The functional significance of theta and upper alpha oscillations.

Recent findings are reviewed indicating that upper alpha oscillations - when analyzed with appropriate time/ frequency resolution - show a similar physiological reactivity as theta in working memory tasks. Comparable to theta, a load dependent increase in power can be observed during retention and increased evoked activity during retrieval. During retrieval attempts theta behaves like a traveling wave spreading from anterior to posterior sites. During actual retrieval, however, evoked upper alpha becomes transiently nested in theta. We suggest that theta reflects working memory functions whereas upper alpha may be important for the reactivation of long-term memory codes in short-term memory.

Phase-locked alpha and theta oscillations generate the P1-N1 complex and are related to memory performance.

An oscillatory phase resetting model is presented and data are reported which indicate that early components of the event-related potential are due to the superposition of evoked oscillations. The following hypotheses were tested and could be confirmed: (i) theta and alpha show a significant increase in phase locking during the time window of the P1 and N1 as compared to a prestimulus reference, (ii) the dynamics of event-related changes in evoked theta and alpha power obey the same principles as are known from event-related de-/synchronization research, and (iii) latency measures of the P1-N1 complex are negatively correlated with individual alpha frequency. In addition, we have found that theta phase locking is larger during encoding than recognition and that good memory performers show a larger increase in theta and alpha phase locking during recognition in the time window of the N1. Our general conclusion is that the P1-N1 complex is generated primarily by evoked alpha and theta oscillations reflecting the synchronous activation of a working- and semantic memory system.

The use of time-variant EEG Granger causality for inspecting directed interdependencies of neural assemblies.

Understanding of brain functioning requires the investigation of activated cortical networks, in particular the detection of interactions between different cortical sites. Commonly, coherence and correlation are used to describe interrelations between EEG signals. However, on this basis, no statements on causality or the direction of their interrelations are possible. Causality between two signals may be expressed in terms of upgrading the predictability of one signal by the knowledge of the immediate past of the other signal. The best-established approach in this context is the so-called Granger causality. The classical estimation of Granger causality requires the stationarity of the signals. In this way, transient pathways of information transfer stay hidden. The study presents an adaptive estimation of Granger causality. Simulations demonstrate the usefulness of the time-variant Granger causality for detecting dynamic causal relations within time intervals of less than 100 ms. The time-variant Granger causality is applied to EEG data from the Stroop task. It was shown that conflict situations generate dense webs of interactions directed from posterior to anterior cortical sites. The web of directed interactions occurs mainly 400 ms after the stimulus onset and lasts up to the end of the task.

Multivariate tests for the evaluation of high-dimensional EEG data.

In this paper several multivariate tests are presented, in particular permutation tests, which can be used in multiple endpoint problems as for example in comparisons of high-dimensional vectors of EEG data. We have investigated the power of these tests using artificial data in simulations and real EEG data. It is obvious that no one multivariate test is uniformly most powerful. The power of the different methods depends in different ways on the correlation between the endpoints, on the number of endpoints for which differences exist and on other factors. Based on our findings, we have derived rules of thumb regarding under which configurations a particular test should be used. In order to demonstrate the properties of different multivariate tests we applied them to EEG coherence data. As an example for the paired samples case, we compared the 171-dimensional coherence vectors observed for the alpha1-band while processing either concrete or abstract nouns and obtained significant global differences for some sections of time. As an example for the unpaired samples case, we compared the coherence vectors observed for language students and non-language students who processed an English text and found a significant global difference.

Acute effects of cigarette smoking on cerebral oxygenation and hemodynamics: a combined study with near-infrared spectroscopy and transcranial Doppler sonography.

Cigarette smoking has been shown to increase cerebral blood flow velocity (CBFV) and reduce vasomotor reactivity temporarily. The aim of our study was to clarify whether this results from dilation of resistance vessels alone with subsequent increase in regional cerebral blood flow (rCBF), or an additional constriction of basal cerebral arteries. In 24 healthy smokers (mean age+/-S.D., 32.7+/-10.5 years), cerebral oxygenation and hemodynamics were monitored by transcranial Doppler sonography and near-infrared spectroscopy before, during, and after smoking a cigarette (nicotine 0.9 mg). We simultaneously recorded CBFV of both middle cerebral arteries, mean arterial blood pressure, skin blood flow, end-tidal CO(2), changes in concentration of cerebral oxyhemoglobin, deoxyhemoglobin, and total hemoglobin (micromol/l), and a cerebral tissue oxygenation index. Smoking increased CBFV (p<0.01), oxyhemoglobin (p<0.01), and total hemoglobin (p<0.01). After smoking, the increase in CBFV and total hemoglobin persisted (p<0.01), while oxyhemoglobin returned to baseline. Deoxyhemoglobin and cerebral tissue oxygenation index did not change during the whole procedure. During, but not after smoking, CBFV increase was correlated to ipsilateral changes in oxyhemoglobin and total hemoglobin (p<0.05). The increase in oxyhemoglobin only during smoking and the lack of changes in deoxyhemoglobin and cerebral tissue oxygenation index indicate that smoking did not substantially increase rCBF. The smoking-induced elevation in CBFV might therefore be due to an additional constriction of the middle cerebral artery. The combined effects of smoking on basal cerebral arteries and arterioles might contribute to the increased stroke risk in smokers.

