Neurobiology of Learning and Memory 90 (2008) 404–412

Contents lists available at ScienceDirect

Neurobiology of Learning and Memory

journal homepage: www.elsevier .com/ locate /ynlme

Relationship between nicotinic receptors and cognitive function in earlyAlzheimer’s disease: A 2-[18F]fluoro-A-85380 PET study

J.R. Ellis a,b,*, V.L. Villemagne a, P.J. Nathan c,b, R.S. Mulligan a, S.J. Gong a, J.G. Chan a, J. Sachinidis a,G.J. O’Keefe a, K. Pathmaraj a, K.A. Wesnes d, G. Savage e,b, C.C. Rowe a

a Department of Nuclear Medicine and Centre for PET, Austin Hospital, 145 Studley Road, Heidelberg, Victoria 3084, Australiab School of Psychology, Psychiatry and Psychological Medicine, Monash University, Vic., Australiac Brain Mapping Unit, Department of Psychiatry, University of Cambridge, UKd Cognitive Drug Research Ltd., Goring-on-Thames, UKe Macquarie Centre for Cognitive Science, Macquarie University, NSW, Australia

a r t i c l e i n f o

Article history:Received 12 February 2008Revised 7 May 2008Accepted 9 May 2008Available online 11 July 2008

Keywords:A-85380Alzheimer’s diseaseCholinergicCognitionDementiaMolecular imagingNicotinic receptorsPET imaging

1074-7427/$ - see front matter � 2008 Elsevier Inc. Adoi:10.1016/j.nlm.2008.05.006

* Corresponding author. Address: Department of NuPET, Austin Hospital, 145 Studley Road, Heidelberg, V+61 3 9458 5023.

E-mail address: ellis@petnm.unimelb.edu.au (J.R. E

a b s t r a c t

Neuronal nicotinic acetylcholine receptors (nAChRs) are critical for higher order cognitive processes.Post-mortem studies suggest reductions in nAChRs (particularly the a4b2 subtype) with ageing and inAlzheimer’s disease (AD). This study aimed to; (1) quantify nAChR distribution in vivo with 2-[18F]flu-oro-A-85380 (2-FA) in 15 early AD patients compared to 14 age-matched, healthy controls (HC) and(2) correlate nAChR distribution with cognitive performance in both groups. All participants were non-smokers and underwent cognitive testing along with a dynamic PET scan after injection of 200 MBq of2-FA. Brain regional 2-FA binding was assessed through a simplified estimation of Distribution Volume(DVS). The AD group differed significantly from HC on all cognitive measures employed, with impair-ments on measures of attention, working memory, language, executive function, visuospatial ability, ver-bal learning and verbal memory (p < .05). Contrary to post-mortem data this study found no evidence ofin vivo nAChR loss in early AD despite significant cognitive impairment. Furthermore, no correlationbetween nAChR and cognitive performance was found for either group. The findings of the current studysuggest preservation of nAChRs early in AD supporting previous studies. It is possible that while the clin-ical 2-FA PET method described here may be insensitive in detecting changes in early AD, such changesmay be detected in more advanced stages of the illness.

� 2008 Elsevier Inc. All rights reserved.

1. Introduction

Alzheimer’s disease (AD) is a neurodegenerative disorder andthe most common cause of dementia, accounting for approxi-mately 50–60% of all age-related dementia that affects individualsover 65 years of age. AD is characterised clinically by impairmentsin a number of cognitive processes including episodic memory(Grober et al., 2008; Morris & Kopelman, 1986), working memory(Baddeley, Bressi, Della Sala, Logie, & Spinnler, 1991; Kensinger,Shearer, Locascio, Growdon, & Corkin, 2003), attention (Lawrence& Sahakian, 1995; Perry & Hodges, 1999), executive function (Patt-erson, Mack, Geldmacher, & Whitehouse, 1996; Swanberg, Trac-tenberg, Mohs, Thal, & Cummings, 2004) and language (Laws,Adlington, Gale, Moreno-Martinez, & Sartori, 2007; Vogel, Gade,Stokholm, & Waldemar, 2005).

ll rights reserved.

clear Medicine and Centre forictoria. 3084, Australia. Fax:

llis).

Pathological hallmarks of AD include intracellular accumula-tions of neurofibrillary tangles, deposits of b-amyloid neuritic pla-ques and loss of neurons and synaptic integrity in areas such as thehippocampus, parietal and temporal cortices (Auld, Kornecook,Bastianetto, & Quirion, 2002). Although these markers may bepathognomic of AD, the nature of relationships between the path-ological findings and specific cognitive dysfunction in AD appearstenuous. Neuritic plaque number does not itself correlate withthe severity of dementia, although a clinical correlation betweenelevated levels of b-amyloid peptide in the brain and cognitive de-cline has been reported (Naslund et al., 2000). One of the earliest,most consistent and striking abnormalities in AD, however, is thedegeneration of cholinergic neurons of the basal forebrain nucleusof Meynert and the loss of cholinergic inputs to cerebral cortex andthe hippocampus (for review see Schliebs & Arendt, 2006). Thisneurochemical abnormality is now thought to be critical for thecognitive dysfunction seen in AD. Numerous studies have showndecreases in choline acetyltransferase (ChAT), ACh release, acetyl-cholinesterase (AChE) and both nicotinic receptors (nAChRs) andmuscarinic receptors in the cerebral cortex and/or hippocampus

J.R. Ellis et al. / Neurobiology of Learning and Memory 90 (2008) 404–412 405

of post-mortem AD brains (Auld et al., 2002; Giacobini, 2003; Koch,Haas, & Jurgens, 2005; Woodruff-Pak & Gould, 2002). These basalforebrain cholinergic deficits have been shown to positively corre-late with the cognitive impairments observed in AD (Bierer et al.,1995; Bowen, Benton, Spillane, Smith, & Allen, 1982; Perry, Mar-tin-Ruiz, & Court, 2001). The rationale for the use of cognitiveenhancing AChE inhibitors such as donepezil and galantamine isthus based on the classical cholinergic hypothesis of AD, that theloss of cholinergic input would account for the cognitive dysfunc-tion in AD (Bartus, Dean, Beer, & Lippa, 1982; Whitehouse, 1987).

In AD, reports of changes in muscarinic receptors have beenconflicting (Flores, Rogers, Pabreza, Wolfe, & Kellar, 1992; Nord-berg, Alafuzoff, & Winblad, 1992), while those implicating nAChRshave been more consistent. Evidence from post-mortem bindingstudies indicates that the a4b2 subtype of nAChRs is the major nic-otinic receptor subtype consistently reduced (decreases of up to50%) in AD (Flynn & Mash, 1986; Warpman & Nordberg, 1995),with evidence that this may occur very early in the course of AD(Marutle, Warpman, Bogdanovic, Lannfelt, & Nordberg, 1999).The most significant reductions of these nAChRs are seen in thetemporal, parietal and occipital cortices with no changes in the cer-ebellum (Nordberg, 1992, 1994).

Both PET and single photon emission computed tomography(SPECT) imaging studies have successfully examined cholinergicmarkers including AChE, and vesicular ACh transporter (VAChT)in AD (Kuhl et al., 1996, 1999). However, the reductions were notas great as that observed from post-mortem findings. Moreover,imaging studies of both muscarinic receptors and nAChRs havebeen hindered by the lack of suitable radioligands for in vivo imag-ing. To date, PET imaging studies of nAChRs using [11C]nicotinehave demonstrated a significant reduction in [11C]nicotine bindingin AD patients (Nordberg et al., 1990; Nordberg, Lundqvist, Hartvig,Lilja, & Langstrom, 1995). In general, a number of factors make[11C]nicotine a less than ideal ligand for the imaging of nAChRin vivo in human. It displays high levels of non-specific binding, ra-pid metabolism and rapid washout from the brain (Nordberg et al.,1997). Furthermore, brain uptake and retention of [11C]nicotinemay not be entirely mediated by specific binding to nAChRs, withbrain distribution influenced significantly by cerebral blood flow(CBF) (Nyback, Halldin, Ahlin, Curvall, & Eriksson, 1994). Thesedrawbacks have recently led to the search for new nAChRradioligands.

