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

School of Social Sciences

Nottingham Trent University

Jason Hobman

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.

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

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)

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

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 interference on 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

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.

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.

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.

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.

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.

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.

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.

Control Interference2

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A graph to show the interaction between age group and task types.

Younger AdultsOlder Adults

Task Type

Scor

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VPT

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 differences in 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

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.

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

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

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

(2009) believe the frontal cortex, the most cognitively flexible and strategic component of the brain is the main location for the scaffolding effect.

Limitations of 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

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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Apendix___________________________________________

1 Example of DVN:

Reference: Quinn, J. G., & McConnell, J. (1996). Irrelevant pictures in visual working memory. Quarterly Journal of Experimental Psychology, 49A, 200–215.

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 part in this study.

Signature of participant: ___________________ Date: _______________

Signature of researcher: ___________________ Date: _______________

Number of participant

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 involving abilities such as orientation, 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 part in this study.

Signature of participant: ___________________ Date: _______________

Signature of researcher: ___________________ Date: _______________

Number of participant

______________________________________________________________________________

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 appropriate strategy 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 are given 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:

Reference: Folstein MF, Folstein SE, McHugh PR (1975). ""Mini-mental state". A practical method for grading the cognitive state 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 participant to repeat them (1 point each).

/3

Repeat until the participant has 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, ask 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 participant to name a watch, then a pen. /2

7. Repeat the following “no ifs, ands, or buts” /1

8. Follow a three-stage command –

“take this paper in your right hand, fold it in half, and lay it on the floor”/3

9. Read and obey “close your eyes” message /1

10. Write a sentence /1

11. Copy design /1