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Journal of Alzheimer’s Disease 48 (2015) S161–S170 DOI 10.3233/JAD-150105 IOS Press

Feature Binding Deficits in Subjective Cognitive Decline and in Mild Cognitive Impairment Alexander Kopparaa,b,∗ , Ingo Frommanna,b , Alexandra Polchera,b , Mario A. Parrac,d , Wolfgang Maiera,b , Frank Jessena,b , Thomas Klockgetherb,e and Michael Wagnera,b a Department

of Psychiatry and Psychotherapy, Rheinische-Friedrich-Wilhelms University Bonn, Bonn, Germany Center for Neurodegenerative Diseases (DZNE) Bonn, Bonn, Germany c Human Cognitive Neuroscience and Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK d UDP-INECO Foundation Core on Neuroscience (UIFCoN), Diego Portales University, Santiago, Chile e Department of Neurology, Rheinische-Friedrich-Wilhelms University Bonn, Bonn, Germany b German

Accepted 30 June 2015

Abstract. Background: Feature binding is a sensitive and specific cognitive marker for Alzheimer’s disease (AD). Subjective cognitive decline (SCD) and mild cognitive impairment (MCI) are clinical categories associated with an increased risk for AD. Objective: To investigate whether the SCD and MCI group are impaired with regard to feature binding. Methods: The feature binding test was administered to memory clinic patients with either SCD (n = 19, mean MMSE: 29.2) or with MCI (n = 23, mean MMSE: 26.5), and to a group of healthy controls (HC, n = 23, mean MMSE: 29.0). Participants were assessed with the CERAD Plus neuropsychological test battery. Cognitive performance of the three groups was compared by ANCOVA with age, gender and education as covariates and planned contrasts. Results: Groups differed in the binding condition. Planned contrasts showed significant differences in adjusted means between HC and SCD (p = 0.003), as well as between HC and MCI (p < 0.0001). Discussion: The feature binding task detects subtle cognitive impairments in participants with SCD, who are unimpaired in traditional neuropsychological testing. This corroborates the use of feature binding tests in preclinical AD studies and suggests that specific cognitive deficits can be found in SCD. Future studies incorporating AD biomarkers and longitudinal follow-up are needed to further establish the clinical utility of feature binding. Keywords: Alzheimer’s disease, early detection, feature binding, mild cognitive impairment, subjective cognitive decline

INTRODUCTION Alzheimer’s disease (AD) has a long preclinical period spanning many years or even decades. According to the prevailing hypothesis of AD progression, an ∗ Correspondence

to: Dipl.Psych. Alexander Koppara, Department of Psychiatry and Psychotherapy, Rheinische-FriedrichWilhelms University Bonn, Sigmund-Freud-Straße 25, 53105 Bonn, Germany. Tel.: +49 228 287 16946; E-mail: alexander.koppara@ ukb.uni-bonn.de.

early stage of asymptomatic cerebral amyloidosis is followed by a second stage of still asymptomatic neurodegeneration, before subtle cognitive changes can be observed in stage 3 of preclinical AD [1]. By definition, these cognitive changes do not reach the level required for a diagnosis of mild cognitive impairment (MCI), and cannot reliably be detected with traditional neuropsychological tests. However, a new generation of promising cognitive tasks for the early assessment of AD is approaching [2]. A short-term memory binding

