Session: D. Computation and cognition: from neural processing to psychology
Will talk about: Emergence of subnetworks in plastic recurrent networks
Claudia Clopath is a Lecturer in the Bioengineering Department at Imperial College London, and head of the Computational Neuroscience Laboratory. After having studied Physics at the EPFL, she did her PhD in Wulfram Gerstner's lab, a first postdoc with Nicolas Brunel, and a second postdoctoral research fellowship in the Center for Theoretical Neuroscience at Columbia University. Dr. Clopath is broadly interested in the field of neuroscience, especially insofar as it addresses the questions of learning and memory. She uses mathematical and computational tools to model synaptic plasticity and to study its functional implication in artificial neural networks.
In primary visual cortex, excitatory neurons with similar orientation preference have a high probability of being bidirectionally connected (Ko et al. Nature 2011). However, the refinement of intracortical connectivity only happens after eye-opening (Ko et al. Nature 2013). We recently hypothesized, using a computational model of Hebbian learning, that this process is a result of experienced-dependent plasticity (Clopath et al. 2010, Ko et al. Nature 2013). In contrast to excitatory neurons, parvalbumin-expressing (PV) inhibitory cells are less specific: Hofer et al. (Hofer et al. Nat. Neur. 2011, Bock et al. Nature 2011) showed that PV neurons receive excitatory inputs from neurons with different orientation preferences. We investigated the mechanism by which excitatory to inhibitory connections are formed (how) and their potential function (why) in a small recurrent network.