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P3B and Positive Slow Wave following Real and Dummy Feedback on Arithmetic Rule-Learning and Perceptuomotor Tasks
Perceptual and Motor Skills
Abstract
Event-related Potentials (ERPs) were recorded to feedback during a cognitively demanding, arithmetic rule-learning task and a relatively simple, skill-oriented, perceptuomotor task. For both tasks, a compound feedback display was employed. It consisted of numeric feedback information presented simultaneously with a red or green light (50% each) which indicated whether the numeric information was real (valid) or dummy (invalid). The task and feedback-validity manipulations showed a functional dissociation between the P3b (350-450 msec.) and a Positive Slow Wave (600-900-msec.). P3b was larger for real than for dummy feedback; Positive Slow Wave was larger for rule-learning than for perceptuomotor tasks.
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A model of P300 amplitude is proposed that reduces the many hypothetical constructs invoked to explain variations in P300 amplitude to three dimensions: 1) Subjective Probahility, 2) Stimulus Meaning, and 3) Information Transmission. Evidence is presented to support the assertion that variables on the subjective prwbability and stimulus meaning dimensions have independent and additive contributions to overall P300 amplitude. The amplitude contributions of both of these dimensions, however, are modulated by a multiplicative relation with the proportion of transmitted stimulus information. Within each dimension, the fundamental experimental variables and their interrelations are specified. An example is presented to show how, by using an additive factors method, the respective amplitude effects of the probability and stimulus meaning dimensions can be separated. Supporting data are presented to show that the proposed model provides a reasonable and testable framework in which to conceptualize P300 results. DESCRIPTORS: Event-related potentials, P300. The prospect of having an electrophysio logical index of cognitive operations has led many re- searchers to explore the nature of the P300 com- ponent of the event-related brain potential (ERP). Since its discovery by Sutton and his colleagues (Sutton, Braren, Zubin, & John, 1965; Sutton, Tuet- ing, Zubin, & John, 1967), studies have demon- strated that P300 amplitude and latency can be used as indices of the nature and timing of a subject's cognitive response to a stimulus.' As a result of
This study is concerned with slowly varying, long-duration brain event-related potential (ERP) components, referred to as Slow Wave activity. Slow Wave activity can be observed in the epoch following P3b, suggesting that it reflects further processing invoked by increased task demands, beyond the processing that underlies P3b. The present experiment was designed to distinguish Slow Wave activity related to specific types of task demands which arise during difficult perceptual (pattern recognition) and conceptual (arithmetic) mental operations.
Three late ERP components that respond differentially in amplitude to manipulation of perceptual and conceptual difficulty were identified: 1) A P3b, with a topography focused about Pz, evidently related to the subjective categorization of easy and difficult conceptual operations, that increased when the subjective low-probability operation was performed; 2) A longer latency, centroparietal positive Slow Wave that increased directly with perceptual difficulty but was not affected by conceptual difficulty; 3) A very long latency negative Slow Wave, broadly distributed over centroposterior scalp, that increased directly with conceptual difficulty while its onset was delayed when perceptual difficulty increased.
The bulk of the relevant evidence indicates that stimuli which elicit the P300 component of the human event-related potential (ERP) tend to be unexpected and task relevant. Yet, contradictory evidence has been presented which implied that P300 amplitude is modulated by the intensity difference between two equally relevant, equally probable feedback stimuli (Adams and Benson, 1973). The two experiments reported here were designed to clarify this contradiction. Subjects were instructed to press a button one second after a cue light. A tone at one of two intensities was presented 200 msec later indicating whether the time estimate was ‘correct’ or ‘incorrect.’ The magnitude of P300 varied as a function of the difference in intensity between S+ and S−; the smaller the difference, the smaller was P300, regardless of stimulus meaning (S+ or S−). We attribute this effect to the degree to which the subject chooses to utilize the tones in the performance of the time estimation task. In support of this hypothesis, we found that performance of the subjects as time estimators degraded as the difference between S+ and S− decreased. Moreover, a study of choice reaction times taken for the different pairings of S+ and S− showed that the stimulus pairs were not equally discriminable. It appears that as the S+/S− pairs become increasingly difficult to discriminate, their feedback value decreases and this decrease is positively correlated with a decrease in P300 amplitude.
