Neural Comput - Neural mass activity, bifurcations, and epilepsy.

Tópicos

{ activ(1452) weight(1219) physic(1104) }
{ model(3480) simul(1196) paramet(876) }
{ framework(1458) process(801) describ(734) }
{ general(901) number(790) one(736) }
{ model(2656) set(1616) predict(1553) }
{ model(3404) distribut(989) bayesian(671) }
{ featur(3375) classif(2383) classifi(1994) }
{ imag(2830) propos(1344) filter(1198) }
{ treatment(1704) effect(941) patient(846) }
{ cancer(2502) breast(956) screen(824) }
{ data(1737) use(1416) pattern(1282) }
{ network(2748) neural(1063) input(814) }
{ clinic(1479) use(1117) guidelin(835) }
{ case(1353) use(1143) diagnosi(1136) }
{ system(1050) medic(1026) inform(1018) }
{ method(1219) similar(1157) match(930) }
{ take(945) account(800) differ(722) }
{ assess(1506) score(1403) qualiti(1306) }
{ learn(2355) train(1041) set(1003) }
{ method(1557) propos(1049) approach(1037) }
{ featur(1941) imag(1645) propos(1176) }
{ howev(809) still(633) remain(590) }
{ medic(1828) order(1363) alert(1069) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ structur(1116) can(940) graph(676) }
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{ can(774) often(719) complex(702) }
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{ imag(1057) registr(996) error(939) }
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{ sequenc(1873) structur(1644) protein(1328) }
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{ model(2220) cell(1177) simul(1124) }
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{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ research(1085) discuss(1038) issu(1018) }
{ import(1318) role(1303) understand(862) }
{ model(2341) predict(2261) use(1141) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ can(981) present(881) function(850) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ high(1669) rate(1365) level(1280) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ process(1125) use(805) approach(778) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }

Resumo

In this letter, we propose a general framework for studying neural mass models defined by ordinary differential equations. By studying the bifurcations of the solutions to these equations and their sensitivity to noise, we establish an important relation, similar to a dictionary, between their behaviors and normal and pathological, especially epileptic, cortical patterns of activity. We then apply this framework to the analysis of two models that feature most phenomena of interest, the Jansen and Rit model, and the slightly more complex model recently proposed by Wendling and Chauvel. This model-based approach allows us to test various neurophysiological hypotheses on the origin of pathological cortical behaviors and investigate the effect of medication. We also study the effects of the stochastic nature of the inputs, which gives us clues about the origins of such important phenomena as interictal spikes, interictal bursts, and fast onset activity that are of particular relevance in epilepsy.

Resumo Limpo

letter propos general framework studi neural mass model defin ordinari differenti equat studi bifurc solut equat sensit nois establish import relat similar dictionari behavior normal patholog especi epilept cortic pattern activ appli framework analysi two model featur phenomena interest jansen rit model slight complex model recent propos wendl chauvel modelbas approach allow us test various neurophysiolog hypothes origin patholog cortic behavior investig effect medic also studi effect stochast natur input give us clue origin import phenomena interict spike interict burst fast onset activ particular relev epilepsi

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