1. N0324223
Louise A. Brown
April 2013
The effect of Dynamic Visual
Noise in a study of working
memory using the Visual Patterns
Test in younger and older adults
BSc Psychology with Sports Sciences
Psychology Division
Schoolof Social Sciences
Nottingham Trent University
Jason Hobman
2. Abstract___________________________________________
The purpose of this study was to investigate the effect of Dynamic Visual Noise on younger
and older adults on working memory, as measured by a Visual Patterns Test. The aim of the
study was to build on previous research on effects of DVN on the working memory.
Twenty four participants (12 younger:6 male,6 female: 12 older:5 male,7 female) were
administered a Test of Premorbid Functioning exam an a indictor of IQ, additionally the
older adults also performed a Mini-Mental State Exam to screen for unhealthy cognitive
decline. All participants were assessed using a modified version of the VPT to measure visual
working memory capacity (see Brown et al, 2006; Della Sala et al, 1997). This study
establishes that there was a main effect of age on visual working memory performance. The
results also show that there was no main effect for task type. There was no significant
interaction between age group and task type although there was a trend towards the
interaction between the two variables but that this was not statistically reliable.
In summary this study appears to support the previous research suggesting that working
memory capacity significantly declines as we age. The strategy most participants used in the
VPT was a visual strategy, previous research and this study alike show that older participants
do worse than younger adults when using this strategy. Anecdotal evidence suggests that a
few participants attempted to use a verbal coding strategy when the opportunity arose,
though this was not frequent. The DVN did not have a significant effect on the participants
performing the Visual Patterns Test, though with a larger sample size this could indeed have
been the case. In addition to this the DVN may have had a greater effect on the younger
adults, compared to the older adults who showed minor change between conditions. This
could have been due to the strategy chosen to employ, such as a spatial and/or verbal
strategy which is less sensitive to DVN, opposed to a visual strategy which the young might
have used.
3. Introduction________________________________________
Introduction to working memory
Atkinson’s & Shiffrin’s (1968) multi-store model was extremely successful in terms of the
amount of research it generated. Nonetheless there were a series of problems regarding the
characteristics of short-term memory. Baddeley & Hitch (1974) argue that the structure of
short-term memory is too simplistic within the multi-store model. They rejected the idea of
short-term memory being an unitary store, holding limited amounts of information for short
periods of time with minimal processing. Baddeley & Hitch’s model as seen below in figure 1
(1974) proposes the working memory model, which states that instead of information going
into a single store, the store is divided and consists of separate subsystems; where different
variations of information are processed in these diverse systems.
Figure 1. Working memory model. Baddeley & Hitch (1974)
The Phonological loop and Visuo-spatial sketchpad are the two specialised subsystems
regarded as the slave systems, their functions within the model are information processing
and manipulation, which are relative to their title. The phonological loop is assumed to be
responsible for the manipulation of speech based information, in effect an inner ear,
whereas the visuo-spatial sketchpad is assumed to be responsible for manipulated visual
images, an inner eye. The model describes these components as relatively independent
4. from one another, with each individual component having a limited capacity. Working
memory also includes a central executive which controls and co-ordinates the ‘slave systems’
(Baddeley & Hitch, 2000), connecting them to the long-term memory. The central executive
is the most important component of the model; the role is to elect which information needs
to be attended to. It also decides which subdivisions of the working memory to send the
stimulus, to be dealt with, giving priority to particular activities.
Engle, Kane & Tuholski (1999) and Cowan (1995) define the difference between the working
memory and short-term memory as the strong controlled component, that the working
memory has but the short-term memory does not. Kane, Bleckley, Cowan & Engle (2001)
support this knowledge with findings that individuals with high working memory span also
obtained a greater attention control in comparison to those with lower spans. However,
Miyake , Friedman, Rettinger, Shah & Hegarty (2001) reject the indication of distinguishable
short-term memory and working memory, reporting little distinction between short-term
and working memory in the visuo-spatial domain.
The central executive is the most versatile component of the working memory. However,
despite its importance within the working memory model, we know considerably less about
this component than the two subsystems it controls. Baddeley (2000) suggests that the
central executive acts more like a system which controls attention processes rather than as
a memory store. This is unlike the phonological loop and visuo-spatial sketchpad, which are
specialized storage systems and processing components. The original model of working
memory comprising of 3 components became less reliable when it could not account for
various subsystems combining, in particular how systems could interact with long-term
memory (LTM). Therefore Baddeley (2000) proposed a fourth component, the episodic
buffer; a temporary store of limited capacity, capable of merging a variety of storage
magnitudes. This consequently allowed the episodic buffer to collate information from
perception, LTM and visuo-spatial and verbal subsystems.
Visuo-spatial Memory
The multi-component of working memory contains the visuo-spatial and verbal storage
which is understood to be controlled and manipulated by modality-specific subsystems.
Brown, Brockmole, Gow & Deary (2012) suggests there is a degree of sensitivity regarding
decay and interference in the visual component, whereas the spatial mechanism is
suggested to refresh the contents of the store in order to retain spatio-sequential
information. The majority of previous research into working memory is mainly directed
towards verbal or domain-general components, therefore significantly less research has
been specifically related towards the visuo-spatial component(Brown et al, 2012).Evidence
that does exist in this area suggests that visuo-spatial working memory may in fact be more
age sensitive than verbal memory. This could be due to the decline in the ability of the
visuo-spatial sketchpad, which stores an image for several seconds after the stimulus is
removed but is limited by the visual complexity of the representations (Logie, 2011)
5. Chequered black and white patterns are regularly used to investigate visuo-spatial memory,
these abstract patterns (Phillips & Christie, 1977) have been found to show a significant
decline in memory, representing a particular sensitivity to age (Brown et al, 2012).
