P300 correlates of inspection time

Vol. 20, No. 5, pp. 619427, 1996 1996 Elsevier Science Ltd Printed’k &ea;Britain. Ail rights reserved 0191-8869/96 $15.00+0.00

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P300 CORRELATES

OF INSPECTION

TIME

Mark B. Alcorn* and Grant L. Morris Department

of Psychology, University of Northern Colorado, Greeley, CO 80639, USA (Received 31 March 1995)

Summary-The P300 is an easily elicited psychophysiological phenomenon that may reflect phases of information processing inherent in many complex cognitive endeavors. In this study, cortical event-related potentials were collected from 49 subjects during an inspection time task. P300 amplitude at the temporal and occipital sites correlated with inspection time and with performance on Raven’s Standard Matrices. This study supports some of the previous work on P300 correlates and suggests that future integration of the IT and ERP paradigms will be fruitful. Copyright 0 1996 Elsevier Science Ltd.

INTRODUCTION Inspection time (IT), the minimum exposure duration needed for reliable discrimination of a stimulus, is often assessed in a backward masking task in which the target to be identified is presented briefly (e.g. for less than 100 msec) and then replaced by an overwriting masking stimulus. The mask interrupts or erases iconic storage and precludes target identification from the iconic image after the target has physically offset. This task is well suited to the requirements for collecting eventrelated potentials (ERPs). Just such a brief, discrete stimulus is required to be able to reliably link an evoked cortical response to its eliciting stimulus. The P300 component of the event-related potential is easily elicited when Ss are asked to discriminate a novel stimulus from a previously presented standard. However, the complexity of interpretations surrounding the P300 seem incongruent with the simplicity of the eliciting task. Considerable research suggests that the P300 reflects memory updating by the revision of the neural representation of the standard stimulus (e.g. Donchin, 198 1; Donchin & Coles, 1988; Metcalf, 1992). Furthermore, the amplitude and latency of the P300 are influenced by a number of variables. For example, there is a negative correlation between amplitude and stimulus probability (DuncanJohnson & Donchin, 1982). Additionally, the more similar the stimulus is to the standard (i.e. the more difficult the discrimination) the longer the latency and the smaller the amplitude of the P300. These relationships are likely due to the declining confidence of the Sin his discrimination (Squires, Hillyard & Lindsay, 1973) or, perhaps, amount of meaningful information processed vis-a-vis the discrimination (Ruchkin & Sutton, 1978; Johnson & Donchin, 1978). Johnson (1986) paints and even more complex picture of the variables influencing P300 amplitude. He maintains that the improbability and the meaning of the stimulus have an additive effect whose sum is multiplied by a third variable, the proportion of the stimulus information received. Based on this previous work, one might expect the IT paradigm to yield systematic variation in the P300. While stimulus probability and meaning are held constant across trials, the difficulty of the discrimination varies with stimulus onset asynchrony (SOA). Shorter SOAs should be associated with longer latency and smaller amplitude. Given the cognitive correlates of the P300, one might wonder if it is also related to psychometric IQ. While several studies have now implicated an earlier ERP component, the P200 slope, as a primary correlate of intelligence (Zhang, Caryl & Deary, 1989a,b; Caryl, 1994; Morris & Alcorn, 1995), the relationship between P300 and IQ is less clear. McGarry-Roberts, Stelmack and Campbell (1992) assessed IQ with the Multidimensional Aptitude Battery and obtained P3OOsacross a series of tasks for a sample of young adults. Significant negative correlations between P300 latency and IQ were found for a category-matching task and a digit-recognition task. P300 amplitude was

