validation of the cantab paired associates learning (pal) test in ...€¦ · the cantab paired...

Validation of the Cantab Paired

Associates Learning (PAL) test in

measuring Alzheimer’s Disease (AD)

and Mild Cognitive Impairment (MCI)

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© Cambridge Cognition Limited 2014. All rights reserved.

Contents

Scientific rationale 2

Paired Associates Learning: an overview 3

Cognitive decline over the lifespan 4

Cognitive decline in Mild Cognitive Impairment 6

Cognitive decline in Alzheimer’s Disease 8

PAL and Biomarkers/Neuroimaging in MCI and AD 10

Ecological and concurrent validity 12

Psychometric considerations 13

References 14

Contact us 15

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Scientific Rationale

Alzheimer’s disease (AD) is characterised by an insidious onset with progressive

cognitive decline. Mild Cognitive Impairment (MCI) is a state of cognitive functioning

below what is expected for normal aging, associated with increased risk of progression

to dementia.

Early cognitive difficulties patients with AD commonly experience include deterioration in

visuospatial/episodic memory. This is also the most common cognitive impairment seen

in patients with MCI who progress to a diagnosis of AD dementia (Albert et al., 2011).

Tests of episodic memory are especially sensitive to AD pathology because they rely

heavily on the brain regions first affected in the progression of Alzheimer’s pathology

(Braak & Braak, 1991).

The Cantab Paired Associates Learning (PAL) test assesses visual associative learning

and memory, both of which are dependent on the functional integrity of the temporal

lobe, particularly the entorhinal cortex (Owen et al., 1995).

PAL has sound preclinical validation and task performance is sensitive to

pharmacological manipulation. For example, scopolamine impairs PAL performance in

rhesus monkeys (Taffe et al., 2002). In addition, PAL task performance can differentiate

subjects with AD and MCI from subjects with depression, and healthy volunteers

(Swainson et al., 2001).

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Paired Associates Learning (PAL): An Overview

PAL assesses visual associative learning and memory

Boxes are displayed on the screen and are

automatically opened in a randomised order to

show a number of patterns. Participants must learn

to associate the patterns with locations on the

screen. After all the boxes have been opened each

pattern is then shown in the centre of the screen

and the participant must touch the box where that

pattern was located.

If the participant makes an error, the patterns are

re-presented to remind the participant of their

locations. The difficulty level increases with the

number of patterns to be remembered, thereby making the test suitable for use

in both high-functioning individuals and patient populations.

For participants who fail to complete all levels, an adjusted total is calculated that

allows for errors predicted in the stages that were not attempted.

PAL is a non-verbal test that utilizes abstract stimuli. This allows research to be

comparable across a diverse range of cross-cultural populations to support multi-

centre, global studies.

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Cognitive Decline over the Lifespan

Different cognitive domains show characteristic lifecourse functions. Figure 1 contrasts

the age-related performance on the Cantab Paired Associates Learning (PAL) test, a task

depending upon medial temporal lobe function. Cognitive performance on this test

declines with age, and the rate of decline increases significantly from age 50.

Figure 1. Cantab normative data indicating change in PAL performance across the lifespan

Focusing specifically on older adults, Figure 1 maps this significant decline in PAL

performance across later life, based on cross-sectional performance of healthy

volunteers aged 48 to 89 years. This normative sample excludes individuals showing

signs of dementia (as screened by an extended Mini Mental State Examination (MMSE).

Regression analysis demonstrates a mean increase in PAL total error (adjusted) score of

1.6 errors per year. More rapid deterioration was seen between the ages of 60 and 80,

where performance declined by 2.3 errors per year. This decline would be exacerbated

in patients with increased likelihood of developing dementia, for example in MCI, or in

patients with risk factors such as poor cardiovascular health, low education or vitamin

deficiency.

