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Topic: Spike-timing dependent plasticity

Seminar
5 seminars
Seminar · Computational Neuroscience

Learning predictive maps in the brain for spatial navigation

William de Cothi · Barry lab, UCL

Wed, Oct 12, 2022 · 17:00 UTC

The predictive map hypothesis provides a promising framework to model representations in the hippocampal formation. I will introduce a tractable implementation of a predictive map called the successor representation (SR), before presenting data showing that rats and humans display SR-like navigational choices on a novel open-field maze. Next, I will show how such a predictive map could be implemented using spatial representations found in the hippocampal formation, before finally presenting how such learning might be well approximated by phenomena that exist in the spatial memory system - name

Seminar · Computational Neuroscience

Optimization at the Single Neuron Level:​ Prediction of Spike Sequences and Emergence of Synaptic Plasticity Mechanisms

Matteo Saponati · Ernst-Strüngmann Institute for Neuroscience

Wed, May 4, 2022 · 15:00 UTC

Intelligent behavior depends on the brain’s ability to anticipate future events. However, the learning rules that enable neurons to predict and fire ahead of sensory inputs remain largely unknown. We propose a plasticity rule based on pre-dictive processing, where the neuron learns a low-rank model of the synaptic input dynamics in its membrane potential. Neurons thereby amplify those synapses that maximally predict other synaptic inputs based on their temporal relations, which provide a solution to an optimization problem that can be implemented at the single-neuron level using only local inf

Seminar · Computational Neuroscience

The generation of cortical novelty responses through inhibitory plasticity

Nicholas Gale · University of Cambridge, DAMTP

Wed, Nov 3, 2021 · 16:00 UTC

Animals depend on fast and reliable detection of novel stimuli in their environment. Neurons in multiple sensory areas respond more strongly to novel in comparison to familiar stimuli. Yet, it remains unclear which circuit, cellular, and synaptic mechanisms underlie those responses. Here, we show that spike-timing-dependent plasticity of inhibitory-to-excitatory synapses generates novelty responses in a recurrent spiking network model. Inhibitory plasticity increases the inhibition onto excitatory neurons tuned to familiar stimuli, while inhibition for novel stimuli remains low, leading to a n

Seminar · Electrophysiology

Error correction and reliability timescale in converging cortical networks

Eran Stark · Tel Aviv University

Thu, Apr 29, 2021 · 15:00 UTC

Rapidly changing inputs such as visual scenes and auditory landscapes are transmitted over several synaptic interfaces and perceived with little loss of detail, but individual neurons are typically “noisy” and cortico-cortical connections are typically “weak”. To understand how information embodied in spike train is transmitted in a lossless manner, we focus on a single synaptic interface: between pyramidal cells and putative interneurons. Using arbitrary white noise patterns injected intra-cortically as photocurrents to freely-moving mice, we find that directly-activated cells exhibit precisi

Seminar · Computational Neuroscience

Distinct synaptic plasticity mechanisms determine the diversity of cortical responses during behavior

Michele Insanally · University of Pittsburgh School of Medicine

Fri, Jan 15, 2021 · 15:00 UTC

Spike trains recorded from the cortex of behaving animals can be complex, highly variable from trial to trial, and therefore challenging to interpret. A fraction of cells exhibit trial-averaged responses with obvious task-related features such as pure tone frequency tuning in auditory cortex. However, a substantial number of cells (including cells in primary sensory cortex) do not appear to fire in a task-related manner and are often neglected from analysis. We recently used a novel single-trial, spike-timing-based analysis to show that both classically responsive and non-classically responsiv

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