Cortical and subcortical correlates of electroencephalographic alpha rhythm modulation

Neural correlates of electroencephalographic (EEG) alpha rhythm are poorly understood. Here, we related EEG alpha rhythm in awake humans to blood-oxygen-level-dependent (BOLD) signal change determined by functional magnetic resonance imaging (fMRI). Topographical EEG was recorded simultaneously with fMRI during an open versus closed eyes and an auditory stimulation versus silence condition. EEG was separated into spatial components of maximal temporal independence using independent component analysis. Alpha component amplitudes and stimulus conditions served as general linear model regressors of the fMRI signal time course. In both paradigms, EEG alpha component amplitudes were associated with BOLD signal decreases in occipital areas, but not in thalamus, when a standard BOLD response curve (maximum effect at approximately 6 s) was assumed. The part of the alpha regressor independent of the protocol condition, however, revealed significant positive thalamic and mesencephalic correlations with a mean time delay of approximately 2.5 s between EEG and BOLD signals. The inverse relationship between EEG alpha amplitude and BOLD signals in primary and secondary visual areas suggests that widespread thalamocortical synchronization is associated with decreased brain metabolism. While the temporal relationship of this association is consistent with metabolic changes occurring simultaneously with changes in the alpha rhythm, sites in the medial thalamus and in the anterior midbrain were found to correlate with short time lag. Assuming a canonical hemodynamic response function, this finding is indicative of activity preceding the actual EEG change by some seconds.

Automatic Reduction of Artifacts in EEG-Signals

Electroencephalograms (EEG) are often contaminated with high amplitude artifacts limiting the usability of data. Methods that reduce these artifacts are often restricted to certain types of artifacts, require manual interaction or large training data sets. Within this paper we introduce a novel method, which is able to eliminate many different types of artifacts without manual intervention. The algorithm first decomposes the signal into different sub-band signals in order to isolate different types of artifacts into specific frequency bands. After signal decomposition with principal component analysis (PCA) an adaptive threshold is applied to eliminate components with high variance corresponding to the dominant artifact activity. Our results show that the algorithm is able to significantly reduce artifacts while preserving the EEG activity. Parameters for the algorithm do not have to be identified for every patient individually making the method a good candidate for preprocessing in automatic seizure detection and prediction algorithms.

Theta burst transcranial magnetic stimulation is associated with increased EEG synchronization in the stimulated relative to unstimulated cerebral hemisphere

Theta burst transcranial magnetic stimulation (TBS) may induce behavioural changes that outlast the stimulation period. The neurophysiological basis of these behavioural changes are currently under investigation. Given the evidence that cortical information processing relies on transient synchronization and desynchronization of neuronal assemblies, we set out to test whether TBS is associated with changes of neuronal synchronization as assessed by surface EEG. In four healthy subjects one TBS train of 600 pulses (200 bursts, each burst consisting of 3 pulses at 30 Hz, repeated at intervals of 100 ms) was applied over the right frontal eye field and EEG synchronization was assessed in a time-resolved manner over 60 min by using a non-overlapping moving window. For each time step the linear cross-correlation matrix for six EEG channels of the right and for the six homotopic EEG channels of the left hemisphere were computed and their largest eigenvalues used to assess changes of synchronization. Synchronization was computed for broadband EEG and for the delta, theta, alpha, beta and gamma frequency bands. In all subjects EEG synchronization of the stimulated hemisphere was significantly and persistently increased relative to EEG synchronization of the unstimulated hemisphere. This effect occurred immediately after TBS for the theta, alpha, beta and gamma frequency bands and 10-20 min after TBS for broadband and delta frequency band EEG. Our results demonstrate that TBS is associated with increased neuronal synchronization of the cerebral hemisphere ipsilateral to the stimulation site relative to the unstimulated hemisphere. We speculate that enhanced synchronization interferes with cortical information processing and thus may be a neurophysiological correlate of the impaired behavioural performance detected previously.

