year | 2020 |
author(s) | Jakob Jordan, Mihai A. Petrovici, Walter Senn, João Sacramento |
title | Conductance-based dendrites perform reliability-weighted opinion pooling |
KIP-Nummer | HD-KIP 20-18 |
KIP-Gruppe(n) | F9 |
document type | Paper |
Keywords (shown) | synaptic plasticity, conductance-based coupling, Bayesian cue combination, neural networks, multisensory integration |
source | NAISYS 2020, NICE 2020 |
doi | https://doi.org/10.1145/3381755.3381767 |
Abstract (en) | Cue integration, the combination of different sources of information to reduce uncertainty, is a fundamental computational principle of brain function. Starting from a normative model we show that the dynamics of multi-compartment neurons with conductance-based dendrites naturally implement the required probabilistic compu- tations. The associated error-driven plasticity rule allows neurons to learn the relative reliability of different pathways from data samples, approximating Bayes-optimal observers in multisensory integration tasks. Additionally, the model provides a functional interpretation of neural recordings from multisensory integration experiments and makes specific predictions for membrane potential and conductance dynamics of individual neurons. |
bibtex | @inproceedings{Jordan2020Conductance, author = {Jordan, Jakob and Petrovici, Mihai A. and Senn, Walter and Sacramento, Jo\~{a}o}, title = {Conductance-Based Dendrites Perform Reliability-Weighted Opinion Pooling}, booktitle = {Proceedings of the Neuro-Inspired Computational Elements Workshop}, year = {2020}, volume = {}, number = {11}, series = {NICE }, pages = {3}, address = {New York, NY, USA}, month = {3}, publisher = {Association for Computing Machinery}, note = {ISBN: 9781450377188} } |
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