Averaging of spectral power and phase via vector diagram best fits without reference electrode or reference channel

The application of electro- and magneto-encephalography in tinnitus research - methods and interpretations

In recent years, there has been a significant increase in the use of electroencephalography (EEG) and magnetoencephalography (MEG) to investigate changes in oscillatory brain activity associated with tinnitus with many conflicting results. Current view of the underlying mechanism of tinnitus is that it results from changes in brain activity in various structures of the brain as a consequence of sensory deprivation. This in turn gives rise to increased spontaneous activity and/or synchrony in the auditory centers but also involves modulation from non-auditory processes from structures of the limbic and paralimbic system. Some of the neural changes associated with tinnitus may be assessed non-invasively in human beings with MEG and EEG (M/EEG) in ways, which are superior to animal studies and other non-invasive imaging techniques. However, both MEG and EEG have their limitations and research results can be misinterpreted without appropriate consideration of these limitations. In this article, I intend to provide a brief review of these techniques, describe what the recorded signals reflect in terms of the underlying neural activity, and their strengths and limitations. I also discuss some pertinent methodological issues involved in tinnitus-related studies and conclude with suggestions to minimize possible discrepancies between results. The overall message is that while MEG and EEG are extremely useful techniques, the interpretation of results from tinnitus studies requires much caution given the individual variability in oscillatory activity and the limits of these techniques.

Spatiotemporal analysis of multichannel EEG: CARTOOL

This paper describes methods to analyze the brain's electric fields recorded with multichannel Electroencephalogram (EEG) and demonstrates their implementation in the software CARTOOL. It focuses on the analysis of the spatial properties of these fields and on quantitative assessment of changes of field topographies across time, experimental conditions, or populations. Topographic analyses are advantageous because they are reference independents and thus render statistically unambiguous results. Neurophysiologically, differences in topography directly indicate changes in the configuration of the active neuronal sources in the brain. We describe global measures of field strength and field similarities, temporal segmentation based on topographic variations, topographic analysis in the frequency domain, topographic statistical analysis, and source imaging based on distributed inverse solutions. All analysis methods are implemented in a freely available academic software package called CARTOOL. Besides providing these analysis tools, CARTOOL is particularly designed to visualize the data and the analysis results using 3-dimensional display routines that allow rapid manipulation and animation of 3D images. CARTOOL therefore is a helpful tool for researchers as well as for clinicians to interpret multichannel EEG and evoked potentials in a global, comprehensive, and unambiguous way.

Impaired imagery for upper limbs

The brain processes associated with mental imagery have long been a matter of debate. Neuroimaging and neuropsychological studies have yielded diverging evidence of mental transformation activating the right hemisphere, the left hemisphere, or both. Here, using a mirror/normal discrimination task with rotated body parts (BPs) and external objects (EOs), we describe the case of a patient who developed a selective deficit in mental imagery of such BPs due to left posterior parietal brain damage. In addition, the patient's deficit predominated for pictures of right arms (i.e., arms corresponding to the patient's imagined contralesional arm) and was further characterised by an inability to distinguish between anatomically possible and impossible arm positions. This neuropsychological deficit was corroborated by neuroimaging evidence revealing the absence of activation in the left parietal lobe for the mental rotation of body parts as shown in healthy participants. In contrast, his behavioural performance and brain activation for EOs were similar to those of healthy participants. These data suggest that mental imagery of BPs and EOs relies on different cognitive and neural mechanisms and indicate that the left posterior parietal lobe is a necessary structure for mental transformations of human BPs.

Spherical splines and average referencing in scalp electroencephalography

EEG analysis and interpretation are affected by the reference electrode. Average referenced potentials are used widely to approximate the potentials relative to infinity, but estimates of the average surface potential are prone to errors due to incomplete sampling of the scalp surface. Even if the electrode density is high, this arises by not sampling the inferior scalp surface. This paper shows analytically how the spherical splines represent the average surface potential. It also shows that, for spline orders m > or = 3, the interpolating function is well approximated by its large-m limit, weighting near and distant electrodes with opposite signs. Together these motivate the hypothesis that spherical splines permit a better estimate of the potentials relative to infinity than the discrete average computed over superior scalp electrodes. It tests this hypothesis using numerical simulations in a four-sphere head model with single- and many-dipole sources, and variations in spline order, electrode number and head model parameters. The results confirm that the spherical splines yield a better estimate of the potentials relative to infinity, provided the electrode sampling density is adequate.