Identification of brain structures involved in micturition with functional magnetic resonance imaging (fMRI)

OBJECTIVE: The voluntary control of micturition is believed to be integrated by complex interactions among the brainstem, subcortical areas and cortical areas. Several brain imaging studies using positron emission tomography (PET) have demonstrated that frontal brain areas, the limbic system, the pons and the premotor cortical areas were involved. However, the cortical and subcortical brain areas have not yet been precisely identified and their exact function is not yet completely understood. MATERIALS AND METHODS: This study used functional magnetic resonance imaging (fMRI) to compare brain activity during passive filling and emptying of the bladder. A cathetherism of the bladder was performed in seven healthy subjects (one man and six right-handed women). During scanning, the bladder was alternatively filled and emptied at a constant rate with bladder rincing solution. RESULTS: Comparison between passive filling of the bladder and emptying of the bladder showed an increased brain activity in the right inferior frontal gyrus, cerebellum, symmetrically in the operculum and mesial frontal. Subcortical areas were not evaluated. CONCLUSIONS: Our results suggest that several cortical brain areas are involved in the regulation of micturition.

Effects of verum acupuncture compared to placebo acupuncture on quantitative EEG and heart rate variability in healthy volunteers

OBJECTIVES: The aim of this single-blind randomized crossover study was to evaluate specific effects of manual acupuncture on central and vegetative nervous system activity measured by quantitative electroencephalography (qEEG) and heart rate variability (HRV). DESIGN: Twenty (20) healthy volunteers (mean: 25.2 +/- 3.6 years) were monitored simultaneously using a qEEG system and a 12-channel electrocardiogram recorder during verum acupuncture (VA) at acupuncture point Large Intestine 4 (Hegu) (LI4) or placebo acupuncture (PA) at a sham point. RESULTS: In the EEG conduction of the occipital area, needle stimulation in VA increased alpha1-frequency significantly, and the ratio alpha1/theta was shifted to the benefit of alpha1 over all electrodes. The HRV parameters showed a significant increase of the low frequency/high frequency (HF) ratio during the first minute of stimulation in VA, indicating an initial increase of sympathetic activation. However, an increase of HF power in the minute after stimulation followed by a decrease in heart rate suggests delayed vagal activation. De qi (a sensation that is typical of acupuncture needling) occurred in 16 subjects during VA and in 9 volunteers during PA (80% versus 45%). CONCLUSIONS: Manual stimulation on LI4 seems to lead to specific changes in alpha EEG-frequency and in HRV parameters. A linear relationship between the HRV parameters and the alpha EEG band might point to a specific modulation of cerebral function by vegetative effects during acupuncture.

Improving the performance of GIS/spatial analysts though novel applications of the Emotiv EPOC EEG headset

Geospatial information systems are used to analyze spatial data to provide decision makers with relevant, up-to-date, information. The processing time required for this information is a critical component to response time. Despite advances in algorithms and processing power, we still have many “human-in-the-loop” factors. Given the limited number of geospatial professionals, analysts using their time effectively is very important. The automation and faster humancomputer interactions of common tasks that will not disrupt their workflow or attention is something that is very desirable. The following research describes a novel approach to increase productivity with a wireless, wearable, electroencephalograph (EEG) headset within the geospatial workflow.

Acute disseminated encephalomyelitis in adults: a reappraisal of clinical, CSF, EEG, and MRI findings

OBJECTIVES: To establish an adequate definition of acute disseminated encephalomyelitis (ADEM) in adults, based on our clinical observations of a case-series. METHODS: Over a period of three years 10 adult patients with a para- or postinfectious disseminated (diffuse or multifocal) syndrome of the CNS fulfilling predefined strict criteria for the diagnosis of ADEM were encountered and systematically followed. RESULTS: The age ranged from 21 to 62 years, two were men. MRI was normal in 5 patients and only mildly abnormal in the remaining patients. CSF was normal in 5 patients and mildly abnormal in the remainder, EEG was abnormal in 7/8 patients. All patients survived and were followed over a period of 30 months (range: 8 to 48 months). Nine patients were left with some residual defects, consisting most often of a mild cognitive impairment. CONCLUSIONS: The EEG as an investigation of brain function can be crucial in establishing the organic nature of disease. MRI is important to exclude other diffuse or multifocal encephalopathies. However, in contrast to previous reports in the literature abnormal MRI should not be considered mandatory in adult ADEM. Difficulties in the diagnosis of ADEM are discussed and the importance of clinical and paraclinical findings for establishing the diagnosis is outlined.

