Filtering and thresholding the analytic signal envelope in order to improve peak and spike noise reduction in EEG signals

To remove peak and spike artifacts in biological time series has represented a hard challenge in the last decades. Several methods have been implemented mainly based on adaptive filtering in order to solve this problem. This work presents an algorithm for removing peak and spike artifacts based on a threshold built on the analytic signal envelope. The algorithm was tested on simulated and real EEG signals that contain peak and spike artifacts with random amplitude and frequency occurrence. The performance of the filter was compared with commonly used adaptive filters. Three indexes were used for testing the performance of the filters: Correlation coefficient, mean of coherence function, and rate of absolute error. All these indexes were calculated between filtered signal and original signal without noise. It was found that the new proposed filter was able to reduce the amplitude of peak and spike artifacts with > 0.85, C > 0.8, and RAE 1)

New feature extraction approach for epileptic EEG signal detection using time-frequency distributions

10 pages, 6 figures.-- PMID: 20217264.This paper describes a new method to identify seizures in electroencephalogram (EEG) signals using feature extraction in time–frequency distributions (TFDs). Particularly, the method extracts features from the Smoothed Pseudo Wigner-Ville distribution using tracks estimated from the McAulay-Quatieri sinusoidal model. The proposed features are the length, frequency, and energy of the principal track. We evaluate the proposed scheme using several datasets and we compute sensitivity, specificity, F-score, receiver operating characteristics (ROC) curve, and percentile bootstrap confidence to conclude that the proposed scheme generalizes well and is a suitable approach for automatic seizure detection at a moderate cost, also opening the possibility of formulating new criteria to detect, classify or analyze abnormal EEGs.This work has been funded by the Spain CICYT grant TEC2008-02473.Publicad

Magnetoencephalography

This is a practical book on MEG that covers a wide range of topics. The book begins with a series of reviews on the use of MEG for clinical applications, the study of cognitive functions in various diseases, and one chapter focusing specifically on studies of memory with MEG. There are sections with chapters that describe source localization issues, the use of beamformers and dipole source methods, as well as phase-based analyses, and a step-by-step guide to using dipoles for epilepsy spike analyses. The book ends with a section describing new innovations in MEG systems, namely an on-line real-time MEG data acquisition system, novel applications for MEG research, and a proposal for a helium re-circulation system. With such breadth of topics, there will be a chapter that is of interest to every MEG researcher or clinician

Assessing Neuronal Synchrony and Brain Function Through Local Field Potential and Spike Analysis

Studies of neuronal network oscillations and rhythmic neuronal synchronization have led to a number of important insights in recent years, giving us a better understanding of the temporal organization of neuronal activity related to essential brain functions like sensory processing and cognition. Important principles and theories have emerged from these findings, including the communication through coherence hypothesis, which proposes that synchronous oscillations render neuronal communication effective, selective, and precise. The implications of such a theory may be universal for brain function, as the determinants of neuronal communication inextricably shape the neuronal representation of information in the brain. However, the study of communication through coherence is still relatively young. Since its articulation in 2005, the theory has predominantly been applied to assess cortical function and its communication with downstream targets in different sensory and behavioral conditions. The results herein are intended to bolster this hypothesis and explore new ways in which oscillations coordinate neuronal communication in distributed regions. This includes the development of new analytic tools for interpreting electrophysiological patterns, inspired by phase synchronization and spike train analysis. These tools aim to offer fast results with clear statistical and physiological interpretation

Continuous-time acquisition of biosignals using a charge-based ADC topology

This paper investigates continuous-time (CT) signal acquisition as an activity-dependent and nonuniform sampling alternative to conventional fixed-rate digitisation. We demonstrate the applicability to biosignal representation by quantifying the achievable bandwidth saving by nonuniform quantisation to commonly recorded biological signal fragments allowing a compression ratio of ≈5 and 26 when applied to electrocardiogram and extracellular action potential signals, respectively. We describe several desirable properties of CT sampling, including bandwidth reduction, elimination/reduction of quantisation error, and describe its impact on aliasing. This is followed by demonstration of a resource-efficient hardware implementation. We propose a novel circuit topology for a charge-based CT analogue-to-digital converter that has been optimized for the acquisition of neural signals. This has been implemented in a commercially available 0.35 μm CMOS technology occupying a compact footprint of 0.12 mm 2 . Silicon verified measurements demonstrate an 8-bit resolution and a 4 kHz bandwidth with static power consumption of 3.75 μW from a 1.5 V supply. The dynamic power dissipation is completely activity-dependent, requiring 1.39 pJ energy per conversion

