- Open Access
Memory markers in the continuum of the Alzheimer’s clinical syndrome
Alzheimer's Research & Therapy volume 14, Article number: 142 (2022)
The individual and complementary value of the Visual Short-Term Memory Binding Test (VSTMBT) and the Free and Cued Selective Reminding Test (FCSRT) as markers to trace the AD continuum was investigated. It was hypothesised that the VSTMBT would be an early indicator while the FCSRT would inform on imminent progression.
Healthy older adults (n=70) and patients with mild cognitive impairment (MCI) (n=80) were recruited and followed up between 2012 and 2017. Participants with at least two assessment points entered the study. Using baseline and follow-up assessments four groups were defined: Older adults who were healthy (HOA), with very mild cognitive but not functional impairment (eMCI), and with MCI who did and did not convert to dementia (MCI converters and non-converters).
Only the VSTMBT predicted group membership in the very early stages (HOA vs eMCI). As the disease progressed, the FCSRT became a strong predictor excluding the VSTMB from the models. Their complementary value was high during the mid-prodromal stages and decreased in stages closer to dementia.
The study supports the notion that neuropsychological assessment for AD needs to abandon the notion of one-size-fits-all. A memory toolkit for AD needs to consider tools that are early indicators and tools that suggest imminent progression. The VSTMBT and the FSCRT are such tools.
Alzheimer’s disease (AD) has been defined as a continuum of clinical and pathological events from normal ageing to dementia. Accordingly, the disease has been reconceptualised [1,2,3,4] and new diagnostic frameworks relying on biomarkers have been introduced [5, 6]. The motivation behind these biomarkers-based frameworks has been the limitations that available neuropsychological tests have demonstrated in detecting the pre-dementia stages of such a continuum [3, 7, 8]. In the 10 years since Sperling et al.  suggested the relevance of the long preclinical stages of AD, the emphasis has shifted from the study of mild cognitive impairment (MCI) and progression to dementia to the study of incident cognitive impairment linked to risk of dementia. Recent evidence following such recommendations suggests that neuropsychological measures may provide meaningful signals informing on the different stages of preclinical AD in still cognitively intact older adults . Memory is the cognitive function earliest and most dramatically impacted by the typical forms of AD [8,9,10,11]. However, accrued evidence suggests that neuropsychological assessment needs a paradigm shift if we are to enhance its sensitivity and specificity for the preclinical stages of the disease [8, 12,13,14].
Recent recommendations by the Joint Program for Neurodegenerative Diseases Working Group  fit well with the hypothetical model of memory decline in AD originally proposed by Didic et al.  (see Fig. 1). The Working Group recommended two memory tests that have recently proved useful in the assessment of preclinical AD: the Visual Short-Term Memory Binding Test (VSTMBT ;) and the Free and Cued Selective Reminding Test (FCSRT ;). Both tests assess the ability to integrate information in memory. However, they tap into different memory functions. Visual Short-Term Memory Binding (VSTMB) refers to our ability to integrate objects’ features into unified representations to form and temporarily hold new identities in memory [17,18,19]. Typically, the VSTMBT assesses this ability by asking people to recognise changes in coloured shapes or objects occurring between two consecutive displays (i.e. study and test display of change detection tasks). To detect such changes accurately, participants do not need contextual information, rather they need to judge if the newly presented object (test display) is the same as previously presented or different.
The FCSRT, as well as other tests that follow the selective reminding paradigm, such as the memory capacity test (MCT, [24,25,26]), rely on contextual information to support both encoding and retrieval. The assumption of these tests is that if the contextual cues presented during the encoding (i.e. semantic categories) match those available during recall, they would assist the retrieval of exemplar memories linked to such categories (i.e. the encoding specificity principle ). Binding items (i.e. exemplars) to their context (i.e. semantic categories) effectively, should aid memory performance in the context of tests such as the FCSRT and MCT.
The underlying construct of both these two tests seems to be memory binding. However, they appear to tax two very different binding functions. The VSTMBT assesses a form of conjunctive binding responsible for holding integrated features within object representations, whereas the FCSRT assesses a form or relational binding that supports the retention of associative memories. We briefly illustrate what Didic et al.’s  model implicates about these forms of binding in the AD continuum next in Fig. 1.
Traditionally, studies that have investigated the predictive value of neuropsychological tests to anticipate who among those at risk of AD will eventually develop dementia have conducted retrospective analyses comparing baseline performance of patients in predementia stages (e.g. MCI) who did and did not convert to dementia in the follow-up period. Given the evidence summarised above, such prediction models are most likely to be informative for neuropsychological tests sensitive to advanced stages of the AD continuum (i.e. limbic stage). A function that has started to decline years before people become aware of any cognitive impairments or develop initial symptoms of dementia, may have declined dramatically by the time they reach the MCI stage. At this point in time, separating MCI patients who will and will not develop dementia in 2 or 3 years may be problematic for such tests but may still be possible for tests that assess functions sensitive to the limbic stages, that exhibit a less steep decline (see for example [27, 28]), or that are compensated by protective factors, such as cognitive reserve [29, 30]. Parra et al.  recently suggested that the VSTMBT may need to be titrated to the targeted population (e.g. preclinical or prodromal) by adjusting memory load (i.e. 2 or 3 items) in order to achieve best classification power. Similarly, it has been suggested that future studies using biomarkers will need to rely on adjusted normative data in order to ascertain who the true control participants are . In a conference paper, Parra et al.  reported that older adults who are completely asymptomatic but show poor VSTMB abilities have significantly more accumulation of amyloid deposits in the brain than those whose binding abilities are spared.
We posit that both the VSTMBT and the FCRST will be able to correctly classify most of the older adults at different stages of the continuum of the AD clinical syndrome, but that their discrimination power would differ depending on where people are in such a continuum. We predict that the VSTMBT will be able to discriminate between older adults who are asymptomatic and those who are in the very early stages of cognitive decline more effectively than the FCSRT (H1). On the contrary, the FCSRT will discriminate more accurately than the VSTMBT between older adults with MCI who converted and who did not convert to dementia in follow-up assessments (H2).
We recruited participants self-reporting as being healthy who were either members of the Psychology Volunteer Panel at the University of Edinburgh or relatives of patients with dementia from the Scottish Dementia Clinical Research Network interest register (SDCRN, currently Neuroprogressive and Dementia Network - NDN) who volunteered for the study. We also received referrals from old age psychiatrists based at the NHS Lothian and NHS Forth Valley who regularly see older adults complaining about their cognitive abilities. Recruitment and follow-up assessments ran between 2012 and 2017. To be eligible for the study, participants had to be over 55 years old and native English speakers. MCI patients had to have an available relative or a caregiver and demonstrate the capacity to consent to the study. All the participants needed to be free from any neurological or psychiatric disease that would interfere with their cognitive functions, and had normal or corrected to normal vision. Participants with scores greater than 4 in the Hachinski Ischemia Scale  and 5 in the brief Geriatric Depression Scale (GDS, ) were not included in the final sample. Also, participants who met the criteria for AD dementia at baseline were not eligible. All participants were provided with an Information Sheet describing the longitudinal nature of the study and the assessments involved. They were told that their cognitive and functional abilities would be assessed, that it was possible to detect impairments of which they were not aware, that should this happen, their GPs would be contacted with their consent. After they read the PIS, they signed a consent form prior to participating in the study. The study was approved by the NHS Multi-Site Research Ethics Committee (reference number 06/MRE07/40) and was given approval by local NHS R&D offices. In addition to the above criteria, only participants who had completed at least two assessment points including baseline were entered into the analyses here reported. The final sample consisted of 150 participants. Of these, 70 self-reported as healthy and 80 were referred by consultant old age psychiatrists as patients meeting the criteria for MCI.
