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Conceptual implicit memory impaired in amnestic mild cognitive impairment patient
Neuroscience Letters 484 (2010) 153–156
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Conceptual implicit memory impaired in amnestic mild cognitive impairment patient Liang Gong a,b , Yanghua Tian a , Huaidong Cheng a,c , Zhendong Chen c , Changlin Yin a , Yu Meng a , Rong Ye a , Kai Wang a,∗ a b c
Neuropsychological Laboratory, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui Province, PR China Department of Neurology, People’s Hospital of YuXi City, The Sixth Affiliated Hospital of Kunming Medical College, Yuxi 653100, PR China Cancer and Cognition Laboratory, Department of Oncology, The Second Affiliated Hospital of Anhui Medical University, Hefei 230022, PR China
a r t i c l e
i n f o
Article history: Received 8 June 2010 Received in revised form 4 August 2010 Accepted 12 August 2010 Keywords: Amnestic mild cognitive impairment Alzheimer’s disease Implicit memory
a b s t r a c t Explicit memory has been well proven to be impaired in amnestic mild cognitive impairment (aMCI), and conceptual implicit memory is impaired in Alzheimer’s disease. However, it is unclear whether implicit memory is affected in aMCI. In the present study, 35 patients with aMCI and 35 healthy elderly subjects were administered a neuropsychological battery of tests including conceptual and perceptual implicit memory tasks (category exemplar generation, image identification) as well as explicit memory tasks. Patients with aMCI exhibited impairment in explicit memory tasks and selective impairment in conceptual priming tasks, while the effect of perceptual priming was preserved. More importantly, category exemplar generation task priming, but not perceptual priming, was positively correlated with verbal fluency test performance in the aMCI group. The dissociation between the 2 components of implicit priming suggests that conceptual priming impairment in aMCI patients may be related to frontal lobe dysfunction. © 2010 Elsevier Ireland Ltd. All rights reserved.
Implicit memory is a type of memory in which previous experiences aid in the performance of a task without conscious awareness of these previous experiences [33]. In contrast, explicit memory refers to the conscious or intentional recollection of previous experiences and information. Most common evidence for implicit memory arises in priming, a process whereby subjects show improved performance on tasks for which they have been subconsciously prepared [16]. On the basis of process distinction, priming can be fractionated into 2 subtypes: perceptual priming and conceptual priming. Perceptual priming is modality specific and does not depend on the semantic or elaborative encoding of an item, as in the case of word identification and image identification, whereas conceptual priming is not modality specific and benefits from semantic encoding [5], as in the case of free-association and category exemplar generation tests [34]. It has been reported that patients with focal damage to the occipital cortex fail to show perceptual priming, but do show normal conceptual priming [15]. Frontal cortex damage model schizophrenic patients show lower conceptual priming than control subjects, but comparable perceptual priming [36]. Additional converging evidence concerning the brain regions that are relevant to priming has been provided by recent neuroimaging
∗ Corresponding author. Tel.: +86 0551 2923704; fax: +86 0551 2923704. E-mail address: [email protected] (K. Wang). 0304-3940/$ – see front matter © 2010 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.neulet.2010.08.041
studies. Neuroimaging studies using positron-emission tomography (PET) and functional magnetic resonance imaging (fMRI) have revealed that priming is often accompanied by decreased activity (neural priming) in a variety of brain regions [35]. Different types of behavioral priming may rely on neural priming in different cortex areas. Neural priming in the posterior regions (visual regions, auditory regions, parahippocampal cortex, and fusiform cortex) may be the basis for perceptual priming [2], while neural priming in the left frontal cortex may be the basis for conceptual priming [41]. Mild cognitive impairment (MCI) refers to a clinical condition in which patients experience a memory loss greater than expected for their chronological age, yet not severe enough to meet the currently accepted criteria for clinically probable Alzheimer’s disease (AD) [31]. When memory loss is the predominant symptom, it is termed “amnestic MCI” (aMCI) and is frequently considered to be a risk factor for AD [17]. Much experimental work investigating the qualitative profile of memory dysfunction in aMCI documents the pervasive impairment of declarative or explicit memory [9,24]. The characteristics of explicit memory impairment in aMCI are similar to those in AD. It is a well-established finding that explicit memory is compromised by aging [21] and profoundly impaired in AD [37]. Although most regular priming is impaired in patients with AD, there are numerous examples of preservation. In general, normal perceptual priming has been consistently reported in cases of AD [6,10], while conceptual priming has been shown
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to be impaired in many studies [12,13]. Some investigators have reported implicit memory performance in aMCI patients. Perri et al. [27] found that aMCI priming on fragmented picture identification tasks was lower than that of healthy controls but greater than that of the AD patients, and priming on word-stem completion was greater than that of both AD patients and healthy controls. They explained that explicit memory contamination in the wordstem completion task may be attributed to the inhibition of the implicit priming effect. LaVoie and Faulkner [20] found that both older controls and MCI patients showed lower levels of priming on the word-stem completion task relative to young adults, and reliably greater levels relative dementia patients; equivalent priming on the word identification task was seen in all groups. However, little is known about conceptual and perceptual implicit memory performance in aMCI patients. Amnestic MCI patients are characterized by deficits in explicit recall and recognition, which are produced by cortex changes in the hippocampal formation. A brain structure study in aMCI patients also found atrophy in the entorhinal cortex and the hippocampus [19]. In addition, recent evidence suggests that frontal lobe function is impaired in MCI [40], with relative sparing of the occipital cortex. Traykov et al. [40] found that MCI patients had problems with response inhibition, switching, and cognitive flexibility, which encompass various aspects of executive functions, which are processed by the frontal cortex. Dannhauser et al. [8] found that activation in the left ventrolateral prefrontal cortex (PFC) during encoding in the aMCI group was decreased compared to that in the healthy control group. As the frontal cortex and the occipital cortex are the basis of conceptual priming and perceptual priming, respectively, if priming is impaired in aMCI, the impairment must be related to conceptual priming. The present study aimed to examine whether the memory impairments in aMCI extend to implicit memory as well as explicit memory. Thirty-five aMCI patients and 35 healthy controls were administered with conceptual priming (category exemplar generation) and perceptual priming (image identification) tasks, as well as explicit memory (immediate recall, delayed recall, delayed recognition) tasks. We predicted that individuals with aMCI would exhibit impaired conceptual priming (category exemplar generation) relative to healthy older controls. Each subject underwent a uniform clinical evaluation that included a medical history, a neurological examination, and neuropsychological performance testing. Thirty-five healthy older adults (17 men, 18 women) with a mean education of 10.6 years and an age range of 58–78 (mean 69.1) engaged in the experiment. Thirty-five patients with a diagnosis of probable aMCI [29] (19 men, 16 women) with a mean education of 10.3 years and an age range of 55–84 (mean 68.9) entered the experiment. The aMCI patients were recruited from the outpatients of the first hospital of Anhui Medical University. The performance of the healthy older group was within normal limits for age and education according to measures of: (a) Mini-mental state examination, MMSE [14]; Montreal Cognitive Assessment, MoCA [25]; (b) Auditory Verbal Learning Test Delayed Recall (AVLT) [32]; (c) Self-Rating Depression Scale, SDS [42]; and (d) Clinical Dementia Rating, CDR [4]. The control subjects were required to have a CDR of 0, an MMSE score of 26, and a Delayed Recall score of >4 for those with 8 or more years of education. Patients with aMCI met the following criteria: (a) a recent history of a symptomatic worsening of memory; (b) an objective memory injury for their age, according to cognitive testing, which is 1.5 SD lower than the demonstrated verbal ability of the aMCI group; (c) an MMSE score of 24–30; (d) a global CDR score of 0.5, with a memory score of 0.5 or greater; (e) not meeting the NINCDSADRDA or Diagnostic and Statistical Manual of Mental Disorders IV, Text Revision criteria for dementia; (f) normal or near-normal
