Charles L. Yeager

Relationship between reaction time and electroencephalographic alpha phase.

Demonstrations of a relationship between human 8 to 13 per second (alpha) electroencephalographic activity and simple visual reaction time can be made at reliable levels of confidence by (i) sampling reaction times to stimuli given at phases of the alpha cycle 10 msec apart, (ii) selecting the phase with the slowest reaction times, and (iii) collecting enough reaction times to stimuli at this and some other control phase for statistical comparison.

EEG patterns during ‘cognitive’ tasks. I. Methodology and analysis of complex behaviors

This paper presents a methodology which uses nonlinear pattern recognition to study the spatial distribution of EEG patterns accompanying higher cortical functions. The multivariate decision rules reveal the essential EEG patterns which differentiate performance of two tasks. Cross-validation classification accuracy measures the generality of the findings. Using this method, EEG patterns were derived from a group of 23 adults during performance of several complex tasks, including Kohs block design, writing sentences, mental paper folding, and reading silently. These patterns discriminate between the tasks, are consistent with, and extend the results of, visual EEG interpretations and univariate analysis of spectral intensities. Since writing sentences could not be distinguished from mere scribbling, it is unclear whether the EEG patterns found to distinguish complex behaviors were related to the cognitive components of tasks, or to sensory-motor and performance-related factors.

Automated analysis of the electrical activity of the human brain (EEG): A progress report

Clinical evaluation of electroencephalographic (EEG) recordings is based on complex subjective processes of data reduction and feature extraction. The high dimensionality of the EEG signal, its variability, and the lack of standard population values have retarded development of automated systems. An interactive, real-time analysis system (ADIEEG) has been implemented to develop features to simplify visual interpretation and facilitate automated classification. It uses a 40 000 word PDP15-PDP11 dual processor computer. Resident code occupies approximately 11 000 locations, while a maximum of 12 000 locations are used for buffers. The system performs 1) continuous spectral analysis using the fast Fourier transform to produce estimates of power and coherence, 2) parallel time domain analysis to detect sharp transients significant to diagnosis, 3) several forms of graphics, 4) simple algorithms to reject noncortical and instrumental artifact, 5) interactive parameter alteration and on-line feedback to adjust decision thresholds when necessary, and 6) extraction of diagnostically helpful features using heuristics based on clinical EEG. The ADIEEG system resides in the University of California, San Francisco Medical Center, and Langley Porter Neuropsychiatric Institute.

On-line computer rejection of EEG artifact

Abstract Simple, on-line, frequency domain procedures to detect non-continuous artifact in the waking EEG are presented. Individual algorithms detect head and body movements, large muscle potentials and eye-movement potentials. These algorithms are implemented as program modules in an interactive, real-time, spectral and transient analysis and display system, ADIEEG, described elsewhere. The systems performance in detecting artifact-contaminated EEG in 35 normal and abnormal, 3 min, 8-channel recordings was compared with that of the consensus of three expert scorers. The system correctly detected 65% of the artifact events identified by the consensus of expert scorers. Twenty-seven percent of the detections made by the system were of events that had not been marked by any of the three scorers. This performance was not statistically different from the average of the individual scorers vs. the consensus. The largest number of false detections were of intermittent, high-amplitude events of cortical origin which did not occur during the supervised calibration period.

Visual imagery and electroencephalographic changes

Abstract The changes in the electroencephalogram relating to active vision, visual imagery, recall, and visual-motor performance were studied in a group of 180 psychiatric patients, and in 15 blind adolescent students. The conclusions from this study are as follows: 1. 1. An accurate reproduction of a diagram was associated with a low potential (mean 22.2 μV.), relatively non-rhythmical type of electrical activity from the occipital areas during the subjectss non-stimulated state. 2. 2. An inaccurate reproduction was associated with a higher potential (mean 32 μV), rhythmical activity from the occipital areas during rest. 3. 3. The attempted recall of a previously presented picture resulted in a 31 per cent reduction in potential as opposed to the 54.5 per cent during active vision. 4. 4. The influence of “surprise” or an increased awareness appeared to produce a greater electrical change than that related to the complexity of the diagrams. 5. 5. No significant correlations were found between performance and age or sex, the presence of EEG abnormality, the percentage of reduction during active vision or recall, or the rate of reappearance of the alpha activity on eye closure. 6. 6. Some suggestive evidence was presented that visual imagery in the blind is associated with a greater potential change than other types of imagery, and that visual imagery is more prominent in individuals who have lost their sight after two years of age.