Sample design and rationale
Power calculation was performed which incorporated (1) pilot data obtained from 23 MCI patients and 30 controls as well as from 14 mild AD patients all assessed with the VSTMBT proposed here. In addition, a wide search of the literature was performed to obtain three main variables: (1) average follow-up period within which changes could be observed using sensitive cognitive tasks (3 years, ), (2) MCI to AD conversion rate (median = per annum 12%, 37.65% for a 3-year study), and (3) attrition (14% for a 3-year follow-up study). The results showed that for a desired power of 80%, a medium effect size (Cohen d = 0.5) and alpha set at 0.05, 80 MCI patients and 40 controls at baseline would allow us to reach the study end-point with a number of converters which permits reliable comparisons (≥ 20).
Baseline data were used to define groups by applying classical MCI criteria [37,38,39]. We relied on tests for which valid norms had been previously published (see “Neuropsychological assessment” section). Participants were allocated to the Healthy Older Adults Group (HOA) if they performed within 1.5SD of the norms (we applied the MCI criteria relying on the Neuropsychological Tests described below) and showed normal Instrumental Activities of Daily Living (IADL, ). Participants entered the early Mild Cognitive Impairment Group (eMCI) if they performed below 1.5SD from the norms on any of the tests applied but had intact IADL (see ). Older adults who performed below 1.5SD from the norms of any test and showed mild impairments in IADL at baseline were classified as MCI . The final clinical status of MCI patients was updated in November 2018 by discussing these with the referring consultants who accessed the NHS records. Those whose records confirmed the diagnosis of dementia were grouped within the converter group (MCI converter), while those whose records still reflected the diagnosis of MCI entered the non-Converter Group (MCI non-converter).
Although for the purposes of this study we did not follow the classical classification of MCI subtypes, we did apply such criteria to baseline data. Figure 2 shows the groups split after applying criteria to (1) identify MCI subtypes and (2) conform the core groups for this study. We observed a 35.2% conversion rate among MCI patients (considering eMCI and MCI) who, as Fig. 1 shows, were predominantly multi-domain amnestic MCI (maMCI). This is in line with the literature [4, 42, 43]. None of the non-amnestic MCI (naMCI) patients developed AD dementia in the course of the study, which also seems to agree with the abovementioned literature.
In order to test our first hypothesis (H1), we compared the HOA and eMCI groups (H1: Discrimination between cognitively unimpaired and older adults with very early cognitive impairment). We were interested in identifying individuals who may be displaying early signs of cognitive impairments, among the older adults who had not sought medical advice or were worried about their cognitive abilities independently of their cognitive status. We anticipated that for those displaying cognitive impairments, such impairments would be sufficiently mild as not to cause concern nor to interfere with their IADL. To test our second hypothesis (H2: Discriminate between older adults with MCI who did and did not convert to dementia in the follow-up period) we requested an updated diagnosis from the referring consultants as described above. This allowed us to retrospectively define two groups, MCI converter and MCI non-converter. The demographic, clinical, and cognitive characteristics of these groups are presented in Table 1.
A battery of neuropsychological tests was administered to all participants. The battery consisted of a combination of traditional neuropsychological tests commonly used to assess dementia [44, 45] and more novel tasks, including the VSTMBT and the FCSRT. Baseline and follow-up assessments were carried out a year apart.
The Addenbrooke’s Cognitive Examination Revised (ACE-R) was used as a Global Cognitive screening test . Memory tests included the Hopkins Verbal Learning Test Immediate Total and Delayed Recall ;) and visual memory (Rey-Osterrieth Complex Figure Immediate and Delayed Recall ). Assessment of attention/executive functions (TMT-A and TMT-B ), praxis (Rey-Osterrieth Complex Figure Copy ), and language/executive functions (Phonological - FAS - Fluency ). Speed of processing was assessed with the Digit to Symbol Substitution Test . The premorbid function was assessed with TOPF . We also administered the Instrumental Activities of Daily Living (IADL) Scale .
The FCSRT test began with participants examining a card containing the names of objects (Grober et al., 1988). Each card showed four names, each belonging to a unique semantic category. For instance, ‘banana’ would be an example of a to-be-remembered object with the semantic cue of ‘Fruit’. Each participant learned 16 names of objects, distributed in four printed flashcards presented one at a time with four names of objects on each card. Immediate Free Recall was assessed by asking participants to retrieve the 16 names of objects spontaneously. Cued recall was subsequently assessed with the aid of the semantic cue for those items not recalled under free recall. This procedure was repeated 3 times, with a 20-s interference (counting backwards). The final Immediate Free Recall score is the sum of objects recalled from the three trials, with a minimum score of zero and a maximum of 48. The final total recall score is the sum of free recall and cued recall from all three trials, with a minimum score of 0 and a maximum of 48. We did not assess Delayed Recall in this protocol.
The VSTMB test consisted of three conditions. First, a perceptual binding task was given, as a screening test aimed at ruling out perceptual binding deficits of colour and shape . Each trial began by presenting participants with two arrays of items on a computer screen (see  for a full description of the items’ psychophysics properties including the perceptual impact of the number of sides, colour luminance, and screen dimensions relative to foveal vision). The task was to decide if the two arrays, one on the lower half of the screen and the other on the top half, presented the same or different coloured shapes. Ten trials were included in this screening. A cut-off score of 80% was used to decide who would progress to the memory binding test . All the participants who entered the study met such a criterion. We then presented the two memory conditions. The memory assessment was based on a change detection paradigm. The task comprised two conditions, Shape Only and Shape-Colour Binding. In the Shape Only condition, the study array consisted of three black shapes presented for 2000 ms. This was followed by a retention period (blank screen) for 1000 ms. Finally, a test array was presented, with three shapes in different locations to the study array. At this point, participants were required to respond ‘same’ or ‘different’. In 50% of the trials, the shapes in the study and test array were the same while in the rest of the trials, two shapes not presented at the study appeared in the test display. A similar procedure was followed in the Shape-Colour Binding condition. The to-be-remembered items were combinations of shape and colour. Participants were required to decide if the specific colour and shape combination in the test array was the same as presented in the study array (see Supplementary Figure 1 for example trials). There were 32 trials in each condition. The final score was the percentage of correct recognition. While there are currently no reported studies that have investigated the psychometric properties of the VSTMB test per se, the change detection paradigm, upon which the test is based, has been demonstrated to hold internal consistency (Logie et al., 2009). For the present analyses, we focused on the performance on the Shape-Colour Binding condition of the VSTMBT which achieved the best classification power in AD studies [15, 53, 54]. As for the FCSRT, we chose Immediate Free Recall as this proved to be the most sensitive score to detect AD [55, 56].
To compare groups, we used tests of mean differences (t-Tests, MANOVA/MANCOVA). We also used stepwise linear regression models to investigate the individual and complementary value of the VSTMBT and the FCRST to predict group membership. To test H1 we compared HOA, eMCI and MCI non-Converter groups. To test our second hypothesis (H2) we compared eMCI, MCI non-Converter and MCI Converter groups. We also ran contrasts across groups to explore whether and to what extent the classification power of these memory tests varies as a function of the diseases continuum. The rationale was that by comparing HOA vs eMCI vs MCI non-Converter we would be able to explore the transition from normal to pathological ageing. By keeping eMCI participants separate from those who entered the MCI group (see classification criteria above) we could compare the investigated memory markers across stages where cognitive decline has had different levels of impact (i.e. from subtle without IADL impact, akin to Objectively Defined Subtle Cognitive Decline ) and those with overt impact on IADL. Hence, by comparing eMCI vs MCI non-Converter vs MCI Converter, we would have the opportunity to map the outcomes from these memory markers to the disease continuum and in so doing test the hypotheses set out for this study. We were also interested in the complementary value of these tests (VSTMBT and FCSRT). We defined complementary value as the ability of these tests to account for larger between-group variance (i.e. adjusted R2 from regression model) when used jointly and individually.