PAL Visuospatial paired associate learning across the lifespan - from

CCL norms

0

5

10

15

20

25

30

35

4-5 6-7 8-9 10-11 12-13 14-15 16-23 24-39 40-49 50-59 60-69 70-79 80+

Age Group

PA

L 6

patt

ern

err

ors

ad

juste

d

0

1

2

3

4

5

6

7

8

PA

L s

tag

es

co

mp

lete

d (m

ax

imu

m

po

ss

ible

= 8

)

6 pattern

errors

Stages

completed

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Figure 2. Normative data: PAL total errors (adjusted) for healthy older adults

The effects of education on PAL decline can be seen in Figure 3. Individuals who left

school prior to age 16 show greater error scores at all ages, and their decline with age is

somewhat greater than those who remained in education after age 18.

Figure 3. Normative data: PAL total errors (adjusted) for healthy older adults stratified by level of education (age of leaving education)

PAL total errors (adjusted) = 1.6*Age -

64.8

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Cognitive Decline in Mild Cognitive Impairment

Cognitive deterioration has been recorded in patients with MCI in a number of Cantab

studies. For example, Figure 4 shows the performance of 62 undifferentiated MCI

patients on the Cantab PAL task, over the course of 80 weeks. In this study, a sub-

group of ‘deteriorating’ patients with questionable dementia showed significant

worsening of memory performance assessed using the PAL test within 6 months of

screening, and cognitive decline continued over a period of 2 years (Fowler et al., 2002)

(see decliners in Figure 4).

Figure 4. Performance on PAL (total errors adjusted) for stable and deteriorating patients with MCI (Fowler et al., 2002).

These findings are replicated in a more recent one and a half year follow up of

prodromal AD (Visser et al., 2012), where PAL shows sensitivity to the deterioration in

these patients (see Figure 5).

Decliners

Non-Decliners

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Figure 5. The number of errors made on the PAL memory task over 1.5 years, for a group of subjects fulfilling the criteria of prodromal AD (Visser et al., 2012), compared to healthy older adults.

A separate longitudinal study by Chamberlain et al. (2011) replicated these findings but

with a lesser degree of deterioration in patients with subjective memory impairment

(SMI). The SMI group (N=43; aged 64.9 ± 9.1 years) is characterised by subjective

report of memory complaint without the requirement for a 1.5 standard deviation deficit

on formal neuropsychological testing. These patients showed decline in PAL performance

(total errors adjusted) at a rate of 3.7 errors over 8 months (see Table 1). Furthermore,

a sub-sample of patients with SMI who followed a converting versus stable trajectory showed elevated rates of decline in PAL performance (see Table 1).

Table 1. Absolute change from baseline PAL performance (total errors adjusted) for patients with

subjective memory impairment (Chamberlain et al., 2011)

Subjective memory

impairment

Subjective memory

impairment - converters

Subjective memory

impairment – stable

8 months +3.7 ± 22.0 +13.4 ± 28.4 +0.5 ± 19.0

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Cognitive Decline in Alzheimer’s Disease

As would be expected, the rate of decline in PAL performance in AD is greater than that

seen on average in MCI or healthy elderly populations (see Figure 6). For example, PAL

total error score (adjusted) declined by an average of 24 errors over one year in

patients with dementia of the Alzheimer’s type (Fowler et al., 2002) (see Figure 6).

Figure 6. Performance on PAL (total errors adjusted) for patients with dementia of the Alzheimer’s type, patients with questionable dementia and healthy controls (left) and individual participant trajectories for patients with dementia of the Alzheimer’s type (right) (Fowler et al., 2002).

Research conducted by Swainson et al. (2001) also demonstrated that individuals with

questionable dementia committing more than 20 errors at the 6-pattern stage were

likely to go on to develop AD over the next 32 months while none of those committing

fewer than 20 errors went on to develop AD (Figure 7). Therefore, poor PAL

performance is a good indicator of those likely to progress to an AD diagnosis.

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Figure 7. Paired associates learning test identifies individuals who are likely to develop AD (Swainson et al., 2001).

The OPTIMA study revealed that paired associates learning error scores have a

sensitivity of 0.83 and a specificity of 0.82 when differentiating individuals with mild

cognitive impairment from healthy older adults (Chandler et al., 2008).