Computer rejection of EEG artifact. II. Contamination by drowsiness

As part of an effort to automatically measure a background EEG baseline against which changes due to therapy or experimental manipulations may be measured, algorithms to detect EEG patterns associated with drowsiness have been developed and objectively evaluated. The decision of drowsiness is tentatively based upon changes in simple signal features, including increased ratios of both delta-band to alpha-band and theta-band to alpha-band spectral intensity as compared to thresholds automatically determined from a waking calibration period. Several heuristic criteria are then required to reach a final decision. Thirty-one normal and abnormal, 3-minute, 8-channel clinical EEG recordings containing drowsiness were scored by 5 expert scorers. Out of a total of 106 events labeled drowsy by at least one judge, 85 were found by a consensus of 3 or more of the 5 experts. On the 20 recordings not used for training the decision thresholds (testing data set), the system found 84% for the 85 episodes found by the consensus, and 89% of the 62 episodes found by all 5 scorers. Only one event was found by the system which was not found by any scorer, or which did not border on a consensus-defined episode of drowsiness. This performance is adequate to justify inclusion of these algorithms into a previously described real time EEG analysis system, ADI-EEG, allowing integration of the decisions of the separate subsystems for detection of artifact, sharp transients and drowsiness.

A compact six-channel integrated circuit EEG telemeter.

Abstract 1. 1. The lightweight head-mounted telemeter described permits artifact-free EEG recording during laughter. 2. 2. By utilizing pulse position modulation and reduced battery voltages it has been practical to use integrated circuits without excessive battery drain. 3. 3. Clip-on rechargeable battery packs facilitate recording for fairly long periods. 4. 4. The use of low noise pre-amplifiers with “micropak” transistors has made it practical to telemeter small amplitude EEGs from normal subjects. 5. 5. Either needle or disc electrodes can be used. Depth electrodes can be used with external attenuators. 6. 6. Since the transmitter is crystal controlled, it has virtually no frequency drift. 7. 7. With the addition of external networks, the telemeter can be used for respiration, electrocardiogram and galvanic skin response recording.

Heuristic real time feature extraction of the electroencephalogram (EEG)

The extremely complex nature of the electroencephalogram (EEG), and the subtle, nonquantified methods of pattern recognition used by human interpreters have made EEG analysis resistant to automation. Attempts at pattern recognition using multivariate classification procedures have not produced generalizable results due to the inadequate degree and quality of feature extraction prior to classification. A real time, on-line EEG analysis strategy is described which incorporates feature extracting algorithms derived from models of human EEG interpretation. A system based upon this strategy has been implemented on a dedicated minicomputer. It includes: 1) spectral analysis using the Fast Fourier Transform (FFT) to produce continuous estimates of power and coherence; 2) parallel time domain analysis to detect the occurrence of sharp transient events of possible clinical significance; 3) continuous isometric display of spectral and transient functions; 4) spectral and time domain algorithms for the rejection of noncortical and instrumental artifact; 5) heuristics to isolate patterns and events of potential clinical significance; 6) interactive alteration of analysis and display parameters to facilitate manipulation of data from various experimental paradigms; 7) on-line feedback to alter, when necessary, artifact rejection, transient detection and feature extraction decision thresholds.

Simultaneous study of behavior and brain waves.

A technique for the simultaneous audiovisual recording of behavior and brain waves is described. The absence of muscle movement artifact, despite unlimited activity of the patient, suggests that telemetering may be adaptable for routine electroencephalography.

Electroencephalographic changes in procainization of the frontal lobes

Abstract 1. 1. Procaine injected into the fronto-thalamic fibers produces transitory slowing in the EEG in the majority of cases. 2. 2. Almost complete electrical suppression was observed following 9 of the Procaine injections in which Procaine escaped into the subarachnoid or ventricular system. 3. 3. Paroxysmal cerebral dysrhthmia was observed in the recovery phase following 9 of the Procaine injections. 4. 4. Isotonic saline produced little change in electrical activity.