Distributed source imaging of alpha activity using a maximum entropy principle

OBJECTIVE

We present a method based on the distributed dipole source model to localize sources of spontaneous human brain activity, such as the alpha rhythm. The proposed method relies on the generalized maximum entropy principle and is implemented in frequency-domain.

METHODS

Several computer simulation studies of synchronous and asynchronous distributed dipole sources were carried out to test the validity of the method. The method was also applied to spontaneous electroencephalographic (EEG) recordings from human subjects to estimate the sources of alpha activity. The locations of these sources were registered with actual magnetic resonance images for anatomical visualization.

RESULTS

The simulation studies suggest the validity of the proposed method and its capability to detect distributed and fairly deep synchronous dipole sources. Results of human studies with 6 subjects suggest that the generators of alpha rhythm are mainly concentrated over the posterior regions of the cortex.

CONCLUSION

The proposed distributed source imaging method is a promising technique for localizing rhythmic brain activity.

FFT approximation in Alzheimer's disease

The electroencephalographic modifications that occur during the course of Alzheimer's disease are characterised by an increase in the potential of low frequency bands, a diminution in the potential of alpha activity, and a change in the topographical distribution of the potential of all band frequencies. In this study, the fast Fourier transform (FFT) approximation was used to characterise modifications in the electroencephalogram location or orientation of the source of the dipole equivalent of the delta, theta, alpha1, alpha2, beta1 and beta2 frequencies in 20 with patients with Alzheimer's disease and in a control group of 20 age-matched subjects. A statistical (t-test) comparison of the two groups revealed a significant change in the location of the dipolar source along the vertical axis in 18 (90%) of the patients; this change involved all the frequency bands. There was also a significant movement of the dipolar source of the alpha1 band towards the anterior regions. In addition, the control group showed that there was a significant correlation between age and a more surface expression of the source of the delta, theta, alpha1 and beta1 bands.

Optimal reference electrode selection for electric source imaging

One goal of recording voltages on the scalp is to form images of electrical sources across the cerebral cortex (electric source imaging). In this study, an objective criterion is introduced for selecting the optimal location for the reference electrode to attain the maximum spatial resolution of the source image, for example as provided here by the truncated singular value decomposition pseudo-inverse solution. The head model features a realistic cortex within a 3-shell conductive sphere, and pyramidal cell activity is represented by 9104 normal current elements distributed across the cortical area. On the scalp, 234 electrodes provide the measurements with respect to a chosen reference electrode. The effects of the reference electrode when located at the mastoid, occipital pole, vertex or center of the head are analyzed by a singular value decomposition of the lead field matrices. Sensitivity to noise, and hence the spatial resolution, is found to depend on characteristics of the lead field matrix that are determined by the choice of the image source surface, electrode array and location of the reference electrode. Using a reference close to a source surface increases the sensitivity of the measurement system in identifying the nearby activity of low spatial frequency content. However, this feature is compromised by a reduction in spatial resolution for distant cortical areas due to noise in the measurements. A new performance measure, the image sensitivity map, is introduced to identify the cortical regions that provide peak image sensitivity. This measure may be exploited in designing the geometry of an electrode array and selecting the location of the reference electrode to follow the activity on a specific area of the cortical surface.

Topographic EEG changes due to hypobaric hypoxia at simulated high altitude

Multichannel human EEG signals were studied topographically in subjects exposed to an atmosphere of reduced air pressure in a chamber in which high-altitude conditions were simulated. EEG signals from 16 electrodes placed on the scalp were recorded simultaneously with electrocardiography and vertical eye movement. Baseline records were first obtained at sea level (PRE 0 m), and then at reduced air pressures corresponding to the altitudes of 3000 m, 4000 m, and 6000 m, respectively, and after returning to sea level (POST 0 m). A complete set of EEG records under all 6 conditions was obtained in 5 of the 15 subjects, and under 5 conditions (all except the 6000 m condition) in 3 other subjects. The spectral powers of 1 min epochs of the multichannel EEG signal under each altitude condition were compared to that at PRE 0 m using analysis of variance. Under the 3000 m condition, the spectral power of the 10-11 Hz components was significantly decreased and, with increasing altitude, significant decrease of spectral power was observed in a wider range of the alpha frequency band. Under the 6000 m condition, the decrease of spectral power of the alpha band in the posterior brain areas was -7 dB compared to the baseline. In contrast, the spectral power of the theta frequency band in anterior brain areas increased significantly in the 5000 m and 6000 m conditions. At the POST 0 m condition after return from the 5000 m condition (without exposure to the 6000 m condition), the EEG showed recovery to the level of the baseline PRE 0 m condition.(ABSTRACT TRUNCATED AT 250 WORDS)

