Synthesis of a Liquid State Machine with Hopfield/Brody Transient
Synchrony
Abstract:
Understanding the mechanism of spatiotemporal integration used by our brain to
perform recognition of complex temporal sequences is a challenge for current
researchers in neuroscience. Recent research has proposed transient synchrony
as a plausible mechanism for spatiotemporal integration. This thesis studies
a biologically plausible network architecture made of simulated minicolumns
that performs a temporal integration task, specifically spoken-word
recognition. The network's ability to recognize a spoken word and its natural
variants is independent of variations across speakers, simple masking noises
and variations in system parameters. The network demonstrates inter columnar
and intra columnar synchrony, which in turn leads to word recognition. The
intra columnar synchrony of minicolumns acts as an event detection mechanism
for events in a particular frequency band. The inter columnar transient
synchrony enables the network to recognize words. Each of the minicolumns
exhibit a very unique temporal signature when presented with a temporal
input. These signatures looked nearly the same for similar inputs (e.g., the
same word spoken by different speakers etc.) and were strikingly different
for different temporal inputs (e.g., different words).
Reference: P. Joshi.
Synthesis of a liquid state machine with hopfield/brody transient synchrony.
Master's thesis, Center for Advanced Computer Studies, University of
Louisiana, Lafayette, USA, November 2002.