Subjects chose and pretended to steal one object from a box of nine. They then watched a visual display of verbal representations of objects including their chosen object or one of eight novel objects on each trial. They were told to count one of the novel objects and that although they were welcome to try to beat our test, they would be unable to avoid noticing the chosen object. P3 responses were obtained only to counted and to chosen objects in 7 of 10 subjects not eliminated for artifact or noncooperation.

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Subjects were allowed to choose an item to keep from nine items in a box. They then were shown one of nine words randomly selected on a display screen. One of these words described the chosen item, the others described novel items. The subjects were told to try not to react emotionally to any of the words, but to try to defeat this test of deception. It was found that large positive waves with latencies between 400 and 700 ms poststimulus were present in the ERPS to the chosen but not to the novel words.

Two experiments were performed in which we compared the effects of selected non-deviant versus categorically deviant stimuli on parietal P3 under a variety of conditions in which one, both, or neither stimulus was a target of an experimental task. Subjects were repeatedly presented with series of 8 numeric stimuli and 1 alphabetic (Deviant) stimulus. P3 amplitudes to target and nontarget Deviant stimuli were consistently and significantly larger than to other, non-deviant targets and nontargets, respectively. Nontarget Deviant stimuli evoked P3 amplitudes comparable to those evoked by low-probability non-deviant targets. The observed differences indicate that P3 amplitude is a sensitive indicator of perceived category differences, and that the effect of category deviance on parietal P3 amplitude is independent of task response classification (target or nontarget) and of response probability.

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This paper presents the application ofan overlapping sampling technique usedwith a fast Fourier transform on electroencephalographic data. The use of this sampling and analysis technique is demonstrated on data in which steady state, rate of change, and critical event hypotheses are tested. The benefit of applying computer-generated three-dimensional graphics to the results of using this innovative sampling and analysis technique is emphasized.We determined several years ago that there was an inordinate amount of variance in electroencephalographic (EEG) data (Bremner, Yost, & McKenzie, 1982). Although we believed that the data were gathered using valid techniques, we suspected that the large variances were a function of large inter-and intrasubject differences. We determined that there were large variances in the data gathered on a subject under a given experimental condition and that, when the data gathered on a set of 20 subjects under the same experimental condition were composited in a statistical analysis, the variance for the group more than doubled. Even though the differences in the means of two different groups of subjects under two different experimental conditions were "large," the variances kept us from obtaining statistically significant differences when we believed that the subjects' reactions to the different experimental conditions were significantly different. We were unsuccessful in overcoming the problem oflarge variances using different univariate, multivariate, and nonparametric techniques. Also, after examining several different methods of compositing and transforming data, we determined that each of these tended Address correspondence to Michael Yost, Office of the President, Trinity University, 715 Stadium Dr., San Antonio, TX 78284.to remove some of the information that was contained in the original data.We solved the problem oflarge variances by developing a single-subject experimental design and statistical analysis approach for our research (Bremner, Yost, and Pike, 1984;Bremner, Yost, and Zintgraff, 1985;Yost, Bremner, & Fox, 1985). This approach permitted us to gather data in which the variance was the variation in the response of a single subject under a given experimental condition. When we made comparisons of responses to different experimental conditions, the variances were a function of differences in the response of a subject and not differences among subjects. Using these approaches, we were able to reduce the variances and obtain what we considered to be valid and reliable experimental results.The fast Fourier transform (FFT) and a variety of smoothing functions are used in analyzing neuropsychological data. We examined the effect of these techniques in two studies (yost, Bremner, Helmer, and Chino, 1986;Yost, Cooper, & Bremner, 1983). One of the major conclusions of these studies was that the results obtained from the FFI of EEG data are influenced by where in the data the FFI is initiated. Moving the starting point for the FFI analysis by as little as 16 data points (wher...

Previously, we reported enhanced P3 amplitudes to between‐category deviations among high and low probability events. Here, we tested the effects of a within‐category difference. Subjects performed a go/no‐go button press task as they viewed repeated, randomly‐ordered presentations of nine double‐digit numbers. Eight numbers fell within a prescribed range (42–49, standards); prior to testing, subjects selected one standard number for later recall. A ninth, out‐of‐range (91, deviant) number was also included. Subjects were tested under two conditions, in which they responded either to one (low response probability) or to seven (high response probability) standard nonselected numbers, designated as targets. Relatively larger P3s were consistently apparent only when the deviant nontarget was associated with a low probability response to a nontarget. There was a selective effect of nontarget response probability on P3 amplitude to the deviant nontarget. Our results indicate that within‐category deviation detection is facilitated by “controlled”attention to the structure of the stimulus field.