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PubMed2006

Sensitivity of alpha band ERD to individual differences in cognition.

According to the neural efficiency hypothesis, brighter individuals might be characterized by lower and topographically more differentiated brain activation than less intelligent individuals, presumably reflecting a more specialized recruitment of task-related areas. The findings of several studies analyzing the event-related desynchronization (ERD) in the (upper) alpha frequency band have corroborated and elaborated the original neural efficiency hypothesis. In this chapter, we review classical and recent findings and argue in favor of a more differentiated picture of this phenomenon, emphasizing the role of participants' sex, task complexity, and material specificity, as well as the importance to select an adequate external criterion (intelligence measure). Also, recent ERD findings related to emotional intelligence and creativity as well as recent studies focusing on practice, learning ability, and expertise are presented, which point to the need of a broader neurophysiological ability concept. The reviewed findings point at the high suitability of the ERD method to uncover consistent and stable individual differences in people's brain activation patterns when engaged in performing cognitively demanding tasks.

Alpha Rhythm↗
PubMed2006

Effect of deep brain stimulation and L-Dopa on electrocortical rhythms related to movement in Parkinson's disease.

In the early stages of Parkinson's disease (PD), impaired motor preparation has been related to a decrease in the latency of mu rhythm event-related desynchronisation (ERD) compared with control subjects, suggesting hypo activation of the contralateral, primary sensorimotor (PSM) cortex. Following movement, a decrease in amplitude of beta rhythm ERS was observed over the same region and thought to be related to impairment in cortical deactivation. By monitoring ERD/ERS, we aimed (i) to extend to advanced PD the observations made in less-advanced parkinsonism and (ii) to test the effect of acute L-Dopa, internal pallidal or subthalamic stimulation on these abnormalities. For the clinical evaluation the motor score of UPDRS decreased by about 60% under subthalamic stimulation and following acute L-Dopa administration and by 40% under internal pallidal stimulation. The following concurrent ERD/ERS changes under subthalamic stimulation and L-Dopa were observed: a marked increase in mu ERD latency during movement preparation over contralateral central region; an increase in mu ERD during movement execution over bilateral central regions; a decrease in mu ERD latency over bilateral frontocentral region and an increase in beta ERS over contralateral central region after movement. On the contrary, mu ERD latency was not improved under internal pallidal stimulation. Changes of mu and beta rhythm parameters seemed to be inversely correlated with bradykinesia. Mu rhythm ERD latency and the beta ERS amplitude further decreased in advanced PD compared with early stages, suggesting greater impairment of cortical activation/deactivation as the disease progresses and a partial restoration in relation to clinical improvement under treatments. Consequently, it appears that L-Dopa and deep brain stimulation partially restored the normal patterns of cortical oscillatory activity in PD, possibly by decreasing the low frequency hyper synchronisation at rest. This mechanism could be involved at the basal ganglia level in the sensorimotor integration implicated in the movement control.

Antiparkinson Agents↗
PubMed2006

Motor imagery and EEG-based control of spelling devices and neuroprostheses.

A brain-computer interface (BCI) transforms signals originating from the human brain into commands that can control devices or applications. With this, a BCI provides a new non-muscular communication channel, which can be used to assist patients who have highly compromised motor functions. The Graz-BCI uses motor imagery and associated oscillatory EEG signals from the sensorimotor cortex for device control. As a result of research in the past 15 years, the classification of ERD/ERS patterns in single EEG trials during motor execution and motor imagery forms the basis of this sensorimotor-rhythm controlled BCI. The major frequency bands of cortical oscillations considered here are the 8-13 and 15-30 Hz bands. This chapter describes the basic methods used in Graz-BCI research and outlines possible clinical applications.

Communication Devices for People with Disabilities↗
PubMed2001

A pattern grouping algorithm for analysis of spatiotemporal patterns in neuronal spike trains. 1. Detection of repeated patterns.

