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Topic: precision

Seminar
3 seminars

In Neuroscience and Computational Neuroscience

Seminar · Computational Neuroscience

Trading Off Performance and Energy in Spiking Networks

Sander Keemink · Donders Institute for Brain, Cognition and Behaviour

Wed, Jun 1, 2022 · 15:30 UTC

Many engineered and biological systems must trade off performance and energy use, and the brain is no exception. While there are theories on how activity levels are controlled in biological networks through feedback control (homeostasis), it is not clear what the effects on population coding are, and therefore how performance and energy can be traded off. In this talk we will consider this tradeoff in auto-encoding networks, in which there is a clear definition of performance (the coding loss). We first show how SNNs follow a characteristic trade-off curve between activity levels and coding lo

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 · Neuroscience

Cerebral Cortex Connectomics

Moritz Helmstaedter · Max Planck Institute for Brain Research

Fri, Jul 3, 2020 · 13:00 UTC

Densely mapping neuronal circuits at synaptic resolution is providing unprecedented insight into the formation and structure of the cerebral cortex. I’ll present recent advances and discuss what we can learn about precision, plasticity and possible patterns in mammalian neuronal circuits.