Chequered black and white patterns are the images used in the Visual Patterns Test (VPT:
Della Sala, Gray, Baddeley & Wilson, 1997), this is a test that aimed to restrict the availability
of verbal coding. They intended on doing this through the black and white matrix patterns
that would increase in size as the trails progressed. These patterns were displayed for 3
seconds and then recalled either immediately, or after a short delay of 10 seconds. The VPT
has been described by Cornoldi and Vecchi (2003) as an appropriate test for measuring
visuo-spatial STM.
Paivio’s (1971) dual-coding model theory states that non-verbal stimuli are processed by a
coding system that employs both imagery and verbal resources. Importantly, the theory
holds that images, both concrete and abstract, can be translated into words. If the image is
unfamiliar or abstract, as matrix patterns are said to be, then the availability of verbal
coding should indeed be lower. Similar to this block designs are frequently associated with
central executive function (Lezak et al., 2004; Wallesch, Curio, Galazky, Jost, & Synowitz,
2001) which assesses the right strategy and planning skills in the specific context of a visuo-
spatial construction task.
The Visual Pattern Test has been used to measure visual short-term memory performance
since its development by Phillips and colleagues in the 1970’s. (Phillips & Baddeley, 1971).
However they have not received complete support in their ability to specifically test visuo-
spatial memory. Avons & Phillips (1987) noted, matrix patterns may be comprised of both
unfamiliar and familiar shapes. Given that a pattern would be classified as abstract when
the overall configuration is taken into account, it is possible that the random, familiar
shapes present within some of the patterns could be deemed as concrete and therefore
more amenable to verbal coding (Brown, Forbes & McConnell, 2006). This is supported by
Wilson, Scott & Power (1987) who used similar stimuli, which varied in size to access visual
STM span in children as well as adults. Relating directly to such limitations as random
abstract images or verbal coding availability in the existing VPT, Brown, Forbes & McConnell
(2006) introduced a new version of the test, a lower coded version, therefore becoming
harder for the subject to verbally code within the experiment.
Della Sala & Colleagues (1997) implemented the VPT to show that visual interference
disrupts visual working memory to a greater extent than spatial interference tasks. The
argument is whether visual information has obligatory access to visuo-spatial working
memory, similar to the effects of irrelevant speech on the phonological loop. Evidence
indicates that mere exposure to irrelevant perceptual information can interfere with visuo-
spatial working memory (Della Salla, Gray, Baddeley, Allamano, & Wilson, 1997). Logie (1995)
suggested there is not an immediate link from the store of visuo-spatial working memory
and the sensory system, alternately perceptual information is first interpreted and
6. organised by the long-term memory store then transferred to the visuo-spatial working
memory. Logie (1995) proposes interpolated manual tasks interfere with the working
memory, directly manipulate and disrupt the operation of the ‘inner scribe’; this is a system
dependent on the movement based processing that serves both to store spatial sequences
and to provide a rehearsal function for other visual information held in a passive ‘visual
cache’, refer to figure 2 below . According to Logie (1995) visual images are then
manipulated by the central executive system that interconnects the ‘slave systems’ as well
as the LTM to create conscious imagery. Dent (2010) therefore suggests that such effects as
irrelevant movements are equivalent to the effects of articulatory suppression in the
auditory-verbal domain, specially targeting a spatial rehearsal mechanism.
Figure 2. Working Memory as Consisting of Multiple Components. Logie (1995)
The effect of interferenceon memory
In order to directly influence visuo-spatial memory Quinn & McConnell (1996) devised a
visual interference task, devoid of any higher order semantic content, Dynamic Visual Noise
(DVN), as seen in figure 3. Initially Quinn & McConnell (1996) proposed that the mechanism
of DVN was to give access to and disrupt a passive visual store in working memory. The
disruption of memory by DVN was taken to support an equivalent organisation of verbal and
visuo-spatial working memory, and to provide support for the idea that imagery is
dependent on memory mechanisms. This view has been challenged by Andrade, Kemps,
Werneiers, May & Szmalec (2002), they performed a peg-word mnemonic study including
7. the effects of DVN as a form of disruption to visual memory. This study did not find any
effect on visual memory in relation to the DVN interference. Avons & Sestieri (2005) found
no effect of DVN on memory in an investigation in relation to matrix patterns, even if the
interference was presented throughout the cell-by-cell presentation of the matrices.
Therefore these previous studies show evidence against Quinn & McConnell’s (1996) initial
proposal that DVN could gain access and disrupt the passive visual store in working memory.
Figure 3. An example of DVN interference. Quinn, J. G., & McConnell, J. (1996).
Andrade et al (2002) suggested that the null results were produced because DVN does not
affect memory at all, that it interferes with tasks requiring the process of visual imagery in
the peg-word study. The peg-word system is a technique of remembering list of words, it
applies a system of pre-memorising a list of words that are easy to associate with the
numbers they represent. (e.g. 1, Gun or 2, Zoo.) those objects become the ‘pegs’ of the
strategy. Implementing divisions between visual imagery and memory has distinct
implications for models of visuo-spatial working memory, highlighting the need to find the
true effects of DVN for theoretical progress. Dean, Dewhurst & Whittaker (2008) suggests
that the mechanism of DVN is to actively change and distort the representation of the
stimulus in memory. One hypothesis is that DVN may distort the distribution of image
elements in a practical representation or ‘visual buffer’ (Kosslyn, 1994), disrupting the
remembered form.
