{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T13:46:04Z","timestamp":1760708764768},"reference-count":55,"publisher":"MIT Press - Journals","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Computation"],"published-print":{"date-parts":[[2015,1]]},"abstract":"<jats:p> The collective dynamics of neural ensembles create complex spike patterns with many spatial and temporal scales. Understanding the statistical structure of these patterns can help resolve fundamental questions about neural computation and neural dynamics. Spatiotemporal conditional inference (STCI) is introduced here as a semiparametric statistical framework for investigating the nature of precise spiking patterns from collections of neurons that is robust to arbitrarily complex and nonstationary coarse spiking dynamics. The main idea is to focus statistical modeling and inference not on the full distribution of the data, but rather on families of conditional distributions of precise spiking given different types of coarse spiking. The framework is then used to develop families of hypothesis tests for probing the spatiotemporal precision of spiking patterns. Relationships among different conditional distributions are used to improve multiple hypothesis-testing adjustments and design novel Monte Carlo spike resampling algorithms. Of special note are algorithms that can locally jitter spike times while still preserving the instantaneous peristimulus time histogram or the instantaneous total spike count from a group of recorded neurons. The framework can also be used to test whether first-order maximum entropy models with possibly random and time-varying parameters can account for observed patterns of spiking. STCI provides a detailed example of the generic principle of conditional inference, which may be applicable to other areas of neurostatistical analysis. <\/jats:p>","DOI":"10.1162\/neco_a_00681","type":"journal-article","created":{"date-parts":[[2014,11,7]],"date-time":"2014-11-07T19:42:44Z","timestamp":1415389364000},"page":"104-150","source":"Crossref","is-referenced-by-count":12,"title":["Spatiotemporal Conditional Inference and Hypothesis Tests for Neural Ensemble Spiking Precision"],"prefix":"10.1162","volume":"27","author":[{"given":"Matthew T.","family":"Harrison","sequence":"first","affiliation":[{"name":"Division of Applied Mathematics, Brown University, Providence, RI 02912, U.S.A."}]},{"given":"Asohan","family":"Amarasingham","sequence":"additional","affiliation":[{"name":"Department of Mathematics, The City College of New York, and Departments of Biology and Psychology, The Graduate Center, The City University of New York, New York, NY 10031, U.S.A."}]},{"given":"Wilson","family":"Truccolo","sequence":"additional","affiliation":[{"name":"Department of Neuroscience and Brown Institute for Brain Science, Brown University, Providence, RI 02912, U.S.A."}]}],"member":"281","reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-81708-3"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1002\/sim.738"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1002\/0470114754"},{"key":"B4","unstructured":"Amarasingham, A. (2004). Statistical methods for the assessment of temporal structure in the activity of the nervous system. PhD dissertation, Brown University."},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.2948-05.2006"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00633.2011"},{"key":"B7","volume-title":"Methods of information geometry","author":"Amari S.","year":"2000"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1162\/089976603321043720"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/76.4.633"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1152\/jn.1998.80.6.3345"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcta.2007.03.009"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1016\/j.conb.2007.11.001"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1038\/nn.2842"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511802843"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.1016\/S1364-6613(00)01568-0"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/3348.001.0001"},{"key":"B17","doi-asserted-by":"publisher","DOI":"10.1038\/nn.2134"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00491.2001"},{"key":"B19","doi-asserted-by":"publisher","DOI":"10.2140\/pjm.1957.7.1073"},{"key":"B20","doi-asserted-by":"publisher","DOI":"10.1109\/10.16444"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.1162\/089976602753284464"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1007\/s00422-002-0388-0"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2009.04.008"},{"key":"B24","unstructured":"Harrison, M. T. (2005). Discovering compositional structures. Doctoral dissertation, Brown University."},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/asr079"},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00399"},{"key":"B28","doi-asserted-by":"publisher","DOI":"10.1201\/b14859-6"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2008.03-08-730"},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.1214\/10-AOAS429"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00307"},{"key":"B33","volume-title":"Testing statistical hypotheses","author":"Lehmann E. L.","year":"2005"},{"key":"B36","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/63.3.655"},{"key":"B37","doi-asserted-by":"publisher","DOI":"10.1162\/089976600300014872"},{"key":"B38","doi-asserted-by":"publisher","DOI":"10.1007\/BF00199057"},{"key":"B39","doi-asserted-by":"publisher","DOI":"10.1214\/13-AOS1131"},{"key":"B40","doi-asserted-by":"publisher","DOI":"10.1098\/rsta.2009.0082"},{"key":"B41","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.22-16-07297.2002"},{"key":"B42","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.1831-12.2012"},{"key":"B43","doi-asserted-by":"publisher","DOI":"10.1038\/nature07140"},{"key":"B44","doi-asserted-by":"publisher","DOI":"10.1214\/ss\/1177010027"},{"key":"B45","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1000380"},{"key":"B46","doi-asserted-by":"publisher","DOI":"10.4153\/CJM-1957-044-3"},{"key":"B47","doi-asserted-by":"publisher","DOI":"10.1038\/nature04701"},{"key":"B48","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1002385"},{"key":"B49","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.1282-06.2006"},{"key":"B50","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.2929-08.2008"},{"key":"B51","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2202-10-S1-P108"},{"key":"B52","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.4567-13.2014"},{"key":"B53","doi-asserted-by":"publisher","DOI":"10.1038\/nn.2782"},{"key":"B54","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00697.2004"},{"key":"B55","doi-asserted-by":"publisher","DOI":"10.1038\/nn.2455"},{"key":"B56","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2006.09.020"},{"key":"B57","doi-asserted-by":"publisher","DOI":"10.1038\/373515a0"},{"key":"B58","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00645.2004"},{"key":"B59","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00644.2004"}],"container-title":["Neural Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mitpressjournals.org\/doi\/pdf\/10.1162\/NECO_a_00681","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,12]],"date-time":"2021-03-12T21:40:36Z","timestamp":1615585236000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/neco\/article\/27\/1\/104-150\/8035"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,1]]},"references-count":55,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2015,1]]}},"alternative-id":["10.1162\/NECO_a_00681"],"URL":"https:\/\/doi.org\/10.1162\/neco_a_00681","relation":{},"ISSN":["0899-7667","1530-888X"],"issn-type":[{"value":"0899-7667","type":"print"},{"value":"1530-888X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,1]]}}}