Epibatidine is a potent ligand with subnanomolar affinity forseveral subtypes of nAChRs, including the a4b2 type and the a3b4

type (which is present in sympathetic ganglia; Cimino, Marini, For-nasari, Cattabeni, & Clementi, 1992). Several epibatidine analogueshave been labelled with 11C, 18F and 123I (Sihver et al., 2000). How-ever, the high toxicity of epibatidine analogues, resulting fromtheir high affinity for ganglionic a3b4 nAChRs, has stimulated thesearch for more suitable radioligands (Horti & Villemagne, 2006).Recently, a structurally different nAChR ligand, 3-[2(S)-2-azetidi-nylmethoxy]pyridine (A-85380), has been developed (Abreoet al., 1996). A-85380 has been shown to have affinity comparableto that of epibatidine at nAChRs (Ki approximately 20 pM) (Mukhinet al., 2000) with lower toxicity than epibatidine-related com-pounds (Vaupel et al., 1998). A-85380 has been labelled with 123I(5IA-85380) (Horti et al., 1999; Musachio et al., 1999) and 18F (Hor-ti et al., 1998; Valette et al., 1999). 2-[18F]Fluoro-3-(2(S)azetidinyl-methoxy) pyridine (2-[18F]F-A-85380, abbreviated as 2-FA) PETimaging studies in non-human primates (Chefer et al., 2003;Valette et al., 2003) and healthy volunteers (Bottlaender et al.,2003; Brody et al., 2006; Mitkovski et al., 2005) have revealed apattern of highest uptake in the thalamus, pons and midbrain,intermediate in the cerebellum, cerebral cortices, caudate andputamen, and lowest in white matter, which is consistent withthe known distribution of a4b2 nAChRs (Adem, Nordberg, Jossan,

Sara, & Gillberg, 1989). In the current study we aimed to examinethe in vivo distribution of a4b2 nAChRs in early AD patients andage-matched, healthy controls (HC) using 2-FA PET. In additionwe aimed to examine the relationship between a4b2 nAChRs andcognitive performance in early AD and HC.

2. Methods

2.1. Participants

Fourteen healthy control participants (7 males, 7 females) and 15 early Alz-heimer’s disease (AD) patients (9 males, 6 females) were included in the study.Healthy controls (HC) were recruited from the community by advertisement andwere non-smokers with no history of neurological, psychiatric or major medicalillness, medication free and a Mini-Mental State Examination (MMSE; Folstein,Folstein, & McHugh, 1975) score of 27 or above. AD patients were recruited fromCognitive, Dementia and Memory Service (CDAMS) clinics in and around Mel-bourne. All AD patients met the National Institute of Neurological and Commu-nication Disorders Association (NINCDS-ADRDA) clinical criteria for probable AD(McKhann et al., 1984). AD patients were deemed to be in the mild stage of dis-ease as defined by duration of dementia (symptoms first evident <3 years previ-ously), and global dementia severity scale (Clinical Dementia Rating [CDR] < 2;Hughes, Berg, Danziger, Coben, & Martin, 1982; Morris, 1993). All participantswere non-smokers and were not taking any anticholinesterase or other drugs be-fore or during the study.

Suitability for the study was ascertained through a pre-study telephone screen-ing using the Primary Care Evaluation of Mental Disorders (PRIME-MD) (Spitzeret al., 1994) questionnaire and a subsequent semi-structured clinical assessmentperformed by a physician. The Hospital Anxiety and Depression Scale (HADS) (Zig-mond & Snaith, 1983) was administered to exclude participants with possible anx-iety or depressive states. The exclusion criteria comprised of contraindication for anMRI scan, cerebrovascular disease with evident focal neurological signs or stroke-related changes on MRI, or history of any other neurological or psychiatric illness.

Written informed consent for participation in the experiment was attainedprior to commencement. The experiment was approved by the Austin Health Hu-man Research Ethics Committee, Austin Radiation Subcommittee, the VictorianDepartment of Human Services Radiation Safety Unit and the Monash UniversityHuman Research Ethics Committee.

2.2. Cognitive tests

All participants underwent a comprehensive cognitive assessment comprisingboth traditional neuropsychological tests and a computerised battery, the CognitiveDrug Research system (www.cdr.eu.com). As a measure of global cognitive functionparticipants were administered the MMSE (Folstein et al., 1975).

The Cognitive Drug Research system was used for its validity as a measure ofprocessing speed, attention and working memory and its sensitivity to cholinergicmanipulation (Ebert, Oertel, Wesnes, & Kirch, 1998; Ellis et al., 2006). Prior to com-mencing the study, subjects completed a familiarisation session with the tests,which included two successful completions of the battery. These cognitive testswere presented on a laptop computer with participants responding via ‘‘yes” and‘‘no” buttons on an external button box. Subjects were instructed to respond asquickly as possible on all tasks where appropriate. For each task the primary mea-sures of speed and accuracy were used as the task end-point. For tasks of workingmemory sensitivity indices (SI) were calculated. The SI combines accuracy scoresfor the original (target) as well as the novel (distracter) stimuli, providing an indexof overall task efficiency (Frey & Colliver, 1973). The SI scores range from 0 to1 (0,no evidence of discrimination; 1, perfect discrimination).

Attention was evaluated with the Cognitive Drug Research system using theSimple Reaction Time (SRT), Choice Reaction Time (CRT) and Digit Vigilance (DVig)tasks. The SRT and CRT tasks are similar, however the CRT has an additional elementof stimulus discrimination and response organisation. DVig is a test of sustainedvigilance and ability to ignore distraction (O’Brien et al., 2002). The vigilance systemand sustained attention paradigms have often been associated with fronto-parietalfunction (Coull, Frith, Frackowiak, & Grasby, 1996; Lewin et al., 1996; Mennemeieret al., 1994; Pardo, Fox, & Raichle, 1991). Working memory (WM) was assessedusing the Numeric WM task, which reflects the ability to store a three-digit se-quence in the articulatory loop of WM and rapidly retrieve it and the Spatial WMtask, which is a modified version of Sternberg’s (1966) test of WM maintenancemeasuring intact spatial recognition and the ability to manipulate stored informa-tion (O’Brien et al., 2002). These measures of WM are sensitive to fronto-parietalfunction (Altamura et al., 2007; Bunge, Ochsner, Desmond, Glover, & Gabrieli,2001). For the purpose of analysis, three factors were derived from the various cog-nitive tests in accordance with recent work establishing the factor structure of thesystem (Wesnes, Ward, McGinty, & Petrini, 2000). These factors reflect; (1) theintensity of concentration (power of attention) which is the sum of the reactiontimes from the SRT, CRT and DVig tasks, (2) the ability to sustain attention (conti-nuity of attention) the formula for which takes into account accuracy on both the

Table 1Demographic data for healthy controls (HC) and Alzheimer’s disease (AD) groups

HC AD

N 14 15Age (years) 72.3 ± 8.4 77.3 ± 10.1CDR 0.0 ± 0.0 0.8 ± 0.3*

MMSE 28.8 ± 1.2 22.5 ± 2.5*

* p < .01; CDR, Clinical Dementia Rating; MMSE, Mini-Mental State Examination.

406 J.R. Ellis et al. / Neurobiology of Learning and Memory 90 (2008) 404–412

CRT and DVig tasks [(DVig accuracy � 45/100) + (CRT accuracy � 20/100) � DVigfalse alarms] and (3) the ability to hold information in WM (quality of WM), calcu-lated as the sum of SI scores of the Spatial WM and Numeric WM tasks.

