Face-Name Associative Recognition Deficits in Subjective Cognitive Decline and Mild Cognitive Impairment

Abstract

Background: There is a need for more sensitive neuropsychological tests to detect subtle cognitive deficits emerging in the preclinical stage of Alzheimer’s disease (AD). Associative memory is a cognitive function supported by the hippocampus and affected early in the process of AD.

Objective: We developed a short computerized face-name associative recognition test (FNART) and tested whether it would detect memory impairment in memory clinic patients with mild cognitive impairment (MCI) and subjective cognitive decline (SCD).

Methods: We recruited 61 elderly patients with either SCD (n = 32) or MCI (n = 29) and 28 healthy controls (HC) and compared performance on FNART, self-reported cognitive deterioration in different domains (ECog-39), and, in a reduced sample (n = 46), performance on the visual Paired Associates Learning of the CANTAB battery.

Results: A significant effect of group on FNART test performance in the total sample was found (p < 0.001). Planned contrasts indicated a significantly lower associative memory performance in the SCD (p = 0.001, d = 0.82) and MCI group (p < 0.001, d = 1.54), as compared to HCs, respectively. The CANTAB-PAL discriminated only between HC and MCI, possibly because of reduced statistical power. Adjusted for depression, performance on FNART was significantly related to ECog-39 Memory in SCD patients (p = 0.024) but not in MCI patients.

Conclusions: Associative memory is substantially impaired in memory clinic patients with SCD and correlates specifically with memory complaints at this putative preclinical stage of AD. Further studies will need to examine the predictive validity of the FNART in SCD patients with regard to longitudinal (i.e., conversion to MCI/AD) and biomarker outcomes.

Keywords

Alzheimer’s disease associative memory cognition early detection hippocampus mild cognitive impairment neuropsychological tests recognition subjective cognitive decline

INTRODUCTION

The pathology of Alzheimer’s disease (AD) is manifold and occurs years to decades before the first manifestation of cognitive symptoms [1, 2]. Current research tries to identify and characterize subjects at increased risk for progression to dementia at the preclinical stage of the disease with the aim to target early intervention and to provide an adequate treatment. Preclinical AD is considered as the first stage of AD, initially characterized by an asymptomatic accumulation of amyloid. Further progression of the disease is accompanied by neurodegeneration. Finally, at the transitional stage between preclinical AD and mild cognitive impairment (MCI) due to AD, subtle cognitive impairments on tests with high sensitivity to AD pathology, and self-experienced cognitive decline may arise [2].

Subjective cognitive decline (SCD) may thus represent the first symptomatic manifestation of AD and precede MCI [3]. This assumption is supported by studies which highlighted SCD as a risk factor for future cognitive decline and progression to MCI and AD dementia [4 –8].

Several studies have shown that memory clinic patients with SCD, who were unimpaired in traditional neuropsychological tests, exhibit signs of neurodegeneration and dysfunction, attributed to putative pathological processes underlying AD, e.g., gray matter atrophy in the hippocampus and entorhinal cortex [9 –12]. Furthermore, a decreased activation of the right hippocampus as well as an increased activation of the right dorsolateral prefrontal cortex during performance on an associative memory test has been reported [13]. Moreover, a study including healthy older individuals with SCD and applying positron emission tomography with Pittsburg Compound B (PiB-PET) showed evidence of brain β-amyloidosis in these individuals compared to healthy controls (HC) without SCD [14]. Subtle decline in cognition at the end of the preclinical stage of AD is, by definition, difficult to detect with standardized neuropsychological tests [3]. Only few studies report slight cognitive impairment on established [15, 14] or novel [16] cognitive tests in patients or individuals with SCD.

Some recently developed tests exhibit increased sensitivity for cognitive deficits in preclinical AD and have been associated with AD pathology [17]. For instance, in healthy individuals an association between a face-name associative memory test and amyloid deposition was found in brain regions underlying memory [18]. Delayed associative face-name recall was found to be impaired in amnestic MCI patients and was the memory test that best predicted conversion from MCI to AD within two years [19].

Face-name association has obvious “face validity”, because it relates to a common everyday cognitive complaint of elderly individuals. However, other associative memory tests may also be useful for early detection of AD. In particular, the CANTAB Paired Associates Learning (CANTAB-PAL) [20] is a widely employed visual-spatial paired associate learning test, which discriminated between non-demented memory clinic patients with or without subsequent progression to AD dementia [21], and in one study was sensitive to progressive memory decline in cognitively normal subjects with memory complaints [22]. It remains to be determined whether different associative tasks yield similar results or whether the type of items to be associated matters. Face-name association requires the association of verbal with biologically meaningful visual face stimuli, which might tap into different brain areas than a visual-spatial task with abstract geometricfigures.

Refinement and further validation of tasks with increased sensitivity to changes occurring early in the course of AD will be a valuable enhancement of the neuropsychological toolbox for clinical studies.

The purpose of the present study was to investigate the sensitivity of a face-name associative memory test in memory clinic patients with SCD and MCI, and to examine associations with self-reported cognitive problems in everyday life. Inspired by the similar Face Name Associative Memory Exam (FNAME) [18], we developed a computerized paired-associate recognition test which also requires pairing of faces and names during learning (FNART; Face-Name Associative Recognition Test). However, the FNART, in contrast to the FNAME and other similar tests [23, 24], does not employ free recall of the name which was learned to go with a face. Rather, the FNART only requires a forced choice about which among several presented names belongs to the face shown. This response format is identical to the format used in previous functional imaging studies of face-name association learning, which have consistently shown stronger hippocampal activation during successful learning of face-name associations, which were subsequently recognized outside the scanner [25, 26]. Interestingly, some of these studies have also found evidence of memory-related activity in entorhinal [27] and parahippocampal [25, 28] cortex, regions which in AD are affected by tau-pathology even earlier than the hippocampus [29]. The associative recognition format has also the practical advantage of being easier, both subjectively and objectively, than recalling a name when shown the face alone. This might avoid floor effects when studying subjects with mild cognitive deficits. Thus, such a test can be administered to both normal and subjects with MCI, which is harder to do with free recall paradigms. In addition, the response format may also reduce feelings of threat and frustration in subjects who are concerned about their memory.