In clinical trials, PAL’s sensitivity to pharmacological manipulation in AD allows for

shorter and smaller clinical trials than those required for less sensitive cognitive tests.

Figure 8 shows data from a relatively small (N=72) study in patients with mild to

moderate AD. In this 12-week study, PAL performance deteriorated by an average of 7

points in the placebo-treated group, while no significant change was detected on the

ADAS-cog (Greig et al., 2005).

Figure 8. Performance on PAL and ADAS-cog for patients with mild to moderate AD following 12-

week treatment with the cholinesterase inhibitor phenserine or placebo

All (except 1) went on to

develop Alzheimer’s disease

over 32 month follow-up

None went on to develop

Alzheimer’s disease over 32

month follow-up

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PAL and Biomarkers/Neuroimaging in MCI and AD

A recent review by Jack et al. (2010) proposed a model of the different temporal profiles

of a number of AD biomarkers (see Figure 9). Deposition of Aβ was posited to occur very

early in the disease process, with a lag phase of as yet unknown duration before the

onset of cognitive symptoms. Meanwhile, biomarkers of neurodegeneration, such as tau,

are thought to occur later in the disease and correlate with clinical symptom severity.

Figure 9. Dynamic biomarkers of the Alzheimer’s pathological cascade (Jack et al. 2010).

Figure 10 shows that an increase of Aβ in CSF has a detrimental effect on patients’

ability to perform PAL, and therefore we can infer deterioration of their

visuospatial/episodic memory.

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Figure 10. Paired associates learning performance is associated with CSF beta amyloid and total tau levels (unpublished data) (error bars indicate standard errors of the mean).

Finally, brain atrophy assessed using magnetic resonance imaging (MRI) is seen later

still in the disease process. Therefore, CSF Aβ1-42 represents a biomarker for AD

potentially present in patients with preclinical dementia and MCI. In patients with MCI,

the combination of reduced CSF Aβ1-42 and increased CSF total tau (T-tau) was found to

predict conversion to AD with a sensitivity of 95% and a specificity of 83% over three

years (Hansson et al. 2006).

Figure 11 shows bilateral hippocampal activation during PAL encoding for MCI patients

and healthy controls (de Rover et al., 2011). The hippocampus, located in the medial

frontal lobe, is one of the first brain regions affected in the onset of AD (Braak & Braak,

1991). This fMRI study therefore clearly demonstrates that PAL ‘taps in to’ cognitive

domains (visual associative learning and memory) which are dependent on the

functional integrity of this brain region, particularly the entorhinal cortex (Owen et al.,

1995).

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Figure 11. Bilateral hippocampal activation during PAL encoding for MCI patients and healthy

controls (de Rover et al., 2011).

Ecological and Concurrent Validity

Performance on PAL is highly correlated with other measures of cognition in patients

with AD, including all sub-scales of the Cambridge Behavioural Inventory (CBI) and the

Alzheimer’s Disease Assessment Scale-cognitive subscale (ADAS-cog) (see Figure 12; unpublished data).

Figure 12: Significant correlation between PAL (total trials adjusted) and CBI memory score (left)

and ADAS-cog score (right).

ROI analysis

Significant

clusters p<0.05

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Psychometric Considerations

Test-retest reliability

Findings from a healthy volunteer study carried out by Harrison and colleagues (N=100;

43.6 ± 16.4 years; unpublished) attest to the moderate-to-high test-retest reliability of

the cognitive tasks included in this document. Test-retest reliability would be expected

to be greater in patients with MCI and AD than in healthy controls. For example, Fowler

et al. (1995) recorded one-month test-retest reliabilities of 0.64 (healthy controls), 0.71

(MCI) and 0.88 (AD) for PAL (total errors).