*To whom all correspondence should be addressed. 619

620

Mark B. Alcorn and Grant L. Morris

negatively correlated with IQ for a semantic similarity task. Caryl (1994) however, reported a correlation of just -0.27 between P300 latency and performance on the Alice Heim 5 test of intelligence in a sample of undergraduates. A correlation of 0.28 was found between P300 amplitude and IQ. While much remains to be learned about the P300 and the variables that influence it, the P300 has been established as a psychophysiological marker of information processing inherent in complicated cognitive activities. Understanding the psychophysiological substrate of intelligence might be facilitated by integration of the ERP and inspection time paradigms (e.g. Zhang et al., 1989a,b; Caryl, 1994; Morris & Alcorn, 1995). Inspection time has been widely found to correlate significantly with psychometric IQ (e.g. Vickers, Nettlebeck & Willson, 1972; Nettlebeck, 1982; Longstreth, Walsh, Alcorn, Szeszulski & Manis, 1986; Nettlebeck, Edwards & Vreugdenhil, 1986; Nettlebeck, 1987; Deary, Caryl, Egan & Wight, 1989; Zhang et al., 1989b; Morris & Alcorn, 1995). Vickers et al. (1972) described IT as placing an elemental constraint on initial perceptual stages of information processing. One explanation of this effect is that an individual’s rate of sampling of the target stimulus is limited, and that this sampling rate dictates how long the S needs to be exposed to the target before sufficient information is accumulated to make an identification. This sampling rate varies across S and interacts with the complexity of the target stimuli and difficulty of the discrimination in determining the recognition threshold for that S (Vickers, et al., 1972; Vickers & Smith, 1986). Zhang et al. (1989b) found that P300 amplitude, but not latency, varied significantly with the difficulty of the discrimination; the easier the task, the greater the amplitude. P300 amplitude elicited by the IT stimulus was also correlated positively with IT. However, in sharp contrast to the findings of McGarry-Roberts et al., no significant P300 correlations with intelligence (as measured by the Alice Heim 5 test) were reported. The present study contributes additional data regarding the relationships among the P300, IT and IQ. Among its contributions is an examination of the waveform as a function of recording site (6 homotopic locations as opposed to the single vertex recording site used by Zhang et al.) in the hope that further inferences regarding the relevant cognitive processes will be possible. METHOD Subjects

The Ss were 22 male and 27 female college students (the same sample reported on by Morris & Alcorn, 1995). All Ss displayed normal or corrected to normal vision as assessed by the Snellen Equivalent Visual Acuity Test. Evokedpotential apparatus

Bilateral evoked potential recordings were obtained from four monopolar locations referenced to linked earlobes. The electrodes were placed on the scalp using an electro-cap (Electra Cap International). Eye movement artifact recording electrodes were placed above and to the lower temporal side of the right eye. The impedance for all recording sites was maintained below Ka. The sites that are reported in this paper are 01 (left occipital), T5 (left temporo-occipital), T3 (left temporal), and F7 (left frontal) of the International l&20 System (Jasper, 1958). The waveforms generated during the backward masking task were amplified by a 10 channel Beckman Accutrace electroencephalograph. The amplifiers’ time constant (high pass filter) was 0.1 set, and the low pass filter was bypassed. Amplified and filtered EEG were transformed by a 12 bit resolution analog-todigital converter (Scientific Solutions LabMaster). Stimulus presentation and data collection were microcomputer controlled. Individual epochs of EEG were digitized at 100 samples per second and stored for later averaging and analysis. Procedure

Subjects were given Raven’s Standard Progressive Matrices (untimed) and, on a separate occasion, performed the backward masking task with simultaneous EEG collection. The backward masking task presented a letter-the target stimulus-for a variable interval before it was replaced by a

P300 and IT

621

masking stimulus that interrupted iconic storage of the target. On each trial our Ss were required to identify which one of four possible letters had appeared on the computer screen. Those letters were all in lower case and were ‘b’, ‘p’, ‘d, or ‘q’. The horizontal and vertical visual angles subtended by these stimuli were 1.67 and 2.38”, respectively, at the test distance of 120 cm. This is the same task employed by Longstreth et al. (1986) and is a more cognitively demanding exercise than the more common 2-line discrimination task. The present procedure, however, is not difficult in terms of the actual visual discriminations to be made (see the recognition accuracy data below). The program controlling stimulus presentation and data collection was written in C language, linked to assembly language routines which control the A/D and timer functions in the Labmaster A/D converter. All critical timing functions were under the control of an independent clock in the A/D converter. The delays between target onset and mask onset (stimulus onset asynchrony) were selected in light of the limitations imposed by the 60 Hz screen refresh rate of our monitor. For a discussion of timing and refresh-rate issues in microcomputer-controlled IT tasks, see Barrett and Kranzler (1994). SOAs were 17, 34, 50, 67, 84, and 100 msec. In addition, 0 msec control trials, consisting of the presentation of the mask without the target, were randomly interspersed among the 17-100 msec trials. The Ss were unaware of the inclusion of the 0 msec trials and were asked to respond with one of the four target stimuli, just as in the regular trials. The mask which replaced the target was a random pattern of 5.4 by 3.7 mm blocks with a light intensity that matched the overall luminance of the target letters. The mask subtended the same height and width visual angles as the target letters. Subjects were instructed to respond with one of the four possible target letters on all trials. To familiarize the Ss with the procedure, as well as to minimize eye-and head-movement artifacts during the experimental trials, participants received a minimum of 13 practice trials with SOAs of 67 or more msec. After a S demonstrated reliable letter recognition, eye and head movement artifact detection levels were individually determined. Trials during which eye or head movement artifact exceeded the preset rejection criterion were aborted and the feedback ‘eyes moved’ and/or ‘head moved’ was displayed on the monitor. A trial started with a small fixation point projected on the center of the screen for a duration of 3 sec. The target letter replaced the fixation cue and was presented at one of the SOAs, followed by the mask which remained on the screen until the end of the I-set epoch. At this point the Ss were prompted by the word ‘Letter ?‘, to identify a letter. The Ss responded orally. If the S responded correctly on a given trial, the phrase ‘That’s Correct’ was displayed for a period of 1 sec. After the presentation of feedback, the screen went blank for a period of 1.5 set and then the next trial commenced with the display of the fixation point. Following an incorrect response the screen went blank for 1.5 set prior to the beginning of the next trial. During the I-set trial interval following target onset, EEG was digitized from the four bilateral homotopic electrodes sites at the rate of 100 samples per second. The Ss received 260 experimental trials: the four target letters were each presented 60 times in random order. SOA values were not randomized. Instead, trials were presented in series of increasing or decreasing SOAs (17-100 msec) with each SOA tested twice before moving on to the next higher or lower duration. Testing was interrupted at regular intervals to permit the S a brief rest.

