Bayesian detection of single-trial event-related potentials

Mestre, Maria Rosario; Godsill, Simon; Fitzgerald, William J.

doi:10.1109/icassp.2014.6854492

Cited by 4 publications

(1 citation statement)

References 12 publications

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“…After averaging across trials, the resulting ERP waveforms are indistinguishable to those generated under the classic theory under simulated datasets (Yeung et al 2007). Other methods exist for dealing with trial-by-trial variability in the latency of ERP components (Ouyang et al 2015;Woody 1967;Cecotti and Ries 2017;Dmochowski and Norcia 2015;Mestre et al 2014). The primary advantages of HSMM-MVPA as compared to these other methods are its capability (i) to capture ERP-like components that are not locked to observable events and (ii) to estimate the number of ERP-like components in the task (for a review and comparison of methods, see Walsh et al 2017).…”

Section: Motivation and Overview Of Current Experimentsmentioning

confidence: 99%

The Impact of Inserting an Additional Mental Process

2018

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Pure insertion describes a scenario where a mental process is inserted within a sequence of other processes without altering the other processes. Under the assumption of pure insertion, the duration of the inserted process can be identified by calculating the difference in overall response times when the process is present versus absent (i.e., Donder's subtraction method). Additionally, under the assumption of pure insertion, brain regions associated with the inserted process can be identified in fMRI studies by contrasting activation when the process is present versus absent. However, the assumption of pure insertion does not hold in many situations. In this study, we adopted a novel approach for identifying the impact of insertion by decomposing the EEG signal into a sequence of latent stages, each with a distinct topographical distribution and duration. Based on these latent stages, it is possible to identify when, and for how long, a process occurred. We crossed two factors in the experiment: whether the trial required substituting a letter with a number from memory and whether the trial required calculating the product of two numbers. By crossing these factors, we could examine whether inserting substitution and calculation processes affected the durations of other mental processing stages. Behavioral data in the form of response latencies, and averaged EEG signal in the form of eventrelated potentials (ERPs), provided no evidence of violations of pure insertion. However, our analysis of single-trial EEG signal allowed us both to show that inserting substitution or calculation did affect other stages and to understand why.

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Section: Motivation and Overview Of Current Experimentsmentioning

confidence: 99%

The Impact of Inserting an Additional Mental Process

2018

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Accurate single-trial detection of movement intention made possible using adaptive wavelet transform

Chamanzar

Malekmohammadi

Bahrani

et al. 2015

2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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The outlook of brain-computer interfacing (BCI) is very bright. The real-time, accurate detection of a motor movement task is critical in BCI systems. The poor signal-to-noise-ratio (SNR) of EEG signals and the ambiguity of noise generator sources in brain renders this task quite challenging. In this paper, we demonstrate a novel algorithm for precise detection of the onset of a motor movement through identification of event-related-desynchronization (ERD) patterns. Using an adaptive matched filter technique implemented based on an optimized continues Wavelet transform by selecting an appropriate basis, we can detect single-trial ERDs. Moreover, we use a maximum-likelihood (ML), electrooculography (EOG) artifact removal method to remove eye-related artifacts to significantly improve the detection performance. We have applied this technique to our locally recorded Emotiv(®) data set of 6 healthy subjects, where an average detection selectivity of 85 ± 6% and sensitivity of 88 ± 7.7% is achieved with a temporal precision in the range of -1250 to 367 ms in onset detections of single-trials.

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