1. Stage 3 Project
Is there a difference in the pattern of eye movements during visual
imagery, when spatial or object information is being recalled from
memory?
James Allen
Student number: 011306821
Word Count: 7918
1

2. Contents
Page
Abstract 3
1. Introduction 4
2. Methods 10
2.1 Outline 10
2.2 Subjects 11
2.3 Stimuli 11
2.4 Apparatus 12
2.5 Procedure 12
2.6 Visual working memory test 14
2.7 Data analysis 14
3. Results 16
3.1 Scan paths 16
3.2 Percentage of fixation duration in correct quadrant 18
3.3 Number of fixations in correct quadrant 21
3.4 Total fixation duration of all subjects in all quadrants 25
3.5 Mean duration of fixations in each condition 26
3.6 Comparison of 'what/where trials first' subjects and 27
'imagine trials first' subjects
3.7 Incorrect Responses 29
3.8 Visual Working memory score 29
3.9: Subject reports 31
4. Discussion 32
Appendix 1 36
Appendix 2 37
Appendix 3 38
Appendix 4 39
Appendix 5 42
Appendix 6 43
Appendix 7 44
Appendix 8 45
Appendix 9 46
Appendix 10 47
5. References 48
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3. Abstract
Patterns of eye movements during the recall of visual spatial information, and visual object
information, were investigated. Since the visual system appears to operate with two broadly
separate systems for processing spatial and object information (the ‘what and where’ pathways), it
was hypothesised that the recall of these two types of information may interact with the ocular
system in different ways. This may be reflected in a difference between whether or not eye
movements are made towards the spatial location of the shape being recalled (as it was initially
stored). To test this, 20 subjects were presented with an array of 4 different geometrical shapes to
memorise, on a computer monitor. Eye movements in response to being asked to recall spatial
information (e.g. “where was the triangle?”) and object information (e.g. “what colour was the
square?”) were recorded for 5 seconds per trial (60 trials per subjects). When ‘where’ information
about a shape was recalled, subjects fixated for significantly longer in the quadrant of the screen
that previously displayed the shape (t=4.35 and t=3.60, p<0.01), and made significantly more
fixations in that quadrant (t=4.55 and t=3.52, p<0.01). This effect did not occur when ‘what’
information was recalled. Subject’s visual working memory was controlled for, and did not
interact with eye movements. The implications are discussed in terms of the interaction of visual
imagery with eye movements.
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4. 1. Introduction
There is a large body of experimental evidence that indicates the visual system
can be dissociated into two broadly separate pathways (see Livingstone & Hubel,
1987 for a review). These pathways can be seen to segregate at the level of ganglion
cells of the retina, and continue through the primary visual cortex, to higher visual
areas in the brain. The magnocellular pathway appears to be sensitive to high
temporal and low spatial frequencies, and appears to be best suited for processing
movement and spatial information, hence it is commonly referred to as the ‘where’
pathway. The parvocellular pathway is sensitive to low temporal and high spatial
frequencies, and appears to be suited for processing information about form and
colour, and is often referred to as the ‘what’ pathway.
Evidence for this distinction comes from many sources. Neurophysiological
studies of the primate visual cortex have provided evidence for an inferior temporal
(ventral) pathway selective for processing object information, but not for location, and
a posterior parietal (dorsal) pathway selective for spatial processing but not for form
or colour (for a review, see Van Essen, Anderson & Felleman, 1992). This was
investigated, in one study, using micro-electrodes to record action potentials from the
macaque lateral geniculate nucleus, while macaques were presented with a series of
spatial sinusoidal grating patterns (Derrington & Lennie, 1984).
Neurological damage in primates and humans produces similar results. For
example, Isseroff et el. (1982) found that lesions to the mediodorsal nucleus in rhesus
monkeys leads to an impairment on two spatial memory tasks (spatial delayed
alternation task, and a delayed-response task), whereas performance on two object
discrimination tasks (object reversal and visual pattern discrimination) was
unimpaired. Similarly, Mishkin & Manning (1978) found that lesions to the inferior
prefrontal cortex in monkeys led to a severe impairment on three object memory tasks
(delayed object alternation, delayed object matching, and delayed colour matching),
whereas lesions to the principal sulcus led to severe impairment on spatial memory
tasks. The same phenomenon is observed in humans – Bohbot et al. (1998) found that
patients with lesions to the right hippocampus (made to relieve epilepsy) selectively
impaired spatial memory performance.
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5. Neuroimaging has also produced similar conclusions. PET studies have
revealed a differentiation in activation of brain areas during object tasks and spatial
tasks, which correspond to the same pathways. For example, Haxby et al. (1991)
studied regional cerebral blood flow in 11 normal subjects, while they conducted two
visual match-to-sample tasks. A face-matching task was used to test object vision, and
a dot-locating task was used to test for spatial vision. The two tasks appeared to
activate consistently different areas of the brain.
The fact that there appears to be a strong distinction between the ‘what’ and
‘where’ pathways in the visual system has prompted researchers to propose a similar
distinction in visual memory. Experimental evidence appears to support this
proposition.
For example, Tresch, Sinnamon & Seamon (1993) studied the relative
interference that a secondary task has on the performance of a primary task, when
both are carried out simultaneously by a subject. The two tasks studied were a spatial
memory task (subjects were asked to remember the location of a dot in a spatial
memory test), and an object memory task (remembering the form or colour of an
object). Spatial memory was found to be selectively impaired by a movement
discrimination spatial task, whereas object memory was selectively impaired by a
colour discrimination object task. They conclude that this is evidence for a
dissociation between a ‘what’ visual memory and a ‘where’ visual memory (Tresch et
al., 1993).
PET studies reveal differing activation of brain regions during working
memory tasks involving spatial or object tasks. Smith & Jonides (1997) used simple
memory tasks, in which subject were presented with an array of randomly-located
dots (a spatial memory task) or a pair of objects (an object memory task) After a 3
second retention period, subjects were required to recall the position of one of the
dots, or the shape of an object. The object task generally activated left hemisphere
regions (the posterior parietal region and the premotor region in the left hemisphere),
and the spatial task activated right-hemisphere regions (the posterior parietal cortex
and the anterior occipital cortex in the right hemisphere) (Smith and Jonides, 1997).
Ruchkin, Johnson, Grafman, Canoune & Ritter (1997) recorded ERP scalp
topographies whilst subjects retained and recalled object information (line drawings
of abstract faces) and spatial information (the location of a moving asterisk with
5