General neuropsychological findings
Summaries of the descriptive and inferential statistics for the demographic variables, general cognitive and functional scales, and the neuropsychological and experimental tasks are presented in Tables 1 and 2, respectively. Of note, HOA and eMCI participants did differ on a number of neuropsychological tasks, but as anticipated, IADL were preserved. eMCI participants and MCI non-converter patients significantly differed on most neuropsychological tasks, confirming that the former group still was in the very early stages of the disease continuum. MCI non-converter and converter significantly differed from HOA on all the neuropsychological tasks. However, as MCI patients progressed along the disease continuum (i.e. MCI non-converter and converter), discrepancies on neuropsychological scores became less apparent. Although this study focused on novel neuropsychological tests, some well-established standardised tests showed excellent abilities to discriminate between individuals in the early stages (HVLT in HOA vs eMCI). Regarding the experimental tasks, the ability of FCSRT and VSTMT to predict group membership showed differences throughout the disease continuum, with opposite patterns of sensitivity at its extremes (preclinical: VSTMBT > FCSRT, advanced prodromal: FCSRT > VSTMBT), and varying levels of complementary status throughout its intermediate stages (see Fig. 2).
Transition from normal to pathological ageing
To predict group membership in the very early stages of cognitive decline, we focused on data (FSCRT and VSTMB) from HOA, eMCI and MCI non-converter. To test H1, we first relied on tests of mean differences (MANOVA/MANCOVA or t-Tests) and later used stepwise linear regression models (see Table 3). Both tests displayed excellent abilities to discriminate between HOA, eMCI and MCI non-converter (HOA > eMCI/MCI non-converter). The VSTMB outperformed the FCSRT only in the preclinical stages (HOA > eMCI).
Exploring the prodromal stages
To explore the more advanced prodromal stages of the disease, we focused on data from eMCI, MCI non-converter and MCI converter. The same analytical approach was followed (see Table 3). Relative to the FCSRT, the VSTMB proved less effective in discriminating eMCI from MCI non-Converter, eMCI from MCI Converter, and MCI non-Converter from MCI Converter. In fact, regression models showed that the VSTMB was excluded as a predictor from all the above contrasts, which only retained the FCSRT. The MANOVA/MANCOVA analyses confirmed that such a limited predictive value of the VSTMBT relative to the FCSRT is explained by its reduced ability to differentiate between groups as soon as patients moved into the prodromal stages of the disease, the point at which the FCSRT becomes more sensitive. These findings too support our H1 and H2.
Exploring the individual and complementary value of the VSTMBT and FCSRT
As reported above, the VSTMBT proved a good predictor of group membership in the early preclinical stages. As soon as the levels of cognitive impairment met criteria for the prodromal stages of the continuum, the FCSRT outperformed the VSTMBT. As Table 3 and Fig. 3 show, the complementary value of these tasks varied as the level of cognitive impairment progressed. It was low at the extremes of the stages of the continuum here explored and higher in the medium stages. The individual and combined predictive value of both tests to discriminate between stages closer to dementia (MCI non-converter and MCI converter) was rather low.
The present longitudinal study was set out to investigate the hypotheses that two memory markers for AD recently recommended by consensus  would differently predict dementia throughout its continuum. Based on previous evidence we predicted that the VSTMBT would be able to discriminate between older adults who are asymptomatic and those who are in the very early stages of cognitive decline more effectively than the FCSRT (H1). However, the FCSRT would discriminate between older adults in the prodromal stages (MCI) who later convert versus those who do not convert to dementia more accurately than the VSTMBT (H2). Our results supported both hypotheses and have some implications for our understanding of neuropsychological assessment to track the transition from normal to pathological ageing and to monitor progression throughout the prodromal stages towards conversion to dementia.
Before discussing these implications, it is worth considering some observations drawn from the background neuropsychological assessment. HOA and eMCI participants differed on a number of neuropsychological tasks, yet eMCI participants were not seeking professional help. As patients with MCI progressed along the disease continuum (i.e. MCI non-Converter and Converter), discrepancies in the neuropsychological scores decreased. Hence, standard neuropsychological tests used in our study appear to be effective for detecting impairments but less so for differentiating risk phenotypes. These shortcomings of off-the-shelf neuropsychological tests have been acknowledged previously [8, 57,58,59,60] and called for new tests to better phenotype dementia and detect risk profiles [8, 57]. Notwithstanding such limitations, the ability of some neuropsychological tests used in our assessment battery to detect very early cognitive impairments, particularly of memory, is also worth highlighting.
The HVLT revealed significant memory differences along the disease continuum, particularly between groups informing the very early stages. Lonie et al.  had previously demonstrated that the Delayed Recall component of the HVLT can discriminate between MCI converters and non-converters over a 4-year follow-up period as accurately as the Visuospatial Paired Associates (PAL) Task from CANTAB . Gustavson et al.  recently reported that the California Verbal Learning Test, which assesses constructs similar to those tested by the HVLT, is an early indicator of MCI risk at an age when few individuals are likely to have yet become biomarker positive. Regarding the experimental tasks, the FCSRT and VSTMT showed differential abilities to predict group membership along the disease continuum. Opposite patterns of sensitivity were observed at the extreme ends of the continuum here explored (preclinical: VSTMBT > FCSRT; advanced prodromal: FCSRT > VSTMBT), and varying levels of complementary status throughout its intermediate stages. These findings lend support to the two hypotheses investigated in this study and suggest that these recently recommended tests [10, 14, 53, 64] shall form part of new memory toolkits to assess and monitor AD.
To investigate the individual and complementary values of the two experimental tasks in informing about the transition from normal to pathological ageing we focused on data from HOA, eMCI and MCI non-Converter. We predicted that the VSTMBT should discriminate well in the earlier stages because it would be able to detect gradually increasing levels of impairments whereas the function assessed by the FCSRT would still be preserved. Didic et al.  suggested that AD affects medial temporal lobe (MTL) structures known to support different memory functions in a graded manner (Fig. 1). Within the MTL, the disease first goes through a subhippocampal stage (Braak and Braak’s stages I and II, which correspond to the asymptomatic stages) selectively impairing regions of the anterior MTL network (i.e. perirhinal and lateral entorhinal cortex, the anterior hippocampus, and the temporo-polar cortex). Damage to these regions impairs context-free memory [65, 66]. As the disease progresses to the limbic stage (i.e. Braak and Braak stages III and IV, which correspond to the mild cognitive impairment stage (MCI)), pathology spreads to the posterior MTL network (i.e. parahippocampal cortex, posterior hippocampus, and posterior cingulate) which plays a critical role in context-rich memory. Hence, this model predicts that memory functions such as those assessed by the VSTMBT would be affected earlier than those assessed by selective reminding paradigms such as the FCSRT and the MCT.
Dissociations of these forms of binding in populations with or at risk of AD have been observed earlier. Studies carried out in preclinical samples of carriers of mutations that inevitably lead to familial AD (i.e. E280A-PSEN1 [54, 67]) reported VSTMB deficits in asymptomatic carriers who were about 10 years younger than the average age of onset of dementia in this familial variant. However, using the MCT to assess members of the same kindred, Romero –Vanegas et al.  found impairments only when carriers were in the MCI stages. Using another context-rich memory test memory test, the Paired Associates Learning of WMS ), Parra et al.  reported that the VSTMBT significantly outperformed it when discriminating between asymptomatic carriers and non-carrier controls. Similar results were reported by Koppara et al.  in patients with subjective cognitive decline who presented with VSTMB impairments within an otherwise normal neuropsychological profile. We further observed that in confirmed cases of AD, both tests achieved excellent levels of classification at the individual level, even if the VSTMBT outperformed the FCSRT .
