A Bayesian method to estimate single-trial event-related potentials with application to the study of the P300 variability

D’Avanzo, Costanza; Schiff, Sami; Amodio, Piero; Sparacino, Giovanni

doi:10.1016/j.jneumeth.2011.03.010

Cited by 37 publications

(43 citation statements)

References 51 publications

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“…Single-trial ERPs are estimated through the Bayesian approach extensively described in [38], which also admits further sophistications, recently documented in [39, 44], though not usable in real time and thus unsuited to the BCI setting.…”

Section: Methodsmentioning

confidence: 99%

“…Specifically, as a preliminary proof of concept of the feasibility of an assistive single-channel (SC) BCI, we assess the hypothesis that the performance of the multichannel (MC) BCI system documented in [13], with N = 5, is preserved when only one channel is employed but a Bayesian ERP estimation technique [38, 39] is used to preprocess the signal. For such a scope, an offline comparison is made by using the data collected in 21 ALS patients and 9 healthy controls.…”

Section: Introductionmentioning

confidence: 99%

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Preprocessing by a Bayesian Single-Trial Event-Related Potential Estimation Technique Allows Feasibility of an Assistive Single-Channel P300-Based Brain-Computer Interface

D’Avanzo

Tonin

Piccione

et al. 2014

Computational and Mathematical Methods in Medicine

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A major clinical goal of brain-computer interfaces (BCIs) is to allow severely paralyzed patients to communicate their needs and thoughts during their everyday lives. Among others, P300-based BCIs, which resort to EEG measurements, have been successfully operated by people with severe neuromuscular disabilities. Besides reducing the number of stimuli repetitions needed to detect the P300, a current challenge in P300-based BCI research is the simplification of system's setup and maintenance by lowering the number N of recording channels. By using offline data collected in 30 subjects (21 amyotrophic lateral sclerosis patients and 9 controls) through a clinical BCI with N = 5 channels, in the present paper we show that a preprocessing approach based on a Bayesian single-trial ERP estimation technique allows reducing N to 1 without affecting the system's accuracy. The potentially great benefit for the practical usability of BCI devices (including patient acceptance) that would be given by the reduction of the number N of channels encourages further development of the present study, for example, in an online setting.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Preprocessing by a Bayesian Single-Trial Event-Related Potential Estimation Technique Allows Feasibility of an Assistive Single-Channel P300-Based Brain-Computer Interface

D’Avanzo

Tonin

Piccione

et al. 2014

Computational and Mathematical Methods in Medicine

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“…Usually P300 is computed by the averaging of a number of trials; however, it is possible to compute P300 also on single trials. 80 Recently, using this approach, we have proven that patients with minimal HE have an increased latency variability of single trial P300. 72 This contribute to explain to reduction in P300 calculated by averaging techniques and highlights the variability of responses typical of minimal HE, which was also detected by psychometric testing.…”

Section: Motor Evoked Potentials (Meps)mentioning

confidence: 99%

Clinical Neurophysiology of Hepatic Encephalopathy

Amodio

Montagnese

2015

Journal of Clinical and Experimental Hepatology

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Background/Objectives: Hepatic encephalopathy (HE) has relevant impact on the quality of life of patients and their caregivers and causes relevant costs because of hospitalizations and work days lost. Its quantification is important to perform adequate clinical trials on this relevant complication of cirrhosis and portal-systemic shunting. Clinical neurophysiology, which detects functional alterations of the nervous system, has been applied to the study of HE for over 60 years. This review aims at summarizing and clarifying the role of neurophysiologic techniques in the study of HE. Methods: A narrative review was performed aiming at interpreting the cited papers and the techniques on the basis of their physiological and pathophysiological meaning. Results: The potential role of EEG, quantified EEG, evoked potentials-both exogenous, endogenous and motor-have been clarified to the reader that may be unfamiliar with neurophysiology. Conclusions: The EEG, reflecting the oscillatory changes of neural network is the preferable tool to detect and monitor HE, with the exception of its most severe stage, when EEG flattens. SSEP and MEP have indication to detect and monitor transmission alterations that are likely related to myelin changes and microedema. ( J CLIN EXP HEPATOL 2014;5:S60-S68)

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“…C: the median raw data across animals, replotted from Fig. 6. it is now well established that this model can result in a poor estimate of the evoked response, whose amplitude and latency can vary considerably from trial to trial (D'Avanzo et al 2011;Lange et al 1997;Mocks et al 1987;Truccolo et al 2002). Nevertheless, the most common method for computing the induced response component continues to be subtraction of the time-domain evoked response from single-trial responses (e.g., Crone et al 2001;Steinschneider et al 2008;Trautner et al 2006).…”

Section: Variability In Amplitude and Latency Of Additive Componentsmentioning

confidence: 99%

Analysis of stimulus-related activity in rat auditory cortex using complex spectral coefficients

Krause

Banks

2013

Journal of Neurophysiology

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A Bayesian method to estimate single-trial event-related potentials with application to the study of the P300 variability

Cited by 37 publications

References 51 publications

Preprocessing by a Bayesian Single-Trial Event-Related Potential Estimation Technique Allows Feasibility of an Assistive Single-Channel P300-Based Brain-Computer Interface

Preprocessing by a Bayesian Single-Trial Event-Related Potential Estimation Technique Allows Feasibility of an Assistive Single-Channel P300-Based Brain-Computer Interface

Clinical Neurophysiology of Hepatic Encephalopathy

Analysis of stimulus-related activity in rat auditory cortex using complex spectral coefficients

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