Retinal oscillations carry visual information to cortex

Thalamic relay cells fire action potentials that transmit information from retina to cortex. The amount of information that spike trains encode is usually estimated from the precision of spike timing with respect to the stimulus. Sensory input, however, is only one factor that influences neural activity. For example, intrinsic dynamics, such as oscillations of networks of neurons, also modulate firing pattern. Here, we asked if retinal oscillations might help to convey information to neurons downstream. Specifically, we made whole-cell recordings from relay cells to reveal retinal inputs (EPSPs) and thalamic outputs (spikes) and analyzed these events with information theory. Our results show that thalamic spike trains operate as two multiplexed channels. One channel, which occupies a low frequency band (<30 Hz), is encoded by average firing rate with respect to the stimulus and carries information about local changes in the image over time. The other operates in the gamma frequency band (40-80 Hz) and is encoded by spike time relative to the retinal oscillations. Because these oscillations involve extensive areas of the retina, it is likely that the second channel transmits information about global features of the visual scene. At times, the second channel conveyed even more information than the first.Comment: 21 pages, 10 figures, submitted to Frontiers in Systems Neuroscienc

Applying stochastic spike train theory for high-accuracy human MEG/EEG

Background The accuracy of electroencephalography (EEG) and magnetoencephalography (MEG) in measuring neural evoked responses (ERs) is challenged by overlapping neural sources. This lack of accuracy is a severe limitation to the application of ERs to clinical diagnostics. New method We here introduce a theory of stochastic neuronal spike timing probability densities for describing the large-scale spiking activity in neural assemblies, and a spike density component analysis (SCA) method for isolating specific neural sources. The method is tested in three empirical studies with 564 cases of ERs to auditory stimuli from 94 humans, each measured with 60 EEG electrodes and 306 MEG sensors, and a simulation study with 12,300 ERs. Results The first study showed that neural sources (but not non-encephalic artifacts) in individual averaged MEG/EEG waveforms are modelled accurately with temporal Gaussian probability density functions (median 99.7 %–99.9 % variance explained). The following studies confirmed that SCA can isolate an ER, namely the mismatch negativity (MMN), and that SCA reveals inter-individual variation in MMN amplitude. Finally, SCA reduced errors by suppressing interfering sources in simulated cases. Comparison with existing methods We found that gamma and sine functions fail to adequately describe individual MEG/EEG waveforms. Also, we observed that principal component analysis (PCA) and independent component analysis (ICA) does not consistently suppress interference from overlapping brain activity in neither empirical nor simulated cases. Conclusions These findings suggest that the overlapping neural sources in single-subject or patient data can be more accurately separated by applying SCA in comparison to PCA and ICA.Peer reviewe

Manifestation of ocular-muscle EMG contamination in human intracranial recordings

It is widely assumed that intracranial recordings from the brain are only minimally affected by contamination due to ocular-muscle electromyogram (oEMG). Here we show that this is not always the case. In intracranial recordings from five surgical epilepsy patients we observed that eye movements caused a transient biphasic potential at the onset of a saccade, resembling the saccadic spike potential commonly seen in scalp EEG, accompanied by an increase in broadband power between 20 and 200 Hz. Using concurrently recorded eye movements and high-density intracranial EEG (iEEG) we developed a detailed overview of the spatial distribution and temporal characteristics of the saccade-related oculomotor signal within recordings from ventral, medial and lateral temporal cortex. The occurrence of the saccadic spike was not explained solely by reference contact location, and was observed near the temporal pole for small (< 2 deg) amplitude saccades and over a broad area for larger saccades. We further examined the influence of saccade-related oEMG contamination on measurements of spectral power and interchannel coherence. Contamination manifested in both spectral power and coherence measurements, in particular, over the anterior half of the ventral and medial temporal lobe. Next, we compared methods for removing the contaminating signal and found that nearest-neighbor bipolar re-referencing and ICA filtering were effective for suppressing oEMG at locations far from the orbits, but tended to leave some residual contamination at the temporal pole. Finally, we show that genuine cortical broadband gamma responses observed in averaged data from ventral temporal cortex can bear a striking similarity in time course and band-width to oEMG contamination recorded at more anterior locations. We conclude that eye movement-related contamination should be ruled out when reporting high gamma responses in human intracranial recordings, especially those obtained near anterior and medial temporal lobe