independent functions; and (g) an absence of other factors that might have better explained their memory loss (e.g., depression). The criteria used for MCI were those accepted by the field for clinical research. A comprehensive battery of tests managed to assess both general cognitive functions and memory: the MMSE and MoCA to measure global cognitive function and the Verbal Fluency Test (VFT) [22] to measure frontal lobe functions; Digit Span (DS) [26] was used to measure the working memory. The immediate recall, delayed recall, and delayed recognition trials were performed as a multiple-form test of explicit verbal memory. In each of the 3 learning trials, the participants heard a list of 15 words and tried to recall as many as possible within 2 min. The correct number of responses from the first trial was taken as the immediate recall scores. After a 20 min filled interval (i.e., with nonverbal tasks), the participants completed a delayed recall trial and a delayed recognition trial. In the delayed recall trial, participants were asked to recall the words learned earlier. In the test phase of the delayed recognition trial, participants heard a list of 30 words (15 old and 15 new) and were asked to decide if the words had been heard before or not. Perceptual priming was investigated by an image identification test [7]. The stimuli consisted of 80 grayscale images comprising 40 entity images of common objects and 40 corresponding mosaic images of each picture. The entity images contained animals, fruit, tools, and other common objects, and the mosaic images were manufactured by Photoshop software. The identification rate of each entity image and mosaic image was over 98% and 20–30%, respectively, by 40 adults. During the study phase, the participants were presented with a list of 20 entity images, and were required to rate each image on a 5-point liking scale. The study list assignment was counterbalanced across the participants. The study was self-paced, but the participants were told to respond as quickly as possible. During the test phase, which was administered 15 min after the study phase, participants were presented with the 40 mosaic images (half with studied items and half with new items). The participants were asked to name each image within 10 s. Guessing was allowed. Priming was measured as the increase in the probability of naming a studied versus an unstudied mosaic image. Conceptual priming was evaluated using the category exemplar generation task [13]. During the study phase, the participants were visually presented with 20 words belonging to 1 of 2 categories (e.g., vegetables, household appliances), 1 at a time, individually printed on cards. The categories were matched with respect to category potency [3]. The subjects were asked to indicate whether the words represented living or nonliving entities. During the test phase, which was administered 15 min after the study phase, the subjects were asked to generate 8 examples for each of 4 specified categories (2 old and 2 new) as quickly as they could. The instructions were given without reference to the previously studied list of words. A different category was presented when the individual had generated 8 examples or if the subject failed to produce a new response in a 1-min period. The examiner recorded the words they said with a tape recorder. The examples for the unstudied categories were used as a baseline measurement of performance for this task. Priming was measured as the increase in the probability of producing a studied versus an unstudied category example. The SPSS-15 statistical package was used for the data analysis. Differences in age, education, MMSE, MoCA, VFT, DS, and AVLT score between aMCI and healthy older controls were assessed using ttests. Comparisons among aMCI and healthy older controls on the performance of explicit memory and implicit memory were performed using an Independent Samples T Test. We used Pearson’s correlation to examine the association between aMCI patients’ verbal fluency tests and memory scores. The probability level was 0.05.
L. Gong et al. / Neuroscience Letters 484 (2010) 153–156
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Table 1 Demographic and neuropsychological background tests of healthy elderly and aMCI patients. Characteristic
aMCI patients
Healthy controls
Number of participants Sex (F/M) Age, years (mean (SD)) Educational level MoCA, mean (SD) MMSE, mean (SD) DS, mean (SD) VFT, mean (SD)
35 16/19 68.69 ± 7.85 10.34 ± 3.2 24.63 ± 2.5* 27.53 ± 1.4* 6.51 ± 0.7* 12.43 ± 3.0**
35 18/17 69.09 ± 4.21 10.63 ± 2.9 27.66 ± 0.7 29.46 ± 0.7 7.74 ± 0.4 15.77 ± 3.60
* **
P < 0.05. P < 0.01.
In Table 1, there was no significant difference between the aMCI patients and the healthy controls in terms of age, education, or sex and DS (P > 0.05). The performance of the patients in the aMCI group was significantly poorer than that of the patients in the healthy control group on the MMSE, MoCA, AVLT, and VFT (P < 0.01). The explicit memory performance, including immediate recall, delayed recall, and delayed recognition, was worse in the aMCI group than in the healthy control group. The difference was statistically significant (immediate recall, t = 6.40, P < 0.01, delayed recall, t = 9.29, P < 0.01 delayed recognition, t = 7.65, P < 0.05) (see Table 2). There was no significant difference between the aMCI group and the healthy control group in terms of the image identification task (t = 0.78, P > 0.05). Performance of the category exemplar generation task in the aMCI group was poorer than that in the healthy control group (t = 3.21, P < 0.01) (see Table 2). The verbal fluency score was not associated with the explicit memory score (P > 0.05). The verbal fluency score was not associated with perceptual implicit memory (image identification, r = 0.211, P = 0.22). Conceptual implicit memory (category exemplar generation) was positively associated with the verbal fluency score (r = 0.739, P < 0.01) (see Fig. 1). The present results indicate that aMCI patients were not only impaired in explicit memory, but also in implicit memory, particularly in conceptual priming. Consistent with our predictions, the conceptual priming task score (category exemplar generation) in the aMCI patients was poorer than that in the healthy controls, and the perceptual priming task score (image identification) was identical between the 2 groups. This characteristic of implicit memory performance was similar in MCI and AD patients. The performance on explicit memory tests in our study was similar to that of most prior aMCI studies [27,30]. This finding is in complete accord with the neuroanatomical changes that occur in aMCI patients. Much evidence has proven that mesial-temporal lobe (MTL) structures in aMCI patients were extensively affected [1,18], and MTL is well known to be critically involved in explicit memory functioning [38,39]. In addition, our main finding is that conceptual implicit memory was impaired in aMCI patients, while perceptual implicit memory was spared. Our results conformed to the preliminary findTable 2 Explicit and implicit memory scores of healthy elderly and aMCI patients. Measurement Explicit memory Immediate recall Delayed recall Delayed recognition Implicit memory Image identification Category exemplar generation * **
P < 0.05. P < 0.01.