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(STMB) task has recently been validated as an early and specific indicator for AD. Asymptomatic carriers of the single mutation E280A in the PS1 gene [3] presented with STMB deficits which contrasted with a completely normal neuropsychological test performance. Deficits in STM in this population anticipated deficits in other memory functions known to be sensitive markers for AD such as associative learning [4–6]. A neuroimaging study confirmed that the STMB function assessed by this task relies on structures within the ventral visual stream, specifically the fusiform gyrus, but does not involve the hippocampus [7]. A recent hypothesis paper has proposed that AD first undergoes a sub-hippocampal stage during which the diseases impacts on structures outside the hippocampus including elements of the abovementioned stream [8]. As the vast majority of AD cases are sporadic, the usefulness of the STMB task to detect subtle cognitive deficits in groups at risk for sporadic AD needs to be further established. MCI, and in particular amnestic MCI, is an established clinical at-risk state for AD. Belleville’s group showed that MCI patients are impaired on complex working memory tasks, such as complex span tasks [9]. MCI has also been studied with STMB tasks which were sensitive to preclinical AD, although they did not include a single feature control condition (as the STMB task) [10, 11]. STM is impaired in mild sporadic AD dementia as well as in mild familial AD dementia [12]. Several strategies are currently pursued to study subjects at risk for AD in a pre-clinical (pre-MCI) state, including the study of amyloid-positive healthy elderly [13, 14], of APOE4 gene carriers [15] and of subjects with subjective cognitive decline (SCD) [16]. Memory complaints are highly prevalent in the elderly population, and cross-sectional they are more strongly correlated with depression rather than with neuropsychological impairment [17]. However, longitudinal epidemiological studies of elderly subjects clearly show that memory concerns precede and predict objective memory decline and AD dementia [18]. Healthy elderly with memory complaints also have an increased prevalence of biomarkers of amyloidosis [19]. In clinical settings, subjects who are referred for evaluation of persistent memory complaints, but who perform within normal limits on traditional neuropsychological tasks, more frequently show signs of AD-typical neuronal damage and dysfunction than controls. For example, in studies with patients from our own memory clinic, we found that help-seeking subjects with SCD had smaller

hippocampal and entorhinal volumes [20], had an ADlike pattern of gray matter atrophy, which predicted memory decline [21], and had reduced metabolism in the right precuneus and right medial temporal lobe (MTL) as examined with FDG-PET, which also predicted longitudinal memory decline [22]. Consequently, elderly subjects with SCD who present with certain features (e.g., report of memory decline, associated concerns) are considered to be at an increased risk of preclinical AD [16]. This evidence warrants investigation of STMB in individuals with SCD since this may be the earliest window of opportunity to investigate behavioral impairment associated to pathological changes using inexpensive non-invasive procedures. There are also no studies on STMB in MCI to date, which is an established “clinical” risk group. SCD and MCI are heterogeneous conditions that may or may not lead to AD. Hence, we predicted that if the sensitivity of STMB test previously reported in preclinical studies of AD holds for this population, we should be able to detect impairments within both groups. METHODS Participants A total of 65 participants were assessed with the feature binding test and neuropsychological tests. All participants gave their written informed consent to take part in the study. The study was approved by the Ethical Committee of the Medical Faculty, University of Bonn and it adhered to the Declaration of Helsinki. Participants with SCD (n = 19) were recruited within the memory clinic of the Clinical Treatment and Research Center for Neurodegenerative Disorders (KBFZ), Department of Psychiatry, Department of Neurology, University Hospital Bonn. The definition of SCD was based on the fact that participants were referred to the memory clinic for work-up of memory impairment and on a standard question: “Do you feel like your memory is getting worse? ”. To be classified as SCD in this study, the participants had to answer “yes, this worries me”. Possible answers to this question were: “no”; ”yes, but this does not worry me”, and “yes, this worries me”. This question has been validated with an increased hazard ratio for AD [22, 23, 16]. SCD participants scored within ± 1.5 SD on any subtest of the Consortium to Establish a Registry of Alzheimer’s disease (CERAD) NP battery. To rule out the presence of non-amnestic MCI participants in our SCD sample, CERAD Plus