More recent studies that combined VSTMB tests with biomarker assessments (i.e. PET), have confirmed that such ability is affected by the very early stages of AD. For instance, Norton et al.  reported correlations between performance on the VSTMBT and amyloid deposits in asymptomatic carriers of the mutation E280A-PSEN1. Interestingly, when the disease progressed to the symptomatic stages, such correlations were no longer statistically reliable, likely due to a profound impairment in VSTMB (performance close to floor). The authors suggested that VSTMB impairments may effectively predict dementia in those affected by AD in the preclinical stages. The same research group  recently reported correlations between performance on context-rich tests (Latin American Spanish version of the Face-Name Associative Memory Exam). Significant correlations were not observed when data from only asymptomatic carriers entered the statistical models. However, when data from asymptomatic and symptomatic carriers were lumped together, correlations between memory scores and amyloid deposits reached significance, suggesting that when it comes to context-rich memory tests, such an association becomes apparent in rather advanced pathological stages. Relying on the recently proposed biomarker framework , Papp et al.  reported evidence of impairment in the binding component of the MCT (i.e. cued recall) only between participants in Stage 0 (Aβ−/ND−) and Stage 2 (Aβ+/ND+), but not between those in Stage 0 and Stage 1 (Aβ+/ND−). Cecchini et al.  recently reported that deficits in VSTMB are detectable in individuals with brain amyloid deposition in the absence of overt neurodegeneration (N aspect of the A/T/N framework, ) in the AD continuum. Taken together studies which included the VSTMBT, selective reminding paradigms, and AD biomarkers lend support to Didic et al.’s  hypothetical model.
In fact, accrued evidence using the FCSRT suggests that mapping memory decline along the AD continuum is now possible. The test has unveiled memory decline during subclinical Aβ levels  and has demonstrated to be able to predict incident MCI [76,77,78]. Variables drawn from this test have proved informative of the stages of such a continuum [79, 80]. For instance, a decline in free recall, which is linked to retrieval impairments, tends to inform about stages where either Aβ  or mild tauopathy  become detectable in still asymptomatic individuals. However, a decline of total recall, which is linked to retrieval and storage impairments (demonstrated by the inability to benefit from cuing), seems to reflect the symptomatic stages (Aβ, tau, and neurodegeneration, ). As it is encouraging, this evidence also triggers several questions.
Are current approaches to staging the AD continuum appropriate? The recently proposed framework is aimed at detecting neuropathological signatures using biomarkers [5, 6]. Should these efforts prove fruitful, strategies then focus on identifying the cognitive and functional decline that ensues (e.g. [11, 82]). A growing number of studies are reporting cognitive deficits in subthreshold [33, 63, 75, 83, 84] and subclinical [71, 73, 79] stages of the disease continuum. The former evidence comes from studies using Aβ markers in the brain, CSF or blood [5, 6]. The latter is commonly documented using the Clinical Dementia Rating Scale (CDR=0) . There is consensus that current biomarkers for AD lack specificity [86, 87]. Moreover, the CDR does not allow staging the preclinical/predementia stages of AD, which have become the most investigated in recent years [41, 88, 89]. Therefore, we need to continue refining our understanding and tools to better map cognition along the AD continuum, particularly in its preclinical stages.
Are we mapping promising memory markers for AD onto the correct neural correlates? Based on current understanding [12, 20, 90], tests that tap into the function of the hippocampus are not good candidates to detect the pre-symptomatic stages of AD (i.e. transentorhinal stages, see Fig. 1). So, what brain regions are the memory binding tests investigated here really taxing? Neuroimaging studies have consistently confirmed that the sensitivity of the FCSRT lies on its ability to index the function of the hippocampus [80, 91]. Of note, VSTMB functions can be carried out without functional hippocampi [92,93,94]. The evidence that VSTMB deficits are associated to increase Aβ prior to tau pathology  and neurodegeneration  suits the available neuroanatomical evidence. However, if the FCSRT is informing about the hippocampal stages of AD, the association of such deficits to Aβ deposits (i.e. Stage of Objective Memory Impairment 1, ) prior to tau pathology becomes more challenging to interpret. Parra  recently suggested the need to zoom out if we are to unveil more promising neural correlates of memory functions sensitive to AD. Future efforts will be needed to continue mapping these memory markers onto the continuum of neuropathological events that lead to AD dementia.
The variability of results across the studies discussed above could also reflect task-related artefacts rather than meaningful cognitive decline. For instance, over the last few years, the FCSRT has undergone substantial revisions to improve its construct and cultural validity. Buschke  revised the task to improve the binding construct via the memory capacity test (MCT). In fact, Papp et al.  recently showed that the MCT version holds sensitivity for the preclinical amyloidosis seen in Stage 1 (free recall) and the amyloidosis and neurodegeneration seen in Stage 2 (free and cued recall). The task has been devised in both “word” and “picture” formats with the latter yielding better outcomes . Due to the superiority effect of pictures over words and practice at cued recall in the study phase before the test phase , scores on the two versions are quite different (an 8-point difference in FR and a 4-point difference in TR ). This can explain why the picture version of the FCSRT has yielded better results in illiterate populations .
The VSTMBT too has undergone scrutiny. For instance, an earlier version of the test followed titration procedures [15, 54] which allowed confirming the specificity of such a deficit but would be too challenging for implementation in clinical settings . Parra et al.  later reported the different task settings that may suit different research aims. For instance, the 2-item version was suggested as the most suitable for the symptomatic stages whereas the 3-item version would achieve the best sensitivity in pre-symptomatic stages. Such proposals have been neither extensively explored nor confirmed. Therefore, as suggested by the Joint Program for Neurodegenerative Diseases Working Group , the two tests have proved informative of preclinical AD but their complementary value needs to be further investigated in order to address the above knowledge gaps (e.g. ).
In the current study, we demonstrated that both tests hold excellent abilities to discriminate between HOA, eMCI and MCI non-Converter (HOA > eMCI/MCI non-Converter). The VSTMB outperformed the FCSRT only in the preclinical stages (HOA > eMCI). As the disease progressed, (i.e. eMCI/MCI non-Converter) performance on the VSTMBT became less differentiated between groups, whereas that on the FCSRT continued to effectively discriminate between them. These findings, although encouraging, raise a number of concerns for promising neuropsychological assessments aimed at the preclinical stages of AD. Logie et al.  suggested that a good memory marker for AD should avoid very low-performance levels when the symptoms become severe. Regarding the VSTMBT, which relies on the Change Detection Paradigm, chance levels are set at 50%. This is a constraint of the method. To overcome it, Parra et al.  suggested strategies such as titrating the task difficulty (i.e. memory load, see above and also [54, 67, 70]). In the present study, we chose to use one set size (i.e. 3) for the sake of comparability of findings along the disease continuum, particularly considering our aim of anticipating the MCI stages [9, 23, 63, 83, 84].
The literature supporting the validity of the FCSRT to predict dementia in longitudinal cohorts of MCI patients has grown significantly over the last few years (e.g. [28, 77, 79, 80, 99,100,101,102,103]). This is the first report on the use of the VSTMBT in such longitudinal cohorts. Our results support the notion that the neuropsychological assessment of AD, in its new conceptualization (i.e. a continuum of clinical and pathological stages), ought to abandon the one-size-fits-all approach. Assessment protocols aimed at investigating AD-related disorders (i.e. detection, prediction) need to consider the evidence presented here. Belleville et al.  acknowledged that a cognitive toolkit intended to identify AD at the pre-dementia stage would need tasks that are early indicators and others that might suggest imminent progression.
The fact that the VSTMBT detects AD-related changes early (see [54, 67, 70]) and then performance drops to near or chance levels (see ) has pros and cons. The positive aspect of this is that we have long-needed tests that can detect the very early stages of the disease process, preferably, when people are unaware of or are very little concerned about any cognitive or functional impairment. We have learned that at this stage, the VSTMBT is taxing the early accumulation of amyloid in at-risk individuals even before tau deposits or neurodegeneration become apparent [33, 71, 74]. Such a test would be an ideal tool for clinical trials aiming at dementia prevention as they could enhance recruitment strategies by selecting who will likely meet inclusion criteria (e.g. Aβ+).