The computerized presentation of the FNART also allowed assurance of a minimal exposure time of the face-name associations in order to control depth of encoding, and enables the exploration of decision times during recognition, which may yield additional diagnostic information.

The main objective of the current study was to examine whether the FNART would discriminate not only between MCI and HC, but also between SCD and HC.

We also wanted to examine whether specific complaints about cognitive functions, at least in the SCD group, might be related with, and possibly reflect, objective memory function. We assessed complaints about everyday cognitive functioning by the self-rating version of the Everyday Cognition (ECog) questionnaire.

Furthermore, we explore whether performance on FNART is related to performance on CANTAB-PAL, which requires the recall of previously learned object-position associations.

We hypothesized that the FNART and the CANTAB-PAL would be moderately correlated, as both are paired associate tasks which, however, differ in item content. The number of subjects with data on CANTAB-PAL performance is smaller because this test became available to us only after the study of the FNART had started.

MATERIALS AND METHODS

In this cross-sectional study, patients were recruited within the outpatient clinic at the Clinical Research Center for Neurodegenerative Diseases (KBFZ) at the University Hospital Bonn. HC were acquired using a press release. This sample does not overlap with previous cohorts from our research group [9 , 16].

The study was approved by the ethics committee of the University of Bonn (Medical Faculty). Participants were informed about the study procedure and gave their written informed consent before being enrolled.

Participants

61 patients (>50 years) who were referred to the memory clinic because of self or informant reported cognitive deficits and 28 healthy individuals (mean age: 67.46, SD = 8.12) were included in this study. Patients were classified as MCI (n = 29; mean age: 68.21, SD = 8.97) and SCD (n = 32, mean age: 67.97, SD = 8.51) on the basis of performance on the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) Plus test battery.

MCI was defined by an impaired cognitive performance (below –1.5 SD) in at least one subtest on the CERAD Plus test battery (see below). This decline in cognitive function was noticed either by the patient, an informant, or a clinician.

SCD was defined in line with recently proposed recommendations [3], i.e., by normal cognitive performance (defined as: all CERAD Plus subtests within 1.5 SD; Mini-Mental-State Exam (MMSE) score≥28) and by self-experienced cognitive decline with worries. The latter was operationalized with the following procedure: We assessed global and memory specific SCD, each by two consecutive questions. We first asked participants “Do you feel like your global cognitive performance has become worse?” (possible answers: yes/no). In case of a positive response to this initial question we further specified whether global SCD was experienced as worrisome by asking “Does this worry you?” (possible answers: yes/no). The same procedure was done for memory (“Do you feel like your memory has become worse?”). Self-experienced cognitive decline with worries was defined by endorsement of perceived decline with worries in global cognition and/or memory.

HC individuals were included if they were above the age of 50, reported age-appropriate cognitive functioning and negated self-experienced, worrisome cognitive decline, assessed with the procedure outlined above. HC who reported self-experienced cognitive decline without worries were not excluded, because perceived deterioration was judged as an age-appropriate process. HC performed within the normal range in all CERAD Plus subtests (within 1.5 SD; MMSE score≥28).

While no quantified functional (Instrumental Activities of Daily Living) data are available for our study sample, all MCI and SCD subjects had preserved independence of functional activities according to the physician’s judgment.

Neuropsychological assessment

All participants underwent a neuropsychological examination, including the CERAD Plus testbattery [30].

The CERAD Plus test battery includes the following subtests: Verbal Fluency [31], Boston Naming Test [32], MMSE [33], Word List Memory [34, 35], Constructional Praxis [34], Word List Recall, Word List Recognition [36], Recall of Constructional Praxis, Phonemic Fluency, Trail Making Test A and B. Age-, sex-, andeducation-adjusted German normative data are available at http://www.memoryclinic.ch. A subsample (n = 46, see Table 2) was also assessed with the Paired Associates Learning (PAL) test of the Cambridge-Neuropsychological Automated Battery (CANTAB-PAL) [20], which requires the recognition of previously learned object-position associations. In addition, all participants completed the Geriatric Depression Scale (GDS, short version [37]) and the self-rating Everyday Cognition questionnaire (ECog-39, 39 Items, [38]). The ECog-39 covers the following domains of cognitive function in daily life: Memory, Language, Visuospatial Abilities, Planning, Organization, and Divided Attention. Patients had to rate their cognitive function in daily life compared to 10 years earlier with the opportunity to answer (1) better or no change, (2) questionable/occasionally worse, (3) consistently a little worse, and (4) consistently much worse. An “I don’t know” option is also given. Higher scores represent worse cognitive function in daily life.

Face-Name Associative Recognition Test: Stimuli and procedure

Pictures of 16 male and 16 female faces (20–80 years) with neutral face expressions [39], were obtained from an American face database [40]. The depicted subjects varied in age to maximize distinctiveness among the faces. Age-appropriate popular German first names were selected from an online database [41] to form face-name associations.Figure 1 illustrates the encoding and recognition part of the FNART.

Encoding

32 face-name associations were presented twice in two blocks with a minimal exposure time of 5 seconds. The participants were instructed to read out the name underneath the face and to memorize the association for later retrieval. Participants moved to the next face-name presentation by pressing the button “space”. Except the minimal exposure time, no time limit was set, but exposure time was measured and analyzed. The face-name associations were randomized once and appeared sequentially for each participant afterwards.