aMCI patients
Healthy control subjects
3.74 ± 1.29** 3.83 ± 2.36** 9.11 ± 2.35*
5.57 ± 1.09 8.34 ± 1.64 12.77 ± 1.57
21.11 ± 5.05 5.94 ± 1.51**
22.06 ± 5.13 6.94 ± 1.06
Fig. 1. Positive correlation between verbal fluency test score and category exemplar generation score in aMCI patients.
ings of Fleischman’s [11] study of aging in MCI and AD patients. He found that conceptual priming appears to distinguish MCI and AD from normal cognition (category exemplar generation), while perceptual priming (word-stem completion task, picture naming) appears to be intact in both MCI and normal cognition. It was also reported that higher levels of global neuropathology in AD patients were related to lower levels of explicit memory and implicit memory on the category exemplar generation task. However, it should be noted that these results are not congruent with those reported by Perri et al. [27], who employed the word-stem completion task and the fragmented picture identification task. They found that the priming on the fragmented picture identification task was lower than that of the healthy controls but greater than that of the AD group, and that the priming on the word-stem completion task was greater than that of both the AD group and the healthy controls. LaVoie and Faulkner [20] also tested priming in aMCI patients by the word-stem completion task and showed equivalent priming in MCI patients and healthy older controls. Our study confirmed that category exemplar priming, but not image identification priming, was poorer in aMCI patients than in healthy controls. Our present results indicate that conceptual priming in aMCI patients was poor compared with that in healthy controls, while perceptual priming was shared. This finding is in accord with the neuroanatomical changes that occur in aMCI patients. The posterior cortex, which processes perceptual priming, was verified to be preserved in aMCI patients [28]. In addition, an increasing amount of behavioral and neuroimaging research has recently manifested that the frontal lobe, which mainly mediates conceptual priming [22,42], might be impaired in aMCI patients [3,19,42]. For example, Traykov et al. [40] found that various aspects of the executive functions (which are mainly processed by the frontal lobe, e.g. response inhibition, switching, and cognitive flexibility) were affected in MCI patients. Our results also show that conceptual priming was impaired in aMCI patients, which indicates that frontal lobe dysfunction led to conceptual priming deterioration in aMCI patients. In order to further understand whether frontal lobe dysfunction in aMCI is related to conceptual priming, we conducted a correlation analysis between several memory and verbal fluency test scores. Our results showed that the verbal fluency test score was positively associated with the category exemplar generation score, but not with either the image identification score or the explicit memory score. The verbal fluency test is a common neuropsychological test which is often used to evaluate the frontal lobe function [23]. The findings of this study suggest that some types of implicit memory might be impaired in aMCI, possibly due to frontal lobe dysfunction.
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There are several limitations to this study. First, the sample size was small. Second, we do not have imaging data on our participants to support our contention that the memory impairments seen in aMCI may be limited to specific neural systems that underlie implicit memory processes. Finally, we did not use neuroimaging technology in our study, and if the activity of the PFC was shown to be reduced in aMCI while the conceptual implicit task was being administered, it would provide more convincing support for our thesis. In summary, our results suggest that the 2 types of priming in implicit memory are dissociated in aMCI patients. Compared with healthy older controls, patients with aMCI seem to demonstrate impaired performance on conceptual, but not perceptual, implicit memory tasks. The current study also implies that conceptual priming impairment in aMCI may be associated with frontal lobe dysfunction. Acknowledgments This research was supported by the National Natural Science Foundation of China (81070877), National Basic Research Program of China (2005CB522800). We would like to thank all the participants for taking part in this study. References [1] L.G. Apostolova, I.D. Dinov, R.A. Dutton, K.M. Hayashi, A.W. Toga, J.L. Cummings, P.M. Thompson, 3D comparison of hippocampal atrophy in amnestic mild cognitive impairment and Alzheimer’s disease, Brain 129 (2006) 2867– 2873. [2] R.D. Badgaiyan, D.L. Schacter, N.M. Alpert, Priming within and across modalities: exploring the nature of rCBF increases and decreases, Neuroimage 13 (2001) 272–282. [3] W. Battig, W. Montague, Category norms of verbal items in 56 categories A replication and extension of the Connecticut category norms, J. Exp. Psychol. 80 (1969) 1–46. [4] L. Berg, Clinical Dementia Rating (CDR), Psychopharmacol. Bull. 24 (1988) 637–639. [5] T. Blaxton, Investigating dissociations among memory measures: support for a transfer-appropriate processing framework, J. Exp. Psychol. Learn. Mem. Cogn. 15 (1989) 657–668. [6] R. Buckner, S. Petersen, J. Ojemann, F. Miezin, L. Squire, M. Raichle, Functional anatomical studies of explicit and implicit memory retrieval tasks, J. Neurosci. 15 (1995) 12. [7] L.S. Cermak, N. Talbot, K. Chandler, L.R. Wolbarst, The perceptual priming phenomenon in amnesia, Neuropsychologia 23 (1985) 615–622. [8] T.M. Dannhauser, S.S. Shergill, T. Stevens, L. Lee, M. Seal, R.W. Walker, Z. Walker, An fMRI study of verbal episodic memory encoding in amnestic mild cognitive impairment, Cortex 44 (2008) 869–880. [9] R.B. Dudas, F. Clague, S.A. Thompson, K.S. Graham, J.R. Hodges, Episodic and semantic memory in mild cognitive impairment, Neuropsychologia 43 (2005) 1266–1276. [10] D. Fleischman, J. Gabrieli, S. Reminger, J. Rinaldi, F. Morrell, R. Wilson, Conceptual priming in perceptual identification for patients with Alzheimer’s disease and a patient with right occipital lobectomy, Neuropsychology 9 (1995) 187–197. [11] D.A. Fleischman, Repetition priming in aging and Alzheimer’s Disease: an integrative review and future directions, Cortex 43 (2007) 889–897. [12] D.A. Fleischman, J.D. Gabrieli, D.W. Gilley, J.D. Hauser, K.L. Lange, L.M. Dwornik, D.A. Bennett, R.S. Wilson, Word-stem completion priming in healthy aging and Alzheimer’s disease: the effects of age, cognitive status, and encoding, Neuropsychology 13 (1999) 22–30. [13] D.A Fleischman, R.S. Wilson, J.D. Gabrieli, J.A. Schneider, J.L. Bienias, D.A. Bennett, Implicit memory and Alzheimer’s disease neuropathology, Brain 128 (2005) 2006–2015. [14] M.F. Folstein, S.E. Folstein, P.R. McHugh, Mini-mental state. A practical method for grading the cognitive state of patients for the clinician, J. Psychiatr. Res. 12 (1975) 189–198.
