Neural Comput - Single-snippet analysis for detection of postspike effects.

Tópicos

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Resumo

Corticomotoneuronal cells (CMN), located predominantly in the primary motor cortex, project directly to alpha motoneuronal pools in the spinal cord. The effects of CMN spikes on motoneuronal excitability are traditionally characterized by visualizing postspike effects (PSEs) in spike-triggered averages (SpTA; Fetz, Cheney, & German, 1976; Fetz & Cheney, 1980; McKiernan, Marcario, Karrer, & Cheney, 1998) of electromyography (EMG) data. Poliakov and Schieber (1998) suggested a formal test, the multiple-fragment analysis (MFA), to automatically detect PSEs. However, MFA's performance was not statistically validated, and it is unclear under what conditions it is valid. This paper's contributions are a power study that validates the MFA; an alternative test, the single-snippet analysis (SSA), which has the same functionality as MFA but is easier to calculate and has better power in small samples; a simple bootstrap simulation to estimate SpTA baselines with simulation bands that help visualize potential PSEs; and a bootstrap adjustment to the MFA and SSA to correct for nonlinear SpTA baselines.

Resumo Limpo

corticomotoneuron cell cmn locat predomin primari motor cortex project direct alpha motoneuron pool spinal cord effect cmn spike motoneuron excit tradit character visual postspik effect pses spiketrigg averag spta fetz cheney german fetz cheney mckiernan marcario karrer cheney electromyographi emg data poliakov schieber suggest formal test multiplefrag analysi mfa automat detect pses howev mfas perform statist valid unclear condit valid paper contribut power studi valid mfa altern test singlesnippet analysi ssa function mfa easier calcul better power small sampl simpl bootstrap simul estim spta baselin simul band help visual potenti pses bootstrap adjust mfa ssa correct nonlinear spta baselin

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