One final aspect concerns our control participants. Most participants who were allocated to the eMCI group entered the study as self-referred healthy volunteers (see Fig. 2). Relative to those who met criteria for HOA, eMCI participants displayed significant differences on various standard neuropsychological assessments. This is striking, as these individuals, at the time of the study, had not sought help and a few were only mildly concerned about their cognitive abilities. There is consensus that in the new context of AD research and clinical practice (i.e. following the biological definition of AD), deciding who is a control individual is proving as challenging as deciding who is in the early stages of the disease . There are two issues worth considering here. First, the source of these control volunteers and second, awareness of and stigmas against early symptoms of dementia. Volunteers entering as controls were recruited from the Psychology Volunteer Panel at the University of Edinburgh o were relatives of patients with dementia. In the case of the former source, there is awareness about the impact that such selective samples could have on the interpretation of data . Older adults involved in such panels (1) regularly support research and (2) are often highly educated, thus representing a rather biassed sub-sample of the relevant population. Importantly, they frequently undergo cognitive testing, which grants them additional cognitive reserves and resilience [29, 106, 107]. Therefore, it is not entirely surprising that these older adults overlook or underestimate the level of decline in cognitive abilities here identified. Although volunteering has been considered a protective action against cognitive decline , managers of volunteer panels need to be aware of these risks. In the case of the latter source of recruitment (i.e. relatives of patients with dementia), there is evidence that the burden posed by the patients’ level of cognitive and behavioural problems causes caregiver stress, which in turn leads to impaired cognitive functioning [108, 109]. Therefore, volunteer panels and dyads of dementia patients, two common sources of recruitment in ageing and dementia studies, will need revised approaches if we are going to progress in the new dementia research context with more confidence and reliability. The second issue, awareness of and stigmas against early symptoms of dementia, is also relevant  and suggests that more work is needed to continue raising awareness about the fact that ageing is not a disease  and that seeking help early is the best approach to mitigate the dramatic impact that departures from its normal trajectory will carry.
There are some limitations that need to be considered when interpreting the findings here reported. The first one is the rather small sample size. However, as shown by our inferential statistics, effect sizes were rather large for the hypotheses tested. Moreover, both experimental tests used in this study have demonstrated to hold informative value to identify individual patients and not just during group comparisons. For instance, the VSTMBT test had shown sensitivity and specificity value of over 77% in completely asymptomatic individuals  and of 100% for patients with dementia (see Della Sala et al.  who reported an area under the curve of 96% for the FCSRT). Nevertheless, efforts will be needed to expand such samples within disease stages and along the continuum, and such efforts are already ongoing .
Another limitation is the nature of the control participants who entered this study. This is not a representative sample. Even if unpaired cognitively, it is still possible that some of these older adults were already accumulating disease pathology (see ). Together with the report by Parra et al. , this evidence suggests that some of those who entered our HOA group may still be classified as not healthy controls if the approach recommended by Bos et al.  is followed. This limitation is shared by many studies in the field and urgent strategies will be necessary to address this important caveat. Although we monitored our participants yearly, we did not receive confirmation of the precise date the dementia diagnosis was given but rather the clinical status at the end of the study (see Methods for more details). Time to dementia onset is an important variable for models aimed at investigating the predictive value of assessment tools. Future analysis involving longitudinal assessments with the VSTMBT should pursue such information. One final limitation of this study is that we did not have biomarkers evidence to assess the biological status of our MCI patients and hence we choose to adhere to the definition of Alzheimer’s clinical syndrome as recently recommended [1, 5, 6].
In the current longitudinal study, we have demonstrated that neuropsychological assessments for AD shall move away from the notion of one-size-fits-all. A memory toolkit for AD needs to be considered which contains tools that are early indicators and others that might suggest imminent progression. This study, the first one reporting on the use of the VSTMBT in the longitudinal assessment of MCI, suggests that the VSTMBT may provide an early indicator for such a toolkit while the FCSRT seems to be an excellent tool to assess imminent progression.
Availability of data and materials
This is the first publication emerging from this longitudinal study. The team is currently professing data to generate further publication. The data used to prepare this manuscript can be available on request.
Addenbrooke’s Cognitive Examination Revised
Early Mild Cognitive Impairment Group
Free and Cued Selective Reminding Test
Geriatric Depression Scale
Healthy Older Adults Group
Hopkins Verbal Learning Test
Instrumental Activities of Daily Living
Multi-domain amnestic MCI
Multivariate Analysis of Variance/Covariance
- MCI converter:
MCI patients who developed dementia in the follow-up period
- MCI non-converter:
MCI patients who did not develop dementia in the follow-up period
Mild cognitive impairment stage
Memory capacity test
Medial temporal lobe
Neuroprogressive and Dementia Network
National Health Services
Scottish Dementia Clinical Research Network interest register
Selective Reminding Tests
- TMT-A and TMT-B:
Trail Making Test Parts A and B
Test of Premorbid Functions
Visual Short-Term Memory Binding
Visual Short-Term Memory Binding Test
Dubois B, Hampel H, Feldman HH, Scheltens P, Aisen P, Andrieu S, et al. Preclinical Alzheimer's disease: definition, natural history, and diagnostic criteria. Alzheimers Dement. 2016;12(3):292–323.
Jack CR Jr, Albert MS, Knopman DS, McKhann GM, Sperling RA, Carrillo MC, et al. Introduction to the recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7(3):257–62.
Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, et al. Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7(3):280–92.
Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, et al. 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. Alzheimers Dement. 2011;7(3):270–9.
Jack CR Jr, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, et al. NIA-AA Research Framework: toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018;14(4):535.
Jack CR, Bennett DA, Blennow K, Carrillo MC, Feldman HH, Frisoni GB, et al. A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers. Neurology. 2016;87(5):539–47.
Sperling RA, Karlawish J, Johnson KA. Preclinical Alzheimer disease [mdash] the challenges ahead. Nat Rev Neurol. 2013;9(1):54–8.
Rentz D, Parra MA, Amariglio R, Stern Y, Sperling R, Ferris S. Promising developments in neuropsychological approaches for the detection of preclinical Alzheimer's disease: a selective review. Alzheimers Res Ther. 2013;5(6):58.
Duke Han S, Nguyen CP, Stricker NH, Nation DA. Detectable Neuropsychological differences in early preclinical Alzheimer's disease: a meta-analysis. Neuropsychol Rev. 2017;27(4):305–25.
Costa A, Bak T, Caffarra P, Caltagirone C, Ceccaldi M, Collette F, et al. The need for harmonisation and innovation of neuropsychological assessment in neurodegenerative dementias in Europe: consensus document of the Joint Program for Neurodegenerative Diseases Working Group. Alzheimers Res Ther. 2017;9(1):27.
Jack CR Jr, Wiste HJ, Therneau TM, Weigand SD, Knopman DS, Mielke MM, et al. Associations of amyloid, tau, and neurodegeneration biomarker profiles with rates of memory decline among individuals without dementiaamyloid, tau, and neurodegeneration biomarker profiles and memory decline in individuals without dementiaamyloid, tau, and neurodegeneration biomarker profiles and memory decline in individuals without dementia. JAMA. 2019;321(23):2316–25.
Didic M, Barbeau EJ, Felician O, Tramoni E, Guedj E, Poncet M, et al. Which memory system is impaired first in Alzheimer's disease? J Alzheimers Dis. 2011;27(1):11–22.
Rentz D, Parra MA, Amariglio R, Stern Y, Sperling R, Ferris S. Promising developments in neuropsychological approaches for the detection of preclinical Alzheimer’s disease: a selective review. Alzheimers Res Ther. 2013;5(6):58.