Recognition

All faces, presented in the associative recognition task, were repetitions of faces encountered twice in the encoding phase. Each of the 32 faces was shown with two names underneath: the associated name and a distractor name, which had been associated with another face during encoding. Each name was presented twice during recognition (as target and distractor). Thus, associative recognition is based on memory recollection and not on item familiarity [42]. Position of the correct name versus distractor name was randomized across trials.

The participants were instructed to recognize the names associated with each face during encoding and to indicate the correct name via key press. No time limit was set, but response times were measured and analyzed.

Trials were presented in a pseudorandomized fixed order. The randomization of trial presentation was restricted: after a name’s first presentation, the same name was not shown in the next five trials.

Equipment

The memory test was developed in E-Studio, Eprime 2.0 Professional [43]. Color face pictures were presented on a white background and names were presented in font Verdana size 15. AnotherE-prime application called E-Run was used to run the memory test. The test was presented on a laptop with a 39 cm screen diagonal. The distance between the screen and the participant were approximately 60 cm.

Statistical analysis

Demographic and neuropsychological data were analyzed using SPSS Statistics 21. 29 MCI patients, 32 SCD patients, and 28 HC were included in the analyses. In order to examine group differences in the total sample (N = 89) and in the reduced sample (n = 46; HC: n = 13, SCD: n = 18, MCI: n = 15), which also performed the CANTAB-PAL, we applied Chi-Quadrat-tests for categorical and Analyses of Variance (ANOVAs) for continuous variables, respectively. Following the ANOVA, we performed planned comparisons (significance level≤0.05).

We included covariates (age, level of education, GDS score) in the analyses, if groups differed at least tendencially regarding the covariates and if a relationship between the covariates and the dependent variable was present.

Daily functioning assessed with the ECog-39 were analyzed by calculating the sum of all items completed in each of the functional domains divided by the number of items completed in each domain. Additionally, a total score was calculated. Associations between ECog-39 scores and memory performance on FNART were investigated with Pearsoncorrelations. As we expected a negative relationship between higher ECog-39 scores and lower objective memory performance we calculated one-tailedtests.

For the CANTAB-PAL, we included the variable total errors (adjusted) in our analysis, as it was found to be most efficient in differentiating aMCI, AD, and HC among all PAL variables and high correlations with other PAL variables were reported [44]. The variable PAL total errors (adjusted) “reports the total number of errors with an adjustment for each stage not attempted due to previous failure” [45]. Furthermore, the variable PAL total errors (6 shapes, adjusted) was included [46]. This variable reports the number of errors made at 6-pattern stage, with an adjustment for those who not attempted this stage due to previous failure [45]. Higher scores represent worse memory performance.

The correct responses in the FNART (max. 32) were used to calculate a recognition score ([correct responses/max. correct responses] * 100). We recorded the time (ms) of encoding the face and the name beyond the minimal exposure time of five seconds and the manual response time (RT, ms) in the recognition part for correct and incorrect responses. Additionally, we calculated the difference between mean RT for correct and incorrect answers. The correlation between the number of correct responses (%) and RT difference was also determined. In addition, we calculated the CERAD total score [47] of the three groups as an overall measure of cognitive function, by summing the raw scores of the following subtests of the CERAD test battery: verbal fluency (with a maximum of 24 points), Boston Naming Test, Word List Learning, Constructional Praxis, Word List Recall and Word List Recognition. The CERAD global score is an established measure to detect and predict MCI and dementia [48].

RESULTS

Descriptive statistics of the three groups are listed in Table 1. The groups did not differ significantly with regard to age (F(2,86) = 0.056, p = 0.946), years of education (F(2,86) = 0.181, p = 0.835) or distribution of gender (χ²(2, N = 89) = 1.632, p = 0.442). However, the GDS score did differ significantly between the groups (F(2,82) = 10.705, p < 0.001), such that SCD and MCI patients had higher scoresthan HC.

As expected by group definition, comparisons including the CERAD total score indicated a significantly lower overall performance in the MCI group (M = 73.79, SD = 10.61) compared to HC (M = 89.57, SD = 5.72, p < 0.000) and SCD. However, HC and SCD (M = 87.06, SD = 6.18) did not differ significantly (p = 0.651).

Associative recognition (FNART)

FNART performance of the three groups is shown in Table 1 and Fig. 2, respectively. We observed a significant effect of group on test performance (F(2,86) = 11.929, p < .001). Planned contrasts indicated significantly worse face-name associative memory in the MCI group (M = 60.35, SD = 8.66, p < 0.001, d = 1.39) and also in the SCD group (M = 64.95, SD = 13.40, p = 0.001, d = 0.78) compared to HC (M = 74.74, SD = 11.65). Test performance did not differ significantly between the MCI and SCD group (p = 0.122, d = 0.40).

Age (r = –0.266, p = 0.012) and years of education (r = 0.256, p = 0.015) were significantly correlated to performance on the FNART whereas GDS score (r = 0.145, p = 0.105) was not. However, because groups differed with regard to GDS, we also ran the analysis including GDS as a covariate with almost identical results.

FNART scores correlated with established memory tests of the CERAD test battery, i.e., with word list learning (r = 0.413, p < 0.001), word list recall (r = 0.446, p < 0.001), word list recognition (r = 0.293, p = 0.005), and visual recall (r = 0.345, p = 0.001) as well as with the CERAD total score (r = 0.429, p = 0.000) and with performance on CANTAB-PAL (total errors adjusted, r = –0.547, p < 0.000).