Language was assessed using the 30-item Boston Naming Test (BNT) (Saxtonet al., 2000) and category (semantic) fluency task (Goodglass & Kaplan, 1972; Rosen,1980). The score is the sum of spontaneous correct responses plus correct responsesfollowing a semantic cue. The category fluency task requires participants to sponta-neously produce words that belong to a particular category within a limited time(60 s). The score is the sum of all admissible words for the three categories given(4-legged animals, supermarket items, furniture/fruit). These tasks are sensitive tofrontal and temporal lobe function (Abrahams et al., 2003; Amunts et al., 2004;Seidenberg, Geary, & Hermann, 2005; Wiggs, Weisberg, & Martin, 1999). Executivefunction was investigated using the letter fluency task (Benton, 1968; Benton &Hamsher, 1976), measuring frontal lobe and median cingulate function (Abrahamset al., 2003; Pantel, Schonknecht, Essig, & Schroder, 2004; Phelps, Hyder, Blamire, &Shulman, 1997; Wood, Saling, Abbott, & Jackson, 2001). This task requires participantsto spontaneously produce words beginning with a given letter, within a limited time(60 s). The score is the sum of admissible words for the three letters given (F, A and S).

Visuospatial ability and visuospatial memory was evaluated using the Rey Com-plex Figure Test (RCFT) (Meyers & Meyers, 1995), a test that assesses parietal lobefunction (Lezak, 1995). The RCFT is comprised of 18 elements. Accuracy and place-ment are given an equal value of one point for a total of two points for each of theelements and a maximum total score of 36 (Lezak, 1995). Verbal learning and verbalmemory was evaluated using two measures from either the Hopkins Verbal Learn-ing Test—Revised (HVLT-R) (Benedict, Schretten, Groninger, & Brandt, 1998; Brandt& Benedict, 2001) or the California Verbal Learning Test—Second Edition (CVLT-II)(Delis, Kramer, Kaplan, & Ober, 2000): (1) the total number of correct responsesin free recall of words over the acquisition trials (word recall) and (2) the numberrecalled after a 20 min delay. In addition to the medial temporal lobe, frontal corti-cal regions are involved in this task (Deweer et al., 1995; Johnson, Saykin, Flashman,McAllister, & Sparling, 2001; Saykin et al., 1999).

2.3. 2-FA PET

2.3.1. MRI

All participants underwent a 3D-T1-weighted spoiled gradient echo (SPGR)acquisition on a standard 1.5-T MRI scanner, for screening and subsequent co-reg-istration with the PET images.

2.3.2. Radiolabelling

2-FA was produced in the Department of Nuclear Medicine and Centre for PET,Austin Hospital according to the method of Dolle et al. (1999).

2.3.3. PET data acquisition and image reconstruction

All PET scans were performed 256 mm transverse field of view (FOV) using aPhilips-ADAC Allegro full-ring 3D PET System with PIXELARTM GSO crystal detectors.For each participant, a 20-min dynamic emission scan was acquired 190 min afterslow intravenous bolus injection of 200 ± 20 MBq (�5.3 mCi) 2-FA. The two 10-min frames were reconstructed using 3D row-action maximum likelihood algo-rithm (RAMLA) (Daube-Witherspoon, Matej, Karp, & Lewitt, 2001). A short trans-mission scan (approximately 2 min) was acquired prior to the correspondingemission scan using 740 MBq rotating Cs-137 transmission source. This was usedto position the participant’s head in the centre of the FOV, as well as for non-uni-form attenuation correction of the emission scan. A Velcro strap placed aroundthe forehead and the patient bed head-holder ensured a stable position of the headduring the emission scans. Discrete venous blood samples (3 ml) were obtained at90, 105, 120, 180, 195 and 210 min post-injection to determine plasma radioactiv-ity in a Wizard 300 1480 automatic gamma counter (Wallac).

Gallezot et al. (2005) have recently demonstrated that a minimum scan durationof 120 min is required for kinetic modelling analysis of cortical nAChR by 2-FA. How-ever, PET acquisition for 2 h is arduous, time consuming and a hindrance to clinicalstudies, particularly when the subjects of most interest are either elderly and/or cog-nitively impaired. Consequently, the current study utilised our simplified method of2-FA quantification, which has been previously validated (Mitkovski et al., 2005).

2.3.4. Image analysis

For accurate intra- and inter-individual comparisons a computerised reorienta-tion procedure (SPM2, Statistical Parametric Mapping, MRC Cognition and Brain Sci-ences Unit) (Friston, Frith, Liddle, & Frackowiak, 1991) was used to alignconsecutive PET studies and an average image created from the aligned frames.Where available the participants MRI was spatially normalised to the T1-weightedMontreal Neurological Institute template (MNI) (Collins, Neelin, Peters, & Evans,1994) in the SPM. This was necessary for visual evaluation of atrophy and to assistin the registration to the template, and in turn, to the average PET image in the SPMpackage.

Radioactive counts obtained from the plasma samples were corrected for per-centage of unchanged parent compound using a population-based curve obtainedfrom n = 15. Since no difference in the rate of metabolism was observed betweenAD and HC groups, or within each of the groups, the same metabolite-correctionfactor was used for all participants (Mulligan et al., 2006).

Regional 2-FA binding was assessed through a simplified estimation of Distribu-tion Volume (DVS) (Mitkovski et al., 2005). It was demonstrated that DVS, deter-mined by the tissue-to-plasma ratio using a single post-injection acquisition andconcurrent metabolite-corrected venous plasma activity highly correlates withthe results obtained from both compartmental and graphical analyses of cortical re-gions, indicating that DVS is useful for quantification of cortical 2-FA binding tonAChR (Mitkovski et al., 2005). This outcome measure is based on the assumptionthat receptor affinity remains constant, and therefore changes in DVS reflectchanges in the number of available receptor binding sites.

Each spatially normalised PET image was corrected for plasma radioactivity,resulting in the creation of a PET DVS image for each subject. Volume of interest(VOI) analysis was conducted by applying the previously described Automated Ana-tomical Labelling template (AAL) (Tzourio-Mazoyer et al., 2002) to the individualPET DVS images within an in-house medical image quantitative analysis and visu-alisation package, Wasabi (v2). For analysis of PET data the VOIs were grouped intoseven major areas which were selected for their known association with the specificcognitive domains being assessed: (a) frontal cortex (including the VOIs of inferiorand middle frontal gyrus), (b) parietal cortex (including VOIs of precuneus andsupramarginal gyrus), (c) temporal cortex (including the VOIs of inferior and middletemporal gyrus), (d) hippocampal (including the VOIs of hippocampus and parahip-pocampus), (e) posterior cingulate, (f) median cingulate and (g) thalamus. Volume-weighted means were derived for all grouped VOIs. The above regions were selectedbased on brain areas linked to the specific cognitive domains being assessed.

2.4. Statistical analyses

The data were analysed using SPSS (v11). Continuous variables for each groupwere tested for normality of distribution using the Shapiro–Wilk test and visualinspection of variable histograms. Homogeneity of variance was examined usingLevene’s test. Subsequently, independent samples t tests were used to evaluate differ-ences in nAChR DVS and cognitive function between the HC and AD groups. Two-tailed Pearson’s correlation coefficients or Spearman’s rank-order correlations whereappropriate, were used in correlational analysis between nAChR DVS and the cogni-tive function of each group in regions associated with each cognitive task (for exam-ple, frontal nAChR DVS and letter fluency task performance). In all instances statisticalsignificance was defined as p < .05. Multiple comparisons were controlled for with aFalse Discovery Rate (FDR; Benjamini & Hochberg, 1995). This modified Bonferroniprocedure requires the p values for the number of comparisons to be ordered fromhighest to lowest. Controlling the False Discovery Rate at .05, each p(i) is comparedsequentially with .05 i/m, with m being the number of comparisons made. Thisstep-down procedure is continued until a p value satisfies the constraint, and subse-quently all hypotheses below this p value are also rejected. Data were also analysedusing SPM2 (Friston et al., 1991). Data are expressed as M ± SD.

