Computational Aspects of Feedback in Neural Circuits. Export

@article{maass_07_computational, abstract = {Author SummaryCircuits of neurons in the brain have an abundance of feedback connections, both on the level of local microcircuits and on the level of synaptic connections between brain areas. But the functional role of these feedback connections is largely unknown. We present a computational theory that characterizes the gain in computational power that feedback can provide in such circuits. It shows that feedback endows standard models for neural circuits with the capability to emulate arbitrary Turing machines. In fact, with suitable feedback they can simulate any dynamical system, in particular any conceivable analog computer. Under realistic noise conditions, the computational power of these circuits is necessarily reduced. But we demonstrate through computer simulations that feedback also provides a significant gain in computational power for quite detailed models of cortical microcircuits with in vivo–like high levels of noise. In particular it enables generic cortical microcircuits to carry out computations that combine information from working memory and persistent internal states in real time with new information from online input streams.}, author = {Maass, Wolfgang and Joshi, Prashant and Sontag, Eduardo D. D.}, citeulike-article-id = {1074063}, citeulike-linkout-0 = {http://dx.doi.org/10.1371/journal.pcbi.0020165}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/17238280}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=17238280}, citeulike-linkout-3 = {http://dx.doi.org/http://dx.doi.org/10.1371/journal.pcbi.0020165}, citeulike-linkout-4 = {http://dx.doi.org/10.1371/journal.pcbi.0020165}, day = {19}, doi = {10.1371/journal.pcbi.0020165}, issn = {1553-7358}, journal = {PLoS Computational Biology}, keywords = {chaos, coding, dynamics, information}, month = {January}, number = {1}, pages = {e165+}, pdf = {maass\_07\_computational.pdf}, posted-at = {2007-01-29 09:54:50}, priority = {2}, publisher = {Public Library of Science}, title = {Computational Aspects of Feedback in Neural Circuits.}, url = {http://dx.doi.org/10.1371/journal.pcbi.0020165}, volume = {3}, year = {2007} }

TY - JOUR ID - maass_07_computational L3 - citeulike-article-id:1074063 N2 - Author SummaryCircuits of neurons in the brain have an abundance of feedback connections, both on the level of local microcircuits and on the level of synaptic connections between brain areas. But the functional role of these feedback connections is largely unknown. We present a computational theory that characterizes the gain in computational power that feedback can provide in such circuits. It shows that feedback endows standard models for neural circuits with the capability to emulate arbitrary Turing machines. In fact, with suitable feedback they can simulate any dynamical system, in particular any conceivable analog computer. Under realistic noise conditions, the computational power of these circuits is necessarily reduced. But we demonstrate through computer simulations that feedback also provides a significant gain in computational power for quite detailed models of cortical microcircuits with in vivo–like high levels of noise. In particular it enables generic cortical microcircuits to carry out computations that combine information from working memory and persistent internal states in real time with new information from online input streams. IS - 1 JF - PLoS Computational Biology SN - 1553-7358 TI - Computational Aspects of Feedback in Neural Circuits. PB - Public Library of Science VL - 3 SP - e165 KW - chaos KW - coding KW - dynamics KW - information AU - Maass, Wolfgang AU - Joshi, Prashant AU - Sontag, Eduardo PY - 2007/January/19/ UR - http://dx.doi.org/10.1371/journal.pcbi.0020165 ER -