Subgroup analysis in patients showed that performance on FNART was highly correlated with performance on CANTAB-PAL (total errors adjusted, p = –0.628, p = 0.005) and the CERAD total score in the SCD group (r = 0.460, p = 0.008) but not in the MCI group.

Encoding times during learning (FNART)

While analyses did not show a significant effect of group on ET (F(2,86) = 2.455, p = 0.092), planned contrasts revealed significant differences in ET between HC (M = 6548 ms, SD = 981 ms) and SCD (M = 7571 ms, SD = 2554 ms, p = 0.041, d = 0.51). HC and MCI (M = 7427 ms, SD = 1724 ms) did not differ significantly in ET (p = 0.085), possibly as a result of the large RT variation in MCI.

Across all groups, encoding time (ET) during learning was significantly related to RT in the subsequent associative recognition task (r = 0.460, p < 0.001). Subgroup analyses showed that this effect was only present in HC (r = 0.473, p = 0.011) and SCD r = 0.636, p < 0.001) but not in MCI (r = 0.309, p = 0.103). ET was related to subsequent recognition performance neither in the whole group (r = 0.076, p = 0.481) nor any subgroup. Thus, longer viewing during learning did not result in better memory performance, and differential viewing times could not explain the group differences in associative memory performance.

Response times during recognition (FNART)

The groups differed regarding the RT of correct responses (F(2,86) = 5.364, p = 0.006). MCI patients (M = 6448 ms, SD = 2513 ms) needed more time to indicate the correct name than controls (M = 4898 ms, SD = 1402 ms; p = 0.002, d = 0.75). However, RTs of incorrect responses were similar between the groups (F(2,86) = 1.023, p = 0.364).

Within-group comparisons showed significantly faster RTs for correct compared to incorrect responses in SCD patients (p = 0.005) and HC (p = 0.030). However, MCI patients had comparable mean RT for correct and incorrect responses (p = 0.874).

Across all groups, RT for correct and incorrect responses was not related to the number of correct responses (r = –0.177, p = 0.097 and r = –0.135, p = 0.207).

However, RT differences for correct and incorrect responses were negatively related to FNART recognition accuracy (r = –0.308, p = 0.003), which indicates that better performance on the FNART involves greater RT difference regarding correct and incorrect responses.

Everyday cognition (ECog-39)

All ECog-39 functional domains were highly correlated with depression (e.g., ECog Total score: r = 0.571, p < 0.001). The following results are adjusted for GDS scores. SCD and MCI patients reported significantly more difficulties than HC in everyday cognition in the functional domain of Everyday Memory and on Global Cognition.Additionally, significant differences were present between MCI and HC with regard to Everyday Visualspatial Abilities and between SCD and HC with regard to Everyday Language (Table 1, Fig. 3).

Neither MCI nor SCD patients reported more deficits in executive functioning on ECog-39 (Everyday Planning, Everyday Organization and Everyday Divided Attention) than HC (see Table 1), although SCD tended to report more deficits than controls in dividing their attention (p = 0.052).

Across all groups, correlations indicated a significant relationship of performance on FNART with ECog Total score (r = –0.250, p = 0.023), ECog Memory (r = –0.323, p = 0.003) and ECog Visualspatial Abilites (r = –0.230, p = 0.037).

Within the SCD group, subjective functional memory difficulties (ECog Memory subscore) were significantly related to recognition accuracy on FNART ({r = –0.365, p = 0.024) but neither to learning, delayed recall and recognition on CERAD test battery nor to the CERAD total score and to total errors adjusted on CANTAB-PAL. Within the MCI sample, subjective functional memory deficits were neither related to performance on FNART, to CERAD learning, delayed recall and recognition, to the CERAD total score, nor to the CANTAB PAL total errors adjusted score.∥

Results for the reduced sample with CANTAB-PAL data

Descriptive statistics of the three subgroups are listed in Table 2. They did not differ significantly in age (F(2,43) = 2.347, p = 0.108), years of education (F(2,43) = 0.461, p = 0.634) or in distribution of gender (χi²(2, n = 46) = 0.690, p = 0.708). However, the GDS score did differ significantly between the groups (F(2,40) = 7.813, p = 0.001). Despite insignificant group differences, we included age as a covariate to account for minor group differences, as it was correlated with cognitive performance.∥

Associative recognition (FNART)

The FNART discriminated between the groups also in the reduced sample (F(2,42) = 19.734, p < 0.001). Planned contrasts showed again worse FNART performance in MCI (p < 0.001, d = 1.8) and SCD (p = 0.003; d = 0.58) as compared to controls.∥

Associative recognition (CANTAB-PAL)

Age was significantly correlated with test performance (total errors: r = 0.364, p = 0.013; PAL Total Errors adjusted: r = 0.318, p = 0.031) while depressive symptoms were not significantly correlated with any of the PAL variables.∥The CANTAB-PAL discriminated between MCI and HC regarding the total number of errors adjusted (p < 0.001; d = 1.0), the errors made at 6 pattern stage (p < 0.001; d = 1.0) and the number of stages completed (p < 0.001, d = 0.92), adjusted for the effect of age. However, differences between SCD and HC were not significant for any of the PAL variables (Table 2).

Everyday cognition (ECog-39)

Adjusted for GDS scores, performance on CANTAB-PAL (total errors adjusted) was not related to any of the ECog scores for all in the subsample (n = 46). Likewise, within the SCD group the correlation between ECog Memory and CANTAB-PAL total errors adjusted (r = 0.380) did not reach statistical significance (p = 0.073), possibly due to a small sample size (n = 14). The same comparison within the MCI group revealed no significant relationship between CANTAB-PAL total errors adjusted and any of the ECog scores.

