{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,1,4]],"date-time":"2024-01-04T11:58:40Z","timestamp":1704369520106},"reference-count":55,"publisher":"MIT Press - Journals","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Computation"],"published-print":{"date-parts":[[2018,10]]},"abstract":"<jats:p> Modeling and interpreting spike train data is a task of central importance in computational neuroscience, with significant translational implications. Two popular classes of data-driven models for this task are autoregressive point-process generalized linear models (PPGLM) and latent state-space models (SSM) with point-process observations. In this letter, we derive a mathematical connection between these two classes of models. By introducing an auxiliary history process, we represent exactly a PPGLM in terms of a latent, infinite-dimensional dynamical system, which can then be mapped onto an SSM by basis function projections and moment closure. This representation provides a new perspective on widely used methods for modeling spike data and also suggests novel algorithmic approaches to fitting such models. We illustrate our results on a phasic bursting neuron model, showing that our proposed approach provides an accurate and efficient way to capture neural dynamics. <\/jats:p>","DOI":"10.1162\/neco_a_01121","type":"journal-article","created":{"date-parts":[[2018,8,27]],"date-time":"2018-08-27T20:04:33Z","timestamp":1535400273000},"page":"2757-2780","source":"Crossref","is-referenced-by-count":6,"title":["Autoregressive Point Processes as Latent State-Space Models: A Moment-Closure Approach to Fluctuations and Autocorrelations"],"prefix":"10.1162","volume":"30","author":[{"given":"Michael","family":"Rule","sequence":"first","affiliation":[{"name":"Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guido","family":"Sanguinetti","sequence":"additional","affiliation":[{"name":"Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"281","reference":[{"key":"B1","first-page":"3033","author":"Aghagolzadeh M.","year":"2014","journal-title":"Proceedings of the Engineering in Medicine and Biology Society 36th Annual International Conference of the IEEE"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2015.2470527"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1063\/1.4802475"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1007\/BF00339367"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1007\/BF00337259"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.1983.6313068"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1007\/BF00318010"},{"key":"B8","first-page":"1682","volume-title":"Advances in neural information processing systems, 35","author":"Buesing L.","year":"2012"},{"key":"B9","author":"Chevallier J.","year":"2017","journal-title":"Mean field limits for nonlinear spatially extended Hawkes processes with exponential memory kernels"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1038\/nature11129"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2015.1115357"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1016\/j.spa.2015.01.007"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1162\/089976604773135069"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bht179"},{"key":"B15","author":"Galves A.","year":"2015","journal-title":"Modeling networks of spiking neurons as interacting processes with memory of variable length"},{"key":"B16","first-page":"163","volume-title":"Advances in neural information processing systems","volume":"29","author":"Gao Y.","year":"2016"},{"key":"B17","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1005390"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1063\/1.481811"},{"key":"B19","first-page":"613","author":"Hocker D.","year":"2017","journal-title":"Proceedings of the 8th International IEEE\/EMBS Conference on Neural Engineering"},{"key":"B20","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2003.820440"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.1038\/nature24636"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1115\/1.3658902"},{"key":"B23","author":"Kingman J. 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