6. respect to a cross), and also found different underlying patterns of brain activation.
Mecklinger & Pfeifer (1996) also demonstrated this, by recording ERP topographies
whilst subjects conducted two versions of a delayed match-to-sample task, one using
object forms and the other using 2-dimensional spatial configurations.
Further evidence has been found in case-studies of neurologically damaged
patients. Levine, Warach & Farah (1985) presented two such patients, one of whom
showed selective damage to object memory, and the other spatial memory. ‘Patient 1’
had extreme difficulty recognising faces (including his wife), animals and
occasionally common objects, and equal difficulty in describing imagined faces,
animals and colours of objects, or drawing common items (such as a clock or an
elephant) from memory. Yet he had no difficulty in approaching or reaching for
objects, copying the arrangement of lines from a picture, describing a detailed mental
journey from one place to another, drawing a detailed plan of his house or marking
major cities on a map. This pattern of selective deficits appears to demonstrate a
dissociation of Patient 1’s ‘what’ memory, which is severely impaired, and his
‘where’ memory, which is intact.
Patient 2 showed the reverse pattern of deficits – he could identify objects,
faces and animals easily, but could not reach accurately for objects, draw a straight
line between two points and had difficulty describing the spatial relationship between
two objects presented to him. He also got lost frequently, and could not describe the
route from his home to his local shops.
Farah, Hammond, Levine & Calvanio (1988) also present a patient (L.H.) who
showed similar deficits to Patient 1 described above. Using four visual imagery tasks
(involving the recall of object shape, size, colour) and seven spatial imagery tasks
(involving the recall of the relative locations of objects, and spatial transformations of
objects). They found a clear dissociation in L.H.’s performance on object and spatial
imagery tasks – object imagery was impaired, whereas spatial imagery performance
was normal.
The present study investigated whether a dissociation between ‘what’ imagery
and ‘where’ imagery can be observed in subject’s eye movements during visual recall.
The purpose of eye movements during perception is clear - to focus particular
stimuli of interest on the fovea, so that fine spatial detail can be examined. However,
6

7. the question of whether eye movements during imagery reflect cognitive processes
involved in visual recall is a matter of controversy.
‘Strong’ theories posit a direct, functional role for eye movements during
imagery, such as Norton’s feature network theory (Norton & Stark, 1971a). Norton
and Stark (1971a, 1971b) recorded subject’s eye movements while they viewed large
line drawings, and again when subjects were presented with the same stimulus for
recognition. They found that subjects scanned images with a fixed, repetitive pattern
of eye movements, characteristic for each subject, and that those patterns were
observed again when subjects viewed the stimulus again for recognition.
Based on these observations, Norton proposed that an object stored in visual
memory consists of a network of separate features, which are spatially indexed by
recording the associated eye movements that were required to shift from feature to
feature. Imagery would therefore take place by a serial recall of sensory memory
traces, with a corresponding re-enactment of the eye movements required to shift
attention from one feature to the next.
Support comes from many studies. For example, Brandt and Stark (1997)
presented subjects with a series of irregularly-chequered diagrams, and were then
asked to visualise them. They observed characteristic eye movement patterns during
viewing of a diagram, as Norton & Stark had done, and that similar eye movements
were observed during imagery of the same stimulus.
Laeng and Teodorescu (2002) demonstrated that subjects who maintain their
gaze on a central fixation point during perception of a stimulus make little or no eye
movement when recalling the same stimulus. In contrast, subjects allowed to move
their eyes during perception made eye movements during recall, which are very
similar to those observed during perception. Most importantly, they demonstrated that
those subjects who were allowed to make eye movements during the perception
phase, but were forced to fixate during imagery, were less accurate in recalling details
than subjects allowed to move their eyes during imagery. Laeng and Teodorescu
conclude that this can be taken as evidence for a functional role of eye movements
during imagery – that is, eye movements may be important in the accurate recall of
visual information.
Hall (1974) presented subjects with a series of arrays of 12 geometric shapes,
and then asked to recall the shapes they had seen. During recall, subjects either fixated
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8. on a cross, or were allowed to freely move their eyes. Subjects who fixated during
recall remembered fewer shapes, and had a slower recall latency (Hall, 1974).
However, there are many objections. Movement of the eyes is certainly not a
necessary condition for visual recall. Although Laeng and Teodorescu (2002) did
observe a detrimental effect of forced fixation on imagery performance, this effect
was far from total, and caused only a slight reduction in performance. Furthermore,
Norton and Stark (1971a) only found repetitive, characteristic scan paths during
recognition of stimuli in 65% of trials, and do not provide a quantitative method for
analysing scan paths. If eye movements do play a role in imagery, they are helpful,
but not necessary.
We must also consider studies that find no relationship between eye
movements and imagery performance. For example, Hale and Simpson (1970)
presented noun pairs, using a tape-recorder, to subjects whilst recording their lateral
eye-movements. Their task was to generate mental images that linked each noun pair.
Subjects were instructed either to make eye movements during visual imagery, or not
to make eye movements, and the time it took to generate images, and the reported
‘vividness’ of those images, was recorded under each condition. They found that
making eye movements made no significant difference to the vividness or latency of
generating mental images (Hale and Simpson 1970).
Janssen and Nodine (1974) presented nouns for memory storage, using a tape-
recorder, while subjects either fixated on a cross, or were allowed to move their eyes.
They found no difference in the recall performance of nouns between the two
conditions. These two studies therefore contradict the idea that eye-movements
facilitate recall of visual information.
The disagreement between these studies and those of Norton & Stark (1971a,
1971b), Laeng & Teodorescu (2002) and Hall (1974) may be due to a simple factor:
Janssen & Nodine (1974) and Hale & Simpson (1970) used auditory stimuli,
presented using a tape-recorder, whereas Norton & Stark and others used visual
stimuli. It seems that the precise type of cognitive demand strongly influences
whether or not eye movements occur during imagery, and in what spatial pattern.
The present study was designed to investigate the effects of different cognitive
demands on the pattern of eye movements during visual recall. Considering the
evidence already resented, it is reasonable to hypothesise that recall of ‘what’ visual
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9. information (e.g. colour and shape) may elicit a different pattern of eye movements to
the recall of ‘where’ information. Furthermore, the requirement of a verbal response
from subjects may also be a significant factor.
This will be tested by presenting subjects with a visual array of 4 shapes, in 4
corners of a display screen. Subjects will then be asked to recall either ‘what’ info or
‘where’ info about one of the shapes, whilst their eye movements are recorded.
Subjects will also be asked to simply ‘imagine’ the colour or shape of one of the
shapes, without verbally responding.
Eye movements that subjects made during recall will be analysed to determine
what proportion are directed towards the corner of the screen that previously
displayed the shape being recalled, compared to the other corners of the screen. An
observed difference in eye movements between ‘what’ and ‘where’ imagery
conditions would be evidence that these types of visual imagery operate and interact
with the ocular system in different ways. It would also demonstrate a further
difference in how the brain processes ‘what’ and ‘where’ information.
Furthermore, if one condition elicited a higher proportion of eye movements
towards the corner being tested than another, this would suggest a greater reliance of
this type of visual recall on eye movements which are related to the spatial
arrangement of the stimulus previously stored.
We also tested for a difference between the recall of visual information when
subjects must verbally respond, and recall of the same information without subjects
responding verbally (i.e. simply ‘imagining’ the stimulus). If a difference is observed
here, this would suggest that the task of responding verbally also influences the nature
of eye movements elicited.
A confounding variable, which may influence subject’s responses, is how
good their short-term visual memory is. To control for this, each subject’s visual
working memory capacity was measured in a simple test (see section 2.6), to
investigate whether there is an interaction of memory capacity with eye movement
responses.
To minimise the influence of demand characteristics of the experimental
procedure, subjects were led to believe that pupil size was being measured rather
than eye movements. The idea of pupil measurement was reinforced during the
experiment, and eye movements were not mentioned at any time.
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10. 2. Methods
2.1 Outline
A series of 60 computer images were used as stimuli. Images consisted of a
grey background, with simple shapes in each corner (a triangle, a square, a circle and
a star), which were different colours (red, green, yellow and blue). After viewing each
image for 5 seconds, while eye movements were recorded by an eye-tracker, subjects
were then asked to recall information about those images.
Six types of questions were asked, which constituted six experimental
conditions (see table 1). These were designed to task visual memory in different ways.
Our primary interest is how eye-movement responses to ‘what’ questions compare to
responses to ‘where’ questions. However, of secondary interest is whether using
shape or colour as the ‘reference’ for recall will affect subject responses. For example:
- “What was the red shape?” requires that object information about what the
shape was (its shape), using a colour (red) as the reference for recall. This type
of question will be referred to as What (colour).
- “What colour was the circle?” requires that object information about what
the colour of the shape was, using its shape (circle) as a reference. This type of
question is What (shape).
Therefore there are two conditions for both ‘what’ and ‘where’ questions, one
using colour as a reference, and the other using shape (see table 1). All these
questions require a response from the subject.
Of secondary interest is what happens when similar questions are asked, but a
verbal response is not required – this is investigated using a further two experimental
conditions, in which subjects are asked to imagine a particular shape, again using
colour or shape as a reference.
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11. Table 1: Summary of the 6 experimental conditions
Question type Information to be recalled
‘What’ or ‘Where’
visual memory
tested?
1. What was the yellow shape? Recall shape, with colour as a reference What
2. What colour was the square? Recall colour, with shape as a reference What
3. Where was the red shape? Recall location, with colour as a reference Where
4. Where was the square? Recall location, with shape as a reference Where
5. Imagine the yellow shape. Recall shape, with colour as a reference (with
no verbal response)
?
6. Imagine the colour of the
square.
Recall colour, with shape as a reference (with
no verbal response).
?
2.2 Subjects
Twenty volunteers aged 20-25 took part in the experiment (16 females, 4
males). All subjects were psychology undergraduate students. Subjects were naïve as
to the true purpose of the experiment, as they were informed that their pupil size
would be recorded during a simple memory exercise. No subjects were colour-blind.
Subjects were divided into two equal blocks of ten:
a) Those doing ‘what’ and ‘where’ trials first, and then ‘imagine’ trials.
b) Those doing ‘imagine trials first, then ‘what’ and ‘where’ trials.
The purpose of doing this is to investigate any ‘carry-over’ effects between
conditions in which a response is required, and conditions in which it is.
2.3 Stimuli
60 unique images were used, one image for all 60 trials in one experimental
run. The dimensions of each image were 1024 x 768 pixels, with 4 shapes (a triangle,
a square, a circle and a star), each no larger than 120 x 120 pixels, in the 4 corners
(See figure 1, and appendix 1 for a more
detailed diagram). Each shape covered an
area approximately 4.6° of visual angle at the
distance tested. The arrangement of shapes in
each image was unique, and counterbalanced
across all 60 images.
The background was neutral grey. The
four shapes in each image was either red,
11
Figure 1: Example stimulus