DISCUSSION

The aim of the present study was to investigate whether associative recognition memory is a sensitive measure for detection of subtle memory impairment. We found that associative recognition on the demanding FNART is not only impaired in MCI but also in individuals with SCD who performed normal on tests of an established neuropsychological battery.

Our finding of a slowing in memory RT in MCI cases is consistent with other findings previously reported for AD cases [49, 50] and could be indicative for a general cognitive slowing associated with the disease, memory search and the absence of confidence.

While RT for correct choices was faster in HC (in line with previous findings [51]) and SCD, RT for correct and incorrect decisions did not differ in MCI cases. The difference in RT was negatively related to recognition accuracy on FNART. This suggests that the ease of successful retrieval is reflected in both, better and faster recognition. In subjects with MCI, accuracy (58%) was only slightly better than chance (50%), so that their decisions were largely based on guessing rather than on associative retrieval. Whether or not the RT differences in forced-choice memory paradigms will yield additional diagnostic information beyond accuracy is an interesting issue in need of further research.

In a reduced sample we observed similar results regarding FNART performance across the three groups. In addition, performance on the short visual memory test CANTAB-PAL, which requires the recognition of previously learned association between an abstract (nonverbal) object and a spatial location, was impaired in MCI— as previously shown [52, 53]— but not in SCD. Impairment in associative memory performance on CANTAB-PAL in aMCI cases was shown to be determined by a decrease of short-term memory capacity, difficulties with memory consolidation and less effective executive functioning as, e.g., reduced responsemonitoring [53]. Thus, preserved executive functioning in SCD cases may account for the normal recognition performance on CANTAB-PAL. Because of the small sample sizes and the limited power to discriminate SCD from HC with the CANTAB-PAL, the dissociation between the two paired associate tasks regarding their sensitivity to SCD might be more apparent than real. However, if substantiated with larger samples, such a dissociation could result from face-name association being more reliant on extrahippocampal brain regions [25] where tau pathology occurs early in the course of AD.

Although the association of both tests were substantial (r = –0.547) as expected given both are associative learning tests, the above mentioned specifics as, e.g., abstract visual-spatial versus ecologically valid face-verbal associations and differential involvement of executive functions may account for the fact that both still share less than 30% variance.

Within the MCI sample we observed a floor effect in the FNART performance indicated by near chance level (50%). This effect is due to the relatively high task difficulty of the FNART. Therefore, the use of this test could be limited regarding follow-up examinations within MCI and AD samples and the discrimination between MCI and more impaired AD patients. On the other hand, it is advantageous for the detection of subtle cognitive impairment in individuals with SCD and preclinical AD, i.e., our primary target population.

There is accumulating evidence showing that memory clinic patients with self-experienced cognitive decline and normal test performance have increased risk for abnormal levels of AD biomarkers of amyloidosis and tau-mediated neurodegeneration and dysfunction [9 , 13]. Furthermore, biomarker evidence is relevant for clinical decision making and prediction of future cognitive decline and is of particular importance for the characterization of preclinical AD [3]. In this study, information on CSF biomarker status was available only in a minor number of patients. Biomarker positivity versus negativity might account for the observed variability in test performance especially in SCD cases, beside the extent of cognitive reserve and coexisting pathologies or diseases. Further studies incorporating data on AD biomarkers will clarify whether the FNART can discriminate between SCD/MCI cases due to AD and SCD/MCI due to other causes.

Self-reported cognitive function in daily life is associated cross-sectionally [54, 55] and longitudinally [56] with episodic memory and executive functioning. In our study, we assessed function in daily life with the self-rating instrument “Everyday Cognition” (ECog-39). In the current study, patients with MCI and SCD complained particularly about difficulties in everyday memory. All patients were recruited in a memory clinic, and memory complaints are the most prominent complaint in these settings, and part of the definition of MCI and most SCD criteria. Thus it is not a surprise to us that patients differ from controls on the memory subscale, but that this is a rather specific complaint not evident for the other functions assessed with the ECog. Interestingly, self-reported memory difficulties were significantly related to FNART performance in the SCD group, but not in MCI. In the subgroup analysis, self-reported memory difficulties tended toward significance with CANTAB-PAL performance for SCD but not MCI. This suggests that some subjects with SCD correctly sense and report minor memory deficits, which can be unmasked only with challenging tests like the FNART or the CANTAB-PAL. No such relationships were found in the MCI sample. This might be due to a reduced awareness of cognitive deficits and their impact on daily activities/everyday function in some MCI cases, consistent with previous studies [57 –59]. Underestimation of functional deficits in MCI has been associated with a CSF biomarker profile indicative of AD and progression to AD [57, 58].

As also reported in previous studies [57], functional deficits in our MCI and SCD cases were linked to depressive symptoms.

In sum, our results provide further evidence that associative memory assessment is not only sensitive for age-related cognitive decline in episodic memory function in healthy elderly (Associative Deficit Hypothesis [60]) but also for detecting subtle cognitive decline that might be attributed to AD pathology,

Thus, associative memory assessment seems to be suitable for the investigation of subtle cognitive deficits in preclinical AD. Most assessment batteries in this field rely on non-associative item memory, the inclusion of a short associative memory test might be a useful complement. Several studies found associative memory to be more impaired than item-memory in healthy elderly [61] and MCI [62] and our findings would be consistent with an early sensitivity of associative memory. However, Didic et al. hypothesized that item memory but not associative memory could be affected already in the “clinically silent” transentorhinal stage of AD [63]. This interesting conjecture will need to be tested with psychometrically matched item- and associative memory tasks in biomarker-based studies of the initial stages of preclinical AD.