Dent (2010) suggests that memory disruption caused by DVN supports an equivalent
organisation of verbal and visuo-spatial working memory, in addition to striving to support
the indication that imagery is dependent on memory mechanisms. McConnell & Quinn
(2004) demonstrated effects of DVN on a memory task relating to precise size of circles.
8. Dean et al. (2008) found a similar effect on a task involving precise texture, as well as
Darling, Della Sala & Logie (2009) who recorded an effect of DVN on a letter font task. Dent
(2010) notes that all the authors demonstrating an effect of DVN agree that the
requirement to obtain visual information in order to detect subtle differences in the stimuli
is potentially an important factor. Dent (2010) proposes a possible explanation of the DVN
effects are discrete, and only adequate to affect representations of fine-grain information,
additionally many forms of detail may be affected regardless of domain. In his own
experiment Dent (2010) found effects of DVN were specific to visual properties, even spatial
stimuli had to be retained in a very specific and detailed way.
Age effect on visual working memory
Interference from internal irrelevant representation activates cognitive control mechanisms
in subsequent stages of processing such as working memory. When irrelevant information is
accepted into the working memory and maintained, it increases competition for the limited
resources or capacity within the working memory system (Conway & Engle, 2007). This
competition is the primary cause of forgetting information (Hasher & Zacks, 1988).
Attributes of fluid intelligence such as speed of processing, working memory, long-term
memory and reasoning have been shown to decline as a person ages (Schaie & Willis, 2010).
Previous literature on cognitive ageing signifies findings that even very healthy adults
experience some deterioration in fluid abilities with advancing age, although the age at
which deflection occurs is variable (Schaie, 2005). Evidence indicates that the frontal cortex
of the brain is most susceptible to age-related shrinkage in volume (Raz, 2005) followed by
medial temporal areas, particularly the hippocampus (Raz & Rodrigue, 2006). The occipital
regions are largely protected from volumetric shrinkage with age. This deterioration in
important neural sections is directly related to working memory decline. According to the
Prefrontal Cortex Basal Ganglia Working Memory (PCBWM) the prefrontal cortex has long
been thought to subscribe both with the working memory and the executive function
(O’Reilly & Frank, 2006).
The Scaffolding theory of ageing and cognition (Park & Reuter-Lorenz, 2009) provides an
integrated view of the changes that occur in the neuro-cognitive system with age. The
model states that the neural structures and functions deteriorate as one ages. Decline in
neural structure are represented as ‘neural challenges’ and these are verified by volumetric
shrinkage, white matter changes, cortical thinning, dopamine depletion and amyloid
deposition that increases with age. Deterioration in neural functions occurs in direct
response to the ageing brain and is marked by neural dedifferentiation; a process by which
structures or behaviours that were specialised for a specific function lose their specialisation
and become simplified or generalised, decreased hippocampal recruitment, and poor
structural connectivity and disruption of the default network.
9. Salthouse (1991) proposed that age related changes in ‘fluid’ cognition, such as memory,
reasoning and spatial abilities are due to a decrease in the speed with which cognitive
operations may be carried out. Supporting evidence includes moderate to high proportions
of shared variance between measures of processing speed and a range of cognitive task`s
including memory and attention of the effects of age when processing speed is controlled
(e.g., Finkel, Reynolds, McArdle, & Pederson, 2007). In addition to these theories Hasher,
Lustig & Zacks (2007) propose the Inhibition Deficit theory, which states that as ageing
progresses the inhibitory process is weakened. These processes are accountable for
controlling the stimulus that enters and exits the working memory. Abrams & Farrell state
that the main problem in the ineffective inhibitory processes in older adults is that
irrelevant information is allowed access to the working memory, therefore creating
interference. Inhibition deficits have been used to describe deterioration in the perception
and comprehension in older adults, such as greater difficulty understanding speech when
back ground noise is present (Pichord- Fuller, Scheider, & Daneman, 1995; Tun, O’kane, &
Wingfield, 2002) or when there is completion evident words of similar sounding (sommers,
1996; Sommers & Danielson, 1999).
Jenson (2006) suggests reputed changes in brain structure are responsible for declining
cognitive ability during adulthood and old age may be a mirror image of structural changes
responsible for improving cognitive development during childhood. Previous research in
verbal memory indicates that the rehearsal strategy is more regularly used by older children
in relation to younger (Flavell, Beach & Chinsky, 1966). Only small improvements in
performance can be made in relation to age when the strategy of mental rehearsal is
implemented on more dynamic information. Though more specifically to visual working
memory, it has been demonstrated that short-term and long-term visual memory can be
distinguished in children as young as eight. Wilson, Scott & Power (1987) found that whilst
children of the age of 5 have only a limited ability to remember patterns, older children and
adults have a surprisingly large visual memory span. Wilson et al (1987) also state there is
no evidence to suggest that older adults are able to reduce the capacity of the lost
information.
Salthouse (1996) proposed that processing speed declines on average across adult years
from age 20 to 80, the mean trend being linear. Salthouse (1996) developed a theory that
substantially attributes age-related, reduced effectiveness of higher order cognitive
functioning to general slowing in processing speed, which imposes a fundamental constraint
on the efficiency of working memory. Salthouse’s theory resembles what Fry & Hale (1996)
described as a ‘cognitive developmental cascade’, that is, a sequence of processing stages
within which the effectiveness of processing at the first stage has a flow-on effect for the
next stage, which influences the next and so on. Fry & Hale found that individual differences
in speed influenced memory, and when both age and speed were controlled, working
memory influenced fluid performance.
