RT Journal Article
SR Electronic
T1 Self-organization of Computation in Neural Systems
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 016725
DO 10.1101/016725
A1 Christian Tetzlaff
A1 Sakyasingha Dasgupta
A1 Tomas Kulvicius
A1 Florentin Wörgötter
YR 2015
UL http://biorxiv.org/content/early/2015/03/19/016725.abstract
AB When learning a complex task our nervous system self-organizes large groups of neurons into coherent dynamic activity patterns. During this, a cell assembly network with multiple, simultaneously active, and computationally powerful assemblies is formed; a process which is so far not understood. Here we show that the com- bination of synaptic plasticity with the slower process of synaptic scaling achieves formation of such assembly networks. This type of self-organization allows executing a difficult, six degrees of freedom, manipulation task with a robot where assemblies need to learn computing complex non-linear transforms and – for execution – must cooperate with each other without interference. This mechanism, thus, permits for the first time the guided self-organization of computationally powerful sub-structures in dynamic networks for behavior control.