[15] J. Gabrieli, D. Fleischman, M. Keane, S. Reminger, F. Morrell, Double dissociation between memory systems underlying explicit and implicit memory in the human brain, Psychol. Sci. 6 (1995) 76–82. [16] P. Graf, G. Mandler, Activation makes words more accessible, but not necessarily more retrievable, J. Verbal Learn. Verbal Behav. 23 (1984) 553–568. [17] M Grundman, R.C. Petersen, S.H. Ferris, R.G. Thomas, P.S. Aisen, D.A. Bennett, N.L. Foster, C.R. Jack Jr., D.R. Galasko, R. Doody, J. Kaye, M. Sano, R. Mohs, S. Gauthier, H.T. Kim, S. Jin, A.N. Schultz, K. Schafer, R. Mulnard, C.H. van Dyck, J. Mintzer, E.Y. Zamrini, D. Cahn-Weiner, L.J. Thal, Mild cognitive impairment can be distinguished from Alzheimer disease and normal aging for clinical trials, Arch. Neurol. 61 (2004) 59–66. [18] C.R. Jack Jr., R.C. Petersen, Y. Xu, P.C. O’Brien, G.E. Smith, R.J. Ivnik, B.F. Boeve, E.G. Tangalos, E. Kokmen, Rates of hippocampal atrophy correlate with change in clinical status in aging and AD, Neurology 55 (2000) 484–489. [19] C. Jack Jr., R. Petersen, Y. Xu, P. O’brien, G. Smith, R. Ivnik, B. Boeve, E. Tangalos, E. Kokmen, Rates of hippocampal atrophy correlate with change in clinical status in aging and AD, Neurology 55 (2000) 484. [20] D.J. LaVoie, K.M. Faulkner, Production and identification repetition priming in amnestic mild cognitive impairment, Neuropsychol. Dev. Cogn. B. Aging Neuropsychol. Cogn. 15 (2008) 523–544. [21] L.L. Light, D. LaVoie, D. Valencia-Laver, S.A. Owens, G. Mead, Direct and indirect measures of memory for modality in young and older adults, J. Exp. Psychol. Learn. Mem. Cogn. 18 (1992) 1284–1297. [22] E.J. Lotsof, Intelligence, verbal fluency, and the Rorschach test, J. Consult. Psychol. 17 (1953) 21–24. [23] K.J Murphy, J.B. Rich, A.K. Troyer, Verbal fluency patterns in amnestic mild cognitive impairment are characteristic of Alzheimer’s type dementia, J. Int. Neuropsychol. Soc. 12 (2006) 570–574. [24] K.J. Murphy, A.K. Troyer, B. Levine, M. Moscovitch, Episodic, but not semantic, autobiographical memory is reduced in amnestic mild cognitive impairment, Neuropsychologia 46 (2008) 3116–3123. [25] Z.S Nasreddine, N.A. Phillips, V. Bedirian, S. Charbonneau, V. Whitehead, I. Collin, J.L. Cummings, H. Chertkow, The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment, J. Am. Geriatr. Soc. 53 (2005) 695–699. [26] R.L. Newton, A comparison of two methods of administering the digit span test, J. Clin. Psychol. 6 (1950) 409–412. [27] R. Perri, G.A. Carlesimo, L. Serra, C. Caltagirone, Characterization of memory profile in subjects with amnestic mild cognitive impairment, J. Clin. Exp. Neuropsychol. 27 (2005) 1033–1055. [28] R. Perri, L. Serra, G.A. Carlesimo, C. Caltagirone, Amnestic mild cognitive impairment: difference of memory profile in subjects who converted or did not convert to Alzheimer’s disease, Neuropsychology 21 (2007) 549–558. [29] R.C. Petersen, Mild cognitive impairment as a diagnostic entity, J. Intern. Med. 256 (2004) 183–194. [30] R.C. Petersen, Mild cognitive impairment: current research and clinical implications, Semin. Neurol. 27 (2007) 22–31. [31] R.C. Petersen, R. Doody, A. Kurz, R.C. Mohs, J.C. Morris, P.V. Rabins, K. Ritchie, M. Rossor, L. Thal, B. Winblad, Current concepts in mild cognitive impairment, Arch. Neurol. 58 (2001) 1985–1992. [32] R.M. Savage, W.D. Gouvier, Rey Auditory-Verbal Learning Test: the effects of age and gender, and norms for delayed recall and story recognition trials, Arch. Clin. Neuropsychol. 7 (1992) 407–414. [33] D Schacter, Implicit memory: history and current status, J. Exp. Psychol. Learn. Mem. Cogn. 13 (1987) 501–518. [34] D.L. Schacter, R.L. Buckner, Priming and the brain, Neuron 20 (1998) 185–195. [35] D.L. Schacter, G.S. Wig, W.D. Stevens, Reductions in cortical activity during priming, Curr. Opin. Neurobiol. 17 (2007) 171–176. [36] M.J. Soler, J.C. Ruiz, I. Fuentes, P. Tomas, A comparison of implicit memory tests in schizophrenic patients and normal controls, Span. J. Psychol. 10 (2007) 423–429. [37] P.E. Spaan, J.G. Raaijmakers, C. Jonker, Early assessment of dementia: the contribution of different memory components, Neuropsychology 19 (2005) 629–640. [38] L.R. Squire, C.E. Stark, R.E. Clark, The medial temporal lobe, Annu. Rev. Neurosci. 27 (2004) 279–306. [39] L.R. Squire, S. Zola-Morgan, The medial temporal lobe memory system, Science 253 (1991) 1380–1386. [40] L. Traykov, N. Raoux, F. Latour, L. Gallo, O. Hanon, S. Baudic, C. Bayle, E. Wenisch, P. Remy, A.S. Rigaud, Executive functions deficit in mild cognitive impairment, Cogn. Behav. Neurol. 20 (2007) 219–224. [41] G.S. Wig, S.T. Grafton, K.E. Demos, W.M. Kelley, Reductions in neural activity underlie behavioral components of repetition priming, Nat. Neurosci. 8 (2005) 1228–1233. [42] W.W. Zung, C.B. Richards, M.J. Short, Self-rating depression scale in an outpatient clinic. Further validation of the SDS, Arch. Gen. Psychiatry 13 (1965) 508–515.
