Topic: multielectrode arrays

A central goal of vision science is to understand the principles underlying the perception and neural coding of the complex visual environment of our everyday experience. In the visual cortex, foundational work with artificial stimuli, and more recent work combining natural images and deep convolutional neural networks, have revealed much about the tuning of cortical neurons to specific image features. However, a major limitation of this existing work is its focus on single-neuron response strength to isolated images. First, during natural vision, the inputs to cortical neurons are not isolate

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