{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,17]],"date-time":"2025-04-17T05:49:53Z","timestamp":1744868993356},"reference-count":0,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Neur. Syst."],"published-print":{"date-parts":[[1990,1]]},"abstract":"<jats:p> We investigate feedback networks containing excitatory and inhibitory neurons. The couplings between the neurons follow a Hebbian rule in which the memory patterns are encoded as cell assemblies of the excitatory neurons. Using disjoint patterns, we study the attractors of this model and point out the importance of mixed states. The latter become dominant at temperatures above 0.25. We use both numerical simulations and an analytic approach for our investigation. The latter is based on differential equations for the activity of the different memory patterns in the network configuration. Allowing the excitatory thresholds to develop dynamic features which correspond to fatigue of individual neurons, we obtain motion in pattern space, the space of all memories. The attractors turn into transients leading to chaotic motion for appropriate values of the dynamical parameters. The motion can be guided by overlaps between patterns, resembling a process of free associative thinking in the absence of any input. <\/jats:p>","DOI":"10.1142\/s0129065790000151","type":"journal-article","created":{"date-parts":[[2004,11,29]],"date-time":"2004-11-29T02:14:37Z","timestamp":1101694477000},"page":"249-257","source":"Crossref","is-referenced-by-count":26,"title":["EXCITATORY\u2013INHIBITORY NETWORKS WITH DYNAMICAL THRESHOLDS"],"prefix":"10.1142","volume":"01","author":[{"given":"D.","family":"Horn","sequence":"first","affiliation":[{"name":"School of Physics and Astronomy, Raymond and Beverly Sackler Faculty of Exact Sciences Tel Aviv University, Tel Aviv 69978, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M.","family":"Usher","sequence":"additional","affiliation":[{"name":"School of Physics and Astronomy, Raymond and Beverly Sackler Faculty of Exact Sciences Tel Aviv University, Tel Aviv 69978, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"container-title":["International Journal of Neural Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0129065790000151","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T01:53:28Z","timestamp":1565142808000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0129065790000151"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1990,1]]},"references-count":0,"journal-issue":{"issue":"03","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[1990,1]]}},"alternative-id":["10.1142\/S0129065790000151"],"URL":"https:\/\/doi.org\/10.1142\/s0129065790000151","relation":{},"ISSN":["0129-0657","1793-6462"],"issn-type":[{"value":"0129-0657","type":"print"},{"value":"1793-6462","type":"electronic"}],"subject":[],"published":{"date-parts":[[1990,1]]}}}