Contents lists available at ScienceDirect
Neuroscience Letters journal homepage: www.elsevier.com/locate/neulet
Conceptual implicit memory impaired in amnestic mild cognitive impairment patient Liang Gong a,b , Yanghua Tian a , Huaidong Cheng a,c , Zhendong Chen c , Changlin Yin a , Yu Meng a , Rong Ye a , Kai Wang a,∗ a b c
Neuropsychological Laboratory, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui Province, PR China Department of Neurology, People’s Hospital of YuXi City, The Sixth Affiliated Hospital of Kunming Medical College, Yuxi 653100, PR China Cancer and Cognition Laboratory, Department of Oncology, The Second Affiliated Hospital of Anhui Medical University, Hefei 230022, PR China
a r t i c l e
i n f o
Article history: Received 8 June 2010 Received in revised form 4 August 2010 Accepted 12 August 2010 Keywords: Amnestic mild cognitive impairment Alzheimer’s disease Implicit memory
a b s t r a c t Explicit memory has been well proven to be impaired in amnestic mild cognitive impairment (aMCI), and conceptual implicit memory is impaired in Alzheimer’s disease. However, it is unclear whether implicit memory is affected in aMCI. In the present study, 35 patients with aMCI and 35 healthy elderly subjects were administered a neuropsychological battery of tests including conceptual and perceptual implicit memory tasks (category exemplar generation, image identification) as well as explicit memory tasks. Patients with aMCI exhibited impairment in explicit memory tasks and selective impairment in conceptual priming tasks, while the effect of perceptual priming was preserved. More importantly, category exemplar generation task priming, but not perceptual priming, was positively correlated with verbal fluency test performance in the aMCI group. The dissociation between the 2 components of implicit priming suggests that conceptual priming impairment in aMCI patients may be related to frontal lobe dysfunction. © 2010 Elsevier Ireland Ltd. All rights reserved.
Implicit memory is a type of memory in which previous experiences aid in the performance of a task without conscious awareness of these previous experiences [33]. In contrast, explicit memory refers to the conscious or intentional recollection of previous experiences and information. Most common evidence for implicit memory arises in priming, a process whereby subjects show improved performance on tasks for which they have been subconsciously prepared [16]. On the basis of process distinction, priming can be fractionated into 2 subtypes: perceptual priming and conceptual priming. Perceptual priming is modality specific and does not depend on the semantic or elaborative encoding of an item, as in the case of word identification and image identification, whereas conceptual priming is not modality specific and benefits from semantic encoding [5], as in the case of free-association and category exemplar generation tests [34]. It has been reported that patients with focal damage to the occipital cortex fail to show perceptual priming, but do show normal conceptual priming [15]. Frontal cortex damage model schizophrenic patients show lower conceptual priming than control subjects, but comparable perceptual priming [36]. Additional converging evidence concerning the brain regions that are relevant to priming has been provided by recent neuroimaging
∗ Corresponding author. Tel.: +86 0551 2923704; fax: +86 0551 2923704. E-mail address: [email protected] (K. Wang). 0304-3940/$ – see front matter © 2010 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.neulet.2010.08.041
studies. Neuroimaging studies using positron-emission tomography (PET) and functional magnetic resonance imaging (fMRI) have revealed that priming is often accompanied by decreased activity (neural priming) in a variety of brain regions [35]. Different types of behavioral priming may rely on neural priming in different cortex areas. Neural priming in the posterior regions (visual regions, auditory regions, parahippocampal cortex, and fusiform cortex) may be the basis for perceptual priming [2], while neural priming in the left frontal cortex may be the basis for conceptual priming [41]. Mild cognitive impairment (MCI) refers to a clinical condition in which patients experience a memory loss greater than expected for their chronological age, yet not severe enough to meet the currently accepted criteria for clinically probable Alzheimer’s disease (AD) [31]. When memory loss is the predominant symptom, it is termed “amnestic MCI” (aMCI) and is frequently considered to be a risk factor for AD [17]. Much experimental work investigating the qualitative profile of memory dysfunction in aMCI documents the pervasive impairment of declarative or explicit memory [9,24]. The characteristics of explicit memory impairment in aMCI are similar to those in AD. It is a well-established finding that explicit memory is compromised by aging [21] and profoundly impaired in AD [37]. Although most regular priming is impaired in patients with AD, there are numerous examples of preservation. In general, normal perceptual priming has been consistently reported in cases of AD [6,10], while conceptual priming has been shown
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to be impaired in many studies [12,13]. Some investigators have reported implicit memory performance in aMCI patients. Perri et al. [27] found that aMCI priming on fragmented picture identification tasks was lower than that of healthy controls but greater than that of the AD patients, and priming on word-stem completion was greater than that of both AD patients and healthy controls. They explained that explicit memory contamination in the wordstem completion task may be attributed to the inhibition of the implicit priming effect. LaVoie and Faulkner [20] found that both older controls and MCI patients showed lower levels of priming on the word-stem completion task relative to young adults, and reliably greater levels relative dementia patients; equivalent priming on the word identification task was seen in all groups. However, little is known about conceptual and perceptual implicit memory performance in aMCI patients. Amnestic MCI patients are characterized by deficits in explicit recall and recognition, which are produced by cortex changes in the hippocampal formation. A brain structure study in aMCI patients also found atrophy in the entorhinal cortex and the hippocampus [19]. In addition, recent evidence suggests that frontal lobe function is impaired in MCI [40], with relative sparing of the occipital cortex. Traykov et al. [40] found that MCI patients had problems with response inhibition, switching, and cognitive flexibility, which encompass various aspects of executive functions, which are processed by the frontal cortex. Dannhauser et al. [8] found that activation in the left ventrolateral prefrontal cortex (PFC) during encoding in the aMCI group was decreased compared to that in the healthy control group. As the frontal cortex and the occipital cortex are the basis of conceptual priming and perceptual priming, respectively, if priming is impaired in aMCI, the impairment must be related to conceptual priming. The present study aimed to examine whether the memory impairments in aMCI extend to implicit memory as well as explicit memory. Thirty-five aMCI patients and 35 healthy controls were administered with conceptual priming (category exemplar generation) and perceptual priming (image identification) tasks, as well as explicit memory (immediate recall, delayed recall, delayed recognition) tasks. We predicted that individuals with aMCI would exhibit impaired conceptual priming (category exemplar generation) relative to healthy older controls. Each subject underwent a uniform clinical evaluation that included a medical history, a neurological examination, and neuropsychological performance testing. Thirty-five healthy older adults (17 men, 18 women) with a mean education of 10.6 years and an age range of 58–78 (mean 69.1) engaged in the experiment. Thirty-five patients with a diagnosis of probable aMCI [29] (19 men, 16 women) with a mean education of 10.3 years and an age range of 55–84 (mean 68.9) entered the experiment. The aMCI patients were recruited from the outpatients of the first hospital of Anhui Medical University. The performance of the healthy older group was within normal limits for age and education according to measures of: (a) Mini-mental state examination, MMSE [14]; Montreal Cognitive Assessment, MoCA [25]; (b) Auditory Verbal Learning Test Delayed Recall (AVLT) [32]; (c) Self-Rating Depression Scale, SDS [42]; and (d) Clinical Dementia Rating, CDR [4]. The control subjects were required to have a CDR of 0, an MMSE score of 26, and a Delayed Recall score of >4 for those with 8 or more years of education. Patients with aMCI met the following criteria: (a) a recent history of a symptomatic worsening of memory; (b) an objective memory injury for their age, according to cognitive testing, which is 1.5 SD lower than the demonstrated verbal ability of the aMCI group; (c) an MMSE score of 24–30; (d) a global CDR score of 0.5, with a memory score of 0.5 or greater; (e) not meeting the NINCDSADRDA or Diagnostic and Statistical Manual of Mental Disorders IV, Text Revision criteria for dementia; (f) normal or near-normal