12. green blue or yellow – again the combination of colours was unique for each image,
and counterbalanced. The colour values of all colours used are summarised in table 2.
The shape to be tested (the test shape) in each image was determined prior to
the experiment. All 60 test shapes were unique, and counterbalanced, with respect to
their colour, shape and location.
Table 2: RGB Colour values for images
Colour R value G value B value Hue Saturation Luminance
Red 255 0 0 0 240 120
Green 0 255 0 80 240 120
Blue 0 0 255 160 240 120
Yellow 255 255 0 40 240 120
Grey 128 128 128 160 0 120
2.4 Apparatus
An infra-red based eye-tracker, made by Cambridge Research Systems, was
used to record eye movements. Two separate infra-red sources are used to create two
purkinje images reflected from the subject’s eye. By tracking the relative distance
between the purkinje images and the pupil, the position of the eye (after proper
calibration) can be calculated. Eye movements were tracked at a rate of 50 hertz.
Subjects sat with their head held in position by a chinrest, in a dimly lit room.
Both the table and chair height were adjustable to enable maximum comfort for the
subject. Stimuli were presented at an 8-bit colour depth, on a 21” monitor running at
100hz. The display size was 3960 x 2920 mm. The distance between subject’s eyes
and the screen was 550mm, which gives a stimulus area of 35.7° - 29.7° of visual
angle. The eye tracker is accurate to approximately +/- 0.25° – 0.5° of visual angle.
2.5 Procedure
Subjects were informed, in the first instance, that they were taking part in an
experiment in which we would measure pupil size during a simple memory exercise.
As discussed earlier, this essential step was designed to avoid subjects becoming
aware of their eye movements, and so increasing the validity of our results.
On arrival at the laboratory, they were given an instruction sheet (see
Appendix 2), which described the experimental procedure. Depending on whether
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13. subjects belonged to the ‘what and where trials first’ block or ‘imagine trials first’
block, the instruction sheet only described either the ‘what and where’ trials or the
‘imagine’ trials respectively. Further instructions were only given after completion of
the first set of trials.
Subjects were then seated in the eye-tracker. The system was first calibrated to
each subject for maximum accuracy. Subjects were asked to look directly at a series
of 20 small black dots which appeared at various locations on the screen. The position
of subject’s eyes whilst fixating on each dot was used to calibrate the eye-tracker.
Subjects were informed that this procedure enabled the apparatus to more accurately
measure pupil size.
When the subject was ready, the first set of trials began. Each trial consisted of
the following sequence:
1. Image displayed on screen for 5000 ms
2. Neutral grey screen displayed
3. Either a question was asked about the image, or the subject was asked to
imagine a shape from the image. Simultaneously, co-ordinates of their eye
movements were recorded, for 5000 ms. Accuracy of verbal responses were
also recorded.
This sequence was repeated until that set of trials was complete. For those
subjects who did ‘response-required’ trials first, the set of trials consisted of 40
randomly mixed questions:
- 10 questions asking ‘What colour was the (shape)?’
- 10 questions asking ‘What was the (colour) shape?’
- 10 questions asking ‘Where was the (shape)?’
- 10 questions asking ‘Where was the (colour) shape?’
For those subjects who did ‘imagine’ trials first, the set of trials consisted of
20 randomly mixed questions:
- 10 statements asking subjects to ‘Imagine the (colour) shape.’
- 10 statements asking subjects to ‘Imagine the colour of the (shape)’.
On completion of the first set of trials, subjects were informed of the second
set of trials. After a minute rest period, the second set of trials was conducted. After
completion, all subject were tested for their visual working memory capacity.
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14. 2.6 Visual Working Memory test
Working memory is often tested using the digit span task. This test has been
modified in the present experiment to test working memory capacity for visual
shapes, in which subjects memorize a string of shapes shown on cards, and must then
immediately draw them on paper. Although we cannot rule-out the possibility of
verbal encoding, we will assume that this will give a fair approximation of the visual
memory capacity of each subject.
Example stimuli can be found in appendix 3. Stimuli were presented by the
experimenter on white cards, 19cm x 8cm, with each shape printed in black and
approximately 1cm x 1cm in size. Subject and experimenter sat half a meter apart – at
this distance the shapes were easily visible. Subjects were given a number of seconds
equal to the number of shapes on the card in which to memorise each string. Starting
from 1 shape, each correct response increased the number of shapes to be tested on
the next trial. The test was continued until subjects gave two successive incorrect
answers, and the number of shapes subjects could recall correctly was recorded as the
measure of his/her visual working memory capacity.
2.7 Data Analysis
The temporal sequence of eye positions, recorded for each trial at 20ms intervals
(50hz), was initially processed to discard minor movements, and extract a series of
eye fixations and their durations. This was done by comparing each co-ordinate to the
next, to determine whether a spatial shift of 15 pixels or more (0.5° of visual angle or
more) had occurred. If the shift was smaller, there was considered to be no change in
fixation. If the shift was larger, and this deviation remained for longer than 80ms, this
was considered a change in fixation.
Each fixation was then assigned as being (see Figure 2):
1. In the same quadrant as the shape being tested and recalled. This quadrant will
be referred to from now on as the ‘correct quadrant’.
2. In one of the other quadrants of the screen. These shall be called ‘non-test
quadrants’.
14