Event-related potentials (ERPs) were recorded in a time estimation task under different feedback conditions, in which the informative value of the feedback signals (true versus false) was manipulated. A control condition was added in which no signal was presented. Fifteen subjects pressed a button 3 seconds after presentation of a warning signal. Two seconds after the response, a visual feedback signal was presented, indicating whether the preceding interval was estimated correctly. Two different slow waves were observed: the response was preceded by a readiness potential and the feedback stimulus was preceded by a negative slow wave called the stimulus-preceding negativity. The readiness potential was not influenced by the different feedback conditions. The stimulus-preceding negativity was larger in the true feedback condition compared to the false feedback and no feedback conditions. The P300 to the feedback signal was also larger following a true as compared to a false feedback signal. The conclusion is that the stimulus-preceding negativity is an anticipatory component contingent upon the presentation of an informative feedback signal.
This experiment investigated how the P3a, P3b, and Slow Wave components of the event-related brain potential (ERP) respond to manipulations of the nature, timing, and extent of information delivery. There were two experiments in which the total amount of task information was distributed between pairs of successive stimuli (S1 and S2) within each trail. The task was to predict the relation between S1 and S2. In Experiment 1, the S1 could resolve no, partial, or all uncertainty with respect to the prediction outcome (correct or incorrect). Each S1 delivered three types of information: 1) outcome information--which resolved the subjects' uncertainty about the correctness of their prediction; 2) procedural information--which resolved uncertainty about how much outcome information would be delivered by S1; and 3) memory information--the identity of S1, which had to be stored for subsequent comparison with S2. In Experiment 2, the activity of these components was contrasted in two conditions in which the S1 delivered either memory information alone or both memory and procedural information. P3a and Slow Wave were sensitive only to outcome information. P3b was sensitive to all three types of information, and its scalp topography varied as a function of the type of information. The topographic variations indicate that P3b is not a unitary phenomenon but rather is a composite of activity arising from multiple intracranial sources of bioelectric activity.
Few theories of the P3 component have emphasized the distinction between its parietal and frontocentral parts. This study used a new paradigm for testing the predictions that the parietal P3 is evoked by awaited stimuli (suspense) and the frontal P3 by unexpected stimuli (surprise). Subjects had to make simple responses whenever a yellow ring appeared. This signal appeared on the screen within a clock, most frequently when the pointer was at 12 o'clock (every 6s) but sometimes also at other times. The suspense process should therefore have its minimum shortly after 12 o'clock and then steadily increase until 12 o'clock, and the parietal P3 should accordingly be smallest with stimuli shortly after 12 o'clock, then gradually increase and be largest with 12 o'clock stimuli. Further, the stimuli presented at times other than 12 o'clock should evoke large frontal P3s because they were unexpected. The results confirmed parts of these predictions. A frontocentral and a parietocentral component could indeed be discerned. The frontal P3 was largest with non-12 o'clock stimuli, whereas the parietal P3 was large with all stimuli. The parietal result was not predicted, but these results taken together pose more problems for the usual view, which assumes that the parietal P3 is evoked by unexpected stimuli, than for our assumption that the parietal P3 reflects suspense, and the frontocentral P3 reflects surprise. Generalizing to other paradigms, we assume that different topographies of P3 in different paradigms or in differnt groups of subjects might be due to different mixtures of these two components.
Digital filtering offers more to psychophysiologists than is commonly appreciated. An introduction is offered here to foster the explicit design and use of digital filters. Because of considerable confusion in the literature about terminology important to both analog and digital filtering, basic concepts are reviewed and clarified. Because some time series concepts are fundamental to digital filtering, these are also presented. Examples of filters commonly used in psychophysiology are given, and procedures are presented for the design and use of one type of digital filter. Properties of some types of digital filters are described, and the relative advantages of simple analog and digital filters are discussed.