independent functions; and (g) an absence of other factors that might have better explained their memory loss (e.g., depression). The criteria used for MCI were those accepted by the field for clinical research. A comprehensive battery of tests managed to assess both general cognitive functions and memory: the MMSE and MoCA to measure global cognitive function and the Verbal Fluency Test (VFT) [22] to measure frontal lobe functions; Digit Span (DS) [26] was used to measure the working memory. The immediate recall, delayed recall, and delayed recognition trials were performed as a multiple-form test of explicit verbal memory. In each of the 3 learning trials, the participants heard a list of 15 words and tried to recall as many as possible within 2 min. The correct number of responses from the first trial was taken as the immediate recall scores. After a 20 min filled interval (i.e., with nonverbal tasks), the participants completed a delayed recall trial and a delayed recognition trial. In the delayed recall trial, participants were asked to recall the words learned earlier. In the test phase of the delayed recognition trial, participants heard a list of 30 words (15 old and 15 new) and were asked to decide if the words had been heard before or not. Perceptual priming was investigated by an image identification test [7]. The stimuli consisted of 80 grayscale images comprising 40 entity images of common objects and 40 corresponding mosaic images of each picture. The entity images contained animals, fruit, tools, and other common objects, and the mosaic images were manufactured by Photoshop software. The identification rate of each entity image and mosaic image was over 98% and 20–30%, respectively, by 40 adults. During the study phase, the participants were presented with a list of 20 entity images, and were required to rate each image on a 5-point liking scale. The study list assignment was counterbalanced across the participants. The study was self-paced, but the participants were told to respond as quickly as possible. During the test phase, which was administered 15 min after the study phase, participants were presented with the 40 mosaic images (half with studied items and half with new items). The participants were asked to name each image within 10 s. Guessing was allowed. Priming was measured as the increase in the probability of naming a studied versus an unstudied mosaic image. Conceptual priming was evaluated using the category exemplar generation task [13]. During the study phase, the participants were visually presented with 20 words belonging to 1 of 2 categories (e.g., vegetables, household appliances), 1 at a time, individually printed on cards. The categories were matched with respect to category potency [3]. The subjects were asked to indicate whether the words represented living or nonliving entities. During the test phase, which was administered 15 min after the study phase, the subjects were asked to generate 8 examples for each of 4 specified categories (2 old and 2 new) as quickly as they could. The instructions were given without reference to the previously studied list of words. A different category was presented when the individual had generated 8 examples or if the subject failed to produce a new response in a 1-min period. The examiner recorded the words they said with a tape recorder. The examples for the unstudied categories were used as a baseline measurement of performance for this task. Priming was measured as the increase in the probability of producing a studied versus an unstudied category example. The SPSS-15 statistical package was used for the data analysis. Differences in age, education, MMSE, MoCA, VFT, DS, and AVLT score between aMCI and healthy older controls were assessed using ttests. Comparisons among aMCI and healthy older controls on the performance of explicit memory and implicit memory were performed using an Independent Samples T Test. We used Pearson’s correlation to examine the association between aMCI patients’ verbal fluency tests and memory scores. The probability level was 0.05.
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Table 1 Demographic and neuropsychological background tests of healthy elderly and aMCI patients. Characteristic
aMCI patients
Healthy controls
Number of participants Sex (F/M) Age, years (mean (SD)) Educational level MoCA, mean (SD) MMSE, mean (SD) DS, mean (SD) VFT, mean (SD)
35 16/19 68.69 ± 7.85 10.34 ± 3.2 24.63 ± 2.5* 27.53 ± 1.4* 6.51 ± 0.7* 12.43 ± 3.0**
35 18/17 69.09 ± 4.21 10.63 ± 2.9 27.66 ± 0.7 29.46 ± 0.7 7.74 ± 0.4 15.77 ± 3.60
* **
P < 0.05. P < 0.01.
In Table 1, there was no significant difference between the aMCI patients and the healthy controls in terms of age, education, or sex and DS (P > 0.05). The performance of the patients in the aMCI group was significantly poorer than that of the patients in the healthy control group on the MMSE, MoCA, AVLT, and VFT (P < 0.01). The explicit memory performance, including immediate recall, delayed recall, and delayed recognition, was worse in the aMCI group than in the healthy control group. The difference was statistically significant (immediate recall, t = 6.40, P < 0.01, delayed recall, t = 9.29, P < 0.01 delayed recognition, t = 7.65, P < 0.05) (see Table 2). There was no significant difference between the aMCI group and the healthy control group in terms of the image identification task (t = 0.78, P > 0.05). Performance of the category exemplar generation task in the aMCI group was poorer than that in the healthy control group (t = 3.21, P < 0.01) (see Table 2). The verbal fluency score was not associated with the explicit memory score (P > 0.05). The verbal fluency score was not associated with perceptual implicit memory (image identification, r = 0.211, P = 0.22). Conceptual implicit memory (category exemplar generation) was positively associated with the verbal fluency score (r = 0.739, P < 0.01) (see Fig. 1). The present results indicate that aMCI patients were not only impaired in explicit memory, but also in implicit memory, particularly in conceptual priming. Consistent with our predictions, the conceptual priming task score (category exemplar generation) in the aMCI patients was poorer than that in the healthy controls, and the perceptual priming task score (image identification) was identical between the 2 groups. This characteristic of implicit memory performance was similar in MCI and AD patients. The performance on explicit memory tests in our study was similar to that of most prior aMCI studies [27,30]. This finding is in complete accord with the neuroanatomical changes that occur in aMCI patients. Much evidence has proven that mesial-temporal lobe (MTL) structures in aMCI patients were extensively affected [1,18], and MTL is well known to be critically involved in explicit memory functioning [38,39]. In addition, our main finding is that conceptual implicit memory was impaired in aMCI patients, while perceptual implicit memory was spared. Our results conformed to the preliminary findTable 2 Explicit and implicit memory scores of healthy elderly and aMCI patients. Measurement Explicit memory Immediate recall Delayed recall Delayed recognition Implicit memory Image identification Category exemplar generation * **
P < 0.05. P < 0.01.