A comparison of period amplitude and power spectral analysis of sleep EEG in normal adults and depressed outpatients

Three experiments were carried out to evaluate the relationship between two techniques for quantifying electroencephalographic (EEG) data during sleep: period amplitude analysis (PAA) and power spectral analysis (PSA). In Experiment 1, canonical correlations and regression analyses were computed on PSA and PAA data from 40 undergraduate volunteers. The results yielded an average canonical correlation of 0.98. Further, multiple regression analyses demonstrated that the PSA variables accounted for approximately 66% of the variance in the PAA data, whereas PAA variables captured 88% of the variance in the PSA data. Epoch-to-epoch correlations were higher for PAA measures than for PSA data, perhaps indicating greater stability of PSA measures across epochs of sleep. In Experiment 2, PSA and PAA data were compared in 17 unmedicated outpatients with unipolar depression. Canonical correlations and regression analyses indicated that the overlap in variance between PSA and PAA did not exceed 50%, regardless of whether PSA or PAA variables were used as predictors. Epoch-to-epoch correlations between PAA measures were significantly higher than correlations among PSA variables, again suggesting greater stability of PAA data across epochs of sleep. The range of correlations for either data set was, however, substantially lower in the depressed than in the normal group. Experiment 3 evaluated the possibility that filter settings and artifact-rejection procedures had contributed to reduced overlap in PSA-PAA variance and reduced stability in depressed patients. An additional group of eight healthy volunteers served as subjects. Findings in Experiment 3 indicated that methodological differences between Experiments 1 and 2 did not account for the reduced correlations in the depressed group. It was concluded that PSA and PAA data should be comparable in normal subjects but are relatively independent in depressed patients. Epoch-to-epoch correlations were higher for PAA data than those found between PSA measures in both normal subjects and depressed patients, suggesting that PAA may be more stable across sleep epochs. Reduced stability may be a reflection of nonstationarity in the EEG of depressed patients.

Correlation between cognitive brain function and electrical brain activity in dementia of Alzheimer type

Psychometric tests which assess cognitive brain function in dementia disorders are partly prone to artifacts, e.g., the experience of the investigator and the cooperation of the patient influences the results. An objective way to assess the degree of cognitive disturbance could be to measure neuronal activity represented by the electrical brain activity. The aim of the present study was to investigate how well cognitive function in dementia assessed by psychometric tests correlates with electrical brain activity (EEG). Multichannel EEG data was reduced into 3-D intracerebral equivalent dipole EEG generators allowing a more convenient statistical data management and valid physiological data interpretation. 35 patients suffering from dementia of Alzheimer type were investigated. An increase of dipole strength in the slow frequency bands, a more anterior equivalent dipole of alpha- and beta-activity, and a slowing of the EEG with increasing cognitive deterioration could be demonstrated. The results support the hypothesis that the amount of disturbance of cognitive function in dementia can be assessed by measuring the electrical activity of the brain.

Electrical brain activity in schizophrenia described by equivalent dipoles of FFT-data

Since results of conventional FFT-power-analysis are reference-dependent, only unambiguous neurophysiological data should be used for a functional physiological interpretation of EEG-data. FFT-approximation with successive center-of-gravity-dipole calculation gives unambiguous EEG-data with regard to recording reference. In the present investigation 22 medicated schizophrenic patients were compared with 22 healthy age- and sex-matched controls with regard to spontaneous resting EEG. More anterior and superficial equivalent-dipoles were found in the beta-bands for schizophrenic patients compared to healthy control subjects. There was a tendency of increased beta-activity in schizophrenic subjects. With more severe schizophrenic symptoms (higher BPRS-score), the more anterior was the equivalent-dipole localization in the beta 1-band, and the deeper in the theta-band. The different locations of the beta-band dipoles in schizophrenic patients suggest that different neuronal populations generate beta-activity in schizophrenia compared to healthy controls. FFT-approximation allows a substantial and meaningful data reduction in multichannel recordings and will hopefully help in understanding pathological brain functions in schizophrenia.