A number of novel test developments have recently been reviewed by Rentz et al. [17]. These included, for example, a face-name association tests (FNAME [18]), but also a short-term memory binding test [64], and variants of word list learning tasks(Memory Capacity Test from H. Buschke). Furthermore, composites of traditional, challenging tests (e.g., Preclinical Alzheimer Cognitive Composite [65]) with proposed sensitivity to early AD related changes have been developed. At present, there are yet not enough comparative data in the ability of these tests to identify biomarker-defined AD in the preclinical or prodromal stages of the disease.

In summary, findings of this study suggest that associative recognition is a sensitive neuropsychological measure for detecting subtle cognitive impairment in memory clinic subjects with SCD, a group known to be at increased risk for having preclinical AD. Thus, the FNART, together with other recently developed tests [17, 16], could be a useful supplement to established test batteries for observational and intervention studies in memory clinic patients.

Further longitudinal and biomarker studies should examine the predictive validity of the FNART and aim to identify factors that influence the variability in associative memory accuracy in MCI and especially in SCD cases.

Footnotes

ACKNOWLEDGMENTS

We would like to cordially thank M.Sc. Lisa Miebach, B.Sc. Luca Kleineidam, Sandra Röske, PhD, Dipl.-Psych. Catherine Widmann, Annika Spottke, MD and Klaus Fließbach, PhD, Department of Psychiatry, University of Bonn and German Center for Neurodegenerative Diseases, Bonn, Germany for further support of this study and manuscript.

This work was funded by the DZNE, German Center for Neurdegenerative Diseases, Bonn, Germany.

Authors’ disclosures available online ().

References

Jack

, Knopman

, Jagust

, Shaw

, Aisen

, Weiner

, Petersen

, Trojanowski

(2010) Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol 9, 119–128.

Sperling

, Aisen

, Beckett

, Bennett

, Craft

, Fagan

, Iwatsubo

, Jack

, Kaye

, Montine

, Park

, Reiman

, Rowe

, Siemers

, Stern

, Yaffe

, Carrillo

, Thies

, Morrison-Bogorad

, Wagster

, Phelps

(2011) 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 7, 280–292.

Jessen

, Amariglio

, van Boxtel

, Breteler

, Ceccaldi

, Chételat

, Dubois

, Dufouil

, Ellis

, van der Flier , Wiesje

, Glodzik

, van Harten , Argonde

, de Leon , Mony

, McHugh

, Mielke

, Molinuevo

, Mosconi

, Osorio

, Perrotin

, Petersen

, Rabin

, Rami

, Reisberg

, Rentz

, Sachdev

, de la Sayette , Vincent , Saykin

, Scheltens

, Shulman

, Slavin

, Sperling

, Stewart

, Uspenskaya

, Vellas

, Visser

, Wagner

(2014) A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease. Alzheimers Dement 10, 844–852.

Mitchell

, Beaumont

, Ferguson

, Yadegarfar

, Stubbs

(2014) Risk of dementia and mild cognitive impairment in older people with subjective memory complaints: Meta-analysis. Acta Psychiatr Scand 130, 439–451.

Jessen

, Wiese

, Bachmann

, Eifflaender-Gorfer

, Haller

, Kölsch

, Luck

, Mösch

, van den Bussche , Hendrik , Wagner

, Wollny

, Zimmermann

, Pentzek

, Riedel-Heller

, Romberg

, Weyerer

, Kaduszkiewicz

, Maier

, Bickel

(2010) Prediction of dementia by subjective memory impairment: Effects of severity and temporal association with cognitive impairment. Arch Gen Psychiatry 67, 414–422.

Dufouil

, Fuhrer

, Alpérovitch

(2005) Subjective cognitive complaints and cognitive decline: Consequence or predictor? The epidemiology of vascular aging study. J Am Geriatr Soc 53, 616–621.

van Oijen

, de Jong , Frank

Jan

, Hofman

, Koudstaal

, Breteler

MMB

(2007) Subjective memory complaints, education, and risk of Alzheimer’s disease. Alzheimers Dement 3, 92–97.

Buckley

, Maruff

, Ames

, Bourgeat

, Martins

, Masters

, Rainey-Smith

, Lautenschlager

, Rowe

, Savage

, Villemagne

, Ellis

(2016) Subjective memory decline predicts greater rates of clinical progression in preclinical Alzheimer’s disease. Alzheimers Dement 12, 796–804.

Striepens

, Scheef

, Wind

, Popp

, Spottke

, Cooper-Mahkorn

, Suliman

, Wagner

, Schild

, Jessen

(2010) Volume loss of the medial temporal lobe structures in subjective memory impairment. Dement Geriatr Cogn Disord 29, 75–81.

10.

Jessen

, Feyen

, Freymann

, Tepest

, Maier

, Heun

, Schild

, Scheef

(2006) Volume reduction of the entorhinal cortex in subjective memory impairment. Neurobiol Aging 27, 1751–1756.

11.

Perrotin

, Mézenge

, Landeau

, Egret

, de la Sayette

, Desgranges

, Eustache

, Chételat

(2014) Is hippocampal atrophy in healthy elderly individuals with subjective cognitive decline related to amyloid deposition? Alzheimers Dement 10, P58.

12.

Scheef

, Spottke

, Daerr

, Joe

, Striepens

, Kölsch

, Popp

, Daamen

, Gorris

, Heneka

, Boecker

, Biersack

, Maier

, Schild

, Wagner

, Jessen

(2012) Glucose metabolism, gray matter structure, and memory decline in subjective memory impairment. Neurology 79, 1332–1339.

13.

Erk

, Spottke

, Meisen

, Wagner

, Walter

, Jessen

(2011) Evidence of neuronal compensation during episodic memory in subjective memory impairment. Arch Gen Psychiatry 68, 845–852.

14.

