{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T07:58:08Z","timestamp":1773907088170,"version":"3.50.1"},"reference-count":15,"publisher":"Hindawi Limited","license":[{"start":{"date-parts":[[2012,1,1]],"date-time":"2012-01-01T00:00:00Z","timestamp":1325376000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2012]]},"abstract":"<jats:p>Electrical signals between connected neural nuclei are difficult to model because of the complexity and high number of paths within the brain. Simple parametric models are therefore often used. A multiscale version of the autoregressive with exogenous input (MS-ARX) model has recently been developed which allows selection of the optimal amount of filtering and decimation depending on the signal-to-noise ratio and degree of predictability. In this paper, we apply the MS-ARX model to cortical electroencephalograms and subthalamic local field potentials simultaneously recorded from anesthetized rodent brains. We demonstrate that the MS-ARX model produces better predictions than traditional ARX modeling. We also adapt the MS-ARX results to show differences in internuclei predictability between normal rats and rats with 6OHDA-induced parkinsonism, indicating that this method may have broad applicability to other neuroelectrophysiological studies.<\/jats:p>","DOI":"10.1155\/2012\/580795","type":"journal-article","created":{"date-parts":[[2012,2,15]],"date-time":"2012-02-15T16:02:18Z","timestamp":1329321738000},"page":"1-5","source":"Crossref","is-referenced-by-count":1,"title":["Multiscale Autoregressive Identification of Neuroelectrophysiological Systems"],"prefix":"10.1155","volume":"2012","author":[{"given":"Timothy P.","family":"Gilmour","sequence":"first","affiliation":[{"name":"Electrical Engineering Department, Pennsylvania State University, University Park, PA 16802, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thyagarajan","family":"Subramanian","sequence":"additional","affiliation":[{"name":"Neurology Department, Penn State Hershey Medical Center, 500 University Drive, Hershey, PA 17033, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Constantino","family":"Lagoa","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Pennsylvania State University, University Park, PA 16802, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"W. 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