| Computational aspects of feedback in neural circuits (Maass et al 2006) |
| Accession: 82392 |
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.
References:
1. Maass W, Joshi P, Sontag ED (2007) Computational aspects of feedback in neural circuits. PLoS Comput Biol 3(1):e165 [PubMed]
2. Maass W, Joshi P, Sontag ED (2006) Principles of real-time computing with feedback applied to cortical microcircuit models. Advances in Neural Information Processing Systems |
| Citations Citation Browser
|
Model Information (Click on a link to
find other models with that property)
|
| Search NeuronDB for information about: I Na,t; I K; I M; |
|
|
neural micro circuits
|
|
| |
W. Maass, P. Joshi, and E. D. Sontag, 2006
The package distro_164.tar.gz contains the
software for the simulations for figure 2, 3, 4, and 6 of the
article
- W. Maass, P. Joshi, and E. D. Sontag. Computational aspects of
feedback in neural circuits. submitted for publication, 2005.
Installation
[1]If you have Linux or Windows it should basically suffice to unpack the
tarball files in a directory of your choice and to add this directory to
your Matlab search path. All the software for various experiments
are found in /yourpath/lsm/learning/demos/work_demos directory.
[2]Please don't forget to read the README files in each experiment
directory.
|
| |
 |
|
(C) 2003, Thomas Natschläger
|
last modified 05/15/2006
|
| |
