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Biomedical subjects

D W Duke

Publications and source records attributed to D W Duke.

12 recordsLinked to original sources
PubMed1997

Segregation of the thalamic alpha rhythms from cortical alpha activity using the Savit-Green S-statistic and estimated correlation dimension.

The large-amplitude, occipital alpha rhythm of the human electroencephalogram (EEG) is associated in normal subjects with a state of relaxed wakefulness. We analyzed resting eyes-open and eyes-closed human EEG data using three measures: power in the 8-12-Hz alpha frequency band, estimated correlation dimension (D2), and the Savit-Green S-statistic. At occipital loci, two groups of points were evident in the scatterplot of S vs. estimated D2. Group A was of higher dimension and consisted of predominantly eyes-open records. Group B was of lower dimension and consisted of more eyes-closed than eyes-open records. Furthermore, Group B had a broad range of alpha power, with alpha power being negatively correlated with estimated D2 (higher alpha power associated with lower dynamical complexity). In contrast, Group A had a very small range of low alpha power, and was positively correlated with estimated D2 (higher alpha power associated with increased dynamical complexity). Our results indicate that Group B EEG (the alpha rhythm) and Group A EEG (EEG containing 'other' alpha activity) have fundamentally different dynamical properties.

Adult↗
PubMed1996

Application of dimension estimation and surrogate data to the time evolution of EEG topographic variables.

Dimensional complexity (estimated correlation dimension) was measured for two topographic EEG time series: (a) the time evolution of global field power (GFP) and (b) the time evolution of sequential dissimilarity (SQD) for resting, eyes-closed and eyes-open data. Eyes-closed GFP and eyes-closed/open SQD all had an element of nonlinearity in their dynamics as evidenced by increased dimensional complexity associated with the phase-angle randomization, Gaussian surrogate-data procedure. However, none of the three gave any evidence of being deterministic chaotic processes. Eyes-open GFP dimensional complexity could not be distinguished from a linear-stochastic process.

Adult↗
PubMed1996

On the validity of estimating EEG correlation dimension from a spatial embedding.

We demonstrate by using simulations that spatial embedding of single-variable time series data does not reliably reconstruct state-space dynamics. Instead, correlation dimension estimated from spatially embedded data is largely a measure of linear cross-correlation in the data set. For actual electroencephalographic (EEG) data, we demonstrate a high negative correlation between spatial correlation dimension and the average amount of lag-zero cross-correlation between "nearest-neighbor" embedding channels (the greater the cross-correlation, the lower the dimension). We also show that the essential results obtained from spatially embedding EEG data are also obtained when one spatially embeds across a set of highly cross-correlated stochastic (second-order autoregressive) processes. Although, with appropriate surrogate data, correlation dimension estimated from spatially embedded data detects nonlinearity, its use is not recommended because correlation dimension estimated from temporally embedded data both reconstructs state-space dynamics and, with appropriate surrogate data, detects nonlinearity as well.

Algorithms↗
PubMed1996

Effects of cigarette smoking on EEG spectral-band power, dimensional complexity, and nonlinearity during reaction-time task performance.

Electroencephalogram (EEG) and heart rate (HR) were recorded while individuals performed visual and auditory go/no-go reaction time (RT) tasks. Overnight-abstaining smokers smoked two types of cigarettes in a single morning session. The first type was smoked once and had a nicotine yield of 0.05 mg. Two cigarettes of the second type (1.1 mg) were smoked. Four recordings were made: presmoking, postsmoking 0.05 mg, and postsmoking each 1.1 mg. HR was increased only by the first 1.1-mg cigarette. Smoking both the 1.1-mg cigarettes decreased RT. Smoking the first 1.1-mg cigarette increased EEG power in the beta2 band. A flexible effect of smoking the first 1.1-mg cigarette on EEG dimensional complexity (DCx) was obtained at locus Cz. Specifically, DCx was (a) raised when the presmoking level was low, (b) not affected when the presmoking level was intermediate, and (c) lowered when the presmoking level was high. Surrogate-data testing indicated the presence of nonlinearity in the EEG data that was not affected by smoking. Decreased RT was associated with increased DCx in the visual task only.

Adult↗
PubMed1995

Measuring "chaos" in the brain: a tutorial review of EEG dimension estimation.

The technique of dimension estimation is currently a leading application of nonlinear dynamics (popularly termed "chaos theory") to EEG analysis. A tutorial review of this technique is presented along with some elementary background concepts from nonlinear dynamics. Practical aspects of applying dimension estimation to EEG data are also reviewed, and the possible role of deterministic chaos in brain function is discussed.

Brain↗
PubMed1995

No effect of cigarette smoking on electroencephalographic nonlinearity.

The Gaussian surrogate-date procedure was applied to the measurement of the effect of cigarette smoking on the dimensional complexity of normal, resting EEG. Evidence of significant nonlinearity in the EEG was obtained, replicating previous results. However, unlike EEG dimensional complexity, EEG nonlinearity (difference between original and surrogate data) was not affected by smoking. This indicates that, under resting conditions, smoking/nicotine may have a modulating effect on input from the reticular activating system, with such input having a global, linearizing effect on cortical dynamics. Nonlinear dynamics resulting from intracortical processes appear not to be affected.