15. 3. Within a 100 x 100 pixel area in the middle of the screen (see Figure 2),
referred to as the ’exclusion box’. It was decided that saccades in this area
could not be considered to be definitely in any particular quadrant.
Figure 2: Diagram showing how fixations were divided into quadrants
15

16. 3. Results
3.1 Scan paths
When subjects were presented with a stimulus for 5 seconds (the stimulus inspection
phase), their eyes made saccades to at least two, usually three shapes in that stimulus.
For a typical example, see Figure 3. Analysis of all recordings confirmed that subjects
did not simply fixate in the centre of the screen.
During the memory recall
phase, in response to a
question or a command to
imagine one of the shapes, eye
movements across the screen
were successfully recorded in
most cases. Examples of scan
path recordings during
memory recall can be seen in
Figure 4, superimposed on the
particular image which was
being recalled at the time.
Eye movements were not recorded in 24 trials, due to tracking obstructions such as
closing eyelids, blinking, or looking outside the boundary of the screen. However this
represents only 2% of trials conducted in total.
16
Figure 3: recording of a typical subject's eye movements
when viewing a stimulus for 5 seconds

17. Figure 4: examples of eye-movement recordings during memory recall.
Figure 4A: "What colour was the star?"
Figure 4B: "What was the red shape?"
Figure 4C: "Where was the square?"
Figure 4D: "Where was the red shape?"
17
Figure 4A Figure 4B
Figure 4C Figure 4D

18. 3.2 Percentage of fixation duration in correct quadrant
For each trial, the duration of time subjects fixated in the correct quadrant was
calculated as a percentage of the total duration of time they fixated in all four of the
quadrants. Therefore, a percentage of over 25% would indicate that more eye
movements were being made towards the corner of the screen which previously
displayed the shape being tested, than to any other corner. The means and standard
deviations for all 6 conditions (see table 1) are summarised in table 3. Full data can be
found in appendix 4.
Table 3: Average time spent in correct quadrant (ms),
per condition, as a percentage of total time in all 4 quadrants
Figure 5 shows these data in a bar chart. A line at 25% on the y-axis, i.e. 25% of time
spent in the correct quadrant, rep-resents what would be expected assuming the null
hypothesis that subjects do not make more eye movements towards the quadrant being
tested. There was a slight increase over 25% for 'what' conditions, and a much larger
increase over 25% for 'where' and 'imagine' conditions. The increase in where' and
'imagine' conditions is larger when colour is used as the reference.
To test whether the proportion of time spent in the correct quadrant was significantly
more than 25%, 6 t-tests were carried out on the data, to test whether each condition
varied significantly from having a mean of 25%. Therefore, they tested the probability
that the data for each condition was sampled from a population having a mean of
25%, and a standard deviation equal to the standard deviation found in our data (see
table 3).
Table 4 summarises the t-values and their related one-tailed significance
values for all conditions (see appendix 5 for source data). A one-tailed test was used
because only increases over 25% were observed in the data (see figure 5), and so only
18
Condition Average %
time
St. Dev.
What (colour) 26.28 % 33.30
What (shape) 27.04 % 34.97
Where (colour) 44.44 % 38.60
Where (shape) 36.48 % 36.86
Imagine (colour) 43.04 % 37.34
Imagine (shape) 40.69 % 38.05

19. Figure 5: Time spent in correct quadrant as percentage of time spent in all 4 quadrants
increases were tested for. The Kolmogorov-Smirnov test was used to test whether the
data were normally distributed - the data were approximately normally distributed, but
only with a confidence of p<0.2 (KS value = 0.46, p<0.2). However, the t-test, and
ANOVA test, are robust to small departures from normality. See Appendix 6 for the
appropriate Q-Q plot.
Table 4: T-values for each condition, testing for percentage time in
correct quadrant being more than 25%
Condition Tobt df
Tcrit α=0.05
(1-tailed)
Tcrit α=0.01
(1-tailed)
Significant
?
What (colour) 0.18 19 1.73 2.54 n.s.
What (shape) 0.65 19 1.73 2.54 n.s.
Where (colour) 4.35 19 1.73 2.54 p<0.01
Where (shape) 3.60 19 1.73 2.54 p<0.01
Imagine (colour) 4.66 19 1.73 2.54 p<0.01
Imagine (shape) 4.24 19 1.73 2.54 p<0.01
19

20. For 'what' conditions, there was no significant increase in the average
proportion of time spent by subjects fixating in the correct quadrant, over 25%.
However for 'where' conditions, there was a highly significant increase over 25% (t=
4.35, t=3.60, p<0.01). Recalling the location of a shape, using colour as the reference,
elicited a stronger increase in the proportion of fixation durations in the correct
quadrant, than using shape as a reference (44.4%, compared to 36.5%).
Conditions which subjects were asked to 'imagine' a particular shape also
elicited significant increase in average proportion of fixations in the correct quadrant
over 25% (t=4.66, t=4.24, p<0.01).
A one-way related ANOVA (see Table 5) was also carried out on the data to
test for significant differences between conditions. Condition (what type of question /
statement was given to the subject) was found to have a highly significant effect (F=
7.23, p<0.001). Subjects also represented a significant source of variance (F=2.67,
p<0.001).
Table 5: Related ANOVA table comparing average percentage time in
correct quadrant for all 6 conditions
Source
of Var.
Sum of
Sq.
df Mean
Sq.
F
Ratio
F critical
(α=0.001)
Condition 6606.13 5 1321.23 7.23 F5,95 = 4.48
Subjects 9262.34 19 487.49 2.67 F19,95 = 2.59
Error 17369.06 95 182.83
Total 33237.53 119
To reveal which conditions in particular gave significantly different results, a
posthoc Tukey's honestly significant difference yardstick (R) was calculated, using
α=0.01. Comparing the yardstick (R= 15.09, α=0.01) with the means for each
condition (see Table 3) shows that there was a significant difference between the
'where (colour)' condition, and both 'what' conditions, and a significant difference
between the imagine (colour) condition and both 'what' conditions. Other differences
were not significant.
20