Fifteen subjects were presented with series of tones. Any one tone was either loud or soft, and in any one series the probability of one tone intensity was either 0.9 or 0.1. Subjects were instructed to count the frequent tones or to count the rare tones. The stimuli were also presented while the subjects were solving a word-puzzle. Event-related potentials (ERPs) were recorded from 9 scalp locations (F3, C3, P3, Fz, Cz, Pz, F4, C4, P4) referred to linked mastoids. ERP components were measured with a Principal Components analysis and the relations between these measures and the independent variables were evaluated with the ANOVA procedure. This paradigm allowed an evaluation of the effect of stimulus probability, stimulus relevance, and task relevance on the waveform of the ERPs. We conclude that the P350 component is enhanced whenever the eliciting stimulus is both rare and in some sense relevant to the subject's task and the degree of enhancement is greatest when the rare-relevant tone is loud. A "slow wave" component which follows P350 is related to the same variables but has a scalp distribution quite different from that of P350. The slow waves shows a progressive shift in polarity from negative to positive from the frontal to the parietal sites, while the P350 is of nearly equal amplitude (and positive) at the central and parietal sites and has a smaller (positive) amplitude at Fz. A third prominent component, negative in polarity, peaking at about 210 msec, is most pronounced following rare stimuli, whether or not they were task relevant. The amplitude of N210 tended to be largest at the frontal electrode. This study then demonstrates that when suitable measurement techniques are used, multiple endogenous ERP components can be observed, each related to distinct aspects of cognitive behavior.
Two factors are known to determine the waveform of event-related potentials (ERP) elicited by task-relevant stimuli: the a priori probability of the stimuli and the sequence of immediately preceding stimuli. The relative contribution of these factors to the ERP waveform was assessed at nine levels of a priori probability (from .10 to .90). Random sequences of high (1500 Hz) and low (1000 Hz) tones were presented to 10 male subjects at each level of probability, both when the events were task-relevant and when the subjects were performing an alternate task to which the tones were irrelevant. The EEG was recorded from five midline electrode sites referred to linked mastoids.
The amplitude of the P300 and Slow Wave components was inversely proportional to the a priori probability of task-relevant events. At every level of a priori probability, the magnitude of the P300 complex (N200-P300-Slow Wave) was diminished when the eliciting tone repeated the preceding tone, and was enhanced when it was preceded by the other tone. Thus, a priori probability and sequential structure appear to be independent determinants of the P300 complex.
Event-related brain potentials (ERPs) were recorded from 10 young adults during a version of the continuous recognition memory paradigm. Words were presented after lags of either 2, 8 or 32 intervening items (equiprobable) following their first presentation, and subjects were required on each trial to make a choice: new (never presented previously) or old (previously presented) response. To assess the effect of probability of new to old items, words were presented in separate blocks with ratios of new to old of 2:1 and 1:1.
The relationship between target stimulus probability and interstimulus interval on the P300 (P3) component of the event-related potential was assessed in three experiments. In each study an auditory discrimination paradigm was employed wherein subjects indicated with a finger tap response the occurrence of a randomly presented 2000 Hz target tone embedded in a series of 1,000 Hz tones. Target stimuli were presented with a probability of either .20 or .80 in different conditions which were combined factorially with different interstimulus intervals. Experiment 1 presented stimuli at 2.0, 2.5, or 3.0 second intervals; Experiment 2 presented stimuli at 2.0, 3.0, or 4.0 second intervals; Experiment 3 presented stimuli at 4.0, 6.0, or 10.0 second intervals. P3 amplitude was larger for the .20 relative to the .80 target probability conditions for the shorter interstimulus intervals but not for the longer intervals. P3 latency was consistently longer for the .20 relative to the .80 target probability conditions, with generally little effect observed for interstimulus interval changes. The results suggest that interstimulus interval affects component amplitude by determining the amount of processing resources available when the P3 is produced.
Analysis of variance (ANOVA) interactions involving electrode location are often used to assess the statistical significance of differences between event-related potential (ERP) scalp distributions for different experimental conditions, subject groups, or ERP components. However, there is a fundamental incompatibility between the additive model upon which ANOVAs are based and the multiplicative effect on ERP voltages produced by differences in source strength. Using potential distributions generated by dipole sources in spherical volume conductor models, we demonstrate that highly significant interactions involving electrode location can be obtained between scalp distributions with identical shapes generated by the same source. Therefore, such interactions cannot be used as unambiguous indications of shape differences between distributions and hence of differences in source configuration. This ambiguity can be circumvented by scaling the data to eliminate overall amplitude differences between experimental conditions before an ANOVA is performed. Such analyses retain sensitivity to genuine differences in distributional shape, but do not confuse amplitude and shape differences.
