés afin de mettre en évidence la collaboration synergique temporelle dans les réseaux fonctionnels révélés. Enfin, des spectrogrammes dépendants du taux de décharges entre neurones ou stimulus-dépendants ont été calculés pour observer les oscillations gamma dans les microcircuits émergents. Un indice de corrélation (Rsc) a également été calculé pour les neurones connectés et non connectés. Résultats Les neurones liés fonctionnellement ont une activité accrue durant une période de 50 ms contrairement aux neurones fonctionnellement non connectés. Cela suggère que les connexions entre neurones mènent à une synergie de leur inter-excitabilité. En outre, l’analyse du spectrogramme dépendant du taux de décharge entre neurones révèle que les neurones connectés ont une plus forte activité gamma que les neurones non connectés durant une fenêtre d’opportunité de 50ms. L’activité gamma de basse-fréquence (20-40 Hz) a été associée aux neurones à décharge régulière (RS) et l’activité de haute fréquence (60-80 Hz) aux neurones à décharge rapide (FS). Aussi, les neurones fonctionnellement connectés ont systématiquement un Rsc plus élevé que les neurones non connectés. Finalement, l’analyse des corrélogrammes croisés révèle que dans une assemblée neuronale, le réseau fonctionnel change selon l’orientation de la grille. Nous démontrons ainsi que l’intensité des relations fonctionnelles dépend de l’orientation de la grille sinusoïdale. Cette relation nous a amené à proposer l’hypothèse suivante : outre la sélectivité des neurones aux caractères spécifiques du stimulus, il y a aussi une sélectivité du connectome. En bref, les réseaux fonctionnels «signature » sont activés dans une assemblée qui est strictement associée à l’orientation présentée et plus généralement aux propriétés des stimuli. Conclusion Cette étude souligne le fait que l’assemblée cellulaire, plutôt que le neurone, est l'unité fonctionnelle fondamentale du cerveau. Cela dilue l'importance du travail isolé de chaque neurone, c’est à dire le paradigme classique du taux de décharge qui a été traditionnellement utilisé pour étudier l'encodage des stimuli. Cette étude contribue aussi à faire avancer le débat sur les oscillations gamma, en ce qu'elles surviennent systématiquement entre neurones connectés dans les assemblées, en conséquence d’un ajout de cohérence. Bien que la taille des assemblées enregistrées soit relativement faible, cette étude suggère néanmoins une intrigante spécificité fonctionnelle entre neurones interagissant dans une assemblée en réponse à une stimulation visuelle. Cette étude peut être considérée comme une prémisse à la modélisation informatique à grande échelle de connectomes fonctionnels.Background ‘Connectomics’— the mapping of neural connections, is a rapidly advancing field in neurosciences and it promises significant insights into the brain functioning. The formation of neuronal circuits in response to the sensory environment is an emergent property of the brain; however, the knowledge about the precise nature of these sub-networks is still limited. Even at the level of the visual cortex, which is the most studied area in the brain, how sensory inputs are processed between its neurons, is a question yet to be completely explored. Heuristically, this invites an investigation into the emergence of micro-circuits in response to a visual input — that is, how the intriguing interplay between a stimulus and a cell assembly is engineered and modulated? Methods Neuronal assemblies were recorded in response to randomly presented drifting sine-wave gratings in the layer II/III (area 17) of the primary visual cortex (V1) in anaesthetized cats using tungsten multi-electrodes. Cross-correlograms (CCGs) between simultaneously recorded neural activities were computed to reveal the functional links between neurons that were indicative of putative synaptic connections between them. Further, the peristimulus time histograms (PSTH) of neurons were compared to divulge the epochal synergistic collaboration in the revealed functional networks. Thereafter, perievent spectrograms were computed to observe the gamma oscillations in emergent microcircuits. Noise correlation (Rsc) was calculated for the connected and unconnected neurons within these microcircuits. Results The functionally linked neurons collaborate synergistically with augmented activity in a 50-ms window of opportunity compared with the functionally unconnected neurons suggesting that the connectivity between neurons leads to the added excitability between them. Further, the perievent spectrogram analysis revealed that the connected neurons had an augmented power of gamma activity compared with the unconnected neurons in the emergent 50-ms window of opportunity. The low-band (20-40 Hz) gamma activity was linked to the regular-spiking (RS) neurons, whereas the high-band (60-80 Hz) activity was related to the fast-spiking (FS) neurons. The functionally connected neurons systematically displayed higher Rsc compared with the unconnected neurons in emergent microcircuits. Finally, the CCG analysis revealed that there is an activation of a salient functional network in an assembly in relation to the presented orientation. Closely tuned neurons exhibited more connections than the distantly tuned neurons. Untuned assemblies did not display functional linkage. In short, a ‘signature’ functional network was formed between neurons comprising an assembly that was strictly related to the presented orientation. Conclusion Indeed, this study points to the fact that a cell-assembly is the fundamental functional unit of information processing in the brain, rather than the individual neurons. This dilutes the importance of a neuron working in isolation, that is, the classical firing rate paradigm that has been traditionally used to study the encoding of a stimulus. This study also helps to reconcile the debate on gamma oscillations in that they systematically originate between the connected neurons in assemblies. Though the size of the recorded assemblies in the current investigation was relatively small, nevertheless, this study shows the intriguing functional specificity of interacting neurons in an assembly in response to a visual input. One may form this study as a premise to computationally infer the functional connectomes on a larger scale