Age-related changes of spontaneous EEG described by equivalent dipoles

One of the most commonly used methods for quantification of an EEG is Fast Fourier Transformation (FFT), which suffers from some serious disadvantages, for example: FFT-power data are highly dependent on the choice of reference and thus the topographical distribution of FFT-power data varies according to the used reference. Novel methods which partly resolve this problem have been developed. These methods provide unambiguous data in the frequency domain with regard to reference. In comparison to conventional FFT-power data this approach allows to a higher degree to draw topographical valid conclusions regarding brain function. The aim of the present study on brain electrical activity, using the method of FFT approximation, was to investigate age-related alterations of brain function in carefully screened healthy subjects. The major finding was that, except for a more superficially located beta-activity of higher strength with increasing, age no age-related changes in electrical brain activity were observed.

Dementia of the Alzheimer type: effects on the spontaneous EEG described by dipole sources

The present study on brain electrical activity in healthy subjects (n = 35) and patients suffering from dementia of the Alzheimer type (DAT; n = 35) used Fast Fourier Transformation-dipole approximation to quantify differences between the two groups. DAT patients showed a shift of alpha and beta activity toward frontal brain regions. The amount of this shift correlated with the degree of dementia. The relative distribution of magnitude of activity between the frequency bands differed between DAT patients and control subjects. DAT patients had higher magnitudes in the slow frequency range, correlating with the severity of dementia, and lower ones in the alpha and beta range compared with findings in age-matched control subjects.

Brain electrical activity in depression described by equivalent dipoles

The majority of neurophysiological investigations of waking EEG in depression have been relatively disappointing. Since the topographic distribution of brain electrical activity over the scalp in the frequency domain (FFT-power) varies considerably when choosing another site for the reference, it is not surprising that various investigators reported contradictory results. The aim of the present study was to investigate differences in brain electrical activity in a sample of depressed patients as compared to healthy subjects using a newly developed method called FFT approximation. As the major finding healthy subjects and depressed patients demonstrated significantly divergent patterns of localization between frequency bands in the anterior-posterior direction. The investigation suggests that a non-invasive neurophysiological methods gives results which are comparable to those obtained by other functional and structural imaging methods in depressive illness.

Equivalent dipoles of FFT data visualize drug interaction at benzodiazepine receptors

The aim of the present investigation was to study if the benzodiazepine receptor antagonist flumazenil could reverse the effects on the brain electrical activity induced by the benzodiazepine receptor agonist midazolam. The method of FFT approximation was used for this purpose. It allows the calculation of center of gravity equivalent dipoles of spectral EEG data. The results are reference independent and allow therefore a more unambiguous interpretation compared to conventional FFT data reports. Twelve subjects were investigated before and after 0.1 mg/kg and 0.2 mg/kg midazolam respectively, directly and 4 h after administration of 1 mg flumazenil. Our results imply that the application of flumazenil after midazolam sedation leads to an almost complete restoration of the brain electrical activity. However, especially in the beta frequencies above 20 Hz differences in depth of equivalent dipoles were found directly after flumazenil application as well as 4 h later. This could suggest that neuronal generators in different brain structures were responsible for the electrical activity after flumazenil administration compared to before.

Frequency-domain localization of intracerebral dipolar sources

A frequency-domain localization of intracerebral dipolar sources can be carried out basically in the same way as a time-domain localization, since the minimization problems to be solved in the two cases have exactly the same structure. The quantity to be minimized can be interpreted as a sum of residual variances of independent linear minimization problems. In the time domain there is one linear problem per sampling time, whereas in the frequency domain there are two linear problems per frequency. It is demonstrated that algorithms readily available for the solution of the time-domain inverse problem can also be used for the solution of the frequency-domain inverse problem. In this way it is not only possible to localize multiple dipoles, but also to combine information from different epochs and from different frequencies.

Localization of the sources of EEG delta, theta, alpha and beta frequency bands using the FFT dipole approximation

FFT dipole approximation and 3-dimensional dipole modelling were used to determine the locations of the equivalent dipole model sources of the delta, theta, alpha, beta-1 and beta-2 frequency bands in 13 normal subjects during resting. From each subject, 2 successive data sets were analysed, each consisting of 10 epochs of 2 sec randomly collected during 30 min. ANOVAs showed that over subjects, the source locations of EEG frequency bands differed significantly in the vertical and antero-posterior dimensions. Results of data set 2 confirmed those of data set 1. The source of delta was deepest and most anterior, theta more posterior and less deep, alpha most posterior and highest on the vertical dimension, beta-1 deeper and slightly more anterior than alpha, and beta-2 again more anterior and deeper than beta-1. Thus, the depth of source location was not linearly related to temporal frequency. The sources of all 5 bands were oriented in the sagittal direction; delta mean fields had steeper gradients anteriorly, alpha and beta-1 posteriorly. The power map for any frequency was well described by a single phase angle. The results indicate that the different EEG frequency bands during a given EEG epoch are generated by neural populations in different brain locations.