10. The cascade model therefore provided a good account for average mental age changes and
for ability differences within age bands, in processing speed, working memory and
reasoning. The maturing brain structures improve processing speed, simultaneous with
development in working memory. Such structures reach their peak capacities when
approaching early adulthood, deteriorating progressively across adult ageing. The majority
of prospective memory (performing an intended action at an appropriate point in the future
without being prompted) literature empathises age-related changes (Maylor, 2008), results
ranged from large age deficits to large age benefits (Maylor, 1993, 1996; McDaniel &
Einstein, & Rendell, 2008; Uttl, 2005, 2008). Previous research represents a linear decline
across adult life span, apparent from early adulthood (Li, Lindenberger, Hommel,
Aschersleben, Prinz & Blates, 2004; Salthouse & Babcock, 1991). Verhaeghen, Marcoen &
Goossens (1993) found decline in prospective memory was at least as great as that in
working memory span, relating to moderate age effects. Gregory, Nettelbeck, Howard &
Wilson (2009), therefore concluded that relations between age, processing speed, working
memory and reasoning ability are more complex among elderly adults than among children,
perhaps because age-related changes other than slower speed might directly impact
working memory.
The present Study
The purpose of this study is to investigate the relationship between the effect of the
Dynamic Visual Noise on younger and older adults, as measured by a visual matrix task
(modified VPT; Brown et al., 2006; Della Sala et al., 1997, 1999). There is a need to find the
effects of DVN on the working memory capacity as we age. This study aims to enhance
previous research into this area by identifying the effects of DVN on the working memory
relating to work from Brown et al (2012). It is hypotheses that as we age the working
memory capacity decreases, therefore the older adults will be worse than the younger on
the Visual Patterns Test. Based on the research of the Inhibition Deficit Theory it can be
predicted that within this experiment the older adults will show a greater deficit than the
younger adults. Therefore the older adults will be less affected by the DVN than that of the
younger due to the disadvantage of natural ageing.
11. Method___________________________________________
Design
The study is an experimental mixed 2 x 2 design. The first of the two independent variables
was ‘Age Group’, specify two conditions, younger and older. The second variable was
‘Interference’, whether there was or was not Dynamic Visual Noise shown in the trials. The
dependent variable was the visual working memory capacity which was measured using the
Visual Patterns Test (VPT, see Brown et al, 2006; Della Sala et al, 1997). A counterbalance
system was implemented as a method of controlling for the effects of an extraneous
variable by ensuring that its effects are equal in all treatment conditions throughout the
trials to prevent such problems as order effects , though more specifically to counter order
effects.
Participants
Twenty four participants were applied to two groups, depending on their age either younger
adults or older. The mean age of the younger adults was 20.91 (SD=0.90, Range = 19-22),
while the mean number of years in education was 17.08 (SD= 0.57, Range = 16-18). There
were 6 males and 6 females in the younger adults group. The older adults mean age was
74.58 (SD = 7.08, Range = 65-87), whilst their mean number of years in education was 13.33
(SD = 1.92, Range = 12-17) there were 5 males and 7 females in the older adult group. The
12 participants of the older adults group were deemed cognitively healthy, as determined
by the Mini-Mental State Examination (MMSE), which screened for dementia (Folstein,
Folstein & McHugh, 1975). The mean MMSE score was 27.75 (SD= 1.60, Range = 25-30). All
participants performed the Test of Premorbid Functioning (word-reading IQ estimate,
available within the Division; Pearson, 2009) as an assessment of IQ. The mean score for the
younger adults was 95 (SD = 7.69, Range = 82-108), whereas the older adults mean was
112.16 (SD = 10.35, Range = 99-127). Brown & Brockmole (2010) found evidence that
implies it is normal to observe greater predicted IQ in older adults opposed to younger. This
is because younger adults have not yet reached the higher level of verbal intelligence that
the older adults have, which tends to develop over the ageing period. Interesting this is the
opposite direction of the reported effect of ageing.
12. Materials
Participants were administered a modified version of the VPT (see Brown et al, 2006; Della
Sala et al, 1997). This involved presenting participants with a series of black and white
chequered patterns that increase in size and therefore complexity, the rate of change within
the DVN was 1920 e.g. 1920 dots changed per second. This version of the VPT which is
shown below in figure 4 has greater limiting availability for verbal coding than previous
versions, therefore this version should test the visual working memory with superior specific
access. The test involves a range of levels regarding difficulty, the levels range form 2-15, in
this experiment the older adults began the VPT at level 2 as opposed to level 4 where the
young adults will start. This is based on their expected lower performance and to avoid
floored effects. If the older adults capacity is not much greater than level 4 then the
sensitivity of the task is reduced.
Figure 4. Example of a pattern from the Visual Patterns Test. Brown et al. (2012)
Procedure
First the participants were administered the IQ estimate, which was the Test of Premorbid
Functioning (ToPF). Next all older adults performed the Mini-mental State Exam to screen
for unhealthy cognitive decline. All participants were required to recall each pattern in turn
by placing ‘X’ in the cells of blank paper templates that they remembered to be black. Each
trial consisted of a fixation cross (2s), the presentation of the pattern (3s), a delay
(maintenance) period (10s), and finally the word ‘recall’ displayed on the computer screen,
which promoted participants to respond. If the participants were executing the controlled
conditional then the 10 second period would involve a blank white screen, alternatively if
the condition was that of the experimental then the DVN interference would be present.
