Computational and statistical methods for analyzing event-related potential data

Boxtel, G.J.M. van

doi:10.3758/bf03209419

Cited by 90 publications

(52 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The variance is small near the onset of the stimulus, and large near the end of the recording epoch, and at treatment-dependent ERP component peaks (Kayser and Tenke, 2003;Lehmann and Skrandies, 1980;van Boxtel, 1998). For spectral data, the highest signal variance is generally observed at the lowest frequencies (i.e.…”

Section: Limitations Of the Proposed Methodsmentioning

confidence: 93%

Reference-free quantification of EEG spectra: Combining current source density (CSD) and frequency principal components analysis (fPCA)

Tenke

Kayser

2005

Clinical Neurophysiology

166

225

View full text Add to dashboard Cite

Objective: Definition of appropriate frequency bands and choice of recording reference limit the interpretability of quantitative EEG, which may be further compromised by distorted topographies or inverted hemispheric asymmetries when employing conventional (non-linear) power spectra. In contrast, fPCA factors conform to the spectral structure of empirical data, and a surface Laplacian (2-dimensional CSD) simplifies topographies by minimizing volume-conducted activity. Conciseness and interpretability of EEG and CSD fPCA solutions were compared for three common scaling methods. Methods: Resting EEG and CSD (30 channels, nose reference, eyes open/closed) from 51 healthy and 93 clinically-depressed adults were simplified as power, log power, and amplitude spectra, and summarized using unrestricted, Varimax-rotated, covariance-based fPCA. Results: Multiple alpha factors were separable from artifact and reproducible across subgroups. Power spectra produced numerous, sharplydefined factors emphasizing low frequencies. Log power spectra produced fewer, broader factors emphasizing high frequencies. Solutions for amplitude spectra showed optimal intermediate tuning, particularly when derived from CSD rather than EEG spectra. These solutions were topographically distinct, detecting multiple posterior alpha generators but excluding the dorsal surface of the frontal lobes. Instead a low alpha/theta factor showed a secondary topography along the frontal midline. Conclusions: CSD amplitude spectrum fPCA solutions provide simpler, reference-independent measures that more directly reflect neuronal activity. Significance: A new quantitative EEG approach affording spectral components is developed that closely parallels the concept of an ERP component in the temporal domain.

show abstract

Section: Limitations Of the Proposed Methodsmentioning

confidence: 93%

Reference-free quantification of EEG spectra: Combining current source density (CSD) and frequency principal components analysis (fPCA)

Tenke

Kayser

2005

Clinical Neurophysiology

166

225

View full text Add to dashboard Cite

show abstract

“…Because the variance of the full data pattern defines the components, PCA allows cognitively important components to emerge in the context of the overall variance pattern [Chapman and McCrary, 1995;van Boxtel, 1998]. …”

Section: Introductionmentioning

confidence: 99%

The time course of brain activity in reading English and Chinese: An ERP study of Chinese bilinguals

Liu

Perfetti

2003

Human Brain Mapping

159

105

View full text Add to dashboard Cite

Abstract:Chinese bilinguals performed a delayed naming task, reading both Chinese characters and English words, while EEGs were recorded by a 128-channel system. Principle component analysis (PCA) of Event Related Potentials (ERP) from the onset of the stimulus suggested a temporal unfolding of graphic, phonological, and semantic processing that depended on both language and word frequency. At 150 msec, Chinese produced an earlier and higher amplitude shift (N150) than English. At 250 msec, frequency effects were significant for both Chinese and English, but at 450 msec, only the English frequency effect was reliable. Source localization analysis by Low Resolution Electromagnetic Tomography (LORETA) showed bilateral occipital (left BA 17, right BA 18) visual processing of Chinese characters with left occipital only (left BA 17) for English high-frequency words. Low-frequency English words showed activation bilaterally, but with a more diffused and extended temporal pattern. Right prefrontal area (BA 10) was found to be strongly activated in the mid latency (300 -400 msec) period of Chinese character naming, whereas English word naming showed more medial frontal (BA 8, and 10) activation. A post 450-msec visual verification was found to be general for both writing systems. Hum. Brain Mapping 18:167-175, 2003.

show abstract

“…Such a model fits easily with the procedures of PCA~Donchin, 1966;Donchin & Heffley, 1978;Glaser & Ruchkin, 1976, pp. 233-290;Möcks & Verleger, 1991;Ruchkin, Villegas, & John, 1964;Van Boxtel, 1998!, which is a method for linearly decomposing a multivariate data matrix. When applied to a set of ERPs, PCA produces a set of components.…”

Section: J Principal Component Analysis (Pca) (I) the Type Of Associmentioning

confidence: 99%

Guidelines for using human event-related potentials to study cognition: Recording standards and publication criteria

et al. 2000

View full text Add to dashboard Cite

Event-related potentials~ERPs! recorded from the human scalp can provide important information about how the human brain normally processes information and about how this processing may go awry in neurological or psychiatric disorders. Scientists using or studying ERPs must strive to overcome the many technical problems that can occur in the recording and analysis of these potentials. The methods and the results of these ERP studies must be published in a way that allows other scientists to understand exactly what was done so that they can, if necessary, replicate the experiments. The data must then be analyzed and presented in a way that allows different studies to be compared readily. This paper presents guidelines for recording ERPs and criteria for publishing the results.Descriptors: Event-related potentials, Methods, Artifacts, Measurement, Statistics Event-related potentials~ERPs! are voltage fluctuations that are associated in time with some physical or mental occurrence. These potentials can be recorded from the human scalp and extracted from the ongoing electroencephalogram~EEG! by means of filtering and signal averaging. Although ERPs can be evaluated in both frequency and time domains, these particular guidelines are concerned with ERPs recorded in the time domain, that is, as waveforms that plot the change in voltage as a function of time. These waveforms contain components that span a continuum between the exogenous potentials~obligatory responses determined by the physical characteristics of the eliciting event in the external world! and the endogenous potentials~manifestations of information processing in the brain that may or may not be invoked by the eliciting event!.1 Because the temporal resolution of these measurements is on the order of milliseconds, ERPs can accurately measure when processing activities take place in the human brain. The spatial resolution of ERP measurements is limited both by theory and by our present technology, but multichannel recordings can allow us to estimate the intracerebral locations of these cerebral processes. The temporal and spatial information provided by ERPs may be used in many different research programs, with goals that range from understanding how the brain implements the mind to making specific diagnoses in medicine or psychology. Data cannot have scientific value unless they are published for evaluation and replication by other scientists. These ERP guidelines are therefore phrased primarily in terms of publication criteria. The scientific endeavor consists of three main steps, and these map well onto the sections of the published paper. The first step is the most important but the least well understood-the discovery of Address reprint requests to: Terence W. Picton, Rotman Research Institute,

show abstract

Computational and statistical methods for analyzing event-related potential data

Cited by 90 publications

References 29 publications

Reference-free quantification of EEG spectra: Combining current source density (CSD) and frequency principal components analysis (fPCA)

Reference-free quantification of EEG spectra: Combining current source density (CSD) and frequency principal components analysis (fPCA)

The time course of brain activity in reading English and Chinese: An ERP study of Chinese bilinguals

Guidelines for using human event-related potentials to study cognition: Recording standards and publication criteria

Contact Info

Product

Resources

About