Adult↗
PubMed1995

Dimensional analysis of resting human EEG. II: Surrogate-data testing indicates nonlinearity but not low-dimensional chaos.

Surrogate-data testing has recently been proposed as one way to detect the presence of nonlinearity and low-dimensional chaos in experimental time series. Such testing involves estimating correlation dimension for both the original data and surrogate data from which nonlinearity has been removed. We applied such testing to the same resting, eyes-closed, and eyes-open electroencephalogram (EEG) data set that was originally analyzed using dimension estimation applied only to the original data (Pritchard & Duke, 1992). Two kinds of surrogate-data sets had higher estimated dimension and poorer saturation. This indicates that the normal resting human EEG is nonlinear and therefore not a linear-stochastic system. Because nearly complete saturation at some loci was not differently affected by the surrogate-data procedures, our results also indicate that the normal resting human EEG is high dimensional and does not represent low-dimensional chaos.

Adult↗
PubMed1994

EEG-based, neural-net predictive classification of Alzheimer's disease versus control subjects is augmented by non-linear EEG measures.

Attempts to classify Alzheimer's disease (AD) subjects versus controls using spectral-band measures of electroencephalographic (EEG) data typically achieve around 80% success. This study assessed the ability of adding non-linear EEG measures and using a neural-net classification procedure to improve this performance level. The non-linear EEG measures were estimated correlation dimension ("dimensional complexity," or DCx) and saturation (degree of leveling-off of DCx with increasing embedding dimension). In a sample of 39 subjects (14 ADs, 25 controls), it was found that (a) the addition of non-linear EEG measures improved the classification accuracy of the AD/control status of subjects, and (b) a back-percolation neural net predictively classified the subjects much better than the standard linear techniques of multivariate discriminant analysis or nearest-neighbor discriminant analysis.

Aged↗
PubMed1993

Flexible effects of quantified cigarette-smoke delivery on EEG dimensional complexity.

A quantified smoke delivery system (QSDS) was used to experimentally control the administration of inhaled cigarette smoke to 28 male smokers. One puff (2 s, 35 cc) was taken every 30 s on a cigarette (nicotine yield 1.0 mg) until the char line reached 3 mm from the filter wrap. The smoke was inhaled for 5 s. Resting eyes-closed and eyes-open EEG was recorded from F3, F4, P3, and P4 before and after quantified smoke delivery (QSD). EEG dimensional complexity (DCx, a measure derived from chaos theory) was computed using the Takens-Ellner method. QSD appeared to have a 'flexible' effect on EEG DCx, primarily lowering it in subjects whose pre-smoking level was high, not affecting it in subjects whose pre-smoking level was intermediate, and tending to raise it in subjects whose pre-smoking level was low. This replicates previous results obtained with ad libitum smoking, suggesting the hypothesis that smoking may have an "optimizing" effect on the complexity of brain dynamics.

Adult↗
PubMed1992

HIV and the brain: evidence of early involvement and progressive damage.

AIDS is often accompanied by progressive encephalopathy and 'subcortical' dementia, but there is uncertainty regarding how early the brain involvement may begin in the course of HIV infection. This study used a cognitive auditory 'oddball' paradigm to elicit sensory and cognitive event related potential (ERP) components from healthy controls and from patients at different stages of HIV infection. Sensory component latencies did not differ between groups, but cognitive components showed progressive delays corresponding to increasingly severe clinical stages of HIV infection. The earliest changes were found among asymptomatic HIV + patients, suggesting that this test is a sensitive indicator of early subclinical CNS damage. In contrast, neither frequency analysis nor nonlinear dynamical analysis of the EEG showed differences between healthy controls and patients.

AIDS-Related Complex↗
PubMed1992

Dimensional analysis of no-task human EEG using the Grassberger-Procaccia method.

A method developed by Grassberger and Procaccia allows estimation of the dimensional complexity of the state-space attractor of a time series. Saturation of dimensional-complexity estimates with increasing values of embedding dimension is considered a strong indication that the time series is governed by deterministic chaos. The present investigation employed the Grassberger-Procaccia method to estimate EEG dimensional complexity in a multi-subject, factorial experiment. Twelve subjects were tested under two no-task conditions (eyes closed and open), with the block of two conditions being repeated four times. EEG was recorded from the nineteen 10-20 loci. Dimensional complexity declined across Blocks 1-3 and then leveled off, and was higher in the eyes-open than in the eyes-closed condition. Condition also interacted with locus in that the increase in dimensional complexity associated with opening the eyes was greater over occipital loci. Comparison with the results of Fourier analysis indicated that a similar but not identical pattern of effects was obtained for alpha (8-12 Hz) power. Further, across the entire data set, if alpha power exceeded a value of about 70 microV2, dimensional complexity was uniformly low, a finding in concert with previous results indicating that the eyes-closed, occipital alpha rhythm possibly represents deterministic chaos of relatively low dimension.

Brain Mapping↗