Interelectrode coherences from nearest-neighbor and spherical harmonic expansion computation of laplacian of scalp potential.
ABSTRACT 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.
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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.NeuroImage 12/2010; 55(4):1791-803. · 6.25 Impact Factor
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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.NeuroImage 12/2009; 50(1):302-13. · 6.25 Impact Factor
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ABSTRACT: Recent findings link fronto-temporal gamma electroencephalographic (EEG) activity to conscious awareness in dreams, but a causal relationship has not yet been established. We found that current stimulation in the lower gamma band during REM sleep influences ongoing brain activity and induces self-reflective awareness in dreams. Other stimulation frequencies were not effective, suggesting that higher order consciousness is indeed related to synchronous oscillations around 25 and 40 Hz.Nature Neuroscience 05/2014; · 15.25 Impact Factor