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PubMed1986

EEG cartography of a night of sleep and dreams. A longitudinal study with provoked awakenings.

A night of sleep has been recorded under the conditions of a sleep laboratory. The subject was a woman of 55 years, well-trained in dream recall. The subject was awakened three times at the end of sleep cycles. EEG was monitored for 7 h with a 16-channel polygraph (REEGA 16, Alvar) connected to two systems of EEG cartography: minicomputers (HP Fourier Analyser 5451 C and HP 1000) and a microinformatic system (Cartovar, Alvar). A second 8-channel polygraph (Mini-huit, Alvar) was used in parallel for polygraphy (EOG, EMG, respiration, actogram, EKG). Based on immediate visual inspection of EEG and polygraphic tracings, 500 EEG recordings of selected epochs (of 6, 30 or 60 s length) have been quantified, submitted on-line to spectral analysis (on Cartovar) and stored on floppy disks for further printing of EEG maps. The 16 EEG channels were placed over the scalp according to the 10/20 system and following Giannitrapani's placement. We have chosen a common average electrode. For each of the 500 EEG epochs, four EEG maps were edited (raw EEG between 0 and 30 Hz, 0 and 7 Hz, 8 and 12 Hz, 13 and 30 Hz). Each of these 2,000 maps has been checked visually in comparison with the polygraphic recordings for visual rejection of artifacts or transitory states. The remaining EEG epochs and EEG maps, scored by 2 independent trained sleep scorers, were classified into stages I, II, III-IV, and REM, apart from control runs of active wakefulness with eyes open (EO) and quiet wakefulness with eyes closed (EC), which were undertaken on mini- and microsystems of EEG analysis.(ABSTRACT TRUNCATED AT 250 WORDS)

Brain Mapping↗
PubMed1992

Are there EEG correlates of mental states in animals?

The thesis of this paper emerges from the fact that mental states are generated by neural processes that also produce an associated electroencephalogram (EEG). Thus, it is logical to expect correlations between mental state and EEG. The corollary is that the EEG can serve as an index of mental state, which can be particularly useful for studies in animals, where mental states are much less accessible for objective study than in humans. Herein, I briefly review the traditional approaches that have informed our attitudes about animal mental states. Virtually all of our conclusions about mental states in animals are drawn by inference from behavioral observation, a process that is highly and unavoidably subject to anthropomorphism. Traditionally, the electroencephalogram (EEG) has been used in a crude way as an objective indication of physical and behavioral state in animals. This, however, has led to substantial controversy, because there are several situations in which EEG patterns and behavior seem to be dissociated. We not only fail to understand these dissociated states, but there are also important humane animal-welfare issues that remain unresolved because we do not fully understand the extent to which the EEG can reflect mental state. At issue is whether EEG-behavioral dissociations, to the extent that they exist, are proof that the EEG is dissociated from mental states. Powerful new EEG methods, such as topographical EEG mapping, wavelet analysis, and testing for nonlinear ('chaotic') dynamical properties and short-term serial dependencies, are now available for studying the extent to which the EEG can index thinking and feeling in humans and, by extrapolation, in animals. Critics who have become disenchanted with the utility of the EEG should at least concede that fresh approaches to old problems are now available and should therefore be thoughtfully considered. If such research does nothing more than improve the rigor of the debate over animal welfare and rights issues, it will be worth the effort.

Animals↗
PubMed2000

[Signal processing and quality of displaying waveform at digital EEG machine].