21. 3.3 Number of fixations in correct quadrant
For each trial, the number of fixations in the correct quadrant, in the other 3
quadrants, were counted. The mean number of fixations per trial, for each condition,
and standard deviations are summarised in Table 6.
Table 6: Mean number of fixations per trial in correct
Quadrant and other 3 quadrants
Condition Mean no. fix-
ations in correct
quadrant
St.
Dev.
Mean no. fix-ations
in all other
quadrants
St.
Dev.
What (colour) 1.98 2.71 4.86 3.75
What (shape) 1.77 2.54 4.92 3.70
Where (colour) 3.19 3.32 3.63 3.55
Where (shape) 2.43 2.65 4.12 3.38
Imagine (colour) 3.34 3.66 3.17 2.96
Imagine (shape) 2.89 3.22 4.00 3.36
Figure 6 shows a histogram of average number of fixations in the correct quadrant,
and the average number of fixations in each of the three other quadrants (i.e. the
values from the 4th column in table 6, divided by 3), for each condition. To obtain a
meaningful comparison, the width of bar representing the number of fixations in the
other 3 quadrants is 3 times the width of the bar representing the single, correct
quadrant.
21

22. Figure 6: Histogram of average number of fixations in correct quadrant, and the other 3
quadrants, for each condition.
For both 'what' conditions, there was little difference between the average
number of fixations made in the correct quadrant, and the average number made in the
other three quadrants. In the 'where' conditions there were, on average, significantly
more fixations made in the correct quadrant than in the other three quadrants. The
difference was always larger when colour was the reference. The 'imagine' conditions
again appeared to elicit responses very similar to 'where' conditions - there were
significantly more fixations made in the correct quadrant than the other three
quadrants, and again the difference was larger when colour was used as the reference.
For each condition, related t-tests were used to test the significance of
differences between:
a) the average number of fixations made in the correct quadrant
and
b) the average number of fixations made in the other 3 quadrants, divided by
3. i.e. the average number of fixations made in each of the three other
quadrants.
Table 7 summarises the t-values and their related critical values. See Appendix
7 for the source data. A Kolmogorov-Smirnov test was used to test whether the data
were normally distributed - the data were normally distributed (KS value = 0.17,
p<0.00). See Appendix 8 for the appropriate Q-Q plot.
Table 7: T-values to tests significance of difference between no. of fixations in correct quadrant,
and average no. of fixations in each of the other quadrants, for each condition.
Condition Tobt df
Tcrit α=0.05
(1-tailed)
Tcrit α=0.01
(1-tailed)
Significance
?
What (colour) 1.06 19 1.73 2.54 n.s.
What (shape) 0.70 19 1.73 2.54 n.s.
Where (colour) 4.55 19 1.73 2.54 p<0.01
Where (shape) 3.52 19 1.73 2.54 p<0.01
Imagine (colour) 4.01 19 1.73 2.54 p<0.01
Imagine (shape) 3.80 19 1.73 2.54 p<0.01
22

23. There was a significant difference between the average number of fixations in the
correct quadrant, and the average number in the other three quadrants, in the 'where'
conditions (t=4.55, t=3.53, p<0.01) and 'imagine' conditions (t=4.01, t=3.80, p<0.01)
only. The difference for 'what' conditions was not significant.
Table 8: number of fixations in correct quadrant,
as a percentage of total number of fixations made,
per trial, for each condition
For each condition, the number of
fixations made by subjects in the
correct quadrant was calculated as a
percentage of the total number of
fixations made. The mean
percentages, and standard deviations,
are summarised in Table 8.
A related ANOVA was carried out on the data to test for significant differences in the
proportion of fixations made in the correct quadrant, between conditions. Table 9
shows the ANOVA table (see Appendix 9 for source data).
Table 9: ANOVA table of variance between conditions
for average percentage of number of fixations in test quadrant
Source of
Var.
Sum of
Sq.
df Mean
Sq.
F
Ratio
F critical
(α=0.001)
Condition 7509.32 5 1501.86 6.65 F5,95 = 4.48
Subjects 11367.14 19 598.27 2.65 F19,95 = 2.59
Error 21442.58 95 225.71
Total 40319.04 119
Condition had a significant effect on the proportion of fixations subjects made in the
tested quadrant, compared to the other quadrants (F=4.48, p<0.001). Subjects were
also a significant source of variation (F=2.59, p<0.001). A posthoc Tukey's HSD
yardstick, calculated as R=16.76 (for α=0.01), revealed that there was a significant
difference between where (colour) and both what conditions, and imagine (colour)
and both 'what' conditions.
23
Condition
Mean % fixations
in correct quadrant
St.
Dev.
What (colour) 28.9% 19.1
What (shape) 26.5% 12.0
Where (colour) 46.8% 18.7
Where (shape) 37.1% 13.4
Imagine (colour) 51.3% 17.9
Imagine (shape) 41.9% 16.9

24. 3.4 Total fixation duration of all subjects in all quadrants
Table 10 summarises the total duration of recorded fixations made by all
subjects, across all trials, for each condition. The total duration of fixations made in
the correct quadrant, in the other 3 quadrants, and in the central exclusion box, are
shown separately.
The total recording time for all subjects in each condition should have been
1,000 seconds (10 trials per condition, lasting 5 seconds, for 20 subjects) - however,
some time will have been 'lost' due to blinks, or other disruptions to eye-tracking.
Therefore the total time recorded in each quadrant as a percentage of 1,000 seconds is
also shown, as well as the percentage of recording time which was lost.
Table 10: Total duration of fixations (ms by all subjects, for each condition, with percentage of
total recording time per condition (1,000,000 ms)
Condition Total T in
correct
quad.
Percentage
of total
Total T in
other 3
quads.
Percentage
of total
Total T in
exclusion
box
Percentage
of total
Percentage
of T not
recorded
What (colour) 108220 10.8% 259440 25.9% 553320 55.3% 8%
What (shape) 101680 10.2% 273140 27.3% 556600 55.7% 6.8%
Where (colour) 176240 17.6% 207820 20.7% 537640 53.8% 7.9%
Where (shape) 136980 13.7% 243460 24.3% 561740 56.2% 5.8%
Imagine (colour) 206960 20.7% 241540 24.2% 411120 41.1% 14%
Imagine (shape) 218500 21.9% 291180 29.1% 363200 36.3% 12.7%
For 'what' and 'where' conditions, the time subjects were recorded fixating in
the central exclusion box was always more than 50% of the total time for each
condition.. However this is not true for the 'imagine' conditions - the time subjects
spent in the central exclusion box drops significantly. The total time spent in the
correct quadrant was also higher in both 'imagine' conditions than any other.
Between 5.8 % and 14 % of the total recording time was lost because of loss
of tracking.
The total time subjects spent in the correct quadrant is compared to the total
time subjects spent in the other quadrants in Figure 7. To make a meaningful
comparison, the bar for the total time spent in the three non-test quadrants is three
times the width of the bar representing the single, correct quadrant.
24