The topographic distribution of the amplitudes of the contingent negative variation (CNV) recorded along the midline at the anterior, central, and posterior regions of the human scalp varied as a function of type of information processing demanded. A parietal-dominant CNV was found when active problem-solving behavior was required. A central-dominant CNV was evident in a disjunctive reaction time task. The results are interpreted as evidence supporting a model of cortical function which predicts shifts in cortical involvement as a function of type of task demands. A late positive component (LPC) of the average evoked potential was also found to vary as a function of stage of learning, recording sites, and an attitudinal dimension measured by Rotter's internal-external locus of control scale.
CNV, P300 and slow wave amplitude correlates of auditory detection accuracy were studied for both hits and correct rejections. Baseline-to-peak measures gave no indication of the downturn of P300 at very high detection accuracies reported by Hillyard et al. (1971). Principal Components-Varimax Analyses (PCVA) of the event-related potentials (ERPs) were performed. The PCVA basis wave forms for P300 and slow wave showed that baseline-to-peak measures of P300 represent a composite of the two. The weighting coefficients for P300 and slow wave showed an opposite pattern in relationship to accuracy; P300 weighting coefficients increased monotonically with increased accuracy, whereas slow wave weighting coefficients decreased monotonically with increased accuracy. For both P300 and slow wave, findings were similar for both hits and correct rejections. These and earlier findings suggest that overlap between P300 and slow wave should be examined in future P300 experiments. No differences were found in relation to experimental conditions for the CNV in the baseline-to-peak measures or in the PCVA measures. The PCVA showed that there was significant CNV activity in the post-stimulus epoch and therefore the CNV represents another source of overlap with P300 and slow wave when peak-to-baseline measures are used. P300 and slow wave PCVA components have little activity in the pre-stimulus epoch indicating that they are determined by post-stimulus events. The increase of slow wave amplitude with decreasing accuracy is interpreted as reflecting the need for further processing when intensity is so low as to make a decision difficult. This 'further processing' interpretation is consistent with other studies in which slow wave has been shown to vary with task demands.
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Event-related potentials were recorded in response to visual stimuli in two different reaction tasks in which subjects were instructed to react immediately to the stimuli, or to delay their response for a 2 sec period, respectively. There were four types of stimuli: frequent-degraded, frequent-undegraded, infrequent-degraded and infrequent undegraded letters. In all conditions the stimuli evoked complex waveforms which comprised a frontal-negative wave (N400) and a late positive wave that reached a maximum amplitude on the parietal scalp site (P500). In addition, a slow positive wave with a central-parietal scalp distribution was found in the waveforms that were associated with the delayed reaction task. A principal components analysis of the waveforms yielded two major components: an early composite component that peaked around 400 msec, and a late component that became maximally active towards the end of the recording epoch. The scores of the earlier component were more negative (or less positive) and the scores of the late component were more positive when infrequent or degraded stimuli were presented, in comparison with frequent or undegraded stimuli.
The relationship between the amplitude of P300, the mean amplitude of the Slow Wave, and uncertainty reduction after (dis)confirmation of hypotheses was studied in a Concept‐Identification task. The subjects had to categorize stimuli according to a conceptual rule (joint denial or exclusion) and to rate the confidence that their classification was correct. Three types of feedback were distinguished: confirming (subject's categorization was correct), disconfirming (subject's categorization was incorrect), and non‐informative feedback. The EEG was averaged separately according to the three types of feedback and the two confidence ratings (low, high).
The data showed the predicted interaction between type of feedback and confidence level. A larger P300 amplitude turned up after confirming feedback when the subject was less confident, than when he was more confident. The reverse was found after disconfirming feedback. The P300 amplitude after non‐informative feedback was not influenced by confidence. The mean amplitude of the Slow Wave showed approximately the same interaction pattern.
The results were interpreted in terms of changes in the probability of hypotheses which subjects use to categorize stimuli in a Concept‐Identification task.