Amariglio

, Becker

, Carmasin

, Wadsworth

, Lorius

, Sullivan

, Maye

, Gidicsin

, Pepin

, Sperling

, Johnson

, Rentz

(2012) Subjective cognitive complaints and amyloid burden in cognitively normal older individuals. Neuropsychologia 50, 2880–2886.

15.

Jessen

, Wiese

, Cvetanovska

, Fuchs

, Kaduszkiewicz

, Kölsch

, Luck

, Mösch

, Pentzek

, Riedel-Heller

, Werle

, Weyerer

, Zimmermann

, Maier

, Bickel

(2007) Patterns of subjective memory impairment in the elderly: Association with memory performance. Psychol Med 37, 1753–1762.

16.

Koppara

, Frommann

, Polcher

, Parra

, Maier

, Jessen

, Klockgether

, Wagner

(2015) Feature binding deficits in subjective cognitive decline and in mild cognitive impairment. J Alzheimers Dis 48(Suppl 1), S161–S170.

17.

Rentz

, Parra

Rodriguez

, Mario

, Amariglio

, Stern

, Sperling

, Ferris

(2013) Promising developments in neuropsychological approaches for the detection of preclinical Alzheimer’s disease: A selective review. Alzheimers Res Ther 5, 58.

18.

Rentz

, Amariglio

, Becker

, Frey

, Olson

, Frishe

, Carmasin

, Maye

, Johnson

, Sperling

(2011) Face-name associative memory performance is related to amyloid burden in normal elderly. Neuropsychologia 49, 2776–2783.

19.

Irish

, Lawlor

, Coen

, O’Mara

(2011) Everyday episodic memory in amnestic mild cognitive impairment: A preliminary investigation. BMC Neurosci 12, 80.

20.

CANTAB® [Cognitive assessment software]. Cambridge Cognition (2016), http://www.cantab.com.

21.

Blackwell

, Sahakian

, Vesey

, Semple

, Robbins

, Hodges

(2004) Detecting dementia: Novel neuropsychological markers of preclinical Alzheimer’s disease. Dement Geriatr Cogn Disord 17, 42–48.

22.

Fowler

, Saling

, Conway

, Semple

, Louis

(2002) Paired associate performance in the early detection of DAT. J Int Neuropsychol Soc 8, 58–71.

23.

Kessler

, Ehlen

, Halber

, Bruckbauer

(1999) Namen-Gesichter-Assoziations-Test (NGA), Hogrefe, Göttingen.

24.

Schuri

, Benz

(2000) Gesichter-Namen-Lerntest (GNL), Swets Test Services.

25.

Kirwan

, Stark

CEL

(2004) Medial temporal lobe activation during encoding and retrieval of novel face-name pairs. Hippocampus 14, 919–930.

26.

Westerberg

, Voss

, Reber

, Paller

(2011) Medial temporal contributions to successful face-name learning. Hum Brain Mapp 33, 1717–1726.

27.

Sperling

, Chua

, Cocchiarella

, Rand-Giovannetti

, Poldrack

, Schacter

, Albert

(2003) Putting names to faces: Successful encoding of associative memories activates the anterior hippocampal formation. Neuroimage 20, 1400–1410.

28.

Bangen

, Kaup

, Mirzakhanian

, Wierenga

, Jeste

, Eyler

(2012) Compensatory brain activity during encoding among older adults with better recognition memory for face-name pairs: An integrative functional, structural, and perfusion imaging study. J Int Neuropsychol Soc 18, 402–413.

29.

Braak

, Braak

(1991) Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol 82, 239–259.

30.

Schmid

, Ehrensperger

, Berres

, Beck

, Monsch

(2014) The extension of the German CERAD Neuropsychological Assessment Battery with tests assessing subcortical, executive and frontal functions improves accuracy in dementia diagnosis. Dement Geriatr Cogn Disord Extra 4, 322–334.

31.

Isaacs

, Kennie

(1973) The Set Test as an aid to the detection of dementia in old people. Br J Psychiatry 123, 467–470.

32.

Kaplan

, Goodglass

, Weintraub

(1983) Boston naming test, Lea & Febiger, Philadelphia.

33.

Folstein

, Folstein

, McHugh

(1975) Mini-mental state. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12, 189–198.

34.

Rosen

, Mohs

, Davis

(1984) A new rating scale for Alzheimer’s disease. Am J Psychiatry 141, 1356–1364.

35.

Atkinson

, Shiffrin

(1971) The control of short-term memory. Sci Am 225, 82–90.

36.

Mohs

, Kim

, Johns

, Dunn

, Davis

(1986) Assessing changes in Alzheimer’s disease: Memory and language. In Handbook for Clinical Memory Assessment of Older Adults, Poon

, Crook

, Davis

, Eisdorfer

, Gurland

, Kaszniak

, Thompson

, eds. American Psychological Association, Washington, DC, pp. 149–155.

37.

Yesavage

, Sheikh

(1986) 9/Geriatric Depression Scale (GDS). Clin Gerontol 5, 165–173.

38.

Farias

, Mungas

, Reed

, Cahn-Weiner

, Jagust

, Baynes

, Decarli

(2008) The Measurement of Everyday Cognition (ECog): Scale development and psychometric properties. Neuropsychology 22, 531–544.

39.

Ebner

(2008) Age of face matters: Age-group differences in ratings of young and old faces. Behav Res Methods 40, 130–136.

40.

Minear

, Park

(2004) A lifespan database of adult facial stimuli. Behav Res Methods Instrum Comput 36, 630–633.

41.

Knud Bielefeld, http://www.beliebte-vornamen.de, Accessed January 7, 2016.

42.

Yonelinas

(1997) Recognition memory ROCs for item and associative information: The contribution of recollection and familiarity. Mem Cogn 25, 747–763.