25. Figure 7: Histogram of total duration (ms) of fixations by all subjects, in each quadrant, for all
conditions.
There is little difference in the total time recorded in the correct quadrant and the
other quadrants for both 'what' conditions. There is a large difference for both 'where'
and 'imagine' conditions. Again, these differences are slightly larger when colour was
the reference for recall.
3.5 Mean duration of fixations in each condition
The mean duration of fixation made by subjects, in both the correct quadrant and the
other quadrants, are compared in Table 11. Also shown are the average duration of
fixation made in the central exclusion box, and standard deviations.
Table 11: Mean duration of fixation by all subjects in test quadrant, non-test quadrants and
exclusion box
Condition Tested
quadrant
St.
Dev.
Non-test
quadrants
St.
Dev.
Exclusion
box
St.
Dev.
What (colour) 304.0 ms 283.4 292.2 ms 288.1 352.8 ms 492.7
What (shape) 312.9 ms 352.4 311.1 ms 302.5 296.9 ms 332.3
Where (colour) 285.2 ms 288.8 308.3 ms 284.8 334.6 ms 525.5
Where (shape) 294.6 ms 315.3 326.8 ms 342.6 301.1 ms 343.0
Imagine (colour) 310.8 ms 350.4 381.0 ms 447.0 519.9 ms 754.2
Imagine (shape) 378.0 ms 459.5 362.6 ms 419.6 552.7 ms 714.6
25

26. These data are represented as a bar chart in Figure 8. It shows only small differences
in the duration of fixation that subjects made when fixating in a test quadrant,
compared to when fixating in a non-test quadrant. However, in 'imagine' conditions,
the average duration of fixation is slightly higher in the exclusion box.
Figure 8: Average duration of fixation (ms) in test quadrant, non-test quadrants, and exclusion
box
3.6 Comparison of 'what/where trials first' subjects and 'imagine trials first'
subjects
10 subjects were given 'what' and 'where' conditions first, which required a
verbal response, and then 'imagine' conditions, which did not. 10 different subjects
were given 'imagine' conditions first, then 'what' and 'where' conditions. It was
considered possible that this variable may influence subject's eye movement
behaviour, and so it was equally balanced across subjects in this way.
Table 12 shows the duration of fixations in the correct quadrant, as a
percentage of the duration in all quadrants, spent by subjects who ran the 'imagine'
conditions first, and the subjects who ran the 'what / where' conditions first.
Figure 9 shows these percentages as a bar chart. It shows that there was little
difference between the two groups of subjects.
26

27. Table 12: Average duration of fixation in test quadrant as a percentage of duration in all
quadrants, for each condition, comparing 'what/where 1st' with 'imagine 1st'
Condition
'Imagine'
conditions
presented 1st
St.
Dev.
'What / where'
conditions
presented 1st
St.
Dev.
What (colour) 28.45 % 34.45 24.10 % 32.15
What (shape) 26.65 % 32.79 22.99 % 32.89
Where (colour) 37.12 % 37.31 51.30 % 38.72
Where (shape) 36.47 % 38.37 36.49 % 35.56
Imagine (colour) 39.45 % 37.57 46.58 % 36.87
Imagine (shape) 35.57 % 37.76 45.92 % 37.81
Figure 9: Average % time in tested quadrant, comparing subjects who ran 'what' and 'where'
trials 1st with subjects who ran 'imagine' trials 1st
A two-way, mixed-design ANOVA was used to test for a significant difference
between the two groups. Variable A was whether subjects did 'what/where' trials first
or 'imagine' trials first (the between-subjects variable). Variable B was the condition
(the within-subjects variable). Table 13 shows the ANOVA table for this calculation -
the source data can be found in appendix 10.
The effect of variable A, whether subjects did which trials first, was
insignificant, and there was no interaction with variable B (condition).
27

28. Table 13: 2-way, mixed-design ANOVA to compare effect of 'what/where first'
with 'imagine first', across all conditions
Source of Variance
Sum of
Sq.s
df
Mean
Sq.s
F ratio
Fcrit
α = 0.05
Fcrit
α = 0.01
W/W or Imagine
1st (Var. A)
792.26 1 792.26 0.94 4.96 10.0
Error AS 8470.11 10 847.01
Condition (Var. B) 6606.15 5 1321.23 4.10 2.40 3.41
A x B (interaction) 1275.94 5 255.19 0.793 2.40 3.41
Error B x AS 16093.10 50 321.86
Total 33237.56 119
3.7 Incorrect Responses
The total number of incorrect responses given by all subjects, for the 'what' and
'where' conditions, are compared in Table 14. Since subjects did not respond to
'imagine' trials, the success of recall was not recorded. Table 11 shows that 'where'
questions elicited fewer incorrect responses than 'what' questions. In total, 7% (56) of
'what' and 'where' trials were answered incorrectly.
Table 14: Total number of incorrect responses, for all subjects,
in 'what' and 'where' conditions (out of 200).
Condition
No. of incorrect
responses
What (colour) 18
What (shape) 17
Where (colour) 9
Where (shape) 12
3.8 Visual Working memory score
All subjects scored between 3 and 6 on the visual working memory tests (the vWM
score). That is, subjects could remember a string of between 3 and 6 of the shapes
used on the working memory test (see appendix 3). Figure 10 shows the frequency of
subjects who had working memory scores of 3, 4, 5 and 6. Half of subjects scored 4.
28

29. Figure 10: Histogram of working memory test scores for all subjects
Table 15 is a summary of working memory scores for each subject, and the number of
incorrect answers given by subjects in 'what' and 'where' trials. Figure 11, a plot of
subject's visual working memory scores against the number of incorrect answers
given by subjects, reveals a moderate negative correlation (-0.42).
Table 15: Working memory scores and
number of incorrect responses for each subject
29
Subject vWM
score
No.
wrong
1 4 9
2 3 2
3 4 6
4 6 0
5 6 0
6 3 5
7 5 0
8 4 3
9 5 3
10 4 9
11 4 2
12 6 1
13 4 1
14 3 2
15 5 5
16 5 0
17 4 3
18 4 3
19 4 4
20 4 9