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subtests trail making test A/B and S-Words were added to the assessment. They were considered SCD if they performed within the range of normal age, gender, and education adjusted normative cut-offs of –1.5 SD on these subtests. Participants with MCI (n = 23) were recruited in the same setting. They scored below 1.5 SD on at least one of the sub scores of the CERAD NP battery. Most patients (n = 20) were impaired in memory; three patients were classified as non-amnestic MCI. Dementia was ruled out by at least two clinicians in a consensus meeting, based on the interpretation of the CERAD results and the Structured Interview for the diagnosis of dementia of the Alzheimer type, multi-infarct dementia, and dementia of other etiology according to the DSM-IV and ICD-10 (SIDAM) [24] interview, which relies on a diagnostic algorithm for diagnosis of dementia according to DSM-IV TR. Members of the control group (n = 23) were spouses or close relatives in five cases. They accompanied the patient with SCD to the memory clinic. Moreover, six controls from a previous independent study who gave their permission to be contacted again were included in our study. Additional participants of the control group (n = 12) were recruited from the general population through a newspaper article. Exclusion criteria for all controls were: 1) past or present neurological or medical diseases, including addiction disorders; 2) medication that may interfere with cognition, including any psychotropic medication; and 3) memory complaints (the controls answered the same questions as the participants with SCD), to avoid the inclusion of individuals with a motivation of clinical help seeking. Inclusion as control was only granted if memory impairments were denied in both the telephone screening and face to face interview. Normal cognitive functioning was defined using the neuropsychological test battery of CERAD [25], using German age-, gender-, and education-adjusted norms (http://www.memoryclinic.ch). No control subject scored below −1.5 SD on any of the subtests of the CERAD battery. Patients and controls were matched on demographic characteristics such as age, years of education, and gender. The externally recruited controls were rewarded with a combined compensation for travel costs of 20 D . Inclusion of participants to the study was granted, after a comprehensive vision assessment. These conditions were undertaken to rule out the possibility that poor performance on the STMB task could result from visual or perceptual difficulties. The vision assessment included: 1) Screening for macular degeneration was

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done with the Amsler-Grid test [26]; 2) Color vision was assessed using the Ishihara color vision assessment [27]. This test assesses color vision within the red–green wavelengths. It is accepted that more than two errors suggest borderline or mild color vision problems, while six errors or more are indicative of color vision deficits. In the present study, more than two errors were set as the exclusion criterion; 3) Perception for shape-color binding was then assessed with a task that simultaneously presented two arrays of colored shapes, one in the upper half of the screen and one in the lower half. On each of 10 trials, participants searched for changes between the two arrays. The stimuli and design were the same as those described below for the shape-color memory binding condition. The cut-off score, which indicates perceptual binding difficulties, was set at 90% correct (9 out of 10 trials). Of the participants initially recruited for the present study, four were excluded due to perceptual binding problems and five due to color vision problems. Neuropsychological assessment Patients were tested with the CERAD neuropsychological battery [28]. The CERAD includes the subtests Mini-Mental State Examination (MMSE), Visual Learning and Recall, Copy Figures and Recall, Semantic Fluency, a Wordlist test with three learning and recall trials, and a Delayed Recall trial. The CERAD Plus also includes the Trail making Test A and B and a Lexical Fluency Task. Additionally, the WMS-R digit span forward and backward was administrated. The latter three tests were available only for a subset of participants (see Table 1). Age, gender, and education adjusted norms were available and results of the tests were compared on z-values for diagnostic purposes. After completing the test battery, patients were admitted to the second part of the assessment. Screening tests for visual and cognitive abilities were conducted before the STMB task. STMB task An IBM compatible laptop with 15-inch monitor was used. Research participants sat approximately 28 inches from the bottom of the stimulus. We used the STM task from the original study by Parra et al. [4]. All instructions were translated to German and checked for linguistic accuracy by native speakers. The task assessed visual STM (VSTM) for arrays of stimuli presented on a computer screen. Stimuli were shapes (six-sided random polygons as shown in Fig. 1), or

68.00 14.39 0.39 29.04 10.13 10.65 22.96 0.22 23.74 6.30 8.26 9.17 8.35 34.94 87.94 7 5.5 14.61 0.46 0.81

