Does computational neuroscience need new synaptic learning paradigms?
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Humans and animals learn by modifying the synaptic strength between neurons, a phenomenon known as synaptic plasticity. These changes can be induced by rather short stimuli (lasting, for instance, only a few seconds), yet, in order to be useful for long-te ...
We derive a plausible learning rule updating the synaptic efficacies for feedforward, feedback and lateral connections between observed and latent neurons. Operating in the context of a generative model for distributions of spike sequences, the learning me ...
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The focus of the current research projects in my laboratory revolves around the question of metabolic plasticity of neuron-glia coupling. Our hypothesis is that behavioural conditions, such as for example learning or the sleep-wake cycle, in which synaptic ...
How learning and memory is achieved in the brain is a central question in neuroscience. Key to today’s research into information storage in the brain is the concept of synaptic plasticity, a notion that has been heavily influenced by Hebb’s (1949) postulat ...
Perceptual learning is the ability to modify perception through practice. As a form of brain plasticity, perceptual learning has been studied for more than thirty years in different fields including psychology, neurophysiology and computational neuroscienc ...
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Spike Timing Dependent Plasticity (STDP) is a temporally asymmetric form of Hebbian learning induced by tight temporal correlations between the spikes of pre- and postsynaptic neurons. As with other forms of synaptic plasticity, it is widely believed that ...
Given the complex structure of the brain, how can synaptic plasticity explain the learning and forgetting of associations when these are continuously changing? We address this question by studying different reinforcement learning rules in a multilayer netw ...
Changes of synaptic connections between neurons are thought to be the physiological basis of learning. These changes can be gated by neuromodulators that encode the presence of reward. We study a family of reward-modulated synaptic learning rules for spiki ...