30. Figure 11: Plot of visual working memory
score against number of incorrect answers
30

31. Figures 12 shows the average percentage of fixation duration in the correct quadrant
per trial, for subjects with different working memory scores. Figure 13 shows the
same percentages for subjects who gave different numbers of incorrect responses.
These graphs show that the eye movement data did not appear to be related to
subject's working memory capacity.
Figure 12: Average percentage time in correct Figure 13: Average percentage time in correct
quadrant against visual WM score quadrant against number of incorrect answers
3.9: Subject reports
When informed of the true nature of the experimental hypothesis (after conducting the
experiment), subjects reported being unaware of it - they assumed that pupil diameter
was being measured rather than eye movements.
31

32. 4. Discussion
The present study investigated the effects of different cognitive demands on the
pattern of eye movements during visual recall. It was predicted that the different
demands of recalling ‘what’ visual information (e.g. colour and shape) and ‘where’
visual information may elicit different patterns of eye movements, in terms of whether
or not eye movements during recall of a stimulus are directed towards the spatial
location of the stimulus when it was stored (such eye movements will be referred to
from now on as Towards Eye Movements, or T.E.M.s.)
This was tested by presenting subjects with a visual array of 4 shapes, in 4
corners of a display screen. Eye movements that subjects made during a 5-second
‘recall phase’ were analysed to determine what proportion are directed towards the
corner of the screen that previously displayed the shape being recalled, compared to
the other corners of the screen.
For ‘what’ trials, there was no significant increase in the proportion of time
that subjects fixated in the correct quadrant, compared to in any of the other
quadrants. Neither were there a greater number of fixations in the correct quadrant
compared to other quadrants. We can conclude that the recall of visual information
does not appear to cause the brain to make TEMs.
In contrast, when subjects recalled ‘where’ visual information, they spent a
significantly greater proportion of time fixating in the correct quadrant, compared to
any of the other quadrants. They also made a greater number of fixations. We can
conclude that visual imagery of a stimulus which involves spatial information causes
the brain to make eye movements which are related to the spatial co-ordinates of the
stimulus when it was stored (i.e. they made TEMs).
However, although this is what the brain does, the present experiment does not
tell us whether these eye movements actually helped subjects recall the information.
This is because reaction time was not recorded due to time constraints of this project,
and the difficulty of the task was not great enough to give a high variance in
performance. This means we cannot conclude whether or not eye movements were
functionally involved in any way with visual recall.
For example, it may be, in accordance with Norton and Stark’s feature
network theory (Norton & Stark; 1971a; 1971b), that the eye movements observed in
this study were functionally involved in aiding visual working memory to recall
32

33. spatial information. That is, the re-enactment of the eye movements themselves help
working memory to access features of the image stored in visual memory.
Alternatively, they may be that the TEMs observed were an irrelevant by-
product of thinking about spatial locations. The eyes are almost constantly moving, so
it seems plausible to consider they moved towards the location of the stimulus when it
was stored simply in the absence of anything else relevant to look at. The present
study cannot rule out such explanations.
However, the study has revealed an important question: why did we observe
these eye movements in ‘where’ conditions, but not in ‘what’ conditions? This is an
unexplained and reliable phenomenon, worthy of further investigation.
For example, further research using the same basic procedure as the present
study, but with a more difficult task and with reaction time measured for each subject,
would reveal more information about how eye movements relate to recall
performance. If performance was strongly related to TEMs, this would suggest a more
functional role for eye movements in visual imagery.
Furthermore, the exact timing of subject responses could be recorded on a
microphone, so that eye movements could be analysed in terms of exactly when
subjects succeeded in recalling the stimulus. If TEMs were made before subjects gave
a response, this would suggest they were used to help recall the visual information. If
they were made after subjects responded, this would suggest they play no role in
helping working memory, and are a simple by-product. Unfortunately, the present
studied analysed a whole 5-second time period called the ‘recall phase’, without a
precise record of when during that 5 seconds subjects had succeeded in recalling the
stimulus.
When subjects were asked to recall and simply imagine ‘what’ information
(e.g. “imagine the colour of the square”, “imagine the green shape”), they spent
significantly more time fixating in the correct quadrant than any other quadrants, to
approximately the same extent as during ‘where’ conditions. This suggests that the
‘relaxed’ nature imagine conditions (that is, the subject only has to think), caused
subjects also to recall and imagine the location of the shapes, i.e. the ‘where’
information as well as the ‘what’ information. This would account for the TEMs
observed.
If further research was done to further investigate this, it would be more
appropriate to replace ‘imagine’ statements with replications of the same questions
33

34. used in the ‘what’ and ‘where’ conditions (e.g. “what colour was the square?”,
“Where was the green shape?”), and simply ask subjects not to responds to the
questions (but to think about them). In this was, the effect of making a verbal
response can be directly compared to identical trials in which subjects do not respond,
without any change in what is said to subjects. Also, it would allow testing of both
‘what’ and ‘where’ visual recall without a verbal response, whereas the present study
only investigated ‘what’ visual recall.
No significant differences were found in TEMs between conditions in which
colour was used as the reference for recall (e.g. “What was the green shape?”) and
conditions in which shape was the reference for recall (e.g. “What colour was the
triangle?”). However, there were consistently slightly more TEMs observed in
conditions using colour as the reference. This suggests that the distinction between
recalling colour information and recalling shape information may be a further variable
involved in the pattern of eye movements during visual imagery. A more powerful
experiment may be required to investigate this.
The visual working memory scores (vWM scores) for each subject appeared to
be validated, to some degree, by the negative correlation of vWM scores with the
number of incorrect answers given by subjects. A negative correlation would be
expected if the scores were valid measures of vWM capacity.
It was confirmed that subject’s vWM capacity did not influence or interact
with their eye movement responses. That is, how good each subject’s visual memory
was did not appear to influence the percentage of time subjects spent in the correct
quadrant, compared to other quadrants, during the experiment. We can say therefore
that it was not a confounding variable in the experiment.
It was also confirmed that whether we presented subjects with ‘what’ and
‘where’ trials first (in which they were required to respond), or whether we presented
them with ‘imagine’ trials first, made no significant to the variation in subject’s eye
movements. Therefore, this was also not a confounding variable in our experiment.
Subjects, however, did represent a significant source of variance in this study.
This is important in that it indicates that subjects varied significantly in the behaviour
of their eye movements during visual recall. An in-depth case-by-case analysis of eye
movement patterns would be more revealing in investigating how much subjects
differ, and in what ways, but beyond the scope of the present study.
34

35. Subjects were unaware of the exact nature of the experimental hypothesis, and
so we can be fairly confident that the eye movements observed were not made in
response to the task demands of the experiment – that is, that they did not make eye
movements simply because they felt like this was what was being tested for.
35

36. Appendix 1
Example stimulus image, showing image dimensions in pixels. 60 images in total
were used, each one with a unique combination of 4 shapes (a star, circle, square and
triangle) in 4 corners of the image, with 4 colours (red, green, yellow and blue).
36

