Nonparametric Analysis of Statistic Images from Functional Mapping Experiments

Holmes, Andrew P.; Blair, R. Clifford; Watson, J. D. G.; Ford, Ian

doi:10.1016/b978-012389760-2/50067-0

Cited by 194 publications

(284 citation statements)

References 11 publications

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“…These voxel-by-voxel t values were displayed as statistical parametric maps (SPMs). To correct for multiple comparisons, a non-parametric single-threshold test was applied on the basis of the theory for randomization and permutation tests developed by Holmes et al [62] for functional mapping experiments. Thus, the omnibus null hypothesis of no activation anywhere in the brain was rejected if at least one t value (i.e.…”

Section: Discussionmentioning

confidence: 99%

EEG low-resolution brain electromagnetic tomography (LORETA) in Huntington’s disease

et al. 2010

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Previous studies have shown abnormal electroencephalography (EEG) in Huntington's disease (HD). The aim of the present investigation was to compare quantitatively analyzed EEGs of HD patients and controls by means of low-resolution brain electromagnetic tomography (LORETA). Further aims were to delineate the sensitivity and utility of EEG LORETA in the progression of HD, and to correlate parameters of cognitive and motor impairment with neurophysiological variables. In 55 HD patients and 55 controls a 3-min vigilance-controlled EEG (V-EEG) was recorded during midmorning hours. Power spectra and intracortical tomography were computed by LORETA in seven frequency bands and compared between groups. Spearman rank correlations were based on V-EEG and psychometric data. Statistical overall analysis by means of the omnibus significance test demonstrated significant (p < 0.01) differences between HD patients and controls. LORETA theta, alpha and beta power were decreased from early to late stages of the disease. Only advanced disease stages showed a significant increase in delta power, mainly in the right orbitofrontal cortex. Correlation analyses revealed that a decrease of alpha and theta power correlated significantly with increasing cognitive and motor decline. LORETA proved to be a sensitive instrument for detecting progressive electrophysiological changes in HD. Reduced alpha power seems to be a trait marker of HD, whereas increased prefrontal delta power seems to reflect worsening of the disease. Motor function and cognitive function deteriorate together with a decrease in alpha and theta power. This data set, so far the largest in HD research, helps to elucidate remaining uncertainties about electrophysiological abnormalities in HD.

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Section: Discussionmentioning

confidence: 99%

EEG low-resolution brain electromagnetic tomography (LORETA) in Huntington’s disease

et al. 2010

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“…Randomization analysis is a nonparametric test, which is ideal for complex between-group comparisons in PET studies because, unlike techniques that rely on the General Linear Model for between-group comparison, it makes much fewer assumptions about the data Holmes et al, 1996]. In particular it is unaffected by the difference in variance across groups that often occurs in normal controls and patients with schizophrenia.…”

Section: Discussionmentioning

confidence: 99%

Neural basis of novel and well-learned recognition memory in schizophrenia: A positron emission tomography study

Crespo‐Facorro

Wiser²,

Andreasen³

et al. 2001

Hum. Brain Mapp.

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“…Then, between-group comparisons (current smokers vs never smokers; former smokers vs never smokers; current smokers vs former smokers) of the LORETA current density distribution were performed using the same nonparametric statistical analysis based on voxel-byvoxel t tests (Holmes et al 1996). Further details on statistical imaging of current density differences as voxelby-voxel t tests (Holmes et al 1996) are given elsewhere (Gallinat et al 2002). All tests were performed with a twosided p<0.05.…”

Section: Statistical Analysesmentioning

confidence: 99%