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/2015/03/18/016725.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 combination 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.