PubMed Health⌕ Search

Biomedical subjects

G M Zeitlin

Publications and source records attributed to G M Zeitlin.

7 recordsLinked to original sources
PubMed1987

Human neuroelectric patterns predict performance accuracy.

In seven right-handed adults, the brain electrical patterns before accurate performance differed from the patterns before inaccurate performance. Activity overlying the left frontal cortex and the motor and parietal cortices contralateral to the performing hand preceded accurate left- or right-hand performance. Additional strong activity overlying midline motor and premotor cortices preceded left-hand performance. These measurements suggest that brief, spatially distributed neural activity patterns, or "preparatory sets," in distinct cognitive, somesthetic-motor, and integrative motor areas of the human brain may be essential precursors of accurate visuomotor performance.

Adult↗
PubMed1979

Electroencephalogram correlates of higher cortical functions.

By means of two-stage, nonlinear multivariate pattern recognition, electroencephalograms (EEG's) were analyzed during performance of verbal and spatial tasks. Complex scalp distributions of theta-, beta-, and, to a lesser extent, alpha-band spectral intensities discriminated between the two members of a pair of tasks, such as writing sentences and Koh's block design. Small EEG asymmetries were probably attributable to limb movements and other uncontrolled noncognitive aspects of tasks. Significant EEG differences beteeen cognitive tasks were eliminated when controls for inter-task differences in efferent activity, stimulus characteristics, and performance-related factors were introduced. Each controlled task was associated with an approximately 10 percent reduction, as compared with visual fixation, in the magnitude of alpha- and beta-band spectral intensity. This effect occurred bilaterally and was approximately the same over occipital, parietal, and central regions, with some minor difference over the frontal region in the beta band. With these controls, no evidence for lateralization of different cognitive functions was found in the EEG.

Adult↗
PubMed1979

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 Koh's 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.

Adult↗
PubMed1979

EEG patterns during 'cognitive' tasks. II. Analysis of controlled tasks.

This experiment was designed to distinguish possible EEG correlates of the cognitive components of tasks from EEG patterns associated with stimulus characteristics, limb and eye movements, and performance-related factors such as subjects' ability and effort. Thirty-two right-handed adults each performed 30 trials, lasting 6-15 sec each, of four simplified, controlled tasks: mental rotation of geometric forms, serial addition of a column of signed digits, substitution of letters with subsequent word recognition and visual fixation. The first three tasks could not be differentiated from each other. Each of these tasks could be differentiated from visual fixation by approximately 10% generalized reductions in alpha and beta band intensities, and slight increases in theta band intensities frontally and occipitally. We conclude that the EEG patterns which differentiated the complex tasks described in Part I were due to inter-task differences in stimulus characteristics, efferent activities and/or performance-related factors, rather than to cognitive differences. With these controls, no evidence for lateralization of different types of cognitive activity was found in the EEG.

Adult↗
PubMed1977

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.

Computers↗