3. Results

The demographic characteristics of the participants are pre-sented in Table 1. There was no significant difference in age betweenthe groups: HC and AD (t = 1.43, p > .05). There was a significant dif-ference in CDR severity scores between the groups with the AD groupscore suggesting dementia of mild severity (t = 15.2, p < .001). Globalcognitive function as measured by MMSE scores were significantlylower in AD than in the HC group (t = 8.3, p < .001) with scores forthe AD group falling in the mild range of impairment.

3.1. Cognitive tests

The cognitive data are summarised in Table 2. The AD groupperformed significantly worse than the HC group on the majority

Table 2Cognitive test data for healthy control (HC) and Alzheimer’s disease (AD) groups

Cognitive domain Task HC (n = 14) AD (n = 15)

Sustained attention SRT� (ms) 374.9 ± 40.1 456.6 ± 33.3CRT� (ms) 513.8 ± 25.7 613.0 ± 25.7*

CRT accuracy (%) 97.5 ± 2.6 95.3 ± 5.5DVig� (ms) 434.2 ± 17.6 512.6 ± 14.1*

DVig accuracy (%) 100 ± 0.0 97.3 ± 1.1*

DVig # of false alarms� 0.40 ± .70 1.0 ± 1.2Power of attention� (ms) 1323.1 ± 222.1 1591 ± 214.5*

Continuity of attention 64.1 ± .74 61.8 ± 3*

Working memory(WM)

Numeric WM SI 0.98 ± .05 0.95 ± .08

Spatial WM SI 0.86 ± .07 0.50 ± .08*

Quality of WM 1.8 ± .26 1.4 ± .29*

Language BNT (# of items named) 27.6 ± 3.1 22.1 ± 4.5*

Category fluency (# of wordsgenerated)

50.6 ± 10.6 24.3 ± 8.6*

Executive function Letter fluency (# of wordsgenerated)

40.6 ± 2.8 29.5 ± 11.7*

Visuospatial ability RCFT copy (# items correct) 34.1 ± 1 24.9 ± 9*

RCFT delayed recall (# itemscorrect)

16.6 ± 5.5 1.4 ± 3*

Verbal learning andmemory

Verbal learning^ �0.11 ± .9 �3.4 ± 1*

Verbal memory^ 0.02 ± 1 �4.0 ± .08*

* p < .05, significant following correction for multiple comparisons.� Lower scores represent better performance; RCFT, Rey Complex Figure Test.

^ z-Scores. Table 3Regional nAChR DVS in healthy control (HC) and Alzheimer’s disease (AD) groups

Brain regions HC AD

Average cortical 4.61 ± 0.09 4.92 ± 0.12Frontal cortex 4.69 ± 1.07 4.71 ± 0.55Temporal cortex 4.76 ± 1.15 5.23 ± 0.59Parietal cortex 4.46 ± 1.04 4.67 ± 0.53Posterior cingulate 4.25 ± 0.92 4.59 ± 0.75Median cingulate 4.80 ± 1.06 5.10 ± 0.68Hippocampus 4.68 ± 0.94 5.20 ± 0.82Thalamus 7.94 ± 1.85 8.28 ± 1.23

The average cortical DVS was calculated as a composite of the frontal, temporal andparietal cortices, posterior cingulate, median cingulate and hippocampal regions.

J.R. Ellis et al. / Neurobiology of Learning and Memory 90 (2008) 404–412 407

of the cognitive measures with the exception of the SRT task(t = 1.6, p = .13), accuracy on the CRT task (t = �1.1, p = .26), num-ber of false alarms on the DVig task (t = 1.4, p = .17), and NumericWM SI (t = �1.1, p = .29). The greatest relative difference in cogni-tive performance between the two groups was seen in the RCFT de-layed recall trial (t = 9.2, p < .05). In order to make comparisonsbetween various cognitive tests, raw scores for the verbal learningand memory domain were z-transformed by using reference datafrom a broader study using the same cognitive battery in the

Fig. 1. PET-MRI average fused images illustrating regional nAChR DVS (simplified Distribsignificant difference in nAChR DVS was found between the groups.

Department of Nuclear Medicine, Austin Hospital, Australia(n = 37).

3.2. 2-FA PET imaging

Given that there were no significant differences between hemi-spheres (p > .05), data from the right and left hemispheres of theselected brain regions were averaged for further analysis. In theage-matched controls there was binding in cortical and subcorticalregions with greatest binding in the thalamus. There were no sig-nificant differences in nAChR DVS between the HC and AD groupsfor average cortical, frontal, temporal, parietal, posterior cingulate,median cingulate, hippocampus, or thalamic regions (Fig. 1 and Ta-ble 3).

Results of regional analysis are displayed in Table 3. These re-sults were confirmed by voxel-based SPM analysis, with no areasreaching significance (p > .05) (SPM2, not shown).

3.3. Correlation between nAChR DVS and cognitive performance

After correcting for multiple comparisons there were no signif-icant correlations found between nAChR DVS and cognitive perfor-mance for the HC group. In the AD group, there was a significant

ution Volume) in HC (top row) and mild AD (bottom row) as measured by 2-FA. No

Table 4Correlation coefficients between cognitive function test results and nAChR DVS for Alzheimer’s disease group

Cognitive task Brain regions

FC TC PC M.Cin HC Thal

SRT� (ms) �.69* �.30 �.49 n/a n/a �.13CRT� (ms) �.24 �.25 �.10 n/a n/a �.52CRT accuracy (%) �.12 n/a �.13 n/a n/a �.07DVig� (ms) �.26 �.16 �.17 n/a n/a �.19DVig accuracy (%) �.10 n/a �.10 n/a n/a �.09DVig # of false alarms� �.16 n/a .22 n/a n/a .16Power of attention� (ms) �.57 �.34 �.38 n/a n/a �.42Continuity of attention �.01 n/a �.18 n/a n/a �.02Numeric WM SI �.10 n/a �.27 n/a n/a �.38Spatial WM SI .23 n/a .18 n/a n/a .30Quality of WM .26 n/a .14 n/a n/a .26BNT (# of items named) .21 �.22 n/a n/a n/a �.10Category fluency (# of words generated) .02 �.41 n/a n/a n/a �.24Letter fluency (# of words generated) .10 n/a n/a �.09 n/a �.14RCFT copy (# items correct) .40 .57 .45 n/a n/a .62RCFT delayed recall (# items correct) .30 �.12 .03 n/a n/a �.11Verbal learning^ .11 �.15 n/a n/a .02 .05Verbal memory^ .47 �.20 n/a n/a �.23 �.31

* p < .05, significant following correction for multiple comparisons; FC, frontal cortex; TC, temporal cortex; PC, parietal cortex; M.Cin, median cingulate; HC, hippocampus;Thal, thalamus.� Lower scores represent better performance; n/a, region not primarily related to cognitive task; RCFT, Rey Complex Figure Test.

^ z-Scores.

408 J.R. Ellis et al. / Neurobiology of Learning and Memory 90 (2008) 404–412

negative relationship between performance on the SRT task andnAChR DVS in the frontal cortex (q = �.69, p < .05), with better per-formance (lower RT) associated with higher nAChR DVS in this re-gion. However, no significant correlations were found between thepower of attention factor (which takes into account SRT perfor-mance) and nAChR DVS in the regions sampled (Table 4). Therewere no significant correlations found between nAChR DVS in theseven ROIs and the other cognitive tasks for the AD group. How-ever, there was a trend towards a positive correlation betweenRCFT copy performance and nAChR DVS in the temporal cortex(q = .57, p > .05) and the thalamus (q = .62, p > .05) suggesting thatbetter visuospatial performance may be associated with highernAChR DVs in these regions. No significant correlation found be-tween cortical nAChR DVS and global cognitive function as mea-sured by MMSE for the AD group (q = .02, p > .05).

