Single-trial P300 estimation with a spatiotemporal filtering method

Li, Ruijiang; Keil, Andreas; Prı́ncipe, José C.

doi:10.1016/j.jneumeth.2008.10.035

Cited by 22 publications

(19 citation statements)

References 27 publications

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“…The P300 reflects the averaged summed electrophysiological activity of several brain structures that become active around 300ms after stimulus presentation (Soltani and Knight, 2000). The scalp P300, therefore, reflects a mixture (Makeig et al, 2002; Polich, 2007), which has previously been linked to a variety of phenomena including autonomous reactions, stimulus probability, motivational significance, attention, and task performance (Duncan-Johnson and Donchin, 1977; Isreal et al, 1980; Donchin et al, 1984; Li et al, 2009; Nieuwenhuis et al, 2011). In contrast, the N300H only reflects a highly specific portion of variance of EEG 300 ms after a feedback stimulus: that portion that is shared with variance of beat-to-beat intervals hundreds of ms later.…”

Section: Discussionmentioning

confidence: 99%

Acute tryptophan depletion attenuates brain-heart coupling following external feedback

Mueller¹,

Evers²,

Wacker³

et al. 2012

Front. Hum. Neurosci.

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External and internal performance feedback triggers neural and visceral modulations such as reactions in the medial prefrontal cortex and insulae or changes of heart period (HP). The functional coupling of neural and cardiac responses following feedback (cortico-cardiac connectivity) is not well understood. While linear time-lagged within-subjects correlations of single-trial EEG and HP (cardio-electroencephalographic covariance tracing, CECT) indicate a robust negative coupling of EEG magnitude 300 ms after presentation of an external feedback stimulus with subsequent alterations of heart period (the so-called N300H phenomenon), the neurotransmitter systems underlying feedback-evoked cortico-cardiac connectivity are largely unknown. Because it has been shown that acute tryptophan depletion (ATD), attenuating brain serotonin (5-HT), decreases cardiac but not neural correlates of feedback processing, we hypothesized that 5-HT may be involved in feedback-evoked cortico-cardiac connectivity. In a placebo-controlled double-blind cross-over design, 12 healthy male participants received a tryptophan-free amino-acid drink at one session (TRP−) and a balanced amino-acid control-drink (TRP+) on another and twice performed a time-estimation task with feedback presented after each trial. N300H magnitude and plasma tryptophan levels were assessed. Results indicated a robust N300H after TRP+, which was significantly attenuated following TRP−. Moreover, plasma tryptophan levels during TRP+ were correlated with N300H amplitude such that individuals with lower tryptophan levels showed reduced N300H. Together, these findings indicate that 5-HT is important for feedback-induced covariation of cortical and cardiac activity. Because individual differences in anxiety have previously been linked to 5-HT, cortico-cardiac coupling and feedback processing, the present findings may be particularly relevant for futures studies on the relationship between 5-HT and anxiety.

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Section: Discussionmentioning

confidence: 99%

Acute tryptophan depletion attenuates brain-heart coupling following external feedback

Mueller¹,

Evers²,

Wacker³

et al. 2012

Front. Hum. Neurosci.

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“…Instead of modeling the entire ERP waveform, different spatial and temporal filtering methods have been proposed by researchers to extract the most representative ERP features, components, or patterns that could best represent the user's intent. These includes methods based on orthogonal linear transformation (Dien et al 2003), blind source separation (Xu et al 2004, Li et al 2009a, Li et al 2009b, wavelet transform (Quian Quiroga andGarcia 2003, Bostanov andKotchoubey 2006) and other advanced techniques (Rivet et al 2009). These advanced feature extractors reduce the dimension of the feature space and capture the most distinctive information in a singletrial ERP for subsequent binary classification.…”

Section: Feature Extraction and Classification Algorithmsmentioning

confidence: 99%

Optimizing the P300-based brain–computer interface: current status, limitations and future directions

et al. 2011

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This paper summarizes the presentations and discussions at a workshop held during the Fourth International BCI Meeting charged with reviewing and evaluating the current state, limitations and future development of P300-based brain-computer interface (P300-BCI) systems. We reviewed such issues as potential users, recording methods, stimulus presentation paradigms, feature extraction and classification algorithms, and applications. A summary of the discussions and the panel's recommendations for each of these aspects are presented.

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“…Though P300 latency is an important factor for the P3 Speller, only a few very recent studies have attempted to explicitly calculate or correct for P300 latency. Researchers used Bayesian methods [25] and spatiotemporal filtering methods [26] to estimate properties of single-trial event-related potentials (ERPs), including latency estimates. But, surprisingly only one study has been found in the literature which attempted to correct latency jitter [27], using a maximum-likelihood estimation (MLE) method.…”

Section: Introductionmentioning

confidence: 99%

Enhancing P300-BCI performance using latency estimation

Mowla

Huggins

Thompson

2017

Brain-Computer Interfaces

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Brain Computer Interfaces (BCIs) offer restoration of communication to those with the most severe movement impairments, but performance is not yet ideal. Previous work has demonstrated that latency jitter, the variation in timing of the brain responses, plays a critical role in determining BCI performance. In this study, we used Classifier-Based Latency Estimation (CBLE) and a wavelet transform to provide information about latency jitter to a second-level classifier. Three second-level classifiers were tested: least squares (LS), step-wise linear discriminant analysis (SWLDA), and support vector machine (SVM). Of these three, LS and SWLDA performed better than the original online classifier. The resulting combination demonstrated improved detection of brain responses for many participants, resulting in better BCI performance. Interestingly, the performance gain was greatest for those individuals for whom the BCI did not work well online, indicating that this method may be most suitable for improving performance of otherwise marginal participants.

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Single-trial P300 estimation with a spatiotemporal filtering method

Cited by 22 publications

References 27 publications

Acute tryptophan depletion attenuates brain-heart coupling following external feedback

Acute tryptophan depletion attenuates brain-heart coupling following external feedback

Optimizing the P300-based brain–computer interface: current status, limitations and future directions

Enhancing P300-BCI performance using latency estimation

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