23 23 23 23 23 23 23 23 23 23 23 23 23 17 17 4 4 23 23 23

Age Years of Education Gender % Women MMSE Visual Recall Copy Figures Semantic Fluency Wordlist Intrusions Immediate Recall Wordlist Trial 1 Wordlist Trial 2 Word List Trial 3 Delayed Recall TMT-A TMT-B WMS-R Digit Span forward WMS-R Digit Span backward S-Words Binding Corrected Recognition Shapes Corrected Recognition 19

19 19 19 19 19 19 19 19 19 19 19 19 19 14 14 10 10 19 19

n

0.78

66.79 16.53 0.42 29.16 9.42 10.74 24.53 0.53 23.11 6.16 7.95 9.00 8.11 42.86 92.64 6.20 5.70 18.05 0.32 0.16

1.17 1.68 0.45 5.87 0.96 2.56 1.17 1.08 1.05 1.37 16.74 29.23 2.45 2.21 3.79 0.15

7.58 3.03

SD

SCD (n = 19) Mean

23

23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 20 20 22 23

n

0.60

72.82 13.27 0.55 26.55 4.86 10.09 14.64 2.41 15.73 4.00 5.36 6.36 3.27 56.74 177.48 6.75 5.00 10.68 0.25 0.22

2.34 3.06 1.34 5.53 2.75 3.81 1.57 1.36 1.59 2.16 18.08 82.88 1.51 1.77 5.18 0.14

4.37 2.96

SD

MCI (n(23)) Mean

Symbols for significant post hoc group differences: *HC versus SCD; † HC versus MCI; ‡ SCD versus MCI bold: significant p-values.

0.12

1.07 1.25 0.49 5.75 0.52 3.17 1.40 1.29 0.94 1.23 7.14 26.72 2.31 1.29 4.19 0.17

8.31 3.07

SD

HC (n = 23) Mean

n

Group

Table 1 Demographic and neuropsychological data for patients and controls

0.001

0.013 0.003 χ²(df = 2)=1.577, p = 0.455 0.001 0.001 0.032 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.701 0.611 0.001 0.001

p-value

†,‡

∗,‡

†,‡

†,‡

†,‡

†,‡

†,‡

†,‡

†,‡

†,‡

†,‡

†,‡

†,‡

†,‡

‡ ‡

Post hoc tests

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Fig. 1. Experimental conditions and trial design. The actual set size was three, but we show two to highlight the contrast between same/different trials.

combinations of shapes and colors. Stimuli were randomly selected from a set of eight shapes and a set of eight colors and were presented either as individual shapes (i.e., VSTM for single features) or as shapes combined with colors (i.e., VSTMB). Each type of stimulus was presented in a separate condition. The shapes and colors were assessed for recognition and discriminability in a previous study [4]. We omitted the color only condition, as previous studies have confirmed that this condition leads to ceiling effects in controls whereas shape only provides the best baseline condition to assess the cost of feature binding [29, 30]. During the task patients and healthy controls were presented with arrays of three items. The trial design for each condition of the VSTM task is shown in Fig. 1. The task was based on a change detection paradigm. At the beginning there was a fixation screen for 500 ms. This was followed by the study display which was presented for 2000 ms. The study display presented three items as explained above. The task for the participant was to remember these items. After the study display there was an unfilled retention interval of 900 ms, which was followed by the test display. The participants were asked to recognize if the items presented in the test display were the same or different from those presented at study. In 50% of the trials, the items were the same in both displays (i.e., ‘same trials’). In the other 50%, two items in the test display were different (i.e., ‘different trials’). One block assessed VSTM for single features and one

assessed the binding of these features in VSTM. In the ‘shape only’ condition, arrays of shapes (Fig. 1) were presented in the study display. In the test display for the ‘different trials’, two new shapes from the study array were replaced with two new shapes. Hence, in these conditions, only VSTM for individual features was required to detect a change. In the shape-color binding condition, combinations of shapes and colors were presented in the study display. In the test display for the ‘different trials’, two shapes swapped the colors in which they had been shown in the study display. Hence, memory for bindings of shape and color in the study display was required in order to detect this change. No shape or color was repeated within a given array. Each condition consisted of 32 test trials. Out of 32, 50% were ‘same trials’ (the study and test displays presented identical items) and 50% were ‘different trials’ (Fig. 1). The task for the participants was to detect when a change had occurred and to respond orally ‘same’ or ‘different’ as appropriate. The experimenter entered participants’ responses using the keyboard or mouse. Trials were fully randomized across participants and conditions were delivered in a counterbalanced order. Statistical analysis A one-way ANOVA was conducted to compare performance of the three groups on the CERAD-plus subtests that were considered for group definition.

