Automated identification of ERP peaks through Dynamic Time Warping: an application to developmental dyslexia.

OBJECTIVE: This article proposes a method to automatically identify and label event-related potential (ERP) components with high accuracy and precision. METHODS: We present a framework, referred to as peak-picking Dynamic Time Warping (ppDTW), where a priori knowledge about the ERPs under investigation is used to define a reference signal. We developed a combination of peak-picking and Dynamic Time Warping (DTW) that makes the temporal intervals for peak-picking adaptive on the basis of the morphology of the data. We tested the procedure on experimental data recorded from a control group and from children diagnosed with developmental dyslexia. RESULTS: We compared our results with the traditional peak-picking. We demonstrated that our method achieves better performance than peak-picking, with an overall precision, recall and F-score of 93%, 86% and 89%, respectively, versus 93%, 80% and 85% achieved by peak-picking. CONCLUSION: We showed that our hybrid method outperforms peak-picking, when dealing with data involving several peaks of interest. SIGNIFICANCE: The proposed method can reliably identify and label ERP components in challenging event-related recordings, thus assisting the clinician in an objective assessment of amplitudes and latencies of peaks of clinical interest.

Removing muscle and eye artifacts using blind source separation techniques in ictal EEG source imaging.

OBJECTIVE: The contamination of muscle and eye artifacts during an ictal period of the EEG significantly distorts source estimation algorithms. Recent blind source separation (BSS) techniques based on canonical correlation (BSS-CCA) and independent component analysis with spatial constraints (SCICA) have shown much promise in the removal of these artifacts. In this study we want to use BSS-CCA and SCICA as a preprocessing step before the source estimation during the ictal period. METHODS: Both the contaminated and cleaned ictal EEG were subjected to the RAP-MUSIC algorithm. This is a multiple dipole source estimation technique based on the separation of the EEG in signal and noise subspace. The source estimates were compared with the subtracted ictal SPECT (iSPECT) coregistered to magnetic resonance imaging (SISCOM) by means of the euclidean distance between the iSPECT activations and the dipole location estimates. SISCOM results in an image denoting the ictal onset zone with a propagation. RESULTS: We applied the artifact removal and the source estimation on 8 patients. Qualitatively, we can see that 5 out of 8 patients show an improvement of the dipoles. The dipoles are nearer to or have tighter clusters near the iSPECT activation. From the median of the distance measure, we could appreciate that 5 out of 8 patients show improvement. CONCLUSIONS: The results show that BSS-CCA and SCICA can be applied to remove artifacts, but the results should be interpreted with care. The results of the source estimation can be misleading due to excessive noise or modeling errors. Therefore, the accuracy of the source estimation can be increased by preprocessing the ictal EEG segment by BSS-CCA and SCICA. SIGNIFICANCE: This is a pilot study where EEG source localization in the presurgical evaluation can be made more reliable, if preprocessing techniques such as BSS-CCA and SCICA are used prior to EEG source analysis on ictal episodes.

Computed tomographic changes of the brain and clinical outcome of patients with seizures and epilepsy after an ischaemic hemispheric stroke.

It is not well established whether seizures and epilepsy after an ischaemic stroke increase the disability of patients. Seventy-two patients with delayed seizures after a hemispheric infarct (37 with a single seizure and 35 with epilepsy) were included in the study. The modified Rankin scale was used to compare disability of the patients at 1 month after stroke and at 2 weeks after single or the last seizure, in case of epilepsy. The size of the X-ray hypoattenuation zone was compared on computed tomographic (CT) scans, performed in the weeks after the stroke and 1 week after single or repeated seizures. Lesion size was determined by superimposing the CT slices on digital cerebral vascular maps, on which the contours of the infarct area were delineated. The extent of the infarcts was expressed as the percentage fraction of the total surface area of the cerebral hemisphere. Groups with a single seizure and with epilepsy were mutually compared. Infarcts predominated in the parieto-temporal cortical regions. In the overall group the median Rankin score worsened significantly after seizures. The average size of the X-ray hypoattenuation zone was also significantly increased on the CT scans after the seizures, compared with those after stroke, without clear evidence of recent infarction. Mutual comparison of patients with a single seizure episode and of those with epilepsy showed only a trend of more severe disability and of increase in lesion size in the post-stroke epilepsy group. Delayed seizures and epilepsy after ischaemic stroke are accompanied by an increase in lesion size on CT and by worsening of the disability of the patients. This study does not allow to determine whether this is due to stroke recurrence or due to additional damage as a result of the seizures themselves.