{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,7,11]],"date-time":"2023-07-11T23:10:49Z","timestamp":1689117049046},"reference-count":39,"publisher":"MIT Press","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Computation"],"published-print":{"date-parts":[[2014,7]]},"abstract":"<jats:p>We examined whether and how the balancing of crossmodal excitation and inhibition affects intersensory facilitation. A neural network model, comprising lower-order unimodal networks (X, Y) and a higher-order multimodal network (M), was simulated. Crossmodal excitation was made by direct activation of principal cells of the X network by the Y network. Crossmodal inhibition was made in an indirect manner: the Y network activated glial cells of the X network. This let glial plasma membrane transporters export GABA molecules into the extracellular space and increased the level of ambient GABA. The ambient GABA molecules were accepted by extrasynaptic GABA<jats:sub>a<\/jats:sub>receptors and tonically inhibited principal cells of the X network. Namely, crossmodal inhibition was made through GABAergic gliotransmission. Intersensory facilitation was assessed in terms of multisensory gain: the difference between the numbers of spikes evoked by multisensory (XY) stimulation and unisensory (X-alone) stimulation. The maximal multisensory gain (XY-X) could be achieved at an intermediate noise level by balancing crossmodal excitation and inhibition. This result supports an experimentally derived conclusion: intersensory facilitation under noisy environmental conditions is not necessarily in accord with the principle of inverse effectiveness; rather, multisensory gain is maximal at intermediate signal-to-noise ratio (SNR) levels. The maximal multisensory gain was available at the weakest signal if noise was not present, indicating that the principle of inverse effectiveness is a special case of the intersensory facilitation model proposed here. We suggest that the balancing of crossmodal excitation and inhibition may be crucial for intersensory facilitation. The GABAergic glio-transmission-mediated crossmodal inhibitory mechanism effectively works for intersensory facilitation and on determining the maximal multisensory gain in the entire SNR range between the two extremes: low and high SNRs.<\/jats:p>","DOI":"10.1162\/neco_a_00606","type":"journal-article","created":{"date-parts":[[2014,4,8]],"date-time":"2014-04-08T00:15:53Z","timestamp":1396916153000},"page":"1362-1385","source":"Crossref","is-referenced-by-count":11,"title":["Balanced Crossmodal Excitation and Inhibition Essential for Maximizing Multisensory Gain"],"prefix":"10.1162","volume":"26","author":[{"given":"Osamu","family":"Hoshino","sequence":"first","affiliation":[{"name":"Department of Intelligent Systems Engineering, Ibaraki University, Hitachi, Ibaraki, 316-8511, Japan"}]}],"member":"281","reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pneurobio.2008.08.002"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1016\/S0959-4388(00)00223-3"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1126\/science.276.5312.593"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1111\/j.1460-9568.2005.04462.x"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1002165"},{"key":"B6","first-page":"1","volume-title":"Methods in neuronal modeling","author":"Destexhe A.","year":"1998"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.22-13-05749.2002"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1126\/science.298.5593.556"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.0799-05.2005"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2006.04.008"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1096\/fj.02-0429rev"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2007.19.2.351"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2007.19.12.3310"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2008.08-07-589"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2009.05-08-778"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2010.02-09-969"},{"key":"B17","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00096"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00211"},{"key":"B19","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00356"},{"key":"B20","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00431"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00519"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0603741103"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.1162\/089892902317361930"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.1038\/nn1162"},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.1016\/S0166-2236(03)00237-6"},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.1016\/j.tins.2004.11.010"},{"key":"B27","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.5468-06.2007"},{"key":"B28","doi-asserted-by":"publisher","DOI":"10.1111\/j.1535-7597.2004.46008.x"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00317.2003"},{"key":"B30","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8760(03)00121-1"},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2007.08.008"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.1016\/0304-3940(91)90914-F"},{"key":"B33","doi-asserted-by":"crossref","first-page":"295","DOI":"10.7551\/mitpress\/3422.003.0023","volume-title":"The handbook of multisensory processes","author":"Schroeder C. E.","year":"2004"},{"key":"B34","doi-asserted-by":"publisher","DOI":"10.1016\/j.conb.2005.06.008"},{"key":"B35","doi-asserted-by":"publisher","DOI":"10.1016\/j.actpsy.2007.12.002"},{"key":"B36","doi-asserted-by":"publisher","DOI":"10.1038\/nrn2331"},{"key":"B38","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuint.2010.02.002"},{"key":"B39","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2007.10.021"},{"key":"B40","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00856.2002"}],"container-title":["Neural Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mitpressjournals.org\/doi\/pdf\/10.1162\/NECO_a_00606","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,11]],"date-time":"2023-07-11T22:57:43Z","timestamp":1689116263000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/neco\/article\/26\/7\/1362-1385\/7980"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,7]]},"references-count":39,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2014,7]]}},"alternative-id":["10.1162\/NECO_a_00606"],"URL":"https:\/\/doi.org\/10.1162\/neco_a_00606","relation":{},"ISSN":["0899-7667","1530-888X"],"issn-type":[{"value":"0899-7667","type":"print"},{"value":"1530-888X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,7]]}}}