The existence of precise temporal relations in sequences of spike intervals, referred to as 'spatiotemporal patterns', is suggested by brain theories that emphasize the role of temporal coding. Specific analytical methods able to assess the significance of such patterned activity are extremely important to establish its function for information processing in the brain. This study proposes a new method called 'pattern grouping algorithm' (PGA), designed to identify and evaluate the statistical significance of patterns which differ from each other by a defined and small jitter in spike timing of the order of few ms. The algorithm performs a pre-selection of template patterns with a fast computational approach, optimizes the jitter for each spike in the template and evaluates the statistical significance of the pattern group using three complementary statistical approaches. Simulated data sets characterized by various types of known non stationarities are used for validation of PGA and for comparison of its performance to other methods. Applications of PGA to experimental data sets of simultaneously recorded spike trains are described in a companion paper (Tetko IV, Villa AEP. A pattern grouping algorithm for analysis of spatiotemporal patterns in neuronal spike trains. 2. Application to simultaneous single unit recordings. J Neurosci Method 2000; accompanying article).

Action Potentials↗
PubMed2001

Instantaneous multivariate EEG coherence analysis by means of adaptive high-dimensional autoregressive models.

This study presents an efficient algorithm for the fitting of multivariate autoregressive models (MVAR) with time-dependent parameters to multidimensional signals. Thereby, the dimension of the model may be chosen to equal the number of signal channels. The autoregressive (AR) parameter matrices are estimated by an extension of the recursive least squares (RLS) algorithm with forgetting factor. The estimation procedure includes a single trial as well as an ensemble mean approach. The latter approach allows the simultaneous fit of one mean MVAR model to a set of single trials, each of them representing the measurement of the same task. A particular advantage of this ensemble mean approach is that it requires only a low computation effort in comparison to well known procedures applied to single trials. Furthermore, the ensemble mean approach is linked with a high adaptation capability. The properties of the estimator are investigated using simulated time series. It can be demonstrated that the adaptation capability of the estimation (measured by its adaptation speed and variance) does not depend on the model dimension. The mean MVAR fit is applied to 19-dimensional EEG data, recorded during an elementary comparison procedure. The calculation of ordinary and multiple coherence is discussed. The sensitivity of the multiple instantaneous EEG coherence will be demonstrated.

Algorithms↗
PubMed2001

Trial to trial variability in either stimulus or action causes apparent correlation and synchrony in neuronal activity.

In this report we show that the observed inter-neuronal correlation reflects a superposition of correlations associated with the intrinsic correlation between neurons, and correlations associated with variability in the stimuli presented to, or the actions performed by, the subject. We argue that the effects of either stimulus or action variability on the observed correlation, though generally ignored, can be substantial. Specifically, we demonstrate how observed correlations are effected by trial to trial variability in either stimulus or action. In addition, assuming that all relevant stimuli and actions are known, we outline a method for eliminating their effects on the observed correlation. It is also shown that tuning of correlations to a stimulus or an action might be a direct consequence of variability in that stimulus or action, even in the absence of any modulation of direct inter-neuronal interaction. The effects of stimulus and action variability should therefore be carefully considered when designing and interpreting experiments involving multi-neuronal recordings.

Action Potentials↗
PubMed2003

Multi-channel evoked response detection using only phase information.

The phase consistency of contiguous segments of the electroencephalogram (EEG) has been used in the detection of evoked responses to rhythmic stimulation. One of such techniques is the component synchrony measure (CSM), which is often used since the threshold for the detection task is easily obtained based on the estimates of asymptotic sample distribution. In this work we investigated the appropriateness of such thresholds for practical number of segments (M). The performance of CSM was next evaluated by Monte Carlo simulations with different signal-to-noise ratios (SNR) and values of M, and the results, compared with those for the magnitude-squared coherence. A way of improving the detection with CSM was also proposed, by suggesting the estimation taking into account the mean phase angle of a set of N signals. This multivariate detector was evaluated in simulations and an illustration of the technique was also given with the EEG of 14 subjects during photic stimulation. In simulated signals with equal SNR, the detection rate with this multivariate measure increased with N. The application to EEG data lead to similar results in 70% of the subjects, which suggests that improvements might be expected when more signals are available to detect evoked responses in EEG.

Acoustic Stimulation↗
PubMed1999

Adaptive phase estimation and its application in EEG analysis of word processing.