RESULTS

AND

DISCUSSION

Recognition accuracy

The average percent correct recognition scores for the 6 SOAs are presented in Table 1. These recognition accuracies are collapsed across the four different target letters. These recognition accuracies are quite close to those reported by Longstreth et al. (1986) with a similar population and task. Event-relatedpotentials

Figure 1 consists of the displays of the ERPs recorded from the frontal and occipital regions of a selected S. The displayed epochs are 1000 msec in duration, and positivity is up. The four columns

622

Mark B. Alcorn and Grant L. Morris Table

1. Average

percent

correct

recognition (n = 49)

by stimulus

Stimulus Onset Asynchrony

I44 SD

onset

asynchrony

(msec)

17

34

50

67

84

100

44.8 17.3

72.0 19.8

83.0 16.5

89.3 14.8

92.8 10.0

94.5 7.8

to the right are the ERPs elicited by the target letter which heads the column. The left column is the average across the four target letters, and was used for determining ERP component amplitudes and latencies. The number following each waveform is the number of individual epochs which made up the displayed average waveform. The rows represent the ERPs recorded from homotopic electrode sites at each of the 6 SOAs, and the control condition (0 msec). The displays in Fig. 1 are exemplars of those generated by this task. This figure also illustrates the location and identify of the P300 component used in the analysis. The peak of the P300 was selected visually as the most positive-going (upward, in this display) component between 250 and 1000 msec. Latency and amplitude data were then recorded directly on magnetic media. If the apparent latency of a waveform differed from others, its latency could be recorded separately; however, this was rare, either within homotopic sites or across SOAs at a site. Consequently, amplitudes and latency for a component were determined at the same timepoint for a particular electrode site in a S. Zhang er al. (1989b) also reported no significant variation in P300 latency across the three SOA levels they employed. Zhang et al.‘s and our results appear to contradict other studies which have found increased latency with more difficult discriminations, such as shorter SOAs would represent. Zhang et al. suggest an explanation: in their experiments (and ours) stimulus information was removed (masked) after a brief exposure, while in other studies stimulus information remained available, allowing further sampling, and therefore a later P300 peak, where the discrimination was difficult (p. 1083). For Fig. 1, frontal and occipital displays were selected to illustrate the nature of the differences in the waveforms observed in these regions. T,-T, waveforms closely resembled those seen at O,Oz, while T,-T4 waveforms were very similar to F,-F,. As expected, the occipital region clearly shows a short-latency visual evoked potential conventionally labelled the PlOO with a latency of approximately 100 msec. This feature is absent in the frontal region. As SOA increases, the P300 appears to grow in amplitude. However, the latency of this, and other components in the waveforms, does not vary systematically across SOAs. Frontal waveforms are comparable. The P300 data from the 0 msec trials were not included in the statistical analyses, but are displayed in Fig. 1. These 0 msec waveforms appear consistent with the trend in P300 amplitude change seen across the 17-100 msec SOAs. While hemispheric differences are potentially interesting, preliminary inspection of homotopic electrodes sites did not reveal any systematic differences. Therefore, we decided to simplify our analysis by using ERP data from only the left hemisphere. Table 2 lists the means and standard deviations of the P300 for the various left hemisphere recording sites and SOAs. P300 amplitude variation across SOAs Figure 2 shows the average P300 amplitudes for the four left-hemisphere sites (F3, T3, T5 and 01) and the 6 SOAs at which ERPs were recorded from each site. Zhang et al. (1989b) found a significant increase in P300 amplitude with increasing SOA with recording from the vertex. In the first experiment they report, the three SOAs used were: (1) set at the IT for a S (IT); (2) 0.25 of that SOA (IT-); and (3) 1.75 of that SOA (IT+). Average IT reported for their Ss in that experiment was 34.1 msec. The average range of SOAs they used, then, was approximately 9 - 60 msec. Across the range of SOAs we used (17-100 msec) we find the same approximately linear increase in P300 amplitude as a function of SOA for the 01 and T.5 sites [F(5,240) = 28.8, P < 0.001, F(5,240) = 24.6, P < 0.001, respectively]. The linearity of these functions is supported by a best fit with a first order (linear) polynomial test at 01 and T5 [F(l,48) = 61.8, P < 0.001, F(l,48) = 60.1, P < 0.001, respectively]. A different relationship emerges at the anterior electrode sites: T3 and F3. Significant