There were three practise trials followed by three trials at each of the levels of complexity 2
through to 15, or as far as the participants could progress. Once the participants got all
three patterns wrong in a level the test would end. Once the trial had come to an end the
capacity was drawn from administering the mean size of the last 3 correctly recalled
patterns.
13. Results____________________________________________
Figure 5 below represents the overall performance of both age groups within both variable
tasks. You will see that the younger adults outperformed the older adults on both tasks
significantly, therefore there is a significant different between the age group variable. The
younger adult`s overall performance declines from the control task to the experimental,
suggesting a positive affect from the interference, whereas the older adult`s performance
slightly improved, therefore showing no affect from the interference.
Age group indicated a significant main effect (F(1,22) = 35.88 p< 0.001). Main effect for task
type was not significant (F(1,22) = 1.78 p = 0.19). A 2 (Age group; younger or older adults) x2
(Task type: DVN or no DVN) between-subjects ANOVA showed no significant interaction
F(1,22) = 3.26, p = .085 though there is a trend towards interaction, as you can see in figure
5 below.
The results of the paired t-test analysis shows a significant effect of DVN on younger adults,
t(11) = 2.341, p = .008. No significant effect was evident in the analysis for the older adults,
t(11) = -.318, p = .757
Figure 5. A graph to show the interaction between age group and task types.
2
3
4
5
6
7
8
9
10
11
Control Interference
ScoreontheVPT
Task Type
A graph to show the interaction between age
group and task types.
Younger Adults
Older Adults
14. Discussion_________________________________________
The purpose of this study was to investigate the effects of the Dynamic Visual Noise on
younger and older adults, as measured by a visual matrix task (modified VPT; Brown et al.,
2006; Della Sala et al., 1997, 1999). The results of this study demonstrate the importance of
understanding the effects DVN can have on working memory capacity. Overall this study
established that there was a significant main effect of age on visual working memory
capacity. The results also show that there was no main effect for task type. There was not a
significant interaction between age group and task type variables, though if you refer to
figure 5 the presence of a trend towards an interaction can be seen. Older adults performed
significantly worse than the young adults in both tasks of the VPT, additionally the older
adult’s VPT results were marginally better in the experimental task whereas the younger
adults got worse, therefore a confident conclusion can be made that the inhibition deficit
theory does not account for the effects seen within the results, the older adults were not
more susceptible to the effects of visual interference. The results could provide evidence for
the scaffolding theory, this was due to the intervention used by the older adults of less
specific processing on resources, therefore becoming less vulnerable to the specific forms of
interference. Though only with a larger sample size would it be possible to significantly
suggest this. If the older adults were to use a strategy other than the ideal, i.e. mentally
rehearsing the image, then this may be evidence for the poor overall performance of the
older adults.
Age group differencesin performance
The older adults performed significantly worse in both task variables and showed a minor
mean difference between the two tasks. This might be due to the choice of strategy that the
older participants applied. Older adults may have been unable to obtain the correct strategy
to perform the task. Cansino, Guzzon, Martinelli, Barollo, & Casco (2011) found that in
previous visual memory tasks of working memory participants would try to implement
numerical strategies in order to remember sequences. A few older participants reported
using a strategy of this nature within this experiment, trying to count the number of black
squares on each line of the patterns. Most subjects stated using a visual strategy; this
included both younger and older adults. Though prior studies show that older adults
perform worse than younger adults on visual tasks (Madden, Spaniol, Bucur, & Whiting,
2007; Madden et al., 2002), creating a disadvantage to the older adults. Pickering,
Gathercole, Hall & Lloyd (2001) investigated participants using a verbal coding strategy on
matrix patterns tests; they found that articulatory suppression did not reduce task
performance implying that participants do rely on a visual coding strategy, more specifically
15. a visual-spatial approach. Though Brown et al. (2006) suggests it is important to consider
that the availability of verbal coding may not be the same when the time constraints of the
standard procedure are taken into account. Conflicting with Pickering et al.(2001), Brown et
al. (2006) provides evidence that participants do employ a verbal coding strategy where
available in which aids task performance, although within this investigation the version of
the VPT used limits the verbal coding strategy.
Chequered matrix patterns were developed to restrict the opportunity of verbal coding,
though Avons & Phillips (1987) found that matrix patterns may be comprised of familiar and
unfamiliar shapes. Given that a pattern would be classified as abstract when the overall
classification is taken and administered, it seems that the findings of Brown, Forbes, &
McConnell (2006) are related to the findings of this study. It is possible the random, familiar
shapes present within some patterns could be deemed as concrete and therefore become
more assessable to verbally code. Within this study some participants referred to using a
strategy similar to this, where they would try and locate objects within the abstract patterns
to aid recall. This supports Paivio’s (1971) dual-coding model which states that both
concrete and abstract images can be translated into words. Paivio (1991) also provided
evidence that participants gain advanced recall for pictures of concrete objects. This would
suggest that older adults may have attempted to implement a verbal strategy, though the
efficacy of this technique reduces rapidly as the patterns increase in size as the levels
progress.
