Biology subjects

Bonin, V.

Publications and source records attributed to Bonin, V..

5 recordsLinked to original sources

bioRxiv2018

Segregated encoding of spatiotemporal features in the mouse visual cortex

Visual processing and behavior depend on specialized neural representations and information channels that encode distinct visual information and enable distinct computations. Our understanding of the neural substrate, however, remain severely limited by sparse recordings and the restricted range of visual areas and visual stimuli considered. We characterized in the mouse the multidimensional spatiotemporal tuning properties of > 30,000 layer 2/3 pyramidal neurons across seven areas of the cortex. The dataset reveals population specialized for processing of oriented and non-oriented contrast, spatiotemporal frequency, and motion speed. Areal analysis reveals profound functional diversity and specificity as well as highly specific representations of visual processing channels in distinct visual areas. Clustering analysis shows a branching of visual representations along the posterior to anterior axis, and between lateral and dorsal areas. Overall, this dataset provides a cellular-resolution atlas for understanding organizing principles underlying sensory representations across the cortex. SummaryVisual representations and visual channels are the cornerstones of mammalian visual processing and critical for a range of life sustaining behaviors. However, the lack of data sets spanning multiple visual areas preclude unambiguous identification of visual processing streams and the sparse, singular recording data sets obtained thus far are insufficient to reveal the functional diversity of visual areas and to study visual information channels. We characterized the tunings of over 30,000 cortical excitatory neurons from 7 visual areas to a broad array of stimuli and studied their responses in terms of their ability to encode orientation, spatiotemporal contrast and visual motion speed. We found all mouse visual cortical areas convey diverse information but show distinct biases in terms of numbers of neurons tuned to particular spatiotemporal features. Neurons in visual areas differ in their spatiotemporal tuning but also in their relative response to oriented and unoriented contrast. We uncovered a population that preferentially responds to unoriented contrast and shows only weak responses to oriented stimuli. This population is strongly overrepresented in certain areas (V1, LM and LI) and underrepresented in others (AL, RL, AM, and PM). Spatiotemporal tunings are broadly distributed in all visual areas indicating that all areas have access to broad spatiotemporal information. However, individual areas show specific biases. While V1 is heavily biased in favor of low spatial and temporal frequencies, area LM responds more strongly to mid-range frequencies. Areas PM and LI are biased in favor of slowly-varying high-resolution signals. By comparison, anterior areas AL, RL and AM are heavily biased in favor of fast-varying, low to mid spatial frequency signals. Critically, theses biases express themselves in vastly different number of cells tuned to particular features, suggesting differential sampling of visual processing channels across areas. Comparing across areas, we found divergent visual representations between anterior and posterior areas, and between lateral and dorsal areas, suggesting the segregated organization of cortical streams for distinct information processing.

neuroscience↗

bioRxiv2018

Characterizing the nonlinear structure of shared variability in cortical neuron populations using neural networks

Sensory neurons often have variable responses to repeated presentations of the same stimulus, which can significantly degrade the information contained in those responses. Such variability is often shared across many neurons, which in principle can allow a decoder to mitigate the effects of such noise, depending on the structure of the shared variability and its relationship to sensory encoding at the population level. Latent variable models offer an approach for characterizing the structure of this shared variability in neural population recordings, although they have thus far typically been used under restrictive mathematical assumptions, such as assuming linear transformations between the latent variables and neural activity. Here we leverage recent advances in machine learning to introduce two nonlinear latent variable models for analyzing large-scale neural recordings. We first present a general nonlinear latent variable model that is agnostic to the stimulus tuning properties of the individual neurons, and is hence well suited for exploring neural populations whose tuning properties are not well characterized. This motivates a second class of model, the Generalized Affine Model, which simultaneously determines each neurons stimulus selectivity and a set of latent variables that modulate these stimulus responses both additively and multiplicatively. While these approaches can detect general nonlinear relationships in shared neural variability, we find that neural activity recorded in anesthetized primary visual cortex (V1) is best described by a single additive and single multiplicative latent variable, i.e., an \"affine model\". In contrast, application of the same models to recordings in awake macaque prefrontal cortex discover more general nonlinearities to compactly describe the population response variability. These results thus demonstrate how nonlinear latent variable models can be used to describe population variability, and suggest that a range of methods is necessary to study different brain regions under different experimental conditions.

neuroscience↗

bioRxiv2018

Behavioral response to visual motion impacts population coding in the mouse visual thalamus

Visual motion is a ubiquitous component of animals sensory experience and its encoding is critical for navigation and movement. Yet its impact on behavior and neural coding is not well understood. Combining pupillometry with cellular calcium imaging measurements of thalamocortical axons in awake behaving mice, we examined the impact of arousal and behavioral state on encoding of visual motion in the visual thalamus. We discovered that back-to-front visual motions elicits a robust behavioral response that shapes tunings of visual thalamic responses. Consistent with an arousal mechanism, the effects were pronounced during stillness and weak or absent during locomotor activity and under anesthesia. The impact on neuronal tuning was specific, biasing population response patterns in favor of back-to-front motion. The potent influence of visual motion on behavioral state dynamically affect sensory coding at early visual processing stages. Further research is required to reveal the circuitry and function of this novel mechanism.

neuroscience↗

bioRxiv2018

Astrocytes integrate local sensory and brain-wide neuromodulatory signals.

Astrocytes play multiple functions in the central nervous system, from control of blood flow through to modulation of synaptic activity. Transient increases in intracellular Ca2+ are thought to control these activities. The prevailing concept is that these Ca2+ transients are triggered by distinct pathways, with little mechanistic and functional overlap. Here we demonstrate that astrocytes in visual cortex of mice encode local visual signals in conjunction with arousal state, functioning as multi-modal integrators. Such activity adds an additional layer of complexity to astrocyte function and may enable astrocytes to specifically and subtly regulate local network activity and plasticity.

neuroscience↗

bioRxiv2017

Encoding of Tactile Context in the Mouse Visual Cortex

Multisensory integration is key for perception and animal survival yet how information from separate senses is integrated has been debated for decades. In the cortex, information from each sense is first processed in primary sensory areas and then combined in association areas. An alternative hypothesis to this hierarchical model is that primary sensory cortices partake in multisensory encoding. We probed tactile and visual responses in primary somatosensory and visual cortices in awake behaving animals using two-photon calcium imaging from layer 2/3 excitatory neurons. In support of an hierarchical model we found segregation of visual and tactile responses. Tactile stimuli evoked responses in S1 neurons. In striking contrast, V1 neurons failed to respond to tactile stimuli. This was true for passive whisker stimulation and for stimulation during active whisking. Furthermore, responses of V1 neurons to congruent visuo-tactile cues during active exploration, a condition where vision precedes touch, were completely abolished in darkness. The rostro-lateral area of the visual cortex responded to both visual and tactile aspects of the stimuli and may form a substrate for encoding multisensory signals during active exploration. Our results indicate that primary sensory areas mainly encode their primary sense and that the impact of other modalities may be restricted to modulatory effects.

neuroscience↗