{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:29:09Z","timestamp":1740148149239,"version":"3.37.3"},"reference-count":22,"publisher":"Wiley","license":[{"start":{"date-parts":[[2010,1,1]],"date-time":"2010-01-01T00:00:00Z","timestamp":1262304000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01 DC008701-01","CCF-06-35252"],"award-info":[{"award-number":["R01 DC008701-01","CCF-06-35252"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["R01 DC008701-01","CCF-06-35252"],"award-info":[{"award-number":["R01 DC008701-01","CCF-06-35252"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Onassis Public Benefit Foundation","award":["R01 DC008701-01","CCF-06-35252"],"award-info":[{"award-number":["R01 DC008701-01","CCF-06-35252"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2010]]},"abstract":"<jats:p>We consider the problem of reconstructing finite energy stimuli encoded with a population of spiking leaky integrate-and-fire neurons. The reconstructed signal satisfies a consistency condition: when passed through the same neuron, it triggers the same spike train as the original stimulus. The recovered stimulus has to also minimize a quadratic smoothness optimality criterion. We formulate the reconstruction as a spline interpolation problem for scalar as well as vector valued stimuli and show that the recovery has a unique solution. We provide explicit reconstruction algorithms for stimuli encoded with single as well as a population of integrate-and-fire neurons. We demonstrate how our reconstruction algorithms can be applied to stimuli encoded with ON-OFF neural circuits with feedback. Finally, we extend the formalism to multi-input multi-output neural circuits and demonstrate that vector-valued finite energy signals can be efficiently encoded by a neural population provided that its size is beyond a threshold value. Examples are given that demonstrate the potential applications of our methodology to systems neuroscience and neuromorphic engineering.<\/jats:p>","DOI":"10.1155\/2010\/469658","type":"journal-article","created":{"date-parts":[[2009,9,22]],"date-time":"2009-09-22T10:01:48Z","timestamp":1253613708000},"page":"1-13","source":"Crossref","is-referenced-by-count":6,"title":["Consistent Recovery of Sensory Stimuli Encoded with MIMO Neural Circuits"],"prefix":"10.1155","volume":"2010","author":[{"given":"Aurel A.","family":"Lazar","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Columbia University, New York, NY 10027, USA"}]},{"given":"Eftychios A.","family":"Pnevmatikakis","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Columbia University, New York, NY 10027, USA"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2004.01.022"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSI.2004.835026"},{"year":"2003","series-title":"Applied and Numerical Harmonic Analysis","key":"3"},{"year":"1990","key":"4"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2008.06-07-559"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1155\/2009\/682930"},{"year":"2003","key":"8"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2007.891948"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2008.926716"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/3\/2\/009"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2008.2000163"},{"year":"2001","key":"13"},{"year":"1987","key":"14"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1109\/78.193220"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2002.800391"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1038\/nn0901-877"},{"year":"2004","key":"19"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(01)00078-8"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2008.12-07-680"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2007.11.006"},{"issue":"6-7","key":"23","doi-asserted-by":"crossref","first-page":"1153","DOI":"10.1016\/S0893-6080(05)80164-9","volume":"7","year":"1994","journal-title":"Neural Networks"},{"volume-title":"Splines minimizing rotation-invariant semi-norms in sobolev spaces","year":"1977","key":"24"}],"container-title":["Computational Intelligence and Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2010\/469658.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2010\/469658.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2010\/469658.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,18]],"date-time":"2017-06-18T19:57:35Z","timestamp":1497815855000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.hindawi.com\/journals\/cin\/2010\/469658\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010]]},"references-count":22,"alternative-id":["469658","469658"],"URL":"https:\/\/doi.org\/10.1155\/2010\/469658","relation":{},"ISSN":["1687-5265","1687-5273"],"issn-type":[{"type":"print","value":"1687-5265"},{"type":"electronic","value":"1687-5273"}],"subject":[],"published":{"date-parts":[[2010]]}}}