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For the experimental STMB task, the dependent variable of corrected recognition was defined as the proportion of trials correctly performed (hits) minus false alarms. This is a better memory accuracy measure for recognition tasks than hits plus correct rejection, which often results in ceiling effects in individual patients without cognitive impairments. Because we wanted to test if feature binding underlies a gradual impairment, beginning at the SCD stage and increases toward the MCI stage, planned contrasts were conducted in an ANCOVA model (with the covariates of no interest age, gender, and education) between the control group and SCD, as well as between control group and MCI. Separate one way ANCOVAs were conducted for the shape and shape-color binding conditions. For the main effects in the shapes and shape-color binding condition of the STM task, the effect size Cohen’s d was calculated [31]. An effect of d = 0.2 was considered a small effect, d = 0.5 as a medium effect, and d = 0.8 and above a large effect. RESULTS Neuropsychological data The results of the neuropsychological assessment are presented in Table 1. Comparisons across groups and post hoc tests confirm poorer performance of MCI patients than both healthy controls and SCD participants in the subtests semantic fluency, Boston Naming Test, MMSE, immediate recall, delayed recall, intrusions, recall of figures, and trail making test A and B. Importantly, mean performance of healthy controls and SCD did not differ significantly on any of the neuropsychological test scores. In the SCD group, the analysis of the trail making test A/B and digit span did not confirm a subgroup with non-amnestic features of MCI.

scores, 17.1% was accounted for the three levels of group controlling for the effects of covariates of no interest. The total variance explained of the model was R2 = 0.302 (Adjusted R2 = 0.243). Planned contrasts were calculated to evaluate pairwise differences among the adjusted means of group membership. The results showed that participants of the SCD group had significantly lower feature binding scores (M = 0.304) (Adjusted mean difference: –0.15, p = 0.003, 95% CI: –0.25– –0.05), controlling for the effect of the covariates of no interest, than members of the control group (M = 0.457). Participants of the MCI group had lower feature binding scores (M = 0.273), controlling for covariates of no interest than the control group (Adjusted mean difference: –0.18, p < 0.0001, 95%CI: –2.8 – –0.08) and SCD group. The effect sizes for these significant adjusted mean differences were d = 0.97 for controls versus SCD and d = 1.17 for controls versus MCI and d = 0.18 for SCD versus MCI, respectively. The same procedure was repeated for the shapes condition. The ANCOVA was significant (F(2,59) = 4,186, p = 0.02). Planned contrasts showed that participants of the SCD group did not have significantly lower scores for shapes (M = 0.78) (Adjusted mean difference; –0.059, p = 0.282, 95% CI: –0.17 –0.05), controlling for the effect of the covariates of no interest, than members of the control group (M = 0.81). Participants of the MCI group had lower scores for shapes (M = 0.61), controlling for the effects of covariates of no interest, than the control group (Adjusted mean difference: –0.153, p < 0.005, 95% CI: –0.26 – –0.05). The effect size for the adjusted mean difference were 0.35 for controls versus SCD and d = 0.94 for controls versus MCI. Figure 2 presents the corrected recognition in the binding (Fig. 2a) and the shapes (Fig. 2b) condition. respectively.