Equivalent EEG sources determined by FFT approximation in healthy subjects, schizophrenic and depressive patients

In recent years, as a result of increasing calculation power of computers and with the aid of appropriate computer programs it has been made possible to calculate equivalent dipoles as intracranial representations of cerebral electrical activity. The present study investigated the localization of intracerebral equivalent dipoles in healthy controls and psychiatric patients. The equivalent dipole sources were calculated for conventional frequency bands of the background EEG. This was performed using the FFT approximation by Lehmann and Michel. Results showed more anterior equivalent sources for alpha and beta activity in all patients compared to controls. The beta activity was also generated in deeper brain structures in controls compared to patients. These results indicate that frequency bands may be generated in different brain structures in patients suffering from psychiatric diseases as compared to healthy controls and that the calculation of equivalent dipole sources may be a way to perform a sensible and substantial data reduction.

Intracerebral dipole source localization for FFT power maps

The method treats Fast Fourier Transforms (FFTs) of multichannel EEGs so that they can be used for intracerebral source localizations. For each frequency point, the FFT results are entered into a sine-cosine diagram. Into the diagram's entry constellation (FFT constellation), a straight line (single dipole model) is fitted which produces the least square deviation sum between the entry positions and their orthogonal projections onto the straight line. The map described by the voltages between the projected positions on the straight line is the single source 'FFT approximation' of the FFT constellation. The FFT approximation map is used for dipole source localization. The squared FFT approximation map and the squared map of the forward solution of the computed dipole (power maps) closely resemble the original power map.

Quantitative, waking EEG research on depression

Research published in the past decade that used quantitative indices to evaluate the waking EEG characteristics of depressed patients is reviewed. Methodological problems that make results of different research laboratories difficult to compare include diagnostic heterogeneity of depressed groups, lack of inclusion of control subjects, and differences in the EEG techniques. Despite interpretive problems that arise from such substantial variation, consistencies nevertheless emerge. Unmedicated, actively depressed patients appear to exhibit elevated EEG alpha and beta compared to control subjects. Delta and theta distinguished depressed patients from controls in some single studies, but variation in age, specific diagnostic depression categories, and EEG acquisition and analysis techniques rendered these results less definitive. Quantitative EEG differences that may distinguish depressed subject samples from those with other psychiatric disorders are considered. Factors that limit comparability of the findings are discussed in conjunction with strategies that deserve systematic study in future research.

Intracerebral dipole sources of EEG FFT power maps

The described method opens a way to compute intracerebral source localizations of ongoing EEG activity. A sine-cosine diagram of the Fourier-transformed data is constructed for each frequency point, forming a "FFT constellation" of entries. Into the FFT constellation of each diagram, a straight line is fitted which produces the least squared deviation sum between the original entry positions and their orthogonal projections onto that line. The map landscape described by the voltages between the projected positions ("FFT approximation") is the least error compromise landscape of all possible landscapes during the paradigmatic cycle of the given FFT frequency. The map thus constructed can be used in the usual dipole source localization procedures. There is one for each FFT frequency point. The squared forward solution of the fitted dipole source and the squared FFT approximation map are "power maps" which are very similar to the original power map. For an average-reference power map with two peaks, the source tends to lie between the peaks; a power map with one peak might show closely neighboring maximal and minimal potential values in the FFT approximation, indicative of a tangential source close to the surface.

The reference problem and mapping of coherence: a simulation study

Four techniques are applied to record EEG signals: bipolar recording, referential recording, common average reference recording and source derivation. For the interpretation of EEG parameter maps knowledge of the properties of the applied recording technique is essential. Bipolar recordings are not discussed in this paper. The application of reference and common average reference recording has the disadvantage of an unknown reference potential. This disadvantage is much larger with the use of source derivation because every electrode signal has its particular reference signal. This must be taken into consideration when coherence estimations are made. With actual EEG records the influence of the reference cannot be determined unambiguously. However, simulation studies enable some essential conclusions. In this paper by means of autoregressive processes EEG signals with given power and coherence properties were simulated and different recording situations using the same data set were reconstructed. The essential result is that computation and mapping of coherences yield the most reliable results when reference recording is used. However, measures to ensure a low reference signal must be taken.