aMCI patients
Healthy control subjects
3.74 ± 1.29** 3.83 ± 2.36** 9.11 ± 2.35*
5.57 ± 1.09 8.34 ± 1.64 12.77 ± 1.57
21.11 ± 5.05 5.94 ± 1.51**
22.06 ± 5.13 6.94 ± 1.06
Fig. 1. Positive correlation between verbal fluency test score and category exemplar generation score in aMCI patients.
ings of Fleischman’s [11] study of aging in MCI and AD patients. He found that conceptual priming appears to distinguish MCI and AD from normal cognition (category exemplar generation), while perceptual priming (word-stem completion task, picture naming) appears to be intact in both MCI and normal cognition. It was also reported that higher levels of global neuropathology in AD patients were related to lower levels of explicit memory and implicit memory on the category exemplar generation task. However, it should be noted that these results are not congruent with those reported by Perri et al. [27], who employed the word-stem completion task and the fragmented picture identification task. They found that the priming on the fragmented picture identification task was lower than that of the healthy controls but greater than that of the AD group, and that the priming on the word-stem completion task was greater than that of both the AD group and the healthy controls. LaVoie and Faulkner [20] also tested priming in aMCI patients by the word-stem completion task and showed equivalent priming in MCI patients and healthy older controls. Our study confirmed that category exemplar priming, but not image identification priming, was poorer in aMCI patients than in healthy controls. Our present results indicate that conceptual priming in aMCI patients was poor compared with that in healthy controls, while perceptual priming was shared. This finding is in accord with the neuroanatomical changes that occur in aMCI patients. The posterior cortex, which processes perceptual priming, was verified to be preserved in aMCI patients [28]. In addition, an increasing amount of behavioral and neuroimaging research has recently manifested that the frontal lobe, which mainly mediates conceptual priming [22,42], might be impaired in aMCI patients [3,19,42]. For example, Traykov et al. [40] found that various aspects of the executive functions (which are mainly processed by the frontal lobe, e.g. response inhibition, switching, and cognitive flexibility) were affected in MCI patients. Our results also show that conceptual priming was impaired in aMCI patients, which indicates that frontal lobe dysfunction led to conceptual priming deterioration in aMCI patients. In order to further understand whether frontal lobe dysfunction in aMCI is related to conceptual priming, we conducted a correlation analysis between several memory and verbal fluency test scores. Our results showed that the verbal fluency test score was positively associated with the category exemplar generation score, but not with either the image identification score or the explicit memory score. The verbal fluency test is a common neuropsychological test which is often used to evaluate the frontal lobe function [23]. The findings of this study suggest that some types of implicit memory might be impaired in aMCI, possibly due to frontal lobe dysfunction.
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There are several limitations to this study. First, the sample size was small. Second, we do not have imaging data on our participants to support our contention that the memory impairments seen in aMCI may be limited to specific neural systems that underlie implicit memory processes. Finally, we did not use neuroimaging technology in our study, and if the activity of the PFC was shown to be reduced in aMCI while the conceptual implicit task was being administered, it would provide more convincing support for our thesis. In summary, our results suggest that the 2 types of priming in implicit memory are dissociated in aMCI patients. Compared with healthy older controls, patients with aMCI seem to demonstrate impaired performance on conceptual, but not perceptual, implicit memory tasks. The current study also implies that conceptual priming impairment in aMCI may be associated with frontal lobe dysfunction. Acknowledgments This research was supported by the National Natural Science Foundation of China (81070877), National Basic Research Program of China (2005CB522800). We would like to thank all the participants for taking part in this study. References [1] L.G. Apostolova, I.D. Dinov, R.A. Dutton, K.M. Hayashi, A.W. Toga, J.L. Cummings, P.M. Thompson, 3D comparison of hippocampal atrophy in amnestic mild cognitive impairment and Alzheimer’s disease, Brain 129 (2006) 2867– 2873. [2] R.D. Badgaiyan, D.L. Schacter, N.M. Alpert, Priming within and across modalities: exploring the nature of rCBF increases and decreases, Neuroimage 13 (2001) 272–282. [3] W. Battig, W. Montague, Category norms of verbal items in 56 categories A replication and extension of the Connecticut category norms, J. Exp. Psychol. 80 (1969) 1–46. [4] L. Berg, Clinical Dementia Rating (CDR), Psychopharmacol. Bull. 24 (1988) 637–639. [5] T. Blaxton, Investigating dissociations among memory measures: support for a transfer-appropriate processing framework, J. Exp. Psychol. Learn. Mem. Cogn. 15 (1989) 657–668. [6] R. Buckner, S. Petersen, J. Ojemann, F. Miezin, L. Squire, M. Raichle, Functional anatomical studies of explicit and implicit memory retrieval tasks, J. Neurosci. 15 (1995) 12. [7] L.S. Cermak, N. Talbot, K. Chandler, L.R. Wolbarst, The perceptual priming phenomenon in amnesia, Neuropsychologia 23 (1985) 615–622. [8] T.M. Dannhauser, S.S. Shergill, T. Stevens, L. Lee, M. Seal, R.W. Walker, Z. Walker, An fMRI study of verbal episodic memory encoding in amnestic mild cognitive impairment, Cortex 44 (2008) 869–880. [9] R.B. Dudas, F. Clague, S.A. Thompson, K.S. Graham, J.R. Hodges, Episodic and semantic memory in mild cognitive impairment, Neuropsychologia 43 (2005) 1266–1276. [10] D. Fleischman, J. Gabrieli, S. Reminger, J. Rinaldi, F. Morrell, R. Wilson, Conceptual priming in perceptual identification for patients with Alzheimer’s disease and a patient with right occipital lobectomy, Neuropsychology 9 (1995) 187–197. [11] D.A. Fleischman, Repetition priming in aging and Alzheimer’s Disease: an integrative review and future directions, Cortex 43 (2007) 889–897. [12] D.A. Fleischman, J.D. Gabrieli, D.W. Gilley, J.D. Hauser, K.L. Lange, L.M. Dwornik, D.A. Bennett, R.S. Wilson, Word-stem completion priming in healthy aging and Alzheimer’s disease: the effects of age, cognitive status, and encoding, Neuropsychology 13 (1999) 22–30. [13] D.A Fleischman, R.S. Wilson, J.D. Gabrieli, J.A. Schneider, J.L. Bienias, D.A. Bennett, Implicit memory and Alzheimer’s disease neuropathology, Brain 128 (2005) 2006–2015. [14] M.F. Folstein, S.E. Folstein, P.R. McHugh, Mini-mental state. A practical method for grading the cognitive state of patients for the clinician, J. Psychiatr. Res. 12 (1975) 189–198.