4. Discussion

This study examined the distribution of a4b2 nAChRs in vivousing 2-FA PET in patients with early Alzheimer’s disease in com-parison to age-matched healthy controls. In addition the relation-ship between a4b2 nAChRs and cognitive performance wasexamined.

Evidence from post-mortem binding studies indicates that thea4b2 is the nAChR subtype consistently reduced by up to 50% inAD (Flynn & Mash, 1986; Warpman & Nordberg, 1995). Contraryto these post-mortem studies derived from patients with end-stagedisease (Araujo, Lapchak, Robitaille, Gauthier, & Quirion, 1988;Flynn & Mash, 1986; London, Ball, & Waller, 1989; Perry et al.,1995), we found no evidence of in vivo a4b2 loss in early AD. Inter-estingly these findings were observed despite significant cognitiveimpairment on measures of sustained attention, working memory,language, executive function, visuospatial ability, verbal learningand verbal memory, consistent with previous studies (Baddeleyet al., 1991; Laws et al., 2007; Morris & Kopelman, 1986; Pattersonet al., 1996; Perry & Hodges, 1999). The current findings are inaccordance with a recent in vitro post-mortem study conductedin a sample of patients with mild cognitive impairment (MCI) withequivalent symptom duration (<3 years) and comparable globalcognitive scores (MMSE = 26), where no difference in [3H](±)epi-batidine binding was found between MCI and controls (Sabbagh

et al., 2006). A significant decrease in nAChR binding in AD relativeto controls was only seen in those patients with long or protracteddisease (symptom duration = 9 years, MMSE = 13) (Sabbagh et al.,2006).

Using 2-FA PET imaging, we found preservation of a4b2 nAChRsin early AD in all brain regions examined including frontal, tempo-ral, parietal, posterior and median cingulate, hippocampus andthalamus. Significant reductions in nAChRs have been previouslynoted in various cortical regions of the autopsy brain tissue fromsubjects carrying the Swedish amyloid precursor protein (APP)670/671 mutation (�73% to �87%) as well as in sporadic Alzhei-mer’s disease (AD) cases (�37% to �57%) using the nicotinic ago-nists [3H]epibatidine and [3H]nicotine (Marutle et al., 1999).While the latter study suggests nAChR loss may occur very earlyin the course of AD, our findings support a number of other studiessuggesting the stability and preservation of cholinergic markersduring the early stages of AD (Davis et al., 1999; DeKosky et al.,2002; Gilmor et al., 1999). For example, in a post-mortem studyconducted by Davis et al. (1999) no significant difference in othercholinergic markers including ChAT and AChE activity in mild ADpatients relative to controls, but significantly lower levels of activ-ity were seen in patients with severe dementia. Similarly, animmunohistochemical investigation showed no significant differ-ence in the number of ChAT and vesicular acetylcholine transporter(VAChT) immunopositive neurons in MCI or mild AD compared tocontrols (Gilmor et al., 1999). These findings suggest that detect-able cholinergic deficits are not present until relatively late inthe course of the disease. As presented in Table 3, although not sig-nificant, we found that nAChR DVS values were higher for all brainregions sampled in the early AD patients as compared to controls.Our findings appear to be consistent with recent evidence showingup-regulation of ChAT during the early stages of dementia (MCI)(DeKosky et al., 2002), albeit to a lesser extent. We suggest thatup-regulation of nAChRs may be the first compensatory responseof the cholinergic system to neurodegeneration. While the numberof nAChR and cholinergic neurons is preserved or even increased inearly AD (as a compensatory mechanism) their function may bealtered. It therefore seems plausible that exhaustion of this com-pensatory mechanism and/or neuronal death may eventually leadto a decrease in nAChRs and other cholinergic markers at the latestages of the disease. This is supported by evidence from post-mor-

J.R. Ellis et al. / Neurobiology of Learning and Memory 90 (2008) 404–412 409

tem studies (Nordberg et al., 1992; Perry et al., 1995; Pimlott et al.,2004; Whitehouse et al., 1988), as well as a recent [123I]-5IA-85380SPECT study which observed significant reductions in a4b2 nAChRSin cortical and striatal brain regions of moderately severe AD pa-tients compared to controls (O’Brien et al., 2007) using an equiva-lent scanning protocol to our own. Other in vivo assessments ofnAChRs with 11C-nicotine PET have revealed similar reductions innAChR binding sites in moderate AD patients compared to controls(Nordberg et al., 1990, 1995).

The early AD patients sampled in the current study exhibitedsignificantly poorer performance than controls across the majorityof cognitive domains investigated, with the exception of some ofthe sustained attention and processing speed measures and themeasure of numeric WM. This pattern, in conjunction with theCDR score, likely reflects the mild severity of dementia of this pa-tient group and is in agreement with reports of more severe dis-ruptions to complex rather than simple measures of processingspeed early in the disease (Ferris, Crook, Sathananthan, & Gershon,1976; Gordon & Carson, 1990; Pirozzolo, Christensen, Ogle, Han-sch, & Thompson, 1981). Similarly, lack of a significant decline onthe numeric WM measures is consistent with the notion that thefunctioning of the articulatory loop is relatively unimpaired earlyin AD (Hodges, 2000; Morris, 1984), whereas deterioration is com-mon as severity of the disease increases (Carlesimo et al., 1998).The basal forebrain cholinergic deficits have been shown to be pos-itively correlated with cognitive impairments in AD (Bowen et al.,1982; Bierer et al., 1995) and dementia (Perry et al., 2001). Wedemonstrated that nAChR DVS in the frontal cortex of mild AD pa-tients significantly correlated with performance on the SRT mea-sure of attention and simple processing speed. This result agreeswith a recent study showing a significant correlation between11C-nicotine binding in fronto-parietal regions and another taskof attention/psychomotor speed (digit symbol substitution) in mildAD patients (Kadir, Almkvist, Wall, Langstrom, & Nordberg, 2006).Furthermore, previous studies evaluating the effects of nAChR ago-nist administration on cognitive function have shown improve-ments in sustained visual attention and information processingperformance in AD (Jones, Sahakian, Levy, Warburton, & Gray,1992; Sahakian, Jones, Levy, Gray, & Warburton, 1989; White & Le-vin, 1999). These findings are consistent with a fronto-parietal net-work for attention and information processing (Cabeza & Nyberg,2000).

Interestingly, the current study and that of Kadir et al. (2006)found no correlations between nAChRs and episodic memory per-formance. This finding is consistent with previous studies support-ing nicotine-induced enhancement of attention but not memoryfunction in AD (Jones et al., 1992; White & Levin, 1999). The epi-sodic memory deficits common early in AD may be related to thedisruption of other neurochemical systems such as the glutamater-gic system (Francis, 2003).

The relationship between cognition in AD and cholinergicdysfunction may be related to a number of factors includingthe degree of cholinergic system (or receptor) loss, the nAChRsubtypes involved, as well as contribution of other neurochemi-cal systems. For example, it is possible that a correlation be-tween cholinergic markers and cognitive function occurs inmore severe cases of AD and such a possibility is supported byevidence from post-mortem studies (Bierer et al., 1995; Perryet al., 2001). It is also possible that other nAChR subtypes maybe correlated with cognitive function. Indeed, a7 nAChRs havebeen linked to cognition as well as AD neuropathology. Recentanimal research points to the importance of these receptors incognitive function. For example, learning and memory signifi-cantly improved in rats following administration of the a7 ago-nist ARR 17779 (Boess et al., 2007; Levin, Bettegowda, Blosser,& Gordon, 1999; Van Kampen et al., 2004), and a7 nAChR knock-

out mice show significant impairments on the five-choice serialreaction-time task of sustained attention (Young et al., 2004).Furthermore, neurons in the entorhinal cortex most vulnerableto amyloid plaques appear to be those that abundantly expressthe a7 nAChR, and internalisation of Ab-42 appears to be facili-tated by the high affinity binding of the Ab-42 to the a7 nAChRon neuronal cell surfaces (Wang, Lee, D’Andrea, et al., 2000;Wang, Lee, Davis, & Shank, 2000). Such a mechanism may ex-plain the selective vulnerability of cholinergic neurones in ADbrains (D’Andrea & Nagele, 2006).

