Interchannel coherence is a measure of spatial extent of and timing relationships among cerebral electroencephalogram (EEG) generators. Interchannel coherence of referentially recorded potentials includes components due to volume conduction and reference site activity. The laplacian of the potential is reference independent and decreases the contribution of volume conduction. Interchannel coherences of the laplacian should, therefore, be less than those of referentially recorded potentials. However, methods used to compute the laplacian involve forming linear combinations of multiple recorded potentials, which may inflate interchannel coherences. WE compared 3 methods of computing the laplacian: (1) modified Hjorth (4 equidistant neighbors to each electrode), (2) Taylor's series (4 nonequidistant neighbors), and (3) spherical harmonic expansion (SHE). Average interchannel coherence introduced by computing the laplacian was less for nearest-neighbor methods (0.0207 +/- 0.0766) but still acceptable for the SHE method (0.0337 +/- 0.0865). Average interchannel coherence for simulated EEG (random data plus a common 10 Hz signal) was less for laplacian than for referential data because of removal of the common referential signal. Interchannel coherences of background EEG and partial seizure activity were less with the laplacian (any method) than with referential recordings. Laplacians calculated from the SHE do not demonstrate excessively large interchannel coherences, as have been reported for laplacians from spherical splines.
"When averaged across pairs of electrodes, the index R ij represents a measure of global synchronization strength R À Á . For this analysis, before computing the wavelet-coefficients, the raw EEG trials were first transformed with a modified version of the nearest-neighbor Hjorth Laplacian algorithm computed by Taylor's series expansion (Lagerlund et al., 1995 "
[Show abstract][Hide abstract] ABSTRACT: Skilled performance requires the ability to monitor ongoing behavior, detect errors in advance and modify the performance accordingly. The acquisition of fast predictive mechanisms might be possible due to the extensive training characterizing expertise performance. Recent EEG studies on piano performance reported a negative event-related potential (ERP) triggered in the ACC 70 ms before performance errors (pitch errors due to incorrect keypress). This ERP component, termed pre-error related negativity (pre-ERN), was assumed to reflect processes of error detection in advance. However, some questions remained to be addressed: (i) Does the electrophysiological marker prior to errors reflect an error signal itself or is it related instead to the implementation of control mechanisms? (ii) Does the posterior frontomedial cortex (pFMC, including ACC) interact with other brain regions to implement control adjustments following motor prediction of an upcoming error? (iii) Can we gain insight into the electrophysiological correlates of error prediction and control by assessing the local neuronal synchronization and phase interaction among neuronal populations? (iv) Finally, are error detection and control mechanisms defective in pianists with musician's dystonia (MD), a focal task-specific dystonia resulting from dysfunction of the basal ganglia-thalamic-frontal circuits? Consequently, we investigated the EEG oscillatory and phase synchronization correlates of error detection and control during piano performances in healthy pianists and in a group of pianists with MD. In healthy pianists, the main outcomes were increased pre-error theta and beta band oscillations over the pFMC and 13-15 Hz phase synchronization, between the pFMC and the right lateral prefrontal cortex, which predicted corrective mechanisms. In MD patients, the pattern of phase synchronization appeared in a different frequency band (6-8 Hz) and correlated with the severity of the disorder. The present findings shed new light on the neural mechanisms, which might implement motor prediction by means of forward control processes, as they function in healthy pianists and in their altered form in patients with MD.
"The average of this index across pairs of electrodes represents a measure of global synchronization strength (R). For the bivariate synchronization analysis, a modified version of the nearestneighbour Hjorth Laplacian algorithm computed by Taylor's series expansion (Lagerlund et al., 1995 "
[Show abstract][Hide abstract] ABSTRACT: The ability to anticipate forthcoming events has clear evolutionary advantages, and predictive successes or failures often entail significant psychological and physiological consequences. In music perception, the confirmation and violation of expectations are critical to the communication of emotion and aesthetic effects of a composition. Neuroscientific research on musical expectations has focused on harmony. Although harmony is important in Western tonal styles, other musical traditions, emphasizing pitch and melody, have been rather neglected. In this study, we investigated melodic pitch expectations elicited by ecologically valid musical stimuli by drawing together computational, behavioural, and electrophysiological evidence. Unlike rule-based models, our computational model acquires knowledge through unsupervised statistical learning of sequential structure in music and uses this knowledge to estimate the conditional probability (and information content) of musical notes. Unlike previous behavioural paradigms that interrupt a stimulus, we devised a new paradigm for studying auditory expectation without compromising ecological validity. A strong negative correlation was found between the probability of notes predicted by our model and the subjectively perceived degree of expectedness. Our electrophysiological results showed that low-probability notes, as compared to high-probability notes, elicited a larger (i) negative ERP component at a late time period (400-450 ms), (ii) beta band (14-30 Hz) oscillation over the parietal lobe, and (iii) long-range phase synchronization between multiple brain regions. Altogether, the study demonstrated that statistical learning produces information-theoretic descriptions of musical notes that are proportional to their perceived expectedness and are associated with characteristic patterns of neural activity.
"For each single subject the averaged MMN waveform was cross-correlated to the MMN grand-averaged envelope — defined as the minimum value among all electrodes for each time frame, of the control group, and the maximum delay value resulting from the cross-correlation was then used to align the individual MMN waveform. Prior to SCD estimation by mean of a Laplacian operator (Perrin et al., 1989), individual data were interpolated in a spherical scalp model using 1000 pixels by means of a Spherical Harmonics Expansion (Lagerlund et al., 1995), according to the method described by Ruffini et al. (2002). A scalp area was considered activated on the grand-average SCD map if 4 adjacent pixels showed p b 0.05 relative to prestimulus interval during 6 consecutive time frames using the Holmes non-parametric method, that is corrected from multiple comparisons (Holmes et al., 1996). "
[Show abstract][Hide abstract] ABSTRACT: Previous studies, based on amplitude and latency measurements of auditory event-related brain potentials, yielded inconclusive results about the status of mismatch negativity (MMN) in chronic alcoholics. The present study explores scalp current density (SCD) dynamics during MMN latency range in alcoholics, and correlates electrical SCD results with clinical data of the patients. SCD was computed from 30 electrodes in 16 abstinent chronic alcoholics and 16 healthy control volunteers in a paradigm on MMN elicited by duration changes. Reduced activity was observed in left frontal and right anterior and posterior temporal areas during MMN in alcoholics. Alcohol consumption correlated negatively with SCD intensity in these regions. Delayed activation was observed in the left posterior temporal area in the patients. Alcohol abstinence duration correlated positively with SCD intensity in this region. These results point to an impairment of automatic brain processing mechanisms associated with auditory change detection in chronic alcoholism. The present results suggest a reorganization of the computational neurodynamics of automatic auditory change detection linked to the amount of alcohol consumed in abstinent chronic alcoholics.
International Journal of Psychophysiology 08/2007; 65(1):51-7. DOI:10.1016/j.ijpsycho.2007.03.001 · 2.88 Impact Factor
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.