Logie RH, Parra MA, Della Sala S. From cognitive science to dementia assessment. Policy Insights Behav Brain Sci. 2015;2(1):81–91.
Parra MA, Abrahams S, Logie RH, Della Sala S. Visual short-term memory binding in Alzheimer's disease and depression. J Neurol. 2010;257(7):1160–9.
Grober E, Lipton RB, Hall C, Crystal H. Memory impairment on free and cued selective reminding predicts dementia. Neurology. 2000;54(4):827–32.
Vogel EK, Woodman GF, Luck SJ. Storage of features, conjunctions and objects in visual working memory. J Exp Psychol Hum Percept Perform. 2001;27(1):92–114.
Luck SJ, Vogel EK. The capacity of visual working memory for features and conjunctions. Nature. 1997;390(6657):279–81.
Wheeler ME, Treisman AM. Binding in short-term visual memory. J Exp Psychol Gen. 2002;131(1):48–64.
Braak H, Thal DR, Ghebremedhin E, Del TK. Stages of the pathologic process in Alzheimer disease: age categories from 1 to 100 years. J Neuropathol Exp Neurol. 2011;70(11):960–9.
Braak H, Braak E. Evolution of the neuropathology of Alzheimer's disease. Acta Neurol Scand Suppl. 1996;165(3):12.
Parra MA. Barriers to effective memory assessments for Alzheimer's disease. J Alzheimers Dis. 2022.
Jones JD, Uribe C, Bunch J, Thomas KR. Beyond PD-MCI: objectively defined subtle cognitive decline predicts future cognitive and functional changes. J Neurol. 2021;268(1):337–45.
Buschke H, Kuslansky G, Katz M, Stewart WF, Sliwinski MJ, Eckholdt HM, et al. Screening for dementia with the memory impairment screen. Neurology. 1999;52(2):231–8.
Buschke H, Sliwinski MJ, Kuslansky G, Lipton RB. Diagnosis of early dementia by the Double Memory Test: encoding specificity improves diagnostic sensitivity and specificity. Neurology. 1997;48(4):989–97.
Buschke H. Rationale of the memory binding test. In: Nilsson L, Ohta H, editors. Dementia and Memory. First edn. East Sussex: Psychology Press; 2014. p. 55–71.
Grober E, Hall CB, Lipton RB, Zonderman AB, Resnick SM, Kawas C. Memory impairment, executive dysfunction, and intellectual decline in preclinical Alzheimer's disease. J Int Neuropsychol Soc. 2008;14(2):266–78.
Grober E, An Y, Lipton RB, Kawas C, Resnick SM. Timing of onset and rate of decline in learning and retention in the pre-dementia phase of Alzheimer's disease. J Int Neuropsychol Soc. 2019;25(7):699–705.
Stern Y. How can cognitive reserve promote cognitive and neurobehavioral health? Arch Clin Neuropsychol. 2021;36(7):1291–5.
León I, García-García J, Roldán-Tapia L. Estimating cognitive reserve in healthy adults using the Cognitive Reserve Scale. PLoS One. 2014;9(7).
Parra MA, Calia C, Garcia AF, Olazaran-Rodriguez J, Hernandez-Tamames JA, Alvarez-Linera J, et al. Refining memory assessment of elderly people with cognitive impairment: Insights from the short-term memory binding test. Arch Gerontol Geriatr. 2019;83:114–20.
Bos I, Vos SJB, Jansen WJ, Vandenberghe R, Gabel S, Estanga A, et al. Amyloid-β, tau, and cognition in cognitively normal older individuals: examining the necessity to adjust for biomarker status in normative data. Front Aging Neurosci. 2018;10:193.
Parra MA, Gazes Y, Stern Y. From cognition to molecules: tracking brain amyloid-Beta with memory markers for Alzheimer’s disease. Alzheimers Dementia. 2017;13(7):P692.
Hachinski VC, Iliff LD, Zilhka E, Du Boulay GH, McAllister VL, Marshall J, et al. Cerebral blood flow in dementia. Arch Neurol. 1975;32(9):632–7.
Yesavage JA, Brink TL, Rose TL, Lum O, Huang V, Adey M, et al. Development and validation of a geriatric depression screening scale: a preliminary report. J Psychiatr Res. 1982;17(1):37–49.
Fleisher AS, Sowell BB, Taylor C, Gamst AC, Petersen RC, Thal LJ. Clinical predictors of progression to Alzheimer disease in amnestic mild cognitive impairment. Neurology. 2007;68(19):1588–95.
Petersen RC, Negash S. Mild cognitive impairment: an overview. CNS Spectr. 2008;13(1):45–53.
Petersen RC, Knopman DS. MCI is a clinically useful concept. Int Psychogeriatr. 2006;18(3):394–402.
Winblad B, Palmer K, Kivipelto M, Jelic V, Fratiglioni L, Wahlund LO, et al. Mild cognitive impairment--beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. J Intern Med. 2004;256(3):240–6.
Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179–86.
Morris JC. Revised criteria for mild cognitive impairment may compromise the diagnosis of Alzheimer disease dementia. Arch Neurol. 2012.
Fernández AJ, García E, Parra MA, Guinea SF. Clustering executive functions yields mci profiles that significantly predict conversion to Alzheimer's disease dementia. Alzheimers Dementia. 2019;15(7):P797–8.
Yaffe K, Petersen RC, Lindquist K, Kramer J, Miller B. Subtype of mild cognitive impairment and progression to dementia and death. Dement Geriatr Cogn Disord. 2006;22(4):312–9.
Maruta C, Guerreiro M, de Mendonca A, Hort J, Scheltens P. The use of neuropsychological tests across Europe: the need for a consensus in the use of assessment tools for dementia. Eur J Neurol. 2011;18(2):279–85.
Shulman KI, Herrmann N, Brodaty H, Chiu H, Lawlor B, Ritchie K, et al. IPA survey of brief cognitive screening instruments. Int Psychogeriatr. 2006;18(2):281–94.
Mioshi E, Dawson K, Mitchell J, Arnold R, Hodges JR. The Addenbrooke's Cognitive Examination Revised (ACE-R): a brief cognitive test battery for dementia screening. Int J Geriatr Psychiatry. 2006;21(11):1078–85.
Benedict RHB, Schretlen D, Groninger L, Brandt J. Hopkins Verbal Learning Test – Revised: normative data and analysis of inter-form and test-retest reliability. Clin Neuropsychol. 1998;12(1):43–55.
Fastenau PS, Denburg NL, Hufford BJ. Adult norms for the Rey-Osterrieth Complex Figure Test and for supplemental recognition and matching trials from the Extended Complex Figure Test. Clin Neuropsychol. 1999;13(1):30–47.
Tombaugh TN. Trail Making Test A and B: normative data stratified by age and education. Arch Clin Neuropsychol. 2004;19:203–14.
Tombaugh TN, Kozak J, Rees L. Normative data stratified by age and education for two measures of verbal fluency: FAS and animal naming. Arch Clin Neuropsychol. 1999;14(2):167–77.
Jaeger J. Digit Symbol Substitution Test: The case for sensitivity over specificity in neuropsychological testing. J Clin Psychopharmacol. 2018;38(5):513–9.
Wechsler D. Test of premorbid functioning. UK version. London: Pearson Assessment; 2011.
Della Sala S, Kozlova I, Stamate A, Parra MA. A transcultural cognitive marker of Alzheimer's disease. Int J Geriatr Psychiatry. 2016;33(6):849–56.
Parra MA, Abrahams S, Logie RH, Mendez LG, Lopera F, Della Sala S. Visual short-term memory binding deficits in familial Alzheimer's disease. Brain. 2010;133(9):2702–13.
Lemos R, Simoes MR, Santiago B, Santana I. The free and cued selective reminding test: validation for mild cognitive impairment and Alzheimer's disease. J Neuropsychol. 2015;9(2):242–57.
