Methods

2.1.2.1 Participants

All of the participants were students at the University of Nottingham.

There were 50 participants in each of the four stimulus conditions (faces, fractals, pictures, and trigrams), and the mean age of participants was 21-years-old in each group. In order to exclude data from participants who ‘gave up’ on the tasks, during the relatively long 30 min period, criteria were set for inclusion of the data in analyses. These were adapted from those used by Rubin et al. (1999).

Participants were required to make fewer than 25 ‘no response’ trials (those where no response was measured during the allotted time), to prevent the inclusion of data from participants who had stopped responding. In addition they had to surpass the criterion of achieving recognition measures of at least 0.5 for lag 1 and lag 0 combined, and have a false alarm rate lower than 0.8, to eliminate participants who always responded with ‘old’. The recognition measure referred to here is the same measure used by Rubin and colleagues, [(hits-false alarms)/(1-false alarms)]. Mean numbers of ‘no responses’ for the remaining participants were 4.06 (faces), 4.14 (fractals), 3.04 (pictures), and 0.82 (trigrams).

The mean probabilities of recognition for lags 0 and 1 combined for the remaining participants were 0.83 (SD=0.14) (faces), 0.81 (0.12) (fractals), 0.93 (0.07) (pictures), and 0.82 (0.13) (trigrams). Mean false alarm rates were 0.27 (SD=0.10) (faces), 0.23 (0.13) (fractals), 0.10 (0.06) (pictures), and 0.38 (0.09) (trigrams). To obtain 50 participants with data meeting the inclusion requirements in each group (200 in total), 54 were tested for the faces, 53 for fractals, 51 for bitmaps, and 54 for trigrams. Those excluded in each group were all removed for having failed to achieve mean recognition scores of 0.5 across lags 0 and 1.

2.1.2.2 Stimuli

Four different types of stimuli were generated: faces, fractals, pictures, and trigrams.

2.1.2.2.1 Faces

The faces were a set of 200 computer-generated ‘cartoon’ faces, generated by programs written by Andrew Derrington (see Figure 2.1). A seed for the random number generator was selected, based on the computer’s clock. The faces were generated in sequence by defining, and superimposing, 16 ‘egg-shaped’ ellipses, configured to represent the outline of a face, eyes, nose, hair, mouth, cheeks and eyebrows. Each ellipse was defined by random determination of properties such as length, position, height, curve, angle and RGB values (to define the ellipse’s colour), within pre-defined limits to ensure that the resulting structure resembled a face. The resultant ‘egg-shaped’ ellipses differed from the standard ellipse by having a 2^nd harmonic component on the long axis, meaning that the ellipse could be fatter at one end than the other. In addition ellipses could be made asymmetrical along the long axis, by giving the two halves of the short diameter different lengths, which could be negative giving rise to a crescent-shaped ellipse. Details of each face’s parameters and the seed for the random number generator were stored in a data file.

Figure 2.1: Example face stimuli.

2.1.2.2.2 Fractals

Fractals were generated by a program adapted from an algorithm detailed by Miyashita et al. (1991) on a Viglen PC running Matlab v6.1, equipped with the image processing toolbox (see Figure 2.2). Briefly, a seed for a random number generator was entered and set, in order that the fractals generated could be regenerated at any time, provided the seed and other variables entered were the same. A series of minimum and maximum levels for various properties of the fractals were entered enabling adjustment of the program to produce fractals of sufficiently different appearance. For each fractal the recursion limits and number of superpositions were randomly set between the minimum and maximum values specified. For each superposition random red, green and blue values were generated to define its colour, number of edges was randomly set between the minimum and maximum values, and then a regular or irregular deflection subroutine was called, according to a ratio of regular to irregular set at the start of the program. Both subroutines calculated the co-ordinates of a regular polygon and then carried out deflections on its sides in accordance with the transformations detailed in the appendix of the Miyashita paper. The only difference between the two subroutines was that the regular subroutine always carried out uniform deflections for each edge of the polygon, whereas the irregular routine did not have this constraint. Finally, superpositions were normalised so that each was centred on the same point. Each fractal was composed of a number of such superpositions, which became progressively smaller, in order that early superpositions were not obscured by later ones.

Fractals were plotted in a Matlab figure window, then saved as bitmap images.

Figure 2.2: Example fractal stimuli.

2.1.2.2.3 Pictures

The pictures consisted of 200 unique clipart images of readily nameable objects. The 200 images were made up from 20 categories (see Figure 2.3):

animals, apples, briefcases, bananas, glasses of beer, birds, burgers, butterflies, cats, clowns, coffee pots, dogs, fish, grapes, keys, oranges, shoes, strawberries, suns, and umbrellas. Ten images of each class of object were included (see Figure 2.4). The first 25 participants were tested with full colour bitmaps, but the experimenters noted that almost perfect recognition was obtained for this condition. In an attempt to increase task difficulty and minimise potential ceiling effects, the latter 25 participants were tested with greyscale bitmaps; exactly the same images but with colour information removed.