Effects of interference
Della Sala et al. (1997) states that even mere exposure to irrelevant information can
interfere with visuo-spatial working memory. It is possible that older adults are incapable of
restricting the internal representations of irrelevant stimuli and preserving only useful
information in working memory (Casino et al., 2011). Therefore occurrence of relevant and
irrelevant memories increases competition and confusion. This suggests that a post-stimulus
cue might provide little benefit to older adults because they are unable to selectively attend
to memories of relevant stimulus. Older adults are shown to struggle to distinguish between
relevant and irrelevant memories, affecting the restraint as well as the selection of
memories. In previous research irrelevant information caused a problem for older adults as
the familiar stimuli created representations automatically, creating an influx of irrelevant
information that the participants has to supress or regulate (Hasher & Zacks, 1988). In this
study the older adults were not affected by the DVN interference, placing more emphasis
that they were not using the correct visual memory strategy. The inhibition of distracting
memories and selection of relevant memories are related to internal interference control
(Anderson & Neely, 1996: Bjork, 1989). If the participants happened to accept the irrelevant
information into the store then the limited resources within the working memory become
under threat of competition (Conway & Engle, 2007). Although this appears not to be the
case with the older adults in this investigation.
16. DVN may have a greater effect on the younger adults than it did on the older, even though
only a small effect was recorded, this suggests that DVN did have an effect on memory
regarding matrix patterns. Avons & Sestieri’s (2005) found no effect of DVN on matrix
patterns, the results of the paired t-test in this study displays no effect of DVN on the older
participants though there was a significant effect on the younger adults. Thus these results
support the idea that DVN specifically affects visual working memory, but that is only the
case for the younger adults. If the older adults were using a spatial strategy to scan and
rehearse the patterns then they would gain an advantage over the younger adults, as DVN
affects visual but not spatial memory (Darling, Della Sala & Logie (2009). Location could
avoid the DVN due to the high reliance on coding in motor planning and eye movement
(Quinn, 2008). Therefore Dent (2010) would suggest location is more flexible, resulting in
the system taking advantage of multiple representational codes. The younger adults may
have become affected by the interference of the DVN due to the competition between the
noise array and the matrix pattern (Dent, 2010) The older adults did not improve; they
remained around the same mean score, which could have been due to the incorrect
strategy executed. These results imply that younger adults implemented a visual strategy
which is highly sensitive to the effects of DVN, compared to the spatial and/or verbal
strategies which potentially the older adults could have implemented that is less susceptible
to the effects of DVN. These findings support the work of Logie (2011), suggesting a
distinction between visual and spatial working memory. This evidence could lead us to
believe particular aspects of spatial working memory are not susceptible to DVN, and not
sufficient in storage of colour and form information (Dent, 2011).
Visuo-spatial memory
Logie (1995) suggests there is no direct connection between the contents of visuo-spatial
working memory and sensory systems. Alternately perceptual stimulus is interpreted and
categorised by a long-term memory system first, then directed to visuo-spatial working
memory. This therefore suggested that even though a revised version of the VPT was
created it still cannot completely restrict verbal coding within the matrix abstract images.
Logie (1995) purpose’s that visuo-spatial working memory is divided into two components;
‘visual cache’ which stores the basic visual information and the ‘inner scribe’ which is an
active spatial rehearsal mechanism that refreshes the information. Visual imagery is then
hosted by the central executive system that implements the ‘slave systems’ along with the
long-term memory to generate conscious imagery. In addition to this Pearson (2001) &
Quinn (2008) both explicitly purpose a visual memory store surplus to the visual cache and
separate from the central executive, analogous to the visual buffer proposed by Kosslyn
(1994).
Kosslyn (1994) suggests the visual buffer is directly attached with visual perception,
manipulating memory and hosting visual images. Quinn (2008) suggests the visual buffer is
employed as a memory component when the item is held in consciousness. Therefore the
17. visual buffer is likely to be used when the task of avoiding the influence of the long-term
knowledge base, when attempting to obtain specific details of a recent sensory event.
According to this DVN may be able to gain contact and disturb information in the visual
buffer. This idea then proposes that the DVN will only interfere with the stimulus when
information is deemed important, and less so with less important content. Baddeley (2000)
purposes the episodic buffer, providing a storage capacity that processes specific details by
combining information from the phonological loop and the visuo-spatial sketchpad. The key
feature of the episodic buffer is that the information is coded in a domain general multi-
modal form of representation. DVN would seem more suited to disruption of information in
a system coding representations in a visual sensory code through the visual cache and/or
visual buffer.
Similar to the results of this study Brown et al. (2012) reported that visual working memory
ability is related to changes that occur over the ageing process, and suggests it most likely
reflects the fluid nature of the task. Brown at al. (2012) also reported that processing speed
exhibited the greatest correlation with visual working memory, suggesting that speed of
encoding and/or rate of rehearsal are possible candidates for the source of the marked age-
related deficit in visual work memory. Salthouse (1991) would purpose the relationship
between cognition change and speed of processing reported within these studies could be
explained through these two mechanisms. Firstly the limited time mechanism which
suggests that if elaboration and rehearsal processes slow then the participants would run
out of time to process the information in the tasks, which exerts greater effect as the
difficulty increases. Secondly the Simultaneity model, explaining that the slower processing
of the older adults reduces information required by working memory which then in turn
affects higher order functions such as elaboration and integration, therefore leading to
poorer recall. Poorer recall was accounted for in this investigation when results of previous
matrix patterns were no longer available to the participant by the time subsequent
operations were complete. Participants could therefore employ this strategy of rehearsing
individual sections of the pattern, in turn. Though participants with slower processing speed
may find they run out of time to look at the whole pattern, therefore only recalling certain
sections of the pattern, if any at all.