STMB data DISCUSSION ANCOVA A one-way analysis of covariance (ANCOVA) was conducted for the binding condition. The independent variable, group, included three levels: healthy controls, SCD, and MCI. The dependent variable was the corrected recognition in the binding condition (hits minus false alarms) and the covariates of no interest were age, gender, and education. The ANCOVA was significant, F(2,59) = 8.83, p < 0.0001, ω2 = 0.171. Of the total variance in feature binding corrected recognition

This study leads to two main findings: First, significant binding deficits with fairly large effect sizes were found in SCD and, second, even more pronounced, in MCI patients of this sample. On a group level, the feature binding task is able to distinguish between SCD and control participants, as well as between MCI and control participants. These results show that the feature binding test can aid to objectify deficits in SCD, which are not

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Fig. 2. a. Feature binding performance (corrected recognition) in healthy controls (HC), subjective cognitive decline (SCD), and mild cognitive impairment (MCI). b. Shapes performance (corrected recognition) in healthy controls (HC), subjective cognitive decline (SCD), and mild cognitive impairment (MCI).

detectable with an established neuropsychological test battery (such as the CERAD). The feature binding task identified STMB deficits in SCD in the present study, as it did in a previous study with asymptomatic presenilin-1 mutation carriers [4]. In our sample, the MCI patients performed worse on both the shapes and the binding condition than SCD and controls. The three items version used in this study may overtax the capacity of MCI participants already in the shapes condition. This is possibly because MCI patients are on a stage of impairment closer to that seen in AD patients. In fact, previous studies with the STMB test have equated performance on single features conditions across patient groups and controls by presenting the former with smaller set sizes (e.g., patients with 2 items and controls with 3 items). Under this testing condition, paramount binding deficits have been found in patients [4, 6, 29]. Only at-risk individuals who were asymptomatic at the time of testing were assessed with the same set size used in controls [4]. The results for this earlier study [4] mirror those found here where we consider SCD to represent an at-risk group. Therefore, whereas the drop in accuracy for shape only in MCI participants may indicate a non-specific decline in STM functions, the drop in shape-color binding in SCD patients suggests specific changes that may be linked to AD pathology. This assumption needs further testing in studies incorporating AD biomarkers or longitudinal follow-up. This task assesses VSTM. Participants underwent a comprehensive vision assessment before they were invited to perform the memory task. This assessment

was aimed at confirming that our participants could clearly process the stimuli and also integrate them into perception. However, it should be noted that vision and color vision impairments precluded the STMB assessment in about 10% of the elderly patients. Computerized tasks are not commonly used in the early detection of AD, although their validity as screening tools to detect variants of abnormal aging is being acknowledged [32]. Computerized testing has a number of advantages. Features such as randomization allow ruling out practice effects. The administration on a computer allows standardized and simple conduct (which leads to smaller error variance), and faster results. Efforts by other groups to develop neuropsychological context-free memory tests for early diagnosis of AD include the DMS 48 [33–36]. Why is STMB already affected in preclinical AD, before episodic memory deficits can be detected with established tests? One possible explanation is that STMB requires the functional integrity of brain regions affected by AD even earlier than the hippocampus, i.e., the entorhinal/perirhinal cortices. A recent study reported involvement of the fusiform gyrus in the STMB function assessed here [7]. The authors argue that this indicates involvement of structures of the visual ventral stream in STMB. In AD studies where this task or other context-free memory tests have been used, it has been acknowledged that regions of the visual stream (i.e., right fusiform gyrus and left inferior temporal lobe) might be compromised in AD earlier than the hippocampus. Particularly,