Frasson P, Ghiretti R, Catricala E, Pomati S, Marcone A, Parisi L, et al. Free and cued selective reminding test: an Italian normative study. Neurol Sci. 2011;32(6):1057–62.
Junquera A, García-Zamora E, Olazarán J, Parra MA, Fernández-Guinea S. Role of executive functions in the conversion from mild cognitive impairment to dementia. J Alzheimers Dis. 2020;77(2):641–53.
Parra MA, Butler S, McGeown WJ, Brown Nicholls LA, Robertson DJ. Globalising strategies to meet global challenges: the case of ageing and dementia. J Glob Health. 2019;9(2):020310.
Bondi MW, Edmonds EC, Jak AJ, Clark LR, Delano-Wood L, McDonald CR, et al. Neuropsychological criteria for mild cognitive impairment improves diagnostic precision, biomarker associations, and progression rates. J Alzheimers Dis. 2014;42(1):275–89.
Salmon DP, Bondi MW. Neuropsychological assessment of dementia. Annu Rev Psychol. 2009;60:257–82.
Lonie JA, Parra-Rodriguez MA, Tierney KM, Herrmann LL, Donaghey C, O'Carroll RE, et al. Predicting outcome in mild cognitive impairment: 4-year follow-up study. Br J Psychiatry. 2010;197(2):135–40.
Blackwell AD, Sahakian BJ, Vesey R, Semple JM, Robbins TW, Hodges JR. Detecting dementia: novel neuropsychological markers of preclinical Alzheimer's disease. Dement Geriatr Cogn Disord. 2004;17(1-2):42–8.
Gustavson DE, Elman JA, Sanderson-Cimino M, Franz CE, Panizzon MS, Jak AJ, et al. Extensive memory testing improves prediction of progression to MCI in late middle age. Alzheimers Dementia (Amsterdam, Netherlands). 2020;12(1):e12004.
Killin L, Abrahams S, Parra MA, Della Sala S. The effect of age on the FCSRT-IR and temporary visual memory binding. Int Psychogeriatr. 2017;30(3):331–40.
Gour N, Ranjeva JP, Ceccaldi M, Confort-Gouny S, Barbeau E, Soulier E, et al. Basal functional connectivity within the anterior temporal network is associated with performance on declarative memory tasks. Neuroimage. 2011;58(2):687–97.
Wolk DA, Mancuso L, Kliot D, Arnold SE, Dickerson BC. Familiarity-based memory as an early cognitive marker of preclinical and prodromal AD. Neuropsychologia. 2013;51(6):1094–102.
Parra MA, Della Sala S, Abrahams S, Logie RH, Mendez LG, Lopera F. Specific deficit of colour-colour short-term memory binding in sporadic and familial Alzheimer's disease. Neuropsychologia. 2011;49(7):1943–52.
Romero-Vanegas SJ, Valencia-Marín CM, Aguirre-Acevedo DC, Buschke H, Lopera F. Verbal episodic memory at the preclinical and early phases of familiar early-onset Alzheimer disease caused by E280A mutation at PS1. Acta Neurol Colomb. 2010;26:177–94.
Wechsler D. The Wechsler memory scale-III UK manual. San Antonio: Psychological Corporation; 1997.
Koppara A, Frommann I, Polcher A, Parra MA, Maier W, Jessen F, et al. Feature Binding Deficits in Subjective Cognitive Decline and in Mild Cognitive Impairment. J Alzheimers Dis. 2015;48(Suppl 1):S161–70.
Norton DJ, Parra Rodriguez MA, Sperling RA, Baena A, Guzman-Velez E, Jin DS, et al. Visual short-term memory relates to tau and amyloid burdens in preclinical autosomal dominant Alzheimer’s disease. Alzheimers Res Ther. 2020;12(1):99.
Vila-Castelar C, Muñoz N, Papp KV, Amariglio RE, Baena A, Guzmán-Vélez E, et al. The Latin American Spanish version of the Face-Name Associative Memory Exam is sensitive to cognitive and pathological changes in preclinical autosomal dominant Alzheimer’s disease. Alzheimers Res Ther. 2020;12(1):104.
Papp KV, Amariglio RE, Mormino E, Hedden T, Dekhytar M, Johnson KA, et al. Free and cued memory in relation to biomarker-defined Abnormalities in clinically normal older Adults and those at risk for Alzheimer's disease. Neuropsychologia. 2015.
Cecchini MA, Yassuda MS, Squarzoni P, Coutinho AM, de Paula FD, Duran FLS, et al. Deficits in short-term memory binding are detectable in individuals with brain amyloid deposition in the absence of overt neurodegeneration in the Alzheimer’s disease continuum. Brain Cogn. 2021;152:105749.
Insel PS, Donohue MC, Sperling R, Hansson O, Mattsson-Carlgren N. The A4 study: β-amyloid and cognition in 4432 cognitively unimpaired adults. Ann Clin Transl Neurol. 2020;7(5):776–85.
Hanseeuw BJ, Betensky RA, Mormino EC, Schultz AP, Sepulcre J, Becker JA, et al. PET staging of amyloidosis using striatum. Alzheimers Dement. 2018;14(10):1281–92.
Grober E, Wang C, Kitner-Triolo M, Lipton RB, Kawas C, Resnick SM. Prognostic value of learning and retention measures from the free and cued selective reminding test to identify incident mild cognitive impairment. J Int Neuropsychol Soc. 2022;28(3):292–9.
Mura T, Coley N, Amieva H, Berr C, Gabelle A, Ousset PJ, et al. Cognitive decline as an outcome and marker of progression toward dementia, in early preventive trials. Alzheimers Dement. 2022;18(4):676–87.
Grober E, Lipton RB, Sperling RA, Papp KV, Johnson KA, Rentz DM, et al. Associations of Stages of Objective Memory Impairment (SOMI) with amyloid PET and structural MRI. A4 Study. 2022. https://doi.org/10.1212/WNL.0000000000200046.
Grober E, Veroff AE, Lipton RB. Temporal unfolding of declining episodic memory on the free and cued selective reminding test in the predementia phase of Alzheimer's disease: Implications for clinical trials. Alzheimers Dementia (Amsterdam, Netherlands). 2018;10:161–71.
Mormino EC, Papp KV, Rentz DM, Donohue MC, Amariglio R, Quiroz YT, et al. Early and late change on the preclinical Alzheimer's cognitive composite in clinically normal older individuals with elevated amyloid β. Alzheimers Dement. 2017;13(9):1004–12.
Ghisays V, Goradia DD, Protas H, Bauer RJ 3rd, Devadas V, Tariot PN, et al. Brain imaging measurements of fibrillar amyloid-β burden, paired helical filament tau burden, and atrophy in cognitively unimpaired persons with two, one, and no copies of the APOE ε4 allele. Alzheimers Dement. 2020;16(4):598–609.
Shen XN, Kuo K, Yang YX, Li HQ, Chen SD, Cui M, et al. Subtle cognitive impairment as a marker of Alzheimer's pathologies and clinical progression in cognitively normal individuals. Alzheimers Dementia (Amsterdam, Netherlands). 2021;13(1):e12198.
Thomas KR, Bangen KJ, Edmonds EC, Weigand AJ, Walker KS, Bondi MW, et al. Objective subtle cognitive decline and plasma phosphorylated tau181: Early markers of Alzheimer's disease-related declines. Alzheimers Dementia (Amsterdam, Netherlands). 2021;13(1):e12238.
Morris JC, Ernesto C, Schafer K, Coats M, Leon S, Sano M, et al. Clinical dementia rating training and reliability in multicenter studies: the Alzheimer's Disease Cooperative Study experience. Neurology. 1997;48(6):1508–10.
Khoury R, Ghossoub E. Diagnostic biomarkers of Alzheimer’s disease: A state-of-the-art review. Biomarkers Neuropsychiatry. 2019;1:100005.