The developmental cascade model describes cognitive development from birth up until the
age of around 20. Nettelbeck & Burns (2010) believed that after around 20 years of age, a
negative development process begins to implement and may prevail until middle age. This is
supported by Li et al (2004) who found a linear decline across the adult lifespan, which
begins at early adulthood. Henry, MacLeod, Phillips & Crawford (2004) found young adults
perform better than older adults consistently on both time and event based tasks, even
considering the latter provides greater environmental support. They suggest that beyond
the age of 55, the process of ageing is combined with age-related changes independent
from processing speed. In this study, all the older adults were over the age of 55 and all the
younger adults were close to the age of 20. The difference between the two task groups
18. were not consistent with the proposal put forward by Jenson (2006), although Jenson was
along the right line of thought regarding the process of progression is childhood up to
around the age of 20, it is believed that there is a distinct difference with the negative
development after the age of 20. This idea was that childhood development cascade model
and the model that describes cognitive change during old age are mirror images of one
another. The cascade model offers a sound explanation for the course of improving
performance during childhood, and declining performance during adulthood, though the
model that applies to the deteriorating performance during old age is more complex. Slower
processing is causatively linked to cognitive decline in old age, moderating the relationship
between age and working memory (Nettelbeck & Burns, 2010).
Biology of the deteriorating brain
From a biological aspect, a processing speed deficit could be interlinked with white matter
integrity, which is suggested to be central for connectivity between the distributed cortical
regions that feature cognition. Deary, Bastin, Pattie, Clayden, Whalley, Starr (2006) found
that white matter integrity is related to efficiency of information processing and cognitive
ability in older age. Waiter, Fox, Murray, Starr, Staff, Bourne (2008) found that positive
cognitive ageing is associated to the organisation of neural networks sub-serving simple
information processing, through functional Magnetic Resonance Imagery (fMRI). Relating to
this Nee & Jonides (2008, 2009) performed neuroimageing studies in younger adults, finding
evidence suggesting that both the selection of precepts and the selection of memories are
reliant on several common brain regions in the presence of competing distractors, such as
the right dorsolateral prefrontal cortex and certain parietal regions. Interestingly some
regions of the brain are activated uniquely during certain processes, for instance if the
participants have controlled the interference effects through filtering precepts then the
occipital cortex is activated. Alternatively if participants control interference through
filtering intrusive memories then the left lateral prefrontal cortex is activated.
The scaffolding theory purposed by Park & Reuter-Lorenz (2009) focuses on the changes
that develop in the neuro-cognitive system with increasing natural age. As the evidence
above shows the neural structures and functions deteriorate as ageing occurs. Park &
Reuter-Lorenz (2009)suggest that within the brain these protective scaffolds are created in
an attempt to cope with age related neural deficits such as brain shrinkage, decreased white
matter integrity, and decreased dopamine receptors. Scaffolding is a process not specific to
ageing but occurs due to stresses of cognitive challenges across the lifespan. Increased
frontal bilaterality with ageing is on reflection of this recruitment in response to neural
decline (Goh & Park, 2009). New neural circuitry is developed when engaged in active
learning as a child (Persson, Lustig, Nelson & Reuter-Lorenz2007), though when scaffolds are
built in adulthood it is only under conditions of new learning because the existing neural
circuitry for performing the task has degraded (Goh & Park, 2009). Park & Reuter-Lorenz
19. (2009) believe the frontal cortex, the most cognitively flexible and strategic component of
the brain is the main location for the scaffolding effect.
Limitationsof present study and future research
It is important to highlight the potential limitations of the current study. The sample size in
this study is particularly small, a larger sample size would have been ideal. Due to this small
size it allowed suggestion that lack of power did not allow for detection of small effects
particularly with respect to the correlation between age group and task type. Despite this
limitation, however, clear difference between age conditions was evident. Practise effects
are another possible limitation of this study. Each participant would perform the two tasks
within a very close time. There should have been a substantial time gap between the trials
to reduce these effects, otherwise participants may improve simply through the effect of
practise, another suggestion would be that a study could be performed in which there are
two parallel versions of the task. Similarly participants may have become tired or bored and
their performance may deteriorate as the tasks go on. Counterbalance intervention was
implemented to attempt to restrict practise effects in this study, this meant that 12 of the
participants (6 older, 6 younger) performed the control experiment first and the other 12
participants performed the experimental task first. Sample limitations could be called into
effect within the participants of this study. The results could be interpreted as bias towards
a specific group, this is because all of the younger adults were university students, and
therefore it is not a broad representation of young adults. The older adults group has more
variety due to the range of years in education and level of education. In addition the older
adults have an above average estimated IQ which is similar to what would be expected, with
the young adults due to their university student status and so presumably above average
intelligence.
Future research into this area could involve gender alienated analysis, in order to compare
and measure the difference between males and females capacity of working memory along
with effect of DVN interference. Secondly a larger sample size would be necessary for each
gender e.g.20 participants; this will allow greater power to detect the smaller effects and
therefore more reliable results. Thirdly it would be interesting to add a third age group (e.g.
25-50 years of age) between the two age groups within this study. This would allow use to
observe the trend of deterioration with greater detail through the ageing process. Although
the latter idea has previously been carried by Logie & Maylor (2009), the participants
performed the study at home via the internet, as opposed to in a laboratory environment
within this study.
