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Titolo:
Unitary events in multiple single-neuron spiking activity: II. Nonstationary data
Autore:
Grun, S; Diesmann, M; Aertsen, A;
Indirizzi:
Max Planck Inst Brain Res, Dept Neurophysiol, D-60528 Frankfurt, Germany Max Planck Inst Brain Res Frankfurt Germany D-60528 8 Frankfurt, Germany Max Planck Inst Stromungsforsch, Dept Nonlinear Dynam, D-37073 Gottingen, Germany Max Planck Inst Stromungsforsch Gottingen Germany D-37073 ingen, Germany Univ Freiburg, Inst Biol 3, Dept Neurobiol & Biophys, D-79104 Freiburg, Germany Univ Freiburg Freiburg Germany D-79104 iophys, D-79104 Freiburg, Germany
Titolo Testata:
NEURAL COMPUTATION
fascicolo: 1, volume: 14, anno: 2002,
pagine: 81 - 119
SICI:
0899-7667(200201)14:1<81:UEIMSS>2.0.ZU;2-J
Fonte:
ISI
Lingua:
ENG
Soggetto:
VISUAL-CORTEX; CORTICAL ACTIVITY; FRONTAL-CORTEX; SYNCHRONIZATION; MONKEY; RESPONSES; CONNECTIVITY; SENSITIVITY; DISCHARGE; DYNAMICS;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Engineering, Computing & Technology
Citazioni:
41
Recensione:
Indirizzi per estratti:
Indirizzo: Grun, S Max Planck Inst Brain Res, Dept Neurophysiol, D-60528 Frankfurt, Germany Max Planck Inst Brain Res Frankfurt Germany D-60528 urt, Germany
Citazione:
S. Grun et al., "Unitary events in multiple single-neuron spiking activity: II. Nonstationary data", NEURAL COMP, 14(1), 2002, pp. 81-119

Abstract

In order to detect members of a functional group (cell assembly) in simultaneously recorded neuronal spiking activity, we adopted the widely used operational definition that membership in a common assembly is expressed in near-simultaneous spike activity. Unitary event analysis, a statistical method to detect the significant occurrence of coincident spiking activity in stationary data, was recently developed (see the companion article in this issue). The technique for the detection of unitary events is based on the assumption that the underlying processes are stationary in time. This requirement, however, is usually not fulfilled in neuronal data. Here we describe amethod that properly normalizes for changes of rate: the unitary events bymoving window analysis (UEMWA). Analysis for unitary events is performed separately in overlapping time segments by sliding a window of constant width along the data. In each window, stationarity is assumed. Performance and sensitivity are demonstrated by use of simulated spike trains of independently firing neurons, into which coincident events are inserted. If cortical neurons organize dynamically into functional groups, the occurrence of near-simultaneous spike activity should be time varying and related to behaviorand stimuli. UEMWA also accounts for these potentially interesting nonstationarities and allows locating them in time. The potential of the new method is illustrated by results from multiple single-unit recordings from frontal and motor cortical areas in awake, behaving monkey.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 28/03/20 alle ore 23:28:22