43.

Psychology Software Tools, Inc. [E-Prime 2.0 Professional]. (2013) http://www.pstnet.com.

44.

Junkkila

, Oja

, Laine

, Karrasch

(2012) Applicability of the CANTAB-PAL computerized memory test in identifying amnestic mild cognitive impairment and Alzheimer’s disease. Dement Geriatr Cogn Disord 34, 83–89.

45.

Cognition

(2004) CANTABeclipse test administration guide. Cambridge Cognition, Cambridge, UK.

46.

Swainson

, Hodges

, Galton

, Semple

, Michael

, Dunn

, Iddon

, Robbins

, Sahakian

(2001) Early detection and differential diagnosis of Alzheimer’s disease and depression with neuropsychological tasks. Dement Geriatr Cogn Disord 12, 265–280.

47.

Chandler

, Lacritz

, Hynan

, Barnard

, Allen

, Deschner

, Weiner

, Cullum

(2005) A total score for the CERAD neuropsychological battery. Neurology 65, 102–106.

48.

Wolfsgruber

, Jessen

, Wiese

, Stein

, Bickel

, Mosch

, Weyerer

, Werle

, Pentzek

, Fuchs

, Kohler

, Bachmann

, Riedel-Heller

, Scherer

, Maier

, Wagner

(2014) The CERAD neuropsychological assessment battery total score detects and predicts Alzheimer disease dementia with high diagnostic accuracy. Am J Geriatr Psychiatry 22, 1017–1028.

49.

Pariente

, Cole

, Henson

, Clare

, Kennedy

, Rossor

, Cipoloti

, Puel

, Demonet

, Chollet

, Frackowiak

Richard SJ

(2005) Alzheimer’s patients engage an alternative network during a memory task. Ann Neurol 58, 870–879.

50.

Grady

, Furey

, Pietrini

, Horwitz

, Rapoport

(2001) Altered brain functional connectivity and impaired short-term memory in Alzheimer’s disease. Brain 124, 739–756.

51.

Henke

, Treyer

, Nagy

, Kneifel

, Dürsteler

, Nitsch

, Buck

(2003) Active hippocampus during nonconscious memories. Conscious Cogn 12, 31–48.

52.

Égerházi

, Berecz

, Bartók

, Degrell

(2007) Automated Neuropsychological Test Battery (CANTAB) in mild cognitive impairment and in Alzheimer’s disease. Prog Neuropsychopharmacol Biol Psychiatry 31, 746–751.

53.

Harel

, Darby

, Pietrzak

, Ellis

, Snyder

, Maruff

(2011) Examining the nature of impairment in visual paired associate learning in amnestic mild cognitive impairment. Neuropsychology 25, 752–762.

54.

Grigsby

, Kaye

, Baxter

, Shetterly

, Hamman

(1998) Executive cognitive abilities and functional status among community-dwelling older persons in the San Luis Valley Health and Aging Study. J Am Geriatr Soc 46, 590–596.

55.

Jefferson

, Byerly

, Vanderhill

, Lambe

, Wong

, Ozonoff

, Karlawish

(2008) Characterization of activities of daily living in individuals with mild cognitive impairment. Am J Geriatr Psychiatry 16, 375–383.

56.

Farias

, Cahn-Weiner

, Harvey

, Reed

, Mungas

, Kramer

, Chui

(2008) Longitudinal changes in memory and executive functioning are associated with longitudinal change in instrumental activities of daily living in older adults. Clin Neuropsychol 23, 446–461.

57.

Edmonds

, Delano-Wood

, Galasko

, Salmon

, Bondi

, Alzheimer’s Disease Neuroimaging, Initiative (2014) Subjective cognitive complaints contribute to misdiagnosis of mild cognitive impairment. J Int Neuropsychol Soc 20, 836–847.

58.

Tabert

, Albert

, Borukhova-Milov

, Camacho

, Pelton

, Liu

, Stern

, Devanand

(2002) Functional deficits in patients with mild cognitive impairment: Prediction of AD. Neurology 58, 758–764.

59.

Lenehan

, Klekociuk

, Summers

(2012) Absence of a relationship between subjective memory complaint and objective memory impairment in mild cognitive impairment (MCI): Is it time to abandon subjective memory complaint as an MCI diagnostic criterion? Int Psychogeriatr 24, 1505–1514.

60.

Naveh-Benjamin

, Guez

, Kilb

, Reedy

(2004) The associative memory deficit of older adults: Further support using face-name associations. Psychol Aging 19, 541–546.

61.

Naveh-Benjamin

, Shing

, Kilb

, Werkle-Bergner

, Lindenberger

, Li

(2009) Adult age differences in memory for name–face associations: The effects of intentional and incidental learning. Memory 17, 220–232.

62.

Troyer

, Murphy

, Anderson

, Hayman-Abello

, Craik

Fergus IM

, Moscovitch

(2008) Item and associative memory in amnestic mild cognitive impairment: Performance on standardized memory tests. Neuropsychology 22, 10–16.

63.

Didic

, Barbeau

, Felician

, Tramoni

, Guedj

, Poncet

, Ceccaldi

(2011) Which memory system is impaired first in Alzheimer’s disease? J Alzheimers Dis 27, 11–22.

64.

Parra

, Abrahams

, Logie

, Méndez

, Lopera

, Della

Sala S

(2010) Visual short-term memory binding deficits in familial Alzheimer’s disease. Brain 133, 2702.

65.

Donohue

, Sperling

, Salmon

, Rentz

, Raman

, Thomas

, Weiner

, Aisen

(2014) The preclinical Alzheimer cognitive composite: Measuring amyloid-related decline. JAMA Neurol 71, 961–970.