Common reference coherence data are confounded by power and phase effects

Coherence analysis of the EEG is used to study the coupling between cortical regions. High coherence between signals recorded at 2 electrodes is interpreted as evidence for neuroanatomic connections between the cortical areas underlying the electrodes. When common reference recordings are used, coherence measures the relationship between 2 time series, each of which is the difference between 2 signals measured at the scalp and is confounded by spectral power and phase at the recording and reference electrodes. Using multi-channel EEG data from 3 subjects, we illustrate the confounding of common reference data coherence computations and demonstrate the extreme effects of power and phase changes on coherence by simulating these changes in the EEG data. Common reference coherence data can be either inflated or deflated as a consequence of activity (i.e., spectral power) at the reference. Phase relationships among the reference and recording time series modulate the power effects on coherence. Both the power and phase effects can vary dramatically across frequencies, having profound and complicated effects on the shape of the coherence function. Based on these considerations, we conclude that common reference coherence data must be interpreted very cautiously and recommend that a new body of EEG coherence data must be gathered using reference-free recording methods before the utility of EEG coherence analysis for understanding brain function can be determined.

Time range analysis of evoked potential fields

Potentials evoked by contrast reversing grating stimuli of different spatial frequency and orientation were recorded in 16 channels from twelve healthy adults. The amount of electrical brain activity was quantified independent of the reference electrode by the computation of global field power (GFP). Maxima of the GFP function over times, determined component latencies which turned out to be influenced by spatial frequency and orientation. Both effects were statistically significant. Analysis of GFP at component latencies demonstrated the significant influence of spatial frequency on the amount of activity in the potential fields, whereas different stimulus orientations yielded brain activity of similar strength. Component location on the scalp determined at P100 latency showed no systematic variation with spatial frequency or orientation of the grating pattern. A reference-free topographic segmentation procedure based on the statistical recognition of stable potential field configurations disregarding amplitude characteristics, was used for all subjects and stimulus conditions. Segments were identified over the whole recording epoch and were interpreted as time epochs with identical potential field configurations, that were compatible with identical neuronal generators. The sequence of such segments was further analysed and compared statistically between subjects and stimulus conditions. The results showed topographical differences that were not observed when only selected time points at component latency were considered.

EEG alpha map series: brain micro-states by space-oriented adaptive segmentation

The spontaneous EEG, viewed as a series of momentary scalp field maps, shows stable map configurations (of periodically reversed polarity) for varying durations, and discontinuous changes of the configurations. For adaptive segmentation of map series into spatially stationary epochs, the maps at the times of maximal map relief are selected and spatially described by the two locations of maximal and minimal (extreme) potentials; a segment ends if over time an extreme leaves its pre-set spatial window. Over 6 subjects, the resting alpha EEG showed 210 msec mean segment duration; segments longer than 323 msec covered 50% of the total time; the most prominent segment class (1.5% of all classes) covered 20% of total time (prominence varied strongly over classes; not all possible classes occurred). Spectral power and phase of averages of adaptive and pre-determined segments demonstrated the adequacy of the strategy, and the homogeneity of adaptive segment classes by their reduced within-class variance. It is suggested that different segment classes manifest different brain functional states exerting different effects on information processing. The spatially stationary segments might be basic building blocks of brain information processing, possibly operationalizing consciousness time and offering a common phenomenology for spontaneous activity and event-related potentials. The functional significance of segments might be modes or steps of information processing or performance, tested, e.g., as reaction time.

Transverse relationships of the alpha rhythm on the scalp

Using auto- and cross-spectral analyses on data of 3 normal adult subjects, two components of rhythmic alpha activity were distinguished with respect to their spatial distribution and spatial relationships on the scalp. Derivations from 21 scalp points vs. linked ears were analyzed. The alpha activity with power maxima in the bilateral occipital areas (component A) showed high coherence with activity in the anterior areas and somewhat lower coherence with activity in the central/parietal areas. The other component (B) appeared dominantly in the central areas, showing extremely low values of coherence between the anterior and posterior regions, and an unstable phase relation among recording points. Components A and B appear to correspond to the 'generalized' and 'localized' alpha components described earlier. It is suggested that these two components account for the major properties of the rhythmic alpha activity.