Interpretation of the current data should take into considerationpotential methodological limitations of the 2-FA PET study. In con-trast to most cerebral receptors that have been successfully studiedwith PET (e.g., dopamine D1 and D2 receptors; Fadda, Martellotta,Gessa, & Fratta, 1993; Sun, Ginovart, Ko, Seeman, & Kapur, 2003),a4b2 nAChRs are present in substantially lower numbers in themammalian brain (Horti & Villemagne, 2006). In order to visualisesmall changes in radioligand binding in regions of low nAChR den-sity with PET a sufficient signal-to-noise ratio is required. The mag-nitude of the signal can be significantly influenced by variablessuch as lipophilicity and metabolism, and the affinity of the radio-ligand for the receptor. Maximum signal in regions of low receptordensity requires a radioligand with high affinity. Lipophilicityshould also be in the range that minimises non-specific bindingi.e. permits crossing of the blood–brain barrier while limiting bind-ing to fatty tissues and plasma proteins. In this sense, the low bind-ing affinity of 2-FA combined with the low concentration of corticalbinding sites suggests that 2-FA might not be an ideal PET ligandfor studying small changes in extrathalamic nAChRs in vivo (Horti& Villemagne, 2006).

To our knowledge, this is the first study in which a comparisonhas been made of a4b2 nAChRs as visualised in vivo by 2-FA PETin mild AD and age-matched HC samples. The findings of the cur-rent study suggest that if changes in a4b2 nAChR do occur early inAD, detection of such changes appear to be below the levelsdetectable by the clinical 2-FA PET approach adopted in thisstudy. However, this approach may be appropriate for use inmore advanced AD as evidenced by the findings of O’Brien et al.(2007) in which nAChR loss was detected in moderately severeAD patients, and future studies are necessary to confirm this.Furthermore, this study demonstrated that a4b2 nAChRs are notassociated with the profile of cognitive deficits observed in earlyAD. However it is possible that such an association is moreapparent with disease progression and further investigation iswarranted. In addition it is possible that cognitive function inAD is more strongly linked to a7 nAChRs or non-cholinergic gluta-matergic and or serotonergic receptors and the development ofselective ligands for receptor subtypes within these systems willbe important in examining such relationships.

Disclosure statement

No actual or potential conflicts of interest.

Acknowledgments

Research support was provided by the Austin Hospital MedicalResearch Fund. Fellowship support for J.R.E. was provided by theAustralian Rotary Health Fund and the Monash University Post-graduate Award scheme. Fellowship support for P.J.N. was pro-vided by the National Health and Medical Research Council(NHMRC) of Australia and the Alzheimer’s Australia ResearchFoundation (AARF). The authors thank Drs. Michel Bottlaenderand Frédéric Dollé of the SHFJ PET Centre, Orsay (France) for provi-sion of precursor and technical assistance.

410 J.R. Ellis et al. / Neurobiology of Learning and Memory 90 (2008) 404–412

References

Abrahams, S., Goldstein, L. H., Simmons, A., Brammer, M. J., Williams, S. C.,Giampietro, V. P., et al. (2003). Functional magnetic resonance imaging of verbalfluency and confrontation naming using compressed image acquisition topermit overt responses. Human Brain Mapping, 20(1), 29–40.

Abreo, M. A., Lin, N. H., Garvey, D. S., Gunn, D. E., Hettinger, A. M., Wasicak, J. T., et al.(1996). Novel 3-pyridyl ethers with subnanomolar affinity for central neuronalnicotinic acetylcholine receptors. Journal of Medicinal Chemistry, 39(4), 817–825.

Adem, A., Nordberg, A., Jossan, S. S., Sara, V., & Gillberg, P. G. (1989). Quantitativeautoradiography of nicotinic receptors in large cryosections of human brainhemispheres. Neuroscience Letters, 101(3), 247–252.

Altamura, M., Elvevag, B., Blasi, G., Bertolino, A., Callicott, J. H., Weinberger, D. R.,et al. (2007). Dissociating the effects of Sternberg working memory demands inprefrontal cortex. Psychiatry Research, 154(2), 103–114.

Amunts, K., Weiss, P. H., Mohlberg, H., Pieperhoff, P., Eickhoff, S., Gurd, J. M., et al.(2004). Analysis of neural mechanisms underlying verbal fluency incytoarchitectonically defined stereotaxic space—The roles of Brodmann areas44 and 45. Neuroimage, 22(1), 42–56.

Araujo, D. M., Lapchak, P. A., Robitaille, Y., Gauthier, S., & Quirion, R. (1988).Differential alteration of various cholinergic markers in cortical and subcorticalregions of human brain in Alzheimer’s disease. Journal of Neurochemistry, 50(6),1914–1923.

Auld, D. S., Kornecook, T. J., Bastianetto, S., & Quirion, R. (2002). Alzheimer’s diseaseand the basal forebrain cholinergic system: Relations to beta-amyloid peptides,cognition, and treatment strategies. Progress in Neurobiology, 68(3), 209–245.

Baddeley, A. D., Bressi, S., Della Sala, S., Logie, R., & Spinnler, H. (1991). The decline ofworking memory in Alzheimer’s disease. A longitudinal study. Brain, 114(Pt. 6),2521–2542.

Bartus, R. T., Dean, R. L., 3rd, Beer, B., & Lippa, A. S. (1982). The cholinergichypothesis of geriatric memory dysfunction. Science, 217(4558), 408–414.

Benedict, R., Schretten, D., Groninger, L., & Brandt, J. (1998). Hopkins VerbalLearning Test—Revised: Normative data and analysis of inter-form and test–retest reliability. The Clinical Neuropsychologist, 12, 43–55.

Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practicaland powerful approach to multiple testing. Journal of the Royal Statistical SocietySeries B, 57(1), 289–300.

Benton, A. L. (1968). Differential behavioural effects of frontal lobe disease.Neuropsychologia, 6, 53–60.

Benton, A. L., & Hamsher, K. (1976). Multilingual aphasia examination. Iowa City:University of Iowa.

Bierer, L. M., Haroutunian, V., Gabriel, S., Knott, P. J., Carlin, L. S., Purohit, D. P., et al.(1995). Neurochemical correlates of dementia severity in Alzheimer’s disease:Relative importance of the cholinergic deficits. Journal of Neurochemistry, 64(2),749–760.

Boess, F. G., De Vry, J., Erb, C., Flessner, T., Hendrix, M., Luithle, J., et al. (2007). Thenovel alpha7 nicotinic acetylcholine receptor agonist N-[(3R)-1-azabicyclo[2.2.2]oct-3-yl]-7-[2-(methoxy)phenyl]-1-benzofuran-2-carboxamide improves working and recognition memory in rodents. The Journalof Pharmacology and Experimental Therapeutics, 321(2), 716–725.

Bottlaender, M., Valette, H., Roumenov, D., Dolle, F., Coulon, C., Ottaviani, M., et al.(2003). Biodistribution and radiation dosimetry of 18F-fluoro-A-85380 inhealthy volunteers. Journal of Nuclear Medicine, 44(4), 596–601.

Bowen, D. M., Benton, J. S., Spillane, J. A., Smith, C. C., & Allen, S. J. (1982). Cholineacetyltransferase activity and histopathology of frontal neocortex from biopsiesof demented patients. Journal of the Neurological Science, 57(2–3), 191–202.

