Dear All,
Speaker: Nikola Milićević, Pennsylvania State University
Title: Sensory systems and combinatorial neural codes
Abstract: Neural activity in sensory areas of the brain is shaped both by the stimulus and by the internal neural dynamics. When the stimulus space is known we can compute receptive fields of neurons. Receptive fields of individual neurons are convex
in a number of brain regions (such as the hippocampus, and the visual cortex). The combinatorial neural code are the subsets of co-active neurons for some input to the neural network. Not any combinatorial code is compatible with convex receptive fields. This
raises a natural question: how do recurrent networks produce convex codes? Towards this end, we study a recurrent neural network with the Dale’s law architecture.
We describe the combinatorics of equilibria and steady states of neurons in threshold-linear networks that satisfy Dale's law. The combinatorial code of a Dale network is characterized in terms of two conditions: (i) a condition on the network connectivity
graph, and (ii) a spectral condition on the synaptic matrix. In the weak synaptic coupling regime, the combinatorial code depends only on the connectivity graph, and not on the synaptic strengths. Moreover, we prove that the combinatorial code of a weakly
coupled network is a sublattice, and we provide a learning rule for encoding a sublattice in a weakly coupled excitatory network. Surprisingly, we find that the architecture of a Dale network “enforces” convex code output, in both strong and weak coupling
regimes. Finally, we introduce a method inspired by game theory for inferring receptive fields, when the stimulus space is unknown or at least no consensus has been reached as in the case of olfactory systems.
Time: 17:00, Wednesday, 22 May, 2024.
Location: CEU Budapest (1051 Budapest, Nádor u. 15.) N13. room 118*.
*Anyone not affiliated with CEU wishing to attend in-person must RSVP to
vargai@ceu.edu get access to the lecture hall.
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Mihály Bányai.
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Best regards,