Evolution of sleep and sleep EEG after hemispheric stroke

The evolution of subjective sleep and sleep electroencephalogram (EEG) after hemispheric stroke have been rarely studied and the relationship of sleep variables to stroke outcome is essentially unknown. We studied 27 patients with first hemispheric ischaemic stroke and no sleep apnoea in the acute (1-8 days), subacute (9-35 days), and chronic phase (5-24 months) after stroke. Clinical assessment included estimated sleep time per 24 h (EST) and Epworth sleepiness score (ESS) before stroke, as well as EST, ESS and clinical outcome after stroke. Sleep EEG data from stroke patients were compared with data from 11 hospitalized controls and published norms. Changes in EST (>2 h, 38% of patients) and ESS (>3 points, 26%) were frequent but correlated poorly with sleep EEG changes. In the chronic phase no significant differences in sleep EEG between controls and patients were found. High sleep efficiency and low wakefulness after sleep onset in the acute phase were associated with a good long-term outcome. These two sleep EEG variables improved significantly from the acute to the subacute and chronic phase. In conclusion, hemispheric strokes can cause insomnia, hypersomnia or changes in sleep needs but only rarely persisting sleep EEG abnormalities. High sleep EEG continuity in the acute phase of stroke heralds a good clinical outcome.

Visual and spectral analysis of sleep EEG in acute hemispheric stroke

BACKGROUND: Reports on the effects of focal hemispheric damage on sleep EEG are rare and contradictory. PATIENTS AND METHODS: Twenty patients (mean age +/- SD 53 +/- 14 years) with a first acute hemispheric stroke and no sleep apnea were studied. Stroke severity [National Institute of Health Stroke Scale (NIHSS)], volume (diffusion-weighted brain MRI), and short-term outcome (Rankin score) were assessed. Within the first 8 days after stroke onset, 1-3 sleep EEG recordings per patient were performed. Sleep scoring and spectral analysis were based on the central derivation of the healthy hemisphere. Data were compared with those of 10 age-matched and gender-matched hospitalized controls with no brain damage and no sleep apnea. RESULTS: Stroke patients had higher amounts of wakefulness after sleep onset (112 +/- 53 min vs. 60 +/- 38 min, p < 0.05) and a lower sleep efficiency (76 +/- 10% vs. 86 +/- 8%, p < 0.05) than controls. Time spent in slow-wave sleep (SWS) and rapid eye movement (REM) sleep and total sleep time were lower in stroke patients, but differences were not significant. A positive correlation was found between the amount of SWS and stroke volume (r = 0.79). The slow-wave activity (SWA) ratio NREM sleep/wakefulness was lower in patients than in controls (p < 0.05), and correlated with NIHSS (r = -0.47). CONCLUSION: Acute hemispheric stroke is accompanied by alterations of sleep EEG over the healthy hemisphere that correlate with stroke volume and outcome. The increased SWA during wakefulness and SWS over the healthy hemisphere contralaterally to large strokes may reflect neuronal hypometabolism induced transhemispherically (diaschisis).

Integration of electrical neuroimaging with other functional imaging methods

Integrating evidence from different imaging modalities is important to overcome specific limitations of any given imaging method, such as insensitivity of the EEG to unsynchronized neural events, or the lack of fMRI sensitivity to events of low metabolic demand. Processes that are visible in one modality may be related in a nontrivial way to other processes visible in another modality and insight may only be obtained by integrating both methods through a common analysis. For example, brain activity at rest seems to be at least partly determined by an interaction of cortical rhythms (visible to EEG but not to fMRI) with sub-cortical activity (visible to fMRI, but usually not to EEG without averaging). A combination of EEG and fMRI data during rest may thus be more informative than the sum of two separate analyses in both modalities. Integration is also an important source of converging evidence about specific aspects and general principles of neural functions and their dysfunctions in certain pathologies. This is because not only electrical, but also energetic, biochemical, hemodynamic and metabolic processes characterize neural states and functions, and because brain structure provides crucial constraints upon neural functions. Focusing on multimodal integration of functional data should not distract from the privileged status of the electric field as the primary direct, noninvasive real-time measure of neural transmission. The preceding chapters illustrate how electrical neuroimaging has turned scalp EEG into an imaging modality which directly captures the full temporal dynamics of neural activity in the brain.