[15] J. Gabrieli, D. Fleischman, M. Keane, S. Reminger, F. Morrell, Double dissociation between memory systems underlying explicit and implicit memory in the human brain, Psychol. Sci. 6 (1995) 76–82. [16] P. Graf, G. Mandler, Activation makes words more accessible, but not necessarily more retrievable, J. Verbal Learn. Verbal Behav. 23 (1984) 553–568. [17] M Grundman, R.C. Petersen, S.H. Ferris, R.G. Thomas, P.S. Aisen, D.A. Bennett, N.L. Foster, C.R. Jack Jr., D.R. Galasko, R. Doody, J. Kaye, M. Sano, R. Mohs, S. Gauthier, H.T. Kim, S. Jin, A.N. Schultz, K. Schafer, R. Mulnard, C.H. van Dyck, J. Mintzer, E.Y. Zamrini, D. Cahn-Weiner, L.J. Thal, Mild cognitive impairment can be distinguished from Alzheimer disease and normal aging for clinical trials, Arch. Neurol. 61 (2004) 59–66. [18] C.R. Jack Jr., R.C. Petersen, Y. Xu, P.C. O’Brien, G.E. Smith, R.J. Ivnik, B.F. Boeve, E.G. Tangalos, E. Kokmen, Rates of hippocampal atrophy correlate with change in clinical status in aging and AD, Neurology 55 (2000) 484–489. [19] C. Jack Jr., R. Petersen, Y. Xu, P. O’brien, G. Smith, R. Ivnik, B. Boeve, E. Tangalos, E. Kokmen, Rates of hippocampal atrophy correlate with change in clinical status in aging and AD, Neurology 55 (2000) 484. [20] D.J. LaVoie, K.M. Faulkner, Production and identification repetition priming in amnestic mild cognitive impairment, Neuropsychol. Dev. Cogn. B. Aging Neuropsychol. Cogn. 15 (2008) 523–544. [21] L.L. Light, D. LaVoie, D. Valencia-Laver, S.A. Owens, G. Mead, Direct and indirect measures of memory for modality in young and older adults, J. Exp. Psychol. Learn. Mem. Cogn. 18 (1992) 1284–1297. [22] E.J. Lotsof, Intelligence, verbal fluency, and the Rorschach test, J. Consult. Psychol. 17 (1953) 21–24. [23] K.J Murphy, J.B. Rich, A.K. Troyer, Verbal fluency patterns in amnestic mild cognitive impairment are characteristic of Alzheimer’s type dementia, J. Int. Neuropsychol. Soc. 12 (2006) 570–574. [24] K.J. Murphy, A.K. Troyer, B. Levine, M. Moscovitch, Episodic, but not semantic, autobiographical memory is reduced in amnestic mild cognitive impairment, Neuropsychologia 46 (2008) 3116–3123. [25] Z.S Nasreddine, N.A. Phillips, V. Bedirian, S. Charbonneau, V. Whitehead, I. Collin, J.L. Cummings, H. Chertkow, The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment, J. Am. Geriatr. Soc. 53 (2005) 695–699. [26] R.L. Newton, A comparison of two methods of administering the digit span test, J. Clin. Psychol. 6 (1950) 409–412. [27] R. Perri, G.A. Carlesimo, L. Serra, C. Caltagirone, Characterization of memory profile in subjects with amnestic mild cognitive impairment, J. Clin. Exp. Neuropsychol. 27 (2005) 1033–1055. [28] R. Perri, L. Serra, G.A. Carlesimo, C. Caltagirone, Amnestic mild cognitive impairment: difference of memory profile in subjects who converted or did not convert to Alzheimer’s disease, Neuropsychology 21 (2007) 549–558. [29] R.C. Petersen, Mild cognitive impairment as a diagnostic entity, J. Intern. Med. 256 (2004) 183–194. [30] R.C. Petersen, Mild cognitive impairment: current research and clinical implications, Semin. Neurol. 27 (2007) 22–31. [31] R.C. Petersen, R. Doody, A. Kurz, R.C. Mohs, J.C. Morris, P.V. Rabins, K. Ritchie, M. Rossor, L. Thal, B. Winblad, Current concepts in mild cognitive impairment, Arch. Neurol. 58 (2001) 1985–1992. [32] R.M. Savage, W.D. Gouvier, Rey Auditory-Verbal Learning Test: the effects of age and gender, and norms for delayed recall and story recognition trials, Arch. Clin. Neuropsychol. 7 (1992) 407–414. [33] D Schacter, Implicit memory: history and current status, J. Exp. Psychol. Learn. Mem. Cogn. 13 (1987) 501–518. [34] D.L. Schacter, R.L. Buckner, Priming and the brain, Neuron 20 (1998) 185–195. [35] D.L. Schacter, G.S. Wig, W.D. Stevens, Reductions in cortical activity during priming, Curr. Opin. Neurobiol. 17 (2007) 171–176. [36] M.J. Soler, J.C. Ruiz, I. Fuentes, P. Tomas, A comparison of implicit memory tests in schizophrenic patients and normal controls, Span. J. Psychol. 10 (2007) 423–429. [37] P.E. Spaan, J.G. Raaijmakers, C. Jonker, Early assessment of dementia: the contribution of different memory components, Neuropsychology 19 (2005) 629–640. [38] L.R. Squire, C.E. Stark, R.E. Clark, The medial temporal lobe, Annu. Rev. Neurosci. 27 (2004) 279–306. [39] L.R. Squire, S. Zola-Morgan, The medial temporal lobe memory system, Science 253 (1991) 1380–1386. [40] L. Traykov, N. Raoux, F. Latour, L. Gallo, O. Hanon, S. Baudic, C. Bayle, E. Wenisch, P. Remy, A.S. Rigaud, Executive functions deficit in mild cognitive impairment, Cogn. Behav. Neurol. 20 (2007) 219–224. [41] G.S. Wig, S.T. Grafton, K.E. Demos, W.M. Kelley, Reductions in neural activity underlie behavioral components of repetition priming, Nat. Neurosci. 8 (2005) 1228–1233. [42] W.W. Zung, C.B. Richards, M.J. Short, Self-rating depression scale in an outpatient clinic. Further validation of the SDS, Arch. Gen. Psychiatry 13 (1965) 508–515.