Figure 2.3: Examples of each of the 20 categories of picture stimuli.

Figure 2.4: Examples of stimuli within a category. The figure shows the 10 ‘apple’ stimuli employed in the experiment.

2.1.2.2.4 Trigrams

The trigrams employed were a randomly generated list of 200 ‘legal’

trigrams according to the rules of Rubin et al. (1999). That is that they were digit-letter-digit, with the digit zero excluded, and only letters K, V, W, Y and Z allowed.

The trigrams were presented in white letters on a black background, such that the width of the trigram was approximately 2°.

2.1.2.3 Presentation

All stimuli were presented using an Apple Macintosh G3 computer (300 Mhz, 384 Mb RAM) with a ATI Radeon 7000 (32 Mb) graphics card, on a 21”

Mitsubishi colour display monitor (size: 1024 x 768 pixels, resolution: 72 x 72 dpi,

refresh rate: 75 Hz). Stimuli were presented in the centre of the screen using Matlab v5.2.1 (Mathworks UK), running the psychophysics toolbox (Brainard,

1997). All bitmap images (bitmaps, faces and fractals) were converted to a standard size of 59 x 59 pixels, covering an area of 2 cm x 2 cm on the screen when displayed at the resolution described above. Participants were seated at a distance of 57.5 cm from the screen so stimuli subtended an area of approximately 2° x 2° of visual angle.

2.1.2.4 Session design

A pseudorandomly determined frame of 120 trials was generated for each participant, providing 9 learning and 9 test trials at each of 6 lags (see Figure 2.5). These lags were chosen to be at regular intervals on a logarithmic scale being 0, 1, 2, 4, 6 and 9. Twelve filler trials made up the spaces in the frame. The filler trials were unscored study-test pairs, of variable lag. These were arranged so that the first unfilled space in the frame was a ‘study’ filler trial, the second was its ‘test’, the third was the second ‘study’ filler, and so on. The lag denotes the number of trials intervening between the learning and test presentations. Filler trials consisted of unscored learning and test presentation pairs. This frame was repeated three times, with novel stimuli each time, yielding 27 scored recognition tests for each of the lags. In addition, the experiment began with a buffer of 40 unscored filler trial pairs to prevent the occurrence of primacy effects. The effects encountered here, therefore, reflect memory performance where interference is high. This yielded a total of 400 trials. Once the order of trials for the entirety of a

session had been generated, the 200 stimuli were randomly assigned to the 200 pairs of trials, so that each participant experienced the stimuli in a different order.

2.1.2.5 Procedure

For each trial stimuli appeared on the screen for 2 sec (see Figure 2.6Error! Reference source not found.). During this period participants were instructed to respond either ‘old’ or ‘new’ with the left or right mouse button respectively, ‘old’ to previously seen stimuli and ‘new’ to novel items. In order that participants did not forget which button corresponded to which response during the experiment, a clear notice of which was which was placed next to the mouse.

After 2 sec the stimulus was replaced with a blank screen for 1 sec, and then feedback for 0.5 sec. Feedback consisted of either the word ‘Right’ in green letters if the response was correct, or ‘Wrong’ in red letters if it was incorrect, or no response was registered. Finally, a further 1 sec blank screen separated the feedback from the next trial, bringing each trial to a total of 4.5 sec. For 400 trials, the experiment therefore lasted 30 min.

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Figure 2.5: Schematic of an example region of the pseudorandom order frame. Assuming time proceeds from left to right, with each square representing a distinct trial. Yellow squares represent study trials connected by arrows to their corresponding (red) test trial trials. The number with each arrow is the value of the lag separating the pair. The brown square represents a filler trial.

2.1.2.6 Scoring

As mentioned above, participants’ responses were only collected during the 2 sec presentation period of each stimulus. Once a response had been made it was final, and no opportunity for the correction of responses was allowed. Hit rates and false alarm rates were calculated from test and study trials respectively.

From these scores, d’ was calculated. In addition, reaction time was measured as the latency from the start of the trial until the detection of the response.

Figure 2.6: Schematic of the procedure for each trial. Sequence from top left to bottom right. Initially the stimulus was presented in the centre of the screen for 2000 ms during which time a response was required. This was followed by a blank screen for 1000 ms, appropriate feedback for 500 ms, and a final blank screen for 1000 ms before the start of the next trial.

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