Dynamic Range

PAL increases in difficulty across the task and is therefore are suitable for use in highly

impaired and high-functioning individuals. This test has a large dynamic range and so

we expect there to be minimal floor or ceiling effects. Furthermore, the PAL test is non-

verbal and utilizes abstract stimuli to allow research to be comparable across a diverse

range of cross-cultural populations to support multi-centre, global studies.

14



References

1. Albert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., … Phelps, C. H. (2011). The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimer’s & Dementia : The Journal of the Alzheimer's Association, 7(3), 270–9.

2. Braak, H., & Braak, E. (1991). Neuropathological stageing of Alzheimer-related changes. Acta Neuropathologica, 82(4), 239–259. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/1759558

3. Owen AM, Sahakian BJ, Semple J, Polkey CE, Robbins TW. Visuo-spatial short-term recognition memory and learning after temporal lobe excisions, frontal lobe excisions or amygdalo-hippocampectomy in man. Neuropsychologia. 1995;33(1):1-24.

4. Taffe MA, Weed MR, Gutierrez T, Davis SA, Gold LH. Differential muscarinic and NMDA contributions to visuo-spatial paired-associate learning in rhesus monkeys. Psychopharmacology. 2002;160(3):253–62.

5. Swainson R, Hodges JR, Galton CJ, et al. Early Detection and Differential Diagnosis of Alzheimer’s Disease and Depression with Neuropsychological Tasks. Dementia and Geriatric Cognitive Disorders. 2001;12(4):265-280.

6. Fowler, K. S., Saling, M. M., Conway, E. L., Semple, J. M., & Louis, W. J. (2002). Paired associate

performance in the early detection of DAT. Journal of the International Neuropsychological Society, 8(1), 58–71.

7. Visser, P. J., Vos, S., van Rossum, I., & Scheltens, P. (2012). Comparison of International Working Group criteria and National Institute on Aging-Alzheimer’s Association criteria for Alzheimer's disease. Alzheimer’s & Dementia : The Journal of the Alzheimer's Association, 8(6), 560–3. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/23102126

8. Chamberlain SR, Blackwell AD, Nathan PJ, et al. Differential cognitive deterioration in dementia: a two year longitudinal study. Journal of Alzheimerʼs disease : JAD. 2011;24(1):125-36. Available at:

http://www.ncbi.nlm.nih.gov/pubmed/21206003 [Accessed April 1, 2011].

9. Chandler, J., Marsico, M., Harper-mozley, L. M., Vogt, R., Peng, Y., Lesk, V., & Jager, C. A. De. (2008). Cognitive assessment: Discrimination of impairment and detection of decline in Alzheimer’s disease and mild cognitive impairment. Alzheimer’s and Dementia, 4(4), T551–T552.

10. Greig, N. H., Sambamurti, K., Yu, Q., Brossi, A., Bruinsma, G. B., & Lahiri, D. K. (2005). An Overview of Phenserine Tartrate, A Novel Acetylcholinesterase Inhibitor for the Treatment of Alzheimer’s Disease. Current Alzheimer Research, 2(3), 281–290.

11. Jack Jr CR, Knopman DS, Jagust WJ, et al. Hypothetical model of dynamic biomarkers of the Alzheimerʼs pathological cascade. The Lancet Neurology. 2010;9(1):119–128.

12. De Rover, M., Pironti, V. A., McCabe, J. A., Acosta-Cabronero, J., Arana, F. S., Morein-Zamir, S., …

Sahakian, B. J. (2011). Hippocampal dysfunction in patients with mild cognitive impairment: a functional neuroimaging study of a visuospatial paired associates learning task. Neuropsychologia, in press.

13. Harrison JE, Iddon JL, Stow IA, et al. Cambridge Neuropsychological Test Automated Battery

(CANTAB): Test-Retest Reliability Characteristics. Unpublished.

14. Fowler K. S. Saling M. M. Conway E. L. Semple J. Louis W. J. Computerized delayed matching to

sample and paired associate performance in the early detection of dementia. Applied

Neuropsychology. 1995; 2: 72-78.

http://www.ncbi.nlm.nih.gov/pubmed/23102126

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