37. Appendix 2
Example instruction sheet given to subjects.
Instruction sheet
Thank you for agreeing to take part in our experiment. The first thing we will do is
make sure you do not have any type of colour blindness – is you do, we may not be
able to use you as a subject.
We will be measuring pupil size during a simple memory task. You will be sitting
with your head held in position by a pupilometer. Please make sure you are
comfortable, as the table and chair heights can be adjusted. If it needs changing,
please say so -you will be in it for about 10-15 mins.
Calibration
We will then calibrate the pupilometer to your pupil. After getting a comfortable
position in the pupilometer, you will see a series of 20 small black dots appear at
various locations on the screen – please look directly at them in turn.
The experiment
We can then start the experiment. We will be giving you a simple memory exercise,
in which you have to memorise geometric shapes presented on a computer screen. An
example of what you will see is shown below:
You will see an image like this for 5 seconds – please look directly at each of the
shapes, and try to memorise their colour, shape, and location.
We will then ask you a question about the image - for example, “where was the
triangle?” or “what was the red shape”. You should try to answer this as quickly and
accurately as you can.
This sequence will be repeated a number of times.
37

38. Appendix 3
Test cards used in visual working memory test (See section 2.6). Real size 19 x 8 cm.
38

39. Appendix 4
Data tables, for each condition, of the time spent in the test quadrant as a percentage
of time spent in all 4 quadrants, on each trial and for all subjects. IR = incorrect
response - these trials were omitted from data analyses. ND = no data was recorded
from the whole trial. NQ = the whole time was spent in the exclusion box.
39

40. 40

41. 41

42. Appendix 5
Data table of duration of fixations in tested quadrant as a percentage of total duration
in all 4 quadrants, for each subject, averaged for each condition.
42

43. Appendix 6
Test for normality of the data: average time recorded in the correct quadrant as a
percentage of time recorded in all 4 quadrants, for all subjects over all conditions (see
Appendix 5 for data). The Q-Q plot below is a plot of the quantiles of the data's
distribution against the quantiles of the normal distribution. If the data is normally
distributed, the points cluster around a straight line.
Normal Q-Q plot of percentage of fixation duration in correct quadrant compared to
other three quadrants
43

44. Appendix 7
Number of fixations in tested quadrant and the other 3 non-test quadrants, for each
subject, averaged across each condition.
44

45. Appendix 8
Test for normality of the data: average number of fixations per quadrant (see
Appendix 7 for data). The Q-Q plot below is a plot of the quantiles of the data's
distribution against the quantiles of the normal distribution. If the data is normally
distributed, the points cluster around a straight line.
Normal Q-Q plot of average number of fixations per quadrant
45

46. Appendix 9
Data table showing the number of fixations made in the tested quadrant, as a
percentage of number of fixations made in all quadrants, averaged for each subject,
for each condition:
46

47. Appendix 10
Data table of duration of fixations in test quadrant, as a percentage of total duration in
all quadrants, averaged for each subject in each condition. Subjects who conducted
'what' and 'where' conditions first are compared with subjects who conducted
'imagine' conditions first.
47

48. 5. References
Bohbot, V.D., Kalina, M., Stepankova, K., Spackova, N., Petrides, M. & Nadel, L.
(1998) Spatial memory deficits in patients with lesions to the right hippocampus
and to the right parahippocampal cortex. Neuropsychologia, 36, 1217-1238e
Brandt, S.A., Stark, L.W. (1997) Spontaneous eye movements during visual
imagery reflect the content of the visual scene. Journal of Cognitive Neuroscience,
9, 27-38
Derrington, A.M. & Lennie, P. (1984) Spatial and temporal contrast sensitivities
of neurones in lateral geniculate nucleus of Macaque. Journal of Physiology, 357,
219-240
Farah, M.J., Hammond, K.M., Levine, D.N. & Calvanio, R. (1988) Visual and
spatial mental imagery: Dissociable systems of representation. Cognitive
Psychology, 20, 439-462
Hale, S.M. & Simpson, H.M. (1970) Effects of eye movements on the rate of
discovery and the vividness of visual images. Perception and Psychophysics, 9,
242-245
Hall, D.C. (1974) Eye fixation and spatial organization in imagery. Bulletin of the
Psychonomic Society, 3, 335-337
Haxby, J.V., Grady, C.L., Horwitz, B., Ungerleider, L.G., Mishkin, M., Carson,
R.E., Herscovitch, P., Schapiro, M.B. & Rapoport, S.I. (1991) Dissociation of
object and spatial visual processing pathways in human extrastriate cortex.
Proceedings of the National Academy of Science, USA, 88, 1621-1625
Isseroff, A., Rosvold, H.E., Galkin, T., Goldman-Rakic, P. (1982) Spatial memory
impairments following damage to the mediodorsal nucleus of the thalamus in
rhesus monkeys. Brain Research, 232, 97-113
Janssen, W.H. & Nodine, C.F. (1974) Eye movements and visual imagery in free
recall. Acta Psychologia, 38, 267-276.
Laeng, B. & Teodorescu, D.S. (2002) Eye scanpaths during visual imagery
reenact those of perception of the same visual scene. Cognitive Science, 26, 207-
231.
Levine, D.N., Warach, J. & Farah, M.J. Two visual systems in mental imagery:
dissociation of ‘what’ and ‘where’ in imagery disorders due to bilateral posterior
cerebral lesions. Neurology, 35, 1010-1018
Livingstone, M.S. & Hubel, D.H. (1987) Psychophysical evidence for separate
channels for the perception of form, color, movement and depth. The Journal of
Neuroscience, 7(11), 3416-3468
Marks, D.F. (1973) Visual imagery differences and eye movements in the recall of
pictures. Perception and Psychophysics, 14(3), 407-412
Mecklinger, A. & Pfeifer, E. (1996) Event-related potentials reveal topographical
and temporal distinct neuronal activation patterns for spatial and object working
memory. Cognitive Brain Research, 4(3), 211-224
48

49. Mishkin, M. & Manning, F.J. (1978) Non-spatial memory after selective
prefrontal lesions in monkeys. Brain Research, 143, 313-323
Norton, D. & Stark, L. (1971a) Scanpaths in saccadic eye movements while
viewing and recognizing patterns. Vision Research, 11, 929-942.
Norton, D. & Stark, L. (1971b) Scanpaths in eye movements during pattern
perception. Science, 171, 308-311
Ruchin, D.S., Johnson, R., Grafman, J., Canoune, H. & Ritter, W. (1997) Multiple
visuospatial working memory buffers: Evidence from spatio-temporal patterns of
brain activity. Neuropsychologia, 35(2), 195-209.
Smith, E.E. & Jonides, J. (1997) Working memory: A view from neuroimaging.
Cognitive Psychology, 33, 5-42
Tresch, M.C., Sinnamon, H.M. & Seamon, J.G. (1993) Double dissociation of
spatial and object visual memory: Evidence from selective interference in intact
human subjects. Neuropsychologia, 31(3), 211-219
Van Essen, D.C., Anderson, C.H. & Felleman, D.J. (1992) Information processing
in the primate visual system: An integrated systems perspective. Science, 255,
419-423.
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