TY  - BOOK
AB  - An increasing number of research groups develop
dedicated hybrid analog/digital very large scale integration
(VLSI) devices implementing hundreds of spiking neurons with
bio–physically realistic dynamics.
However, despite the significant progress in their design, there
is still little insight in translating circuitry of neural assemblies
into desired (non-trivial) function.
In this work, we propose to use neural circuits implementing the
soft Winner–Take–All (WTA) function. By showing that recur-
rently connected instances of them can have persistent activity
states, which can be used as a form of working memory, we argue
that such circuits can perform state–dependent computation.
We demonstrate such a network in a distributed neuromorphic
system consisting of two multi–neuron chips implementing soft
WTA, stimulated by an event–based vision sensor. The resulting
network is able to track and remember the position of a localized
stimulus along a trajectory previously encoded in the system.
DA  - 2010
DO  - 10.1109/ISCAS.2010.5537007
LA  - eng
PY  - 2010
SN  - 978-1-4244-5309-2
TI  - State-dependent sensory processing in networks of VLSI spiking neurons
UR  - https://nbn-resolving.org/urn:nbn:de:0070-pub-24277611
Y2  - 2024-11-22T08:27:03
ER  -