Conclusion
In conclusion this study appears to support the previous research suggesting that working
memory capacity significantly declines as we age. The strategy most participants used in the
VPT was a visual strategy, previous research and this study alike show that older participants
20. do worse than younger adults when using this strategy. Anecdotal evidence suggests that a
few participants attempted to use a verbal coding strategy when the opportunity arose,
though this was not frequent. It appears that the occurrence of relevant and irrelevant
information increased competition of storage space in the working memory as well as
creating confusion to participants even though there was no reliable effect of interference
overall. The DVN may have had a greater effect on the younger adults, compared to the
older. This could have been due to the strategy chosen to employ, such as a spatial and/or
verbal strategy which is less sensitive to DVN, opposed to a visual strategy that the young
might have used. It is believed that processing speed has a great effect on working memory,
suggesting that speed of encoding and rate of rehearsal are certain aspects that are directly
affected by ageing and cause a deterioration in working memory. From a biological
prospective of the neuroanatomical regions of the brain the reduction of such sections of
the brain as the white matter integrity appear to have a severe effect in the working
memory capacity as ageing progresses. The DVN did not have a significant effect on the
participants performing the Visual Patterns Test within this study, though with a larger
sample size this could indeed have been the case if a future study was to be instigated.
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28. 2 Example of Visual Pattern:
Reference: Louise A. Brown, James R. Brockmole, Alan J. Gow & Ian J. Deary (2012): Processing Speed and
Visuospatial Executive Function Predict Visual Working Memory Ability in Older Adults, Experimental Ageing
Research, 38:1, 1-19
3 Example of consent form for younger adults:
Within this experiment you will perform a brief reading task followed by two versions of a visual short-term
memory task. One in which you see black and white chequered patterns and then try to recall them after a
delay, and another which is the same except you will also be asked to view abstract visual information (like
static on an old television set) in between presentation and recall.
All information collected within this research will remain strictly confidential and securely stored with only my
supervisor and I having access. Your participation is voluntary and you have the right to withdraw at any point
during the session, and afterwards up until the deadline date of 1st March 2013, by quoting the identifier
specified in the debrief sheet provided at the end of your session. All data will be not be kept after the study
and will be disposed of.
I hereby give consent to take partin this study.
Signature of participant: ___________________ Date: _______________
Signature of researcher:___________________ Date: _______________
Number of participant
29. 4 Example of consent form for older adults:
Within this experiment you will perform a brief reading task followed by two versions of a visual short-term
memory task. One in which you see black and white chequered patterns and then try to recall them after a
delay, and another which the is same except you will also be asked to view abstract visual information (like
static on an old television set) in between presentation and recall. Before you start the experiment there will
be a brief general task involvingabilities such asorientation,memory and concentration
All information collected within this research will remain strictly confidential and securely stored with only my
supervisor and I having access. Your participation is voluntary and you have the right to withdraw at any point
during the session, and afterwards up until the deadline date of 1st March 2013, by quoting the identifier
specified in the debrief sheet provided at the end of your session. All data will be not be kept after the study
and will be disposed of.
I hereby give consent to take partin this study.
Signature of participant: ___________________ Date: _______________
Signature of researcher:___________________ Date: _______________
Number of participant
______________________________________________________________________________
30. 5 Example of Debrief:
Thank you again for giving up your time to participate in this research. The purpose of this study was to test
the decline in visual working memory in older adults in comparison to younger adults, and to assess the extent
to which each age group uses the most appropriatestrategy of visual rehearsal.
Your results will now be gathered together with the results of other people participating in the research. The
data will then be analysed as a whole rather than there being any examination of anybody’s scores in isolation.
For this reason we will be unable to feedback any information to you about your own responses. If however
you would like to know the findings of our overall research please contact one of the research team and we
will send you a summary of our findings.
Remember that you have the right to withdraw from the research up until the deadline date of 1st March
2013. You may do so by contacting either me or my supervisor and quoting your participant number
:__________
If you have any queries about the research please feel free to ask now, or to get in touch after the session. Our
contact details aregiven below.
Jason Hobman(Student): N0324223@my.ntu.ac.uk
Project Supervisor:Dr Louise Brown, 0115-848-2387,
Email:Louise.Brown@ntu.ac.uk
Thank you again for your participation!
6 Example of MMSE:
31. Reference: Folstein MF, Folstein SE, McHugh PR (1975). ""Mini-mental state". A practical method for grading
the cognitivestate of patients for the clinician".Journal of Psychiatric Research 12 (3): 189–98.
MMSE
Participant:__________ Date:__________ Score:__________
Orientation
1. What is the (year) (season) (date) (day) (month) /5
2. Where are we, e.g. (country) (county) (town/city) (hospital/area) (floor/street)
/5
Registration
3. Ask the participant if you may test his/her memory. Name 3 objects – ‘apple’, ‘penny’, ‘table’ –
(1/second). Then ask the participantto repeat them (1 point each).
/3
Repeat until the participanthas learned all three. (Number of extra trials until learned =____).
Attention and Calculation
4. Serial 7s. Ask participant to count backwards from 100 by 7s. If P cannot or will not, as k P to spell
‘world’ backwards.
93 – 86 – 79 – 72 – 65 /5
Recall
5. Ask for the three earlier named objects (1 point each) /3
Language
6. Ask participantto name a watch, then a pen. /2
7. Repeat the following“no ifs,ands,or buts” /1
8. Followa three-stage command –
“take this paper in your righthand, fold it in half,and lay iton the floor”
/3
9. Read and obey “close your eyes” message /1
10. Write a sentence /1
11. Copy design /1