P300 and IT

623

s 8 i

0 A

t e

Target stimuli

(nsec)

0

F5 ‘4

17

r3 r4

24

F3 F4

SO

F3 F4

67

3 F4 F3

I4

F4 5

IIN)

F4

(tLWC)

0

01 9

17

OJ 01

24

01 02

50

01 02

(7

01 02

14

01 02

Jrn

4 O2

Fig. 1. Example display of ERPs recorded from the frontal and occipital regions of a selected subject.

differences also exist among the SOA levels at T3 and F3 [F(5,240) = 15.4, P < 0.001, I;(5,240) = 29.3, P < 0.001, respectively]. The trend at these sites, however, is not linear, as supported by nonsignificant first order polynomial tests, but fits best with second order (quadratic) polynomial tests at T3 and F3 [F( 1,48) = 24.5, P < 0.001, F(1,48) = 88.0, P < 0.001, respectively]. While posterior P300 amplitudes appear to continue to increase with the longer SOAs, at the

624

Mark B. Alcorn and Grant L. Morris Table 2. Average latency and amplitude stimulus onset asynchrony and recording SOA F3 recording site lat. (msec) amp. W) amp. PV) amp.

Ail 17 34 50

T3 recording site lat. (msec) amp. W) amp. W) amp. W) amp. (!w amp. (YV) amp. (YV T5 recording site lat. (msec) amp. (PV) amp. (PV) amp. W) amp. W) amp. W) amp. W)

M SD M SD M SD

M SD

67

W)

amp. (PV amp. W)

P300

(leftfrontal)

W) amp.

of P3OOs by site (n = 49)

84 100

(leftanterior All 17 34 50 67 84 100

(leftposrerior All 17 34 50 67 84 100

01 recording site (left occipital) lat. All (msec) amp. 17 (PV) amp. 34 W) amp. 50 (PV) amp. 67 W) amp. 84 (P) amp. 100 W)

M

SD M SD M SD temporal) M SD M SD M SD M SD M SD M SD M SD temporal) M SD M SD M SD M SD M SD M SD M SD

M SD M SD M SD M SD M SD M SD M SD

463.2 55 x 2.6 2.6 3.4 2.9 42 3.1 4.5 2.5 4.6 2.9 1.5 2.3

462.2 35.4 4.1 3.6 4.6 3.4 5.8 40 6.6 4.4 6.5 4.2 3.x 3.8

448.1 48.0 1.6 2.1 2.6 2.8 3.6 2.7 4.3 2.1 4.4 2.6 4.5 3.0

443.0 54.3 3.9 3.5 4.5 3.2 5.4 3.7 6.6 4.3 7.5 4.3 7.6 4.3

sites P300 amplitude peaks at approximately the point of average IT (near 67 msec SOA; see Table 1) and then declines markedly. Subjective reports from participants suggest that, beyond 67 msec SOA, many found the task unchallenging (many performed at 100% RA levels). This complex interaction between anterior-posterior site, task difficulty and P300 amplitude seems to be a novel finding with the backward masking procedure, in that it is not reported elsewhere in the P300 literature. This differential diminution of P300 amplitude in the frontal area but not posteriorly anterior

P300 and IT

8

625

i

1 I 50 67 SOA (msec) -=-F3 Fig. 2. Average

P300 amplitudes

+T3 as a function

+T5

-+-01

of left-hemisphere

recording

site and SOA

with increasing SOA does support the speculation that the P300 has multiple origins rather than being a pervasive/unitary phenomenon across the cerebrum. Raven’s standardprogressive

matrices

The average RSPM score of the 49 participants was 49.2 with a standard deviation of 4.8. This places our sample at the 75th percentile, with markedly attenuated variation. Relationship of RSPM scores and RA with P300 amplitude