Oscillations are a general phenomenon of neuronal activity during information processing. Mostly, widespread networks are involved in brain functioning. In order to investigate network activity coherence analysis turned out to be a useful tool for examining the functional relationship between different cortical areas. This parameter allows the investigation of synchronisation phenomena with regard to defined frequencies or frequency bands. Coherence and cross phase are closely connected spectral parameters. Coherence may be understood as a measure of phase stability. Whereas coherence describes the amount of information transfer, the corresponding phase, from which time delays can be computed, hints at the direction of information transfer. Mental processes can be very brief and coupling between different areas may be highly dynamic. For this reason a two-dimensional approach of adaptive filtering was developed to estimate coherence and phase continuously in time. Statistical and dynamic properties of instantaneous phase are discussed. In order to demonstrate the value of this method for studying higher cognitive processes the method was applied to EEG recorded during word processing. During visual presentation of abstract nouns an information transfer from visual areas to frontal association areas in the Alpha1 frequency band could be verified within the first 400 ms. The Alpha1 band predominately seems to reflect sensory processing and attentional processes. In addition to conventional coherence analyses during word processing phase estimations may yield valuable new insights into the physiological mechanisms during word processing.

Adult↗
PubMed2003

Interneuron Diversity series: Rhythm and mood in perisomatic inhibition.

GABAergic interneurons innervating the perisomatic region of pyramidal cells control population discharge patterns, and thereby all cognitive operations in the cerebral cortex. A striking dichotomy in the function of this interneuron population seems to emerge from the synthesis of recent molecular, anatomical and electrophysiological data. Synaptically and electrically coupled networks of parvalbumin-containing basket cells operate as a non-plastic, precision clockwork for gamma and theta oscillations, and are indispensable for basic cortical processing. By contrast, a highly modifiable interneuron syncytium containing cholecystokinin carries information from subcortical pathways about the emotional, motivational and general physiological state of the animal, and appears to be involved in the fine-tuning of network cooperativity. Impairment of this inhibitory mechanism is likely to result in mood disorders such as anxiety.

Affect↗
PubMed2000

Discharge patterns of neurons in cholinergic regions of the basal forebrain during waking and sleep.

A subset of neurons recorded in the magnocellular basal forebrain (mBF) of cats and rats exhibit elevated discharge rates during waking and REM sleep, and diminished discharge during sleep with cortical EEG synchrony (nonREM sleep). This pattern is observed in mBF neurons in cats with identified ascending projections, and in neurons located in cholinergic regions of the rat mBF. However, the cholinergic versus noncholinergic nature of recorded cells could not be determined with the extracellular recording method employed. During waking, discharge of mBF neurons is strongly movement-related. Peak discharge rates occur during a variety of head and limb movements. Discharge rates during waking immobility are reduced by >50% compared to rates during waking movement. The absence of movement accounts for more of the variance in discharge across the sleep-wake cycle than does the presence of cortical EEG synchronization. Several factors participate in the regulation of mBF neuronal activity across arousal states. Tonic inhibition mediated by adenosine appears to be present during both waking and sleep. In some mBF neurons, increased GABAergic inhibition contributes to nonREM sleep-related reductions in discharge rate. Fluctuations in mBF cell activity during waking behaviors may reflect changing excitatory input from neurons in the pontine and midbrain tegmentum.

Animals↗
PubMed2002

Sleep and wakefulness in the southern sea lion.

We recorded an electroencephalogram from the two hemispheres, a neck musculature electromyogram, an electrooculogram, and respiratory acts during sleep and wakefulness on land in three 1-year-old sea lion females for 3 or 4 consecutive days. On average active wakefulness (AW) occupied 20.4+/-2.0% of the 24-h period; quiet wakefulness (QW) 54.9+/-2.5%; slow wave sleep (SWS) 15.0+/-2.5% and paradoxical sleep (PS) 9.7+/-2.0%. Between 30 and 50% (average 39.1+/-3.4%) of total sleep time was spent in PS. From 8 to 31 episodes of PS were recorded per day (average 17+/-6 per day), with the longest episode lasting 20 min (average 5.6+/-0.5 min). Episodes of interhemispheric EEG asymmetry accounted for 5.5+/-1.3% of total SWS time. Respiratory pauses in these animals varied in QW between 4 and 36 s (average 15.7+/-0.4 s), in SWS between 11 and 37 s (20.9+/-0.6 s) and in PS between 2 and 69 s (15.0+/-1.5 s). AW, QW, SWS and PS were approximately equally distributed between light (07:00-19:00) and dark time (19:00-07:00). The low amount of SWS with interhemispheric EEG asymmetry, the high proportion of PS in total sleep time and the nearly even distribution of sleep and wakefulness over the 24-h period could be both species-specific features and/or ontogenetic characteristics of the animals studied.

Animals↗