TY  - JOUR
A1  - Klos, Christian
A1  - Miner, Daniel
A1  - Triesch, Jochen
T1  - Bridging structure and function : a model of sequence learning and prediction in primary visual cortex
T2  - PLoS Computational Biology
N2  - Recent experiments have demonstrated that visual cortex engages in spatio-temporal sequence learning and prediction. The cellular basis of this learning remains unclear, however. Here we present a spiking neural network model that explains a recent study on sequence learning in the primary visual cortex of rats. The model posits that the sequence learning and prediction abilities of cortical circuits result from the interaction of spike-timing dependent plasticity (STDP) and homeostatic plasticity mechanisms. It also reproduces changes in stimulus-evoked multi-unit activity during learning. Furthermore, it makes precise predictions regarding how training shapes network connectivity to establish its prediction ability. Finally, it predicts that the adapted connectivity gives rise to systematic changes in spontaneous network activity. Taken together, our model establishes a new conceptual bridge between the structure and function of cortical circuits in the context of sequence learning and prediction.
KW  - Neurons
KW  - Neuronal plasticity
KW  - Neural networks
KW  - Learning
KW  - Synaptic plasticity
KW  - Action potentials
KW  - Visual cortex
KW  - Synapses
Y1  - 2018
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/46597
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-465973
SN  - 1553-7358
SN  - 1553-734X
N1  - Copyright: © 2018 Klos et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
VL  - 14
IS  - (6): e1006187
SP  - 1
EP  - 22
PB  - Public Library of Science
CY  - San Francisco, Calif.
ER  -