ePoster · Computational Neuroscience
Predicting V1 contextual modulation and neural tuning using a convolutional neural network
Cem Uran, Martin Vinck · Bernstein Conference 2024
We propose a novel method to predict contextual modulation of local field potential (LFP) gamma synchronization and multi-unit activity (MUA) in a single framework. Convolutional neural networks are state-of-the-art models of the primary visual cortex (V1). Sensory processing in V1 is determined by contextual modulation via feedback and recurrent connections. However, the computational goal and the neural implementation that shape V1 activity are not yet fully understood. We use transfer learning to use an object recognition convolutional neural network (VGG-16) to predict firing rates and gam