With great advances in computer technology, the digital EEG machine was developed and has become widely used. In this paper, signal processing and quality of display of waveform at digital EEG machine were discussed to confirm its advantages and drawbacks. Signal processing on a digital EEG machine is summarized in 3 parts as follows: i) A/D conversion(sampling) of EEG signals in the head box, ii) Digital signal processing to obtain mathematically reconstructed EEG on the computer, iii) Displaying EEG on a monitor. For sampling, it was recommended that sampling rate was 200 or 256 Hz, and resolution in 12 bits or preferably 16 bits per sample. A high amplitude artifact caused EEG flattening called DC build up saturation. Montage reformatting had a clinical advantage. However, re-filtering using 15 Hz high cut filter influenced the EEG interpretation. The maximal resolution of digital EEG machine with a 17-inch CRT display using 1600 x 1200 dots was about 22 Hz. The performance of paper used for conventional EEG surpassed the performance of CRT display using digital EEG machine. It seemed that understanding the characteristics of digital EEG machine and realization of data processing were important for utilizing its functions effectively.

Analog-Digital Conversion↗
PubMed2001

The use of EEG in aircrew selection.

The value of the electroencephalograph (EEG) as a screening device in aviation medicine is questioned, because few subjects are disqualified on grounds of an EEG exam. At the Netherlands Aeromedical Institute, pilot applicants are rejected with a diagnosis of epilepsy or with severe EEG abnormalities (including epileptiform patterns where epilepsy is highly suspected). Although several studies have shown a low incidence of epileptiform EEG abnormalities in candidate pilots, subjects with an epileptiform EEG have a substantially increased risk of sudden incapacitation during their flying careers. In this review, we calculate the probability that a candidate with epileptiform EEG, but no history of epileptic seizures, will develop seizures during his flying career. This probability is about 25%, more than 12 times higher than for subjects with normal EEG and no history of epileptic seizures (2%). Subjects with epileptiform EEGs not only have increased risk of future epileptic seizures, but additionally it is recognized that epileptiform EEG discharges may be associated with episodic functional impairment, which can be a danger when a subject is flying. Taking this into account, one should consider rejecting all candidates with epileptiform EEGs in the future. This is at the expense of a small group of subjects with false-positive EEGs, but we believe that concern for public safety must override other considerations in these rare cases. To improve the understanding of the usefulness of the EEG in pilot screening procedures, an international classification and coding system should be developed, so that data from different countries can be compared.

Aerospace Medicine↗
PubMed2006

Ellen R. Grass Lecture: Rapid EEG analysis for intensive care decisions in status epilepticus.

Nonconvulsive status epilepticus in intensive care units (ICUs) is common and increases the risk of death. Nonconvulsive status epilepticus treatment delays are associated with poor patient outcomes. Continuous EEG or EEG-video monitoring is used in ICU settings to diagnose subtle seizures and nonconvulsive status epilepticus among at-risk populations including patients with closed head injuries and altered consciousness, stroke, subarachnoid hemorrhage, neonates at-risk for sepsis or hypoxic-ischemic encephalopathy, and children who have undergone surgery for congenital heart disease. However expert EEG interpretation, currently required for accurate diagnosis, often lags behind the real-time recordings by hours or even longer. At most hospitals the numbers of at-risk patients in intensive care units far exceeds the capacity of the available EEG equipment and personnel to perform and interpret EEGs. Seizure-detection software, compressed EEG spectral arrays, and near real-time remote EEG interpretation have brought us closer to the goal of real-time analysis of EEG for intensive care decisions, but even at major tertiary referral centers the vast majority of at-risk ICU patients do not undergo EEG monitoring. Additional technological advances, innovative use of EEG technologists and ICU personnel, and clinical trials of new EEG monitoring technology and associated clinical outcomes are needed to achieve the goal of optimal use of EEG data for intensive care decisions.

Critical Care↗
PubMed1989

Effect of after-discharge EEG patterns on performance and latency of the conditioned avoidance response in hippocampally kindled cats.