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regions of such a stream within the MTL [8, 37] are promising candidates. It is known that MTL regions such as perirhinal and entorhinal cortex are targeted by AD earlier than the hippocampus [38]. Our current results and those from previous studies using the same VSTMB task investigated here lend support to this hypothesis. Staresina & Davachi [39] suggested that regions within the MTL such as the perirhinal cortex seem to track the amount of item-related information successfully encoded (i.e., memory load). However, they found that unitization of object fragments seems to be accomplished in visual/ventral temporal processing stages prior to perirhinal cortex (e.g., fusiform gyrus). In humans, the identity of individual objects appears to be integrated in the object selective posterior fusiform cortex [40]. The outcomes form these processes would feed into the MTL via perirhinal and entorhinal cortex and from there into the hippocampus and other neocortical regions. Recently, it has been found that the lateral entorhinal cortex is affected in the preclinical stages of AD and that such a dysfunction can spread to neocortical areas such as the parietal cortex during preclinical stages [41]. A recent fMRI study confirmed that the VSTMB task investigated here activated a posterior network which involves parietal and occipito-temporal regions but not the hippocampus [7]. Furthermore, amyloid-PET studies with asymptomatic carriers of the mutation E280A-PS1 who develop familiar AD at the mean age of 47 and who have previously shown significant STMB deficits with the same task used in this study, have unveiled increased amyloid deposits in parieto-temporal areas [42]. Taken together these results suggest that dysfunction of the occipital-parietal-temporal network in stages proceeding the hippocampal phase of AD may account for the STMB deficits reported in studies with pre-symptomatic populations (see [43] for similar views). The impairment detected by the STM binding test in preclinical AD might reflect the spread of the disease from transentorhinal cortex to fusiform gyrus [44]. There is evidence of disruption of the fusiform network in prodromal AD and this impairment may be independent of the type of stimulus used as long as identify formation is needed whether such identity entails faces [45], landmarks [44, 46], or shape-color binding [47]. These regions are relevant for context-free memory [8, 37] and remain largely preserved across the lifespan [48] in normal aging. The change detection task reported here has proved to be performed in the absence of a functional hippocampus [49, 50]. Recent neuroimaging studies in

healthy young volunteers confirmed that the hippocampus is not involved in this memory binding function as assessed by the change detection task (CDT) [51]. The fact that there is no accumulation of information from trial to trial in this CDT [52, 53] and items randomly change location from study to test (rendering contextual spatial information uninformative), makes this task less reliant on contextual memory. Recently [51] activation of regions of the visual ventral stream, which are known to support object identity formation, was shown. The involvement of entorhinal/perirhinal cortices is hypothesized based on the understanding that these are MTL regions of the ventral stream and are important for context-free memory functions known to be affected by AD earlier than context-rich memory functions [8]. Such a hypothesis about the neuroanatomy of STM binding within the MTL is currently under investigation. Limitations of this study include the small sample size and the lack of biomarkers. The cohort may also have different characteristics than a population-based sample. There are no longitudinal studies about feature binding and how it correlates to changes in cognition so far. How sensitive feature binding is to changes in cognition and/or neuropathology thus remains to be shown. Also, deficits could be present on complex or even higher-load traditional working memory tests, such as longer sequences of the Digit Span backwards. However, the digit span data available in our sample did not suggest the existence of such deficits in the SCD group. Moreover, an unmet need in the assessment of AD is the identification of tasks which can detect impairments not attributable to task demands or disease severity [54]. The VSTMB test seems to meet such a need. In sum, this study provided evidence for specific VSTMB deficits in participants with SCD, a group which is at increased risk for AD. The STMB task is a promising candidate to become an inexpensive and non-invasive clinical tool for the assessment of first signs of AD in individuals who seek help for their subjective memory impairments.

ACKNOWLEDGMENTS The study was supported by the University of Bonn, Department of Psychiatry and Psychotherapy, Department of Neurology and the German Center for Neurodegenerative Diseases (DZNE). M.A.P. work is supported by Alzheimer’s Society, Grant # AS-R42303.

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We appreciated the support of Sandra R¨oske, Hanna Hundhausen, Luca Kleineidam, Elisa Kreienkamp, Lisa Miebach, Klaus Fliessbach, and Anja Steinbrecher in the recruitment and assessment of patients and healthy controls. Authors’ disclosures available online (http://www.jalz.com/manuscript-disclosures/15-0105r2).

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Feature Binding Deficits in Subjective Cognitive Decline and in Mild Cognitive Impairment.

Feature binding is a sensitive and specific cognitive marker for Alzheimer's disease (AD). Subjective cognitive decline (SCD) and mild cognitive impai...
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