Brandt, J., & Benedict, R. H. (2001). Hopkins Verbal Learning Test—Revised. Professionalmanual. Lutz, FL: Psychological Assessment Resources.

Brody, A. L., Mandelkern, M. A., London, E. D., Olmstead, R. E., Farahi, J., Scheibal, D.,et al. (2006). Cigarette smoking saturates brain alpha 4 beta 2 nicotinicacetylcholine receptors. Archives of General Psychiatry, 63(8), 907–915.

Bunge, S. A., Ochsner, K. N., Desmond, J. E., Glover, G. H., & Gabrieli, J. D. (2001).Prefrontal regions involved in keeping information in and out of mind. Brain,124(Pt. 10), 2074–2086.

Cabeza, R., & Nyberg, L. (2000). Imaging cognition: II. An empirical review of 275PET and fMRI studies. Journal of Cognitive Neuroscience, 12(1), 1–47.

Carlesimo, G. A., Mauri, M., Graceffa, A. M., Fadda, L., Loasses, A., Lorusso, S., et al.(1998). Memory performances in young, elderly, and very old healthyindividuals versus patients with Alzheimer’s disease: Evidence fordiscontinuity between normal and pathological aging. Journal of Clinical andExperimental Neuropsychology, 20(1), 14–29.

Chefer, S. I., London, E. D., Koren, A. O., Pavlova, O. A., Kurian, V., Kimes, A. S., et al.(2003). Graphical analysis of 2-[18F]FA binding to nicotinic acetylcholinereceptors in rhesus monkey brain. Synapse, 48(1), 25–34.

Cimino, M., Marini, P., Fornasari, D., Cattabeni, F., & Clementi, F. (1992). Distributionof nicotinic receptors in cynomolgus monkey brain and ganglia: localization ofalpha 3 subunit mRNA, alpha-bungarotoxin and nicotine binding sites.Neuroscience, 51(1), 77–86.

Collins, D. L., Neelin, P., Peters, T. M., & Evans, A. C. (1994). Automatic 3Dintersubject registration of MR volumetric data in standardized Talairach space.Journal of Computer Assisted Tomography, 18(2), 192–205.

Coull, J. T., Frith, C. D., Frackowiak, R. S., & Grasby, P. M. (1996). A fronto-parietal network for rapid visual information processing: A PET study ofsustained attention and working memory. Neuropsychologia, 34(11),1085–1095.

D’Andrea, M. R., & Nagele, R. G. (2006). Targeting the alpha 7 nicotinic acetylcholinereceptor to reduce amyloid accumulation in Alzheimer’s disease pyramidalneurons. Current Pharmaceutical Design, 12(6), 677–684.

Daube-Witherspoon, M. W., Matej, S., Karp, J. S., & Lewitt, R. M. (2001). Applicationof the 3D row action maximum likelihood algorithm to clinical PET imaging.IEEE Transactions on Nuclear Science, 48(1), 24–30.

Davis, K. L., Mohs, R. C., Marin, D., Purohit, D. P., Perl, D. P., Lantz, M., et al. (1999).Cholinergic markers in elderly patients with early signs of Alzheimer disease.The Journal of the American Medical Association, 281(15), 1401–1406.

DeKosky, S. T., Ikonomovic, M. D., Styren, S. D., Beckett, L., Wisniewski, S., Bennett,D. A., et al. (2002). Upregulation of choline acetyltransferase activity inhippocampus and frontal cortex of elderly subjects with mild cognitiveimpairment. Annals of Neurology, 51(2), 145–155.

Delis, D. C., Kramer, J. H., Kaplan, E., & Ober, B. A. (2000). California Verbal LearningTest—Second edition adult version. San Antonio, TX: The PsychologicalCorporation.

Deweer, B., Lehericy, S., Pillon, B., Baulac, M., Chiras, J., Marsault, C., et al. (1995).Memory disorders in probable Alzheimer’s disease: The role of hippocampalatrophy as shown with MRI. Journal of Neurology, Neurosurgery, and Psychiatry,58(5), 590–597.

Dolle, F., Dolci, L., Valette, H., Hinnen, F., Vaufrey, F., Guenther, I., et al. (1999).Synthesis and nicotinic acetylcholine receptor in vivo binding properties of 2-fluoro-3-[2(S)-2-azetidinylmethoxy]pyridine: A new positron emissiontomography ligand for nicotinic receptors. Journal of Medicinal Chemistry,42(12), 2251–2259.

Ebert, U., Oertel, R., Wesnes, K. A., & Kirch, W. (1998). Effects of physostigmine onscopolamine-induced changes in quantitative electroencephalogram andcognitive performance. Human Psychopharmacology, 13, 199–210.

Ellis, J. R., Ellis, K. A., Bartholomeusz, C. F., Harrison, B. J., Wesnes, K. A., Erskine, F. F.,et al. (2006). Muscarinic and nicotinic receptors synergistically modulateworking memory and attention in humans. International Journal ofNeuropsychopharmacology, 9(2), 175–189.

Fadda, P., Martellotta, M. C., Gessa, G. L., & Fratta, W. (1993). Dopamine and opioidsinteractions in sleep deprivation. Progress in Neuropsychopharmacology &Biological Psychiatry, 17(2), 269–278.

Ferris, S., Crook, T., Sathananthan, G., & Gershon, S. (1976). Reaction time as adiagnostic measure in senility. Journal of the American Geriatrics Society, 24(12),529–533.

Flores, C. M., Rogers, S. W., Pabreza, L. A., Wolfe, B. B., & Kellar, K. J. (1992). A subtypeof nicotinic cholinergic receptor in rat brain is composed of alpha 4 and beta 2subunits and is up-regulated by chronic nicotine treatment. MolecularPharmacology, 41(1), 31–37.

Flynn, D. D., & Mash, D. C. (1986). Characterization of L-[3H]nicotine binding inhuman cerebral cortex: Comparison between Alzheimer’s disease and thenormal. Journal of Neurochemistry, 47(6), 1948–1954.

Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). ‘‘Mini-mental state”. Apractical method for grading the cognitive state of patients for the clinician.Journal of Psychiatric Research, 12(3), 189–198.

Francis, P. T. (2003). Glutamatergic systems in Alzheimer’s disease. InternationalJournal of Geriatric Psychiatry, 18(Suppl. 1), S15–S21.

Frey, P. W., & Colliver, J. A. (1973). Sensitivity and response measures fordiscrimination learning. Learning and Motivation, 4, 327–334.

Friston, K. J., Frith, C. D., Liddle, P. F., & Frackowiak, R. S. (1991). Comparingfunctional (PET) images: The assessment of significant change. Journal ofCerebral Blood Flow and Metabolism, 11(4), 690–699.

Gallezot, J. D., Bottlaender, M., Gregoire, M. C., Roumenov, D., Deverre, J. R., Coulon,C., et al. (2005). In vivo imaging of human cerebral nicotinic acetylcholinereceptors with 2-18F-fluoro-A-85380 and PET. Journal of Nuclear Medicine, 46(2),240–247.

Giacobini, E. (2003). Cholinergic function and Alzheimer’s disease. InternationalJournal of Geriatric Psychiatry, 18(Suppl. 1), S1–S5.

Gilmor, M. L., Erickson, J. D., Varoqui, H., Hersh, L. B., Bennett, D. A., Cochran, E. J.,et al. (1999). Preservation of nucleus basalis neurons containing cholineacetyltransferase and the vesicular acetylcholine transporter in the elderlywith mild cognitive impairment and early Alzheimer’s disease. Journal ofComputational Neuroscience, 411(4), 693–704.

Goodglass, H., & Kaplan, E. (1972). The assessment of aphasias and related disorders.Philadelphia: Lea and Febiger.

Gordon, B., & Carson, K. (1990). The basis for choice reaction time slowing inAlzheimer’s disease. Brain and Cognition, 13(2), 148–166.