The relation between different EEG after-discharge patterns and memory retrieval of the conditioned avoidance response was studied in 8 hippocampally kindled cats. The after-discharge patterns were classified into 5 basic EEG types. The relation was analyzed in three different situations: A, at the conditioning stimulation onset, B, at the conditioning stimulus termination, and C, when conditioning stimulus onset and termination were studied within the same type of EEG pattern of after-discharge. The moment of presentation of the conditioning stimulus was determined by the type of EEG after-discharge pattern. Significant relation was observed between reflex performance and type II and III EEG AD types. The type II (4.5-12/s spiking activity) was associated with a greater proportion of positive responses if presented on the uniform background of EEG after-discharge patterns. During the type III pattern (EEG dysrhythmia), there were more negative than positive responses in all the three experimental situations, especially if the type III EEG pattern was observed at the time of conditioned stimulus termination. The latency of reflex performance measured in the experimental condition C (the same pattern of EEG during conditioning stimulus onset and termination) was longer during the type II EEG pattern of after-discharges than the latencies found during type III EEG activity and in the control group. During type III pattern associated with greatest proportion of response failures there was, however, no increase of reflex latencies. The results suggest differential effect of different EEG after-discharge patterns on memory retrieval of the well established conditioned avoidance response in cats.

Animals↗
PubMed1995

Cellular basis of EEG slow rhythms: a study of dynamic corticothalamic relationships.

A slow oscillation (< 1 Hz) has recently been described in intracellular recordings from the neocortex and thalamus (Steriade et al., 1993c-e). The aim of the present study was to determine the phase relations between cortical and thalamic neuronal activities during the slow EEG oscillation. Intracellular recordings were performed in anesthetized cats from neurons in motor and somatosensory cortical areas, the rostrolateral sector of the reticular (RE) thalamic nucleus, and thalamocortical (TC) cells from ventrolateral (VL) nucleus. The EEG was used as time reference for alignment of activities in different, simultaneously recorded neurons, including dual impalements of cortical cells as well as cortical and TC cells. The spontaneous EEG oscillation was characterized by slowly recurring (0.3-0.9 Hz) sequences of surface-positive (depth-negative) sharp deflections, often followed by oscillatory activity within the frequency range of sleep spindles (7-14 Hz) or at faster frequencies. Cortical and RE cells were similarly hyperpolarized during the depth-positive EEG waves and were depolarized during the depth-negative EEG deflections. In many instances, the cell depolarization was associated with oscillations at the spindle frequency or with tonic firing at rates related to the level of depolarization. TC neurons were hyperpolarized during the depth-positive EEG waves and displayed a series of IPSPs, at the spindle frequencies, during the depth-negative EEG waves. Depending on the membrane potential (Vm), TC cells could fire spike bursts at the onset of the EEG depth-negativity, or their firing could be delayed by subsequent IPSPs. The sequence of spontaneous EEG and cellular events described above also characterized the responses to cortical and thalamic stimulation. Simultaneous intracellular recordings of pairs of cortical cells or cortical and TC cells showed that spontaneous transitions from less synchronized to more synchronized EEG states were marked by a simultaneous hyperpolarization, coincident with an overt depth-positive EEG wave. We conclude that during low-frequency oscillatory states, characteristic of slow-wave sleep, neocortical and thalamic neurons display phase relations that are restricted to narrow time windows, and that synchronization results from a generalized inhibitory phenomenon. Moreover, EEG synchronization is reflected as active inhibition in TC neurons. That this pattern is also present in states of hypersynchronization, such as seizure activity, is shown in the following paper (Steriade and Contreras, 1994).

Animals↗
PubMed1997

EEG spectral analysis of the neuroprotective kappa opioids enadoline and PD117302.

