|
|
|
Data
|
Computational aspects of feedback in neural circuits (Maass et al 2006)
|
|
|
|
|
|
|
It had previously been shown that generic cortical microcircuit models
can perform complex real-time computations on continuous input
streams, provided that these computations can be carried out with a
rapidly fading memory. We investigate ... the computational
capability of such circuits in the more realistic case where not only
readout neurons, but in addition a few neurons within the circuit have
been trained for specific tasks. This is essentially equivalent to
the case where the output of trained readout neurons is fed back into
the circuit. We show that this new model overcomes the limitation of
a rapidly fading memory. In fact, we prove that in the idealized case
without noise it can carry out any conceiv- able digital or analog
computation on time-varying inputs. But even with noise the resulting
computational model can perform a large class of biologically relevant
real-time computations that require a non-fading memory. ... In
particular we show that ... generic cortical microcircuits with
feedback provide a new model for working memory that is consistent
with a large set of biological constraints. See paper for more and details.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
-
Maass W, Joshi P, Sontag ED (2007) Show
Other
-
Maass W, Joshi P, Sontag ED (2006) Show
Other
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
