Orientation tuning

A fundamental property of neurons in the primary visual cortex is their preference for orientation of edges. It was shown that this orientation tuning is mostly invariant under contrast changes [1], a property that is not explained by a simple feed-forward scheme [2, 3]. We designed a synthetic hybrid neural circuit to study the emergence of orientation selectivity under different thalamo-cortical connections. To this end, a computational model of the retino-thalamic pathway was combined with an in-vitro model of cortical input layer 4. The latter was either a primary culture of cortical neur

…of 'salt-and-pepper' organization of orientation tuning preference. A controversy has emerged on whether the organization is truly spatially disorganized, or if there is long-range (~100 μm) or short range (~10 μm) spatial clustering of orientation tuning. We imaged and analyzed the response profile (to orientated gratings) of in vivo populations of layer 2/3 (L2/3) and layer 4 (L4) neurons with a neuropil-free nuclear-targeted GCaMP6s indicator. These datasets provide an un

…that correlated variability depends on orientation tuning. However, it is challenging to interpret this tuning dependence when the spikes are generated from a doubly stochastic Poisson process, which is commonly assumed. In this case, spikes can exhibit tuning-dependent noise correlation, e

Understanding the neural code for vision remains a major challenge for neuroscience, with recent efforts influenced by the success of convolutional neural networks. However, spiking neurons make biological vision fundamentally different from the firing rate model implicit in these artificial neural networks. In region V1 of the primate visual cortex, a flashed image is processed in tens of milliseconds, allowing time for only a few action potentials, typically across a small subset of neurons. Moreover, persistent eye motion (ocular drift) changes the location of retinal responses, and thus

Information processing is energetically expensive. In the mammalian brain, it is unclear how information coding and energy usage are regulated during food scarcity. I addressed this in the visual cortex of awake mice using whole-cell recordings and two-photon imaging to monitor layer 2/3 neuronal activity and ATP usage. I found that food restriction reduced synaptic ATP usage by 29% through a decrease in AMPA receptor conductance. Neuronal excitability was nonetheless preserved by a compensatory increase in input resistance and a depolarized resting membrane potential. Consequently, neurons sp

Information processing is energetically expensive. In the mammalian brain, it is unclear how information coding and energy usage are regulated during food scarcity. We addressed this in the visual cortex of awake mice using whole-cell patch clamp recordings and two-photon imaging to monitor layer 2/3 neuronal activity and ATP usage. We found that food restriction resulted in energy savings through a decrease in AMPA receptor conductance, reducing synaptic ATP usage by 29%. Neuronal excitability was nonetheless preserved by a compensatory increase in input resistance and a depolarized resting m

At any given moment the brain receives more sensory information than it can use to guide adaptive behaviour, creating the need for mechanisms that promote efficient processing of incoming sensory signals. One way in which the brain might reduce its sensory processing load is to encode successive presentations of the same stimulus in a more efficient form, a process known as neural adaptation. Conversely, when a stimulus violates an expected pattern, it should evoke an enhanced neural response. Such a scheme for sensory encoding has been formalised in predictive coding theories, which propose t