Fitting of one ARMA model to multiple trials increases the time resolution of instantaneous coherence.

This study presents a least mean squares (LMS) algorithm for the ensemble modeling of a multivariate ARMA process. Generally, an LMS algorithm makes possible the tracking of parameters for nonstationary time series. Our estimation incorporates multiple process observations that improve the accuracy of the parameter estimation. As a consequence, the estimation sequences come close to the true model parameters with a fast adaptation speed. This advantage also holds true of spectral quantities (e.g., the momentary coherence), which are derived from the model parameters. Thus the extension of the ARMA fitting from one to multiple trajectories allows the investigation of nonstationary biological signals with an increased time resolution. The applicability of the algorithm is demonstrated for event-related EEG coherence analysis of the Sternberg task. The changing interaction between posterior association cortex and anterior brain area was shown for verbal and nonverbal stimuli by means of the time-variant theta coherence.

Single-trial classification of elementary comparison processes on the basis of instantaneous EEG and MEG coherences.

The present study is focused on the evidence of possible single-trial EEG/MEG analysis of information processing. The discrimination between thinking modalities of concept activation and pattern comparison for single tasks of elementary comparison procedures is investigated. A neural network classifier with backpropagation learning algorithm is used. The input vector is constructed by parameters of instantaneous coherence (13-20 Hz) between several channel pairs of the EEG and/or of the MEG. Thereby, the strength of synchronization and the time location of synchronization phenomena are taken into consideration. The combination of EEG and MEG coherence parameters led to a classification accuracy of 85-94% for single subjects. Generally, results reached by neural network classifier show a better generalization than linear discriminant analysis.

Noninvasive monitoring of cerebral oxygenation during vasomotor reactivity tests by a new near-infrared spectroscopy device.

BACKGROUND: Spatially resolved spectroscopy is a recently developed technique for noninvasive monitoring of cerebral tissue oxygenation using the photon diffusion theory. METHODS: We studied this technique with a new, commercial near-infrared spectroscopy (NIRS) device during vasomotor reactivity tests in 28 healthy volunteers (mean age 31.0 years; SD 10.6 years) and compared it with values assessed by the modified Beer-Lambert law and indices from simultaneous transcranial Doppler sonography of both middle cerebral arteries. We measured O(2) reactivity as percentage change of cerebral blood flow velocity (CBFV), as absolute change in the concentrations (measured in micromol/l) of oxygenated (HbO(2)), deoxygenated (Hb) and total hemoglobin (HbT), and as change in the tissue oxygenation index (TOI) during inhalation of 100% oxygen. CO(2) reactivity was calculated as percentage change of CBFV (NCR), as absolute change in the concentrations of HbO(2), Hb, and HbT (micromol/l), and as change in TOI (%) per 1% increase in end-tidal CO(2). RESULTS: One hundred percent oxygen inhalation lead to a decrease in CBFV (mean +/- SD: left -8.0 +/- 7.0%, p = 0.000; right -9.6 +/- 7.6%, p = 0.000), an increase in HbO(2) (0.99 +/- 1.07 micromol/l), Hbdiff (2.23 +/- 1.72 micromol/l), and TOI (3.1 +/- 1.5%), and a decrease in Hb (-1.22 +/- 0.74 micromol/l), significant from baseline values (p = 0.0000). CO(2) reactivity was: NCR left 25.4 +/- 14.7%; NCR right 25.9 +/- 13.4%; HbO(2) 1.99 +/- 0.97 micromol/l; Hb -1.24 +/- 0.81 micromol/l; HbT 0.81 +/- 1.0 micromol/l, and TOI 3.7 +/- 2.2%. O(2) reactivity in TCD did not correlate with NIRS reactivities (Pearson p > 0.05), but NCR did correlate with changes in HbO(2), Hb, and TOI (Pearson p < 0.01). TOI was closely related to indices derived from the Beer-Lambert law (Pearson p < 0.03), but not with mean arterial blood pressure or skin blood flow during vasomotor reactivity tests. CONCLUSION: Spatially resolved spectroscopy provides an encouraging, noninvasive new tool to study cerebral tissue oxygenation during vasomotor reactivity tests consistent with physiological changes.