{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T12:06:22Z","timestamp":1763467582102},"reference-count":38,"publisher":"MIT Press - Journals","issue":"11","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Computation"],"published-print":{"date-parts":[[2003,11,1]]},"abstract":"<jats:p> The directional control of reaching after stroke was simulated by including cell death and firing-rate noise in a population vector model of movement control. In this model, cortical activity was assumed to cause the hand to move in the direction of a population vector, defined by a summation of responses from neurons with cosine directional tuning. Two types of directional error were analyzed: the between-target variability, defined as the standard deviation of the directional error across a wide range of target directions, and the within-target variability, defined as the standard deviation of the directional error for many reaches to a single target. <\/jats:p><jats:p> Both between and within-target variability increased with increasing cell death. The increase in between-target variability arose because cell death caused a nonuniform distribution of preferred directions. The increase in within-target variability arose because the magnitude of the population vector decreased more quickly than its standard deviation for increasing cell death, provided appropriate levels of firing-rate noise were present. Comparisons to reaching data from 29 stroke subjects revealed similar increases in between and within-target variability as clinical impairment severity increased. Relationships between simulated cell death and impairment severity were derived using the between and within-target variability results. For both relationships, impairment severity increased similarly with decreasing percentage of surviving cells, consistent with results from previous imaging studies. These results demonstrate that a population vector model of movement control that incorporates cosine tuning, linear summation of unitary responses, firing-rate noise, and random cell death can account for some features of impaired arm movement after stroke. <\/jats:p>","DOI":"10.1162\/089976603322385090","type":"journal-article","created":{"date-parts":[[2003,9,25]],"date-time":"2003-09-25T19:55:04Z","timestamp":1064519704000},"page":"2619-2642","source":"Crossref","is-referenced-by-count":37,"title":["Modeling Reaching Impairment After Stroke Using a Population Vector Model of Movement Control That Incorporates Neural Firing-Rate Variability"],"prefix":"10.1162","volume":"15","author":[{"given":"David J.","family":"Reinkensmeyer","sequence":"first","affiliation":[{"name":"Department of Mechanical and Aerospace Engineering and Center for Biomedical Engineering, University of California at Irvine, Irvine, CA 92697, U.S.A.,"}]},{"given":"Mario G.","family":"Iobbi","sequence":"additional","affiliation":[{"name":"Department of Physics and Center for Biomedical Engineering, University of California at Irvine, Irvine, CA 92697, U.S.A.,"}]},{"given":"Leonard E.","family":"Kahn","sequence":"additional","affiliation":[{"name":"Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL 60611, U.S.A., and Department of Biomedical Engineering, Northwestern University, Evanston, IL 60208, U.S.A.,"}]},{"given":"Derek G.","family":"Kamper","sequence":"additional","affiliation":[{"name":"Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL 60611, U.S.A., and Department of Physical Medicine and Rehabilitation, Northwestern University Medical School, Evanston, IL 60208, U.S.A.,"}]},{"given":"Craig D.","family":"Takahashi","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Aerospace Engineering, University of California at Irvine, Irvine, CA 92697, U.S.A.,"}]}],"member":"281","reference":[{"key":"p_1","doi-asserted-by":"publisher","DOI":"10.1007\/s002219900275"},{"key":"p_2","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00364.2002"},{"key":"p_3","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.11-05-01182.1991"},{"key":"p_4","doi-asserted-by":"publisher","DOI":"10.1152\/jn.1968.31.1.14"},{"key":"p_5","doi-asserted-by":"publisher","DOI":"10.1002\/ana.410360311"},{"key":"p_6","doi-asserted-by":"publisher","DOI":"10.1152\/jn.1989.62.1.198"},{"key":"p_8","doi-asserted-by":"publisher","DOI":"10.1016\/0926-6410(95)00040-2"},{"key":"p_9","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.02-11-01527.1982"},{"key":"p_10","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.08-08-02928.1988"},{"key":"p_11","doi-asserted-by":"publisher","DOI":"10.1161\/01.STR.28.1.101"},{"key":"p_12","doi-asserted-by":"publisher","DOI":"10.1161\/01.STR.24.1.58"},{"key":"p_13","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00403.2001"},{"key":"p_14","first-page":"525","volume":"73","author":"Kalaska J. 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