Langford O, Raman R, Sperling RA, Cummings J, Sun CK, Jimenez-Maggiora G, et al. Predicting amyloid burden to accelerate recruitment of secondary prevention clinical trials. J Prev Alzheimers Dis. 2020;7(4):213–8.
Wada-Isoe K, Kikuchi T, Umeda-Kameyama Y, Mori T, Akishita M, Nakamura Y. Global Clinical Dementia Rating Score of 0.5 May not be an accurate criterion to identify individuals with mild cognitive impairment. J Alzheimers Dis Rep. 2019;3(1):233–9.
Fagan AM, Vos SJB. Preclinical Alzheimer's disease criteria. Lancet Neurol. 2013;12(12):1134.
Braak E, Griffing K, Arai K, Bohl J, Bratzke H, Braak H. Neuropathology of Alzheimer's disease: what is new since A. Alzheimer? Eur Arch Psychiatry Clin Neurosci. 1999;249(Suppl 3):14–22.
Sarazin M, Chauvire V, Gerardin E, Colliot O, Kinkingnehun S, de Souza LC, et al. The amnestic syndrome of hippocampal type in Alzheimer's disease: an MRI study. J Alzheimers Dis. 2010;22(1):285–94.
Jonin P-Y, Calia C, Muratot S, Belliard S, Duche Q, Barbeau EJ, et al. Refining understanding of working memory buffers through the construct of binding: Evidence from a single case informs theory and clinical practise. Cortex. 2019;112:37.
Parra MA, Fabi K, Luzzi S, Cubelli R, Hernandez VM, Della Sala S. Relational and conjunctive binding functions dissociate in short-term memory. Neurocase. 2015;21(1):56–66.
Baddeley A, Jarrold C, Vargha-Khadem F. Working memory and the hippocampus. J Cogn Neurosci. 2011;23(12):3855–61.
Zimmerman ME, Katz MJ, Wang C, Burns LC, Berman RM, Derby CA, et al. Comparison of Word vs. Picture version of the Free and Cued Selective Reminding Test (FCSRT) in older adults. In: Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring. vol. 1: Elsevier; 2015. p. 94–100.
Grober E, Merling A, Heimlich T, Lipton RB. Free and cued selective reminding and selective reminding in the elderly. J Clin Exp Neuropsychol. 1997;19(5):643–54.
Montesinos R, Parodi JF, Diaz MM, Herrera-Perez E, Valeriano-Lorenzo E, Soto A, et al. Validation of picture free and cued selective reminding test for illiteracy in Lima, Peru. Am J Alzheimers Dis Other Dement. 2022;37:15333175221094396.
Slachevsky A, Zitko P, Martínez-Pernía D, Forno G, Court FA, Lillo P, et al. GERO Cohort Protocol, Chile, 2017–2022: community-based cohort of functional decline in subjective cognitive complaint elderly. BMC Geriatr. 2020;20(1):505.
Grande G, Vanacore N, Vetrano DL, Cova I, Rizzuto D, Mayer F, et al. Free and cued selective reminding test predicts progression to Alzheimer's disease in people with mild cognitive impairment. Neurol Sci. 2018;39(11):1867–75.
Matias-Guiu JA, Cabrera-Martín MN, Curiel RE, Valles-Salgado M, Rognoni T, Moreno-Ramos T, et al. Comparison between FCSRT and LASSI-L to Detect Early Stage Alzheimer's Disease. J Alzheimers Dis. 2018;61(1):103–11.
Sala I, Illán-Gala I, Alcolea D, Sánchez-Saudinós MB, Salgado SA, Morenas-Rodríguez E, et al. Diagnostic and Prognostic Value of the Combination of Two Measures of Verbal Memory in Mild Cognitive Impairment due to Alzheimer's Disease. J Alzheimers Dis. 2017;58(3):909–18.
Lemos R, Afonso A, Martins C, Waters JH, Blanco FS, Simoes MR, et al. Selective reminding and free and cued selective reminding in mild cognitive impairment and Alzheimer disease. Appl Neuropsychol Adult. 2016;23(2):85–93.
Grober E, Sanders AE, Hall C, Lipton RB. Free and cued selective reminding identifies very mild dementia in primary care. Alzheimer Dis Assoc Disord. 2010;24(3):284–90.
Belleville S, Fouquet C, Hudon C, Zomahoun HTV, Croteau J. Consortium for the Early Identification of Alzheimer’s d-Q: Neuropsychological measures that predict progression from mild cognitive impairment to Alzheimer's type dementia in older adults: a systematic review and meta-analysis. Neuropsychol Rev. 2017;27(4):328–53.
Ganguli M, Lytle ME, Reynolds MD, Dodge HH. Random versus volunteer selection for a community-based study. J Gerontol Ser A. 1998;53A(1):M39–46.
Infurna FJ, Okun MA, Grimm KJ. Volunteering is associated with lower risk of cognitive impairment. J Am Geriatr Soc. 2016;64(11):2263–9.
Stern Y, Arenaza-Urquijo EM, Bartrés-Faz D, Belleville S, Cantilon M, Chetelat G, et al. Whitepaper: defining and investigating cognitive reserve, brain reserve, and brain maintenance. Alzheimers Dement. 2020;16(9):1305–11.
de Vugt ME, Jolles J, van Osch L, Stevens F, Aalten P, Lousberg R, et al. Cognitive functioning in spousal caregivers of dementia patients: findings from the prospective MAASBED study. Age Ageing. 2006;35(2):160–6.
Oken BS, Fonareva I, Wahbeh H. Stress-related cognitive dysfunction in dementia caregivers. J Geriatr Psychiatry Neurol. 2011;24(4):191–8.
Fletcher JR. Destigmatising dementia: The dangers of felt stigma and benevolent othering. Dementia. 2021;20(2):417–26.
Rattan SI. Aging is not a disease: implications for intervention. Aging Dis. 2014;5(3):196–202.
Parra MA, Muniz-Terrera G, Danso SO, Ritchie K, Ritchie CW. Memory assessment and dementia risk in the PREVENT study. In: Alzheimer's and Dementia: The Journal of the Alzheimer's Association; 2021. p. 2021.
The support from the Alzheimer’s Scotland Dementia Research Centre and the Centre for Cognitive Ageing and Cognitive Epidemiology part of the cross-council Lifelong Health and Wellbeing Initiative (MR/K026992/1) both from the University of Edinburgh is also acknowledged. We also acknowledge the contribution from Dr Robert Clafferty who supported the study by identifying suitable patients. The contributions from Ellen Backhouse, Serge Hoefeijzers, and Federica Guazzo regarding data collection is also acknowledged. We want to specially acknowledge the contribution of Professor John Starr, who although no longer with us, provided continued support to this study from its outset. Finally, the contribution of the Neuroprogressive Disease and Dementia Network was key to engage relevant patients and stakeholders.
The study presented here was supported by Alzheimer’s Society Grants AS-R42303 and AS-SF-14-008 awarded to MAP in collaboration with SDS.
Ethics approval and consent to participate
MCI patients all had the capacity to consent to the study. All participants were provided with an Information Sheet describing the longitudinal nature of the study and the assessments involved. After they read the PIS, they provided signed consent to participate in the study. The study was approved by the NHS Multi-Site Research Ethics Committee (reference number 06/MRE07/40) and was given approval by local NHS R&D offices (Lothian R&D: 2006/P/PSY/22 and Forth Valley: FV682).
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Results from the Regression Analyses.
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Parra, M.A., Calia, C., Pattan, V. et al. Memory markers in the continuum of the Alzheimer’s clinical syndrome. Alz Res Therapy 14, 142 (2022). https://doi.org/10.1186/s13195-022-01082-9
- Visual Short-Term Memory Binding
- Alzheimer’s disease
- Neuropsychological assessment
- Early detection