The present study characterized the electroencephalographic (EEG) effects of the neuroprotective kappa opioids enadoline and PD117302 in conscious, freely moving rats with the use of computer-assisted spectral analysis (CASA). Enadoline (25-100 microg/kg) or PD117302 (1.25-5.0 mg/kg) was administered intravenously to rats implanted with cortical EEG electrodes. Although both drugs produced an immediate, mild sedation, there were no signs of head-weaving or ataxia, and there was little visual evidence of opioid-like EEG slow-wave bursts or seizures. Both drugs produced only modest increases in total EEG power that were not dose dependent. In contrast, CASA revealed significant dose-dependent frequency shifts in relative power distributions, thereby identifying distinct kappa opioid alterations in awake EEG activity; EEG power decreased in the 0- to 4-Hz frequency band with concomitant increases in power measured in the 4- to 8-Hz frequency range. The kappa opioids produced a dose-dependent consolidation of the EEG waveform centered about a peak frequency of 5.0 Hz (for enadoline) or 4.8 Hz (for PD117302) and a significant shift in the mean EEG frequency from 6.6 Hz (predrug) to 6.2 Hz (postdrug). Further CASA revealed significant postdrug decreases in the edge frequency, mobility and complexity of the EEG. Both drugs produced moderate increases in the latency to slow-wave sleep (SWS). Overall, enadoline (ED50 = 18 microg/kg) was approximately 94 times more potent than PD117302 (ED50 = 1690 microg/kg) in producing the kappa EEG profile. Because the kappa-induced EEG changes were stereospecific for the (-)-enantiomers and inhibited by norbinaltorphimine (nor-BNI), the EEG "fingerprint" described in this study could be attributed to specific activation of brain kappa opioid receptors.

Animals↗
PubMed1998

Biophysical linkage between MRI and EEG amplitude in closed head injury.

Nuclear magnetic resonance of brain water proton (1H) T2 relaxation times and measures of absolute amplitude of EEG were obtained from 19 closed head injured patients. The relationship between EEG and T2 relaxation time differed as a function of both EEG frequency and gray matter versus white matter. White matter T2 relaxation time was positively correlated with increased EEG amplitude in the delta frequency band (0.5-3.5 Hz). In contrast, lengthened gray matter T2 relaxation time was inversely correlated with EEG amplitude in the alpha and beta frequency bands (7-22 Hz). These findings are consistent with clinical EEG studies in which white matter lesions are related to increased EEG delta amplitude and gray matter lesions are related to decreased EEG alpha and beta frequency amplitude. Estimates of the severity of injury were obtained by neuropsychological measurements, in which lengthened T2 relaxation times in both the neocortical gray and white matter were correlated with diminished cognitive function. Decreased EEG beta and alpha amplitude and increased EEG delta amplitude were also correlated with diminished cognitive function. The findings imply a biophysical linkage between the state of protein-lipid structures of the brain as measured by the MRI and the scalp-recorded EEG.

Adult↗
PubMed2000

A method for removing imaging artifact from continuous EEG recorded during functional MRI.

Combined EEG/fMRI recording has been used to localize the generators of EEG events and to identify subject state in cognitive studies and is of increasing interest. However, the large EEG artifacts induced during fMRI have precluded simultaneous EEG and fMRI recording, restricting study design. Removing this artifact is difficult, as it normally exceeds EEG significantly and contains components in the EEG frequency range. We have developed a recording system and an artifact reduction method that reduce this artifact effectively. The recording system has large dynamic range to capture both low-amplitude EEG and large imaging artifact without distortion (resolution 2 microV, range 33.3 mV), 5-kHz sampling, and low-pass filtering prior to the main gain stage. Imaging artifact is reduced by subtracting an averaged artifact waveform, followed by adaptive noise cancellation to reduce any residual artifact. This method was validated in recordings from five subjects using periodic and continuous fMRI sequences. Spectral analysis revealed differences of only 10 to 18% between EEG recorded in the scanner without fMRI and the corrected EEG. Ninety-nine percent of spike waves (median 74 microV) added to the recordings were identified in the corrected EEG compared to 12% in the uncorrected EEG. The median noise after artifact reduction was 8 microV. All these measures indicate that most of the artifact was removed, with minimal EEG distortion. Using this recording system and artifact reduction method, we have demonstrated that simultaneous EEG/fMRI studies are for the first time possible, extending the scope of EEG/fMRI studies considerably.

Adult↗
PubMed2001

Topographic time-frequency decomposition of the EEG.