Grober, E., Hall, C. B., Lipton, R. B., Zonderman, A. B., Resnick, S. M., & Kawas, C.(2008). Memory impairment, executive dysfunction, and intellectual decline inpreclinical Alzheimer’s disease. Journal of the International NeuropsychologicalSociety, 14(2), 266–278.

Hodges, J. R. (2000). Memory in the dementias. In E. Tulving & F. I. M. Craik (Eds.),The Oxford handbook of memory (pp. 441–459). Oxford: Oxford University Press.

Horti, A. G., Koren, A. O., Lee, K. S., Mukhin, A. G., Vaupel, D. B., Kimes, A. S., et al.(1999). Radiosynthesis and preliminary evaluation of 5-[123/125I]iodo-3-(2(S)-azetidinylmethoxy)pyridine: A radioligand for nicotinic acetylcholine receptors.Nuclear Medicine and Biology, 26(2), 175–182.

Horti, A. G., Scheffel, U., Koren, A. O., Ravert, H. T., Mathews, W. B., Musachio, J. L.,et al. (1998). 2-[18F]Fluoro-A-85380, an in vivo tracer for the nicotinicacetylcholine receptors. Nuclear Medicine and Biology, 25(7), 599–603.

Horti, A. G., & Villemagne, V. L. (2006). The quest for Eldorado: Development ofradioligands for in vivo imaging of nicotinic acetylcholine receptors in humanbrain. Current Pharmaceutical Design, 12(30), 3877–3900.

J.R. Ellis et al. / Neurobiology of Learning and Memory 90 (2008) 404–412 411

Hughes, C. P., Berg, L., Danziger, W. L., Coben, L. A., & Martin, R. L. (1982). A newclinical scale for the staging of dementia. British Journal of Psychiatry, 140,566–572.

Johnson, S. C., Saykin, A. J., Flashman, L. A., McAllister, T. W., & Sparling, M. B. (2001).Brain activation on fMRI and verbal memory ability: Functional neuroanatomiccorrelates of CVLT performance. Journal of the International NeuropsychologicalSociety, 7(1), 55–62.

Jones, G. M., Sahakian, B. J., Levy, R., Warburton, D. M., & Gray, J. A. (1992). Effects ofacute subcutaneous nicotine on attention, information processing and short-term memory in Alzheimer’s disease. Psychopharmacology (Berlin), 108(4),485–494.

Kadir, A., Almkvist, O., Wall, A., Langstrom, B., & Nordberg, A. (2006). PET imaging ofcortical 11C-nicotine binding correlates with the cognitive function of attentionin Alzheimer’s disease. Psychopharmacology (Berlin), 188(4), 509–520.

Kensinger, E. A., Shearer, D. K., Locascio, J. J., Growdon, J. H., & Corkin, S. (2003).Working memory in mild Alzheimer’s disease and early Parkinson’s disease.Neuropsychology, 17(2), 230–239.

Koch, H. J., Haas, S., & Jurgens, T. (2005). On the physiological relevance ofmuscarinic acetylcholine receptors in Alzheimer’s disease. Current MedicinalChemistry, 12(24), 2915–2921.

Kuhl, D. E., Koeppe, R. A., Minoshima, S., Snyder, S. E., Ficaro, E. P., Foster, N. L., et al.(1999). In vivo mapping of cerebral acetylcholinesterase activity in aging andAlzheimer’s disease. Neurology, 52(4), 691–699.

Kuhl, D. E., Minoshima, S., Fessler, J. A., Frey, K. A., Foster, N. L., Ficaro, E. P., et al.(1996). In vivo mapping of cholinergic terminals in normal aging, Alzheimer’sdisease, and Parkinson’s disease. Annals of Neurology, 40(3), 399–410.

Lawrence, A. D., & Sahakian, B. J. (1995). Alzheimer disease, attention, and thecholinergic system. Alzheimer Disease and Associated Disorders, 9(Suppl. 2),43–49.

Laws, K. R., Adlington, R. L., Gale, T. M., Moreno-Martinez, F. J., & Sartori, G. (2007). Ameta-analytic review of category naming in Alzheimer’s disease.Neuropsychologia.

Levin, E. D., Bettegowda, C., Blosser, J., & Gordon, J. (1999). AR-R17779, and alpha7nicotinic agonist, improves learning and memory in rats. BehaviouralPharmacology, 10(6–7), 675–680.

Lewin, J. S., Friedman, L., Wu, D., Miller, D. A., Thompson, L. A., Klein, S. K., et al.(1996). Cortical localization of human sustained attention: Detection withfunctional MR using a visual vigilance paradigm. Journal of Computer AssistedTomography, 20(5), 695–701.

Lezak, M. D. (1995). Neuropsychological assessment (3rd ed.). New York: OxfordUniversity Press.

London, E. D., Ball, M. J., & Waller, S. B. (1989). Nicotinic binding sites in cerebralcortex and hippocampus in Alzheimer’s dementia. Neurochemical Research,14(8), 745–750.

Marutle, A., Warpman, U., Bogdanovic, N., Lannfelt, L., & Nordberg, A. (1999).Neuronal nicotinic receptor deficits in Alzheimer patients with the Swedishamyloid precursor protein 670/671 mutation. Journal of Neurochemistry, 72(3),1161–1169.

McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M.(1984). Clinical diagnosis of Alzheimer’s disease: Report of the NINCDS-ADRDAWork Group under the auspices of Department of Health and Human ServicesTask Force on Alzheimer’s disease. Neurology, 34(7), 939–944.

Mennemeier, M. S., Chatterjee, A., Watson, R. T., Wertman, E., Carter, L. P., &Heilman, K. M. (1994). Contributions of the parietal and frontal lobes tosustained attention and habituation. Neuropsychologia, 32(6), 703–716.

Meyers, J. E., & Meyers, K. R. (1995). Rey complex figure test and recognition trial.Odessa: Psychological Assessment Resources Inc..

Mitkovski, S., Villemagne, V. L., Novakovic, K. E., O’Keefe, G., Tochon-Danguy, H.,Mulligan, R. S., et al. (2005). Simplified quantification of nicotinic receptors with2[18F]F-A-85380 PET. Nuclear Medicine and Biology, 32(6), 585–591.

Morris, R. G. (1984). Dementia and the functioning of the articulatory loop system.Cognitive Neuropsychology, 1, 147–157.

Morris, J. C. (1993). The clinical dementia rating (CDR): Current version and scoringrules. Neurology, 43(11), 2412–2414.

Morris, R. G., & Kopelman, M. D. (1986). The memory deficits in Alzheimer-typedementia: A review. The Quarterly Journal of Experimental Psychology. A, HumanExperimental Psychology, 38(4), 575–602.

Mukhin, A. G., Gundisch, D., Horti, A. G., Koren, A. O., Tamagnan, G., Kimes, A. S.,et al. (2000). 5-Iodo-A-85380, an alpha4beta2 subtype-selective ligand fornicotinic acetylcholine receptors. Molecular Pharmacology, 57(3), 642–649.

Mulligan, R. S., Ellis, J. R., Smith, C. L., Tochon-Danguy, H. J., Rowe, C. C., &Villemagne, V. L. (2006). Characterization of a population-based metabolitecorrection for [18F]F-A85380 human PET studies. Journal of Nuclear Medicine,47(282).

Musachio, J. L., Villemagne, V. L., Scheffel, U. A., Dannals, R. F., Dogan, A. S., Yokoi, F.,et al. (1999). Synthesis of an I-123 analog of A-85380 and preliminary SPECTimaging of nicotinic receptors in baboon. Nuclear Medicine and Biology, 26(2),201–207.

Naslund, J., Haroutunian, V., Mohs, R., Davis, K. L., Davies, P., Greengard, P., et al.(2000). Correlation between elevated levels of amyloid beta-peptide in thebrain and cognitive decline. The Journal of the American