Table 3 presents the correlations of RSPM scores with P300 amplitude measures at each SOA and recognition accuracies for the 17 and 34 msec SOAs, within the four electrode sites in the left hemisphere. Significant P300 amplitude correlations with intelligence appear only at the anterior temporal (T3) and occipital (01) sites. These correlations are comparable to those reported by McGarry-Roberts et al. (1992) for P300 amplitude and latency but are of smaller magnitude than those seen for the slope of the P200 component (P2OOs)reported by Morris and Alcorn (1995). CONCLUSION

This research illustrates significant relationships among recognition accuracy, P300 amplitude and intelligence. The general increase in P300 amplitude with greater duration of target exposure is as expected and, in comparable target recognition tasks reported in the literature, is sometimes interpreted as reflecting the ‘confidence’ which the S has in identification of that target. However, the apparent difference in P300 amplitude change between the anterior and posterior recording sites when SOA levels exceed average IT is remarkable, and suggest that the P300 may reflect functional anterior/posterior cerebral differences in the processes of the backward masking task. Clearly, the posterior P300 amplitude seems to be driven by a physical property of the stimulus (duration) while anterior P300 amplitude levels off at the SOA range corresponding to average inspection time (90% recognition accuracy) and then declines at the longest SOA, trials which the Ss report as being ‘easy’.

Mark B. Alcorn and Grant L. Morris

626

Table 3. Correlations

of RSPM scores and recognition tudes (n = 49) Recognition

accuracies with P300 ampli-

accuracy at SOA = 17

SOA = 34

Site and SOA

RSPM

P300 amplitude at F7 SOA 0 17 34 50 67 84 100

-0.17 -0.08 -0.02 -0.12 -0.04 -0.13 0.19

-0.10 -0.09 0.02 -0.20 -0.05 -0.11 0.16

- 0.00 - 0.08 0.00 -0.15 0.02 -0.00 0.17

P3W amplitude at T3 SOA 0 17 34 50 67 84 100

-0.21 0.23 0.25 0.39* 0.35* 0.32 0.29

-0.16 0.14 0.28 0.28 0.45; 0.34 0.24

-0.15 0.04 0.11 0.20 0.35’ 0.27 0.12

P300 amplitude at T5 SOA 0 17 34 50 67 84 100

0.11 0.16 -0.11 -0.06 -0.10 -0.02 -0.15

- 0.02 0.18 -0.14 -0.13 -0.14 -0.01 -0.05

-0.06 0.14 -0.12 -0.08 -0.12 0.06 0.01

P300 amplitude at 01 SOA 0

17 34 50 67 84 100

0.08 0.29 0.33’ 0.331 0.45* 0.35; 0.30

0.05 0.26 0.17 0.36’ 0.29 0.35’ 0.37’

0.05 0.06 0.05 0.24 0.27 0.32 0.34’

*P < 0.05

Our method differs from many others in that we used only lateral rather than midline, or even vertex only, recording. Whether the difference in the P300 amplitude trend between anterior and posterior recording sites is specific to this task, or is an example of typical P300 effects which are detectable with a lateral montage, should be clarified. The P300, which may reflect stimulus evaluation in working memory (Kutas, McCarthy & Donchin, 1977) appears to be a weaker correlate of IQ than P200 slope (Zhang et af., 1989b; Caryl, 1994; Morris & Alcorn, 1995), which may reflect the completion of sensory decision making and the transfer of information from the sensory register into working memory (Chapman, McCrary & Chapman, 1978). None the less, the present study further establishes the value of integrating the IT and ERP paradigms. This integration yields a better understanding of the psychophysiological bases of performance on cognitive tasks via an information processing model. Of particular interest is that Morris and Alcorn report strong correlations between IQ and P200 slope recorded at the frontal (F7) and temporo-occipital (TS) locations whereas the present IQ correlation is with the P300 recorded at the temporo-parietal (T3) and posterio-occipital (01) sites. The role of recognition accuracy is unclear as Morris and Alcorn report that it also correlates significantly with IQ and P200 slope at F7 and T5 while the present study finds it correlating with P300 at T3 and 01. Additional research that manipulates the cognitive demand of the IT task, measures ERPs at multiple locations, and relates to psychometric IQ assessments that vary in g-loading is desirable. REFERENCES

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