Frequency-transformed EEG resting data has been widely used to describe normal and abnormal brain functional states as function of the spectral power in different frequency bands. This has yielded a series of clinically relevant findings. However, by transforming the EEG into the frequency domain, the initially excellent time resolution of time-domain EEG is lost. The topographic time-frequency decomposition is a novel computerized EEG analysis method that combines previously available techniques from time-domain spatial EEG analysis and time-frequency decomposition of single-channel time series. It yields a new, physiologically and statistically plausible topographic time-frequency representation of human multichannel EEG. The original EEG is accounted by the coefficients of a large set of user defined EEG like time-series, which are optimized for maximal spatial smoothness and minimal norm. These coefficients are then reduced to a small number of model scalp field configurations, which vary in intensity as a function of time and frequency. The result is thus a small number of EEG field configurations, each with a corresponding time-frequency (Wigner) plot. The method has several advantages: It does not assume that the data is composed of orthogonal elements, it does not assume stationarity, it produces topographical maps and it allows to include user-defined, specific EEG elements, such as spike and wave patterns. After a formal introduction of the method, several examples are given, which include artificial data and multichannel EEG during different physiological and pathological conditions.

Adult↗
PubMed1991

The value of EEG-mapping in focal cerebral lesions.

In 148 patients with focal cerebral lesions the findings of EEG mapping, routine EEG and CT were compared. Regarding etiology 43 patients suffered from completed stroke (CS), 43 patients from transient ischemic attack (TIA), 33 patients had an intracerebral hemorrhage (ICH) and 29 an hemispheric tumor. In 37 patients with CS (86%) and 27 patients with TIA (63%) the EEG mapping revealed focal changes, but only in 28 patients with CS (65%) and in 11 patients (26%) with TIA using routine EEG alone. Thus the EEG mapping showed focal abnormalities significantly more often. In the remaining patient groups no significant difference in the results of EEG mapping or routine EEG could be demonstrated. Focal abnormalities corresponding to focal lesions seen in CT were obtained by means of EEG mapping in 27 patients (90%) with CS and 10 patients (77%) with TIA, but only in 17 patients (57%) with CS and 4 patients (31%) with TIA using routine EEG and in that way the EEG mapping could indicate focal lesions in CT significantly more often than routine EEG. In the remaining patient groups no significant difference in the number of focal changes corresponding to lesions in CT could be seen.

Aged↗
PubMed2004

EEG-mapping differences between narcolepsy patients and controls and subsequent double-blind, placebo-controlled studies with modafinil.

The aim of the present study was to investigate the role of EEG mapping as an objective and quantitative measure of vigilance in untreated and modafinil-treated narcoleptics, and compare it with the conventional neurophysiological method of the Multiple Sleep Latency Test (MSLT) and the subjective Epworth Sleepiness Scale (ESS). In 16 drug-free narcoleptics and 16 normal controls a baseline 3-min vigilance-controlled EEG (V-EEG) and a 4-min resting EEG (R-EEG) were recorded during midmorning hours. Thereafter, in a double-blind, placebo-controlled crossover design, patients were treated with a 3-week fixed titration of modafinil (200, 300, 400 mg) and placebo. EEG-mapping, MSLT and ESS measures were obtained before and at the end of the third week of therapy. Statistical overall analysis by means of the omnibus significance test demonstrated significant EEG differences between untreated patients and controls in the resting condition only (R-EEG). Subsequent univariate analysis revealed an increase in absolute and relative theta power, a decrease in alpha-2 and beta power as well as a slowing of the dominant frequency and the centroids of the alpha, beta and total power spectrum and thus objectified a vigilance decrement in narcolepsy. Modafinil 400 mg/d significantly improved vigilance as compared with placebo (p < or = 0.01), inducing changes opposite to the aforementioned baseline differences (key-lock principle). The MSLT and the ESS also improved under modafinil as compared with placebo, but changes were less consistent. Spearman rank correlations revealed the highest correlations between EEG mapping and the ESS, followed by those between EEG mapping and the MSLT, while the lowest correlation was found between the MSLT and the ESS. In conclusion, EEG mapping is a valuable instrument for measuring vigilance decrements in narcolepsy and their improvement under psychostimulant treatment.

Adult↗
PubMed2002

Nonlinear dynamics of the EEG separated by independent component analysis after sound and light stimulation.

The electroencephalogram (EEG) is a multiscaled signal consisting of several time-series components each with different dominant frequency ranges and different origins. Nonlinear measures of the EEG reflect the complexity of the overall EEG, but not of each component in it. The aim of this study is to examine effect of the sound and light (SL) stimulation on the complexity of each component of the EEG. We used independent component analysis to obtain independent components of the EEG. The first positive Lyapunov exponent (L1) was estimated as a nonlinear measure of complexity. Twelve subjects were administered photic and auditory stimuli with a frequency of 10 Hz, which corresponded to the alpha frequency of the EEG, by a sound and light entrainment device. We compared the L1 values of the EEGs and their independent components between baseline and after the SL stimulation. We detected that the L1 values of the EEG decreased after the SL stimulation in all channels except C3 and F4, indicating that the complexity of the EEG decreased. We showed that alpha components increased in proportion but decreased in complexity after the SL stimulation. The beta independent components were found to decrease in proportion and complexity. These results suggest that decreased complexity of the EEG after the SL stimulation may be principally caused by decreased complexity and increased proportion of the alpha independent components. We showed also that theta components increased in complexity after the SL stimulation. We propose that nonlinear dynamical analysis combined with independent component analysis may be helpful in understanding the temporal characteristics of the EEG, which cannot be detected by conventional linear or nonlinear methods.

Acoustic Stimulation↗
PubMed2000

Topographic analysis of dimension estimates of EEG and filtered rhythms in epileptic patients with complex partial seizures.

Nonlinear dynamic properties were analyzed on the EEG and filtered rhythms recorded from healthy subjects and epileptic patients with complex partial seizures. Estimates of correlation dimensions of control EEG, interictal EEG and ictal EEG were calculated. The values were demonstrated on topograms. The delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz) and gamma (30-40 Hz) components were obtained and considered as signals from the cortex. Corresponding surrogate data was produced. Firstly, the influence of sampling parameters on the calculation was tested. The dimension estimates of the signals from the frontal, temporal, parietal and occipital regions were computed and compared with the results of surrogate data. In the control subjects, the estimates between the EEG and surrogate data did not differ (P > 0.05). The interictal EEG from the frontal region and occipital region, as well as its theta component from the frontal region, and temporal region, showed obviously low dimensions (P < 0.01). The ictal EEG exhibited significantly low-dimension estimates across the scalp. All filtered rhythms from the temporal region yielded lower results than those of the surrogate data (P < 0.01). The dimension estimates of the EEG and filtered components markedly changed when the neurological state varied. For each neurological state, the dimension estimates were not uniform among the EEG and frequency components. The signal with a different frequency range and in a different neurological state showed a different dimension estimate. Furthermore, the theta and alpha components demonstrated the same estimates not only within each neurological state, but also among the different states. These results indicate that the theta and alpha components may be caused by similar dynamic processes. We conclude that the brain function underlying the ictal EEG has a simple mechanism. Several heterogeneous dynamic systems play important roles in the generation of EEG.

Adult↗
PubMed1991

EEG and neuroimaging localization in partial epilepsy.

We have studied cortical localization provided by surface and sphenoidal electroencephalograms (EEGs) and that of computed tomography (CT), magnetic resonance imaging (MR) and single photon emission tomography (SPECT) in 58 patients with partial epilepsy. Each patient had EEG, MR and SPECT during a hospitalization period of 1-2 weeks. CT scans were obtained either during the same period or had been performed in the preceding year. EEG evaluation consisted of 3-5 days of continuous monitoring including video-telemetry and ambulatory recording as well as conventional EEGs with special electrode placements. Additionally 33 of 58 patients (55%) who were potential surgical candidates had sphenoidal recordings. All patients had an abnormal EEG which showed evidence of epileptic hyperexcitability. EEG abnormality was localized in 43 patients (74%). Neuroimaging studies were focally abnormal in 38 patients (66%); 12 CT (21%), 29 MR (50%) and 24 SPECT (41%). Thirty four of 43 patients with localized EEG had at least 1 focally abnormal neuroimaging study (79%), whereas 4 of 15 (27%) patients with non-localized EEG did so. Twenty-eight of 29 patients with focal MR (97%), 11 of 12 patients with focal CT (92%) and 20 of 24 patients with focal SPECT (83%) had a concordant focal EEG. EEG and neuroimaging localization agreed in all 15 patients in whom both MR and SPECT disclosed a concordant focal abnormality. This study demonstrates a significant (P less than 0.005) correlation between surface/sphenoid EEG and neuroimaging localization in partial epilepsy.

Adolescent↗
PubMed1991

Striatal depth EEG reveals postsynaptic activity of striatal neurons following dopamine receptor stimulation and blockade.

This paper demonstrates a technique for measuring depth electroencephalographic (EEG) recordings from the freely moving mouse. This technique minimizes electrical artifact associated with gross movements by amplifying the current of the EEG signal directly at permanently indwelling electrodes. Stable EEG signals, with high signal-to-noise ratios, can be obtained from these animals while their movement inside the testing cage remains relatively unrestricted. We used this technique to examine the effects of dopamine (DA) receptor agonist and antagonist treatments on depth EEG signals generated within the striatum. Baseline measures of spontaneous striatal EEG activity were obtained prior to drug administration and post-drug measures of striatal activity were subsequently obtained. Apomorphine treatment resulted in desynchronization of striatal EEG signals while haloperidol or sulpiride treatment induced slow wave synchronization. Fast Fourier analysis of EEG signals revealed that DA agonist and antagonist treatment altered spontaneous striatal EEG activity in an opposite manner--relative to baseline signals, apomorphine attenuated low frequency components and augmented higher frequency components of the signal while haloperidol augmented low frequency components and attenuated higher frequency components of the signal. Moreover, mice pretreated with unilateral intracerebral injections of sulpiride and subsequently administered systemic apomorphine simultaneously demonstrated EEG synchronization on the side ipsilateral to the injection of sulpiride and EEG desynchronization on the contralateral side. The population of neurons examined in the medial striatum appear to have the properties of being excitatory to DA agonist stimulation and show decreased activity following DA antagonist treatment. These results suggest that striatal EEG activity may be used as measure of postsynaptic activity of dopaminergic neurons.

Animals↗
PubMed1984

EEG assessment of brain activity: spatial aspects, segmentation and imaging.

High temporal resolution and sensitivity to index different functional brain states makes the EEG a powerful tool in psychophysiology. Its full potential can now be utilized since recording technology and computational power for the large data masses has become affordable. However, basic traditional strategies in EEG need reviewing. Conventional, spontaneous or evoked EEG traces which are used for various complex analyses give ambiguous information on EEG power (amplitude) and phase for a given point on the scalp. Principally, analysis should first be done over space, then over time, to avoid ambiguities or pre-selections. First or second spatial derivative computations can provide "reference-free" data for analyses over time. We propose to use direct, spatial approaches for the analysis of the scalp EEG field distributions when simultaneous recordings in several EEG channels can be examined. The ambiguity of the conventional EEG waveshapes results in different, equally "correct" scalp maps of EEG power of the same multichannel data for different reference electrodes. An exception are scalp maps of EEG power computed against the common, average reference, as they are related to the reference-free spatial distribution (maps) of the maximal and minimal (extreme) field values over time, and thus are directly interpretable in terms of net orientation of the generator process. A proposed, reference-free EEG segmentation into epochs of periodically stationary spatial distributions of the mapped scalp EEG fields uses the locations of maximal and minimal (extreme) field values at each moment in time as classifiers, and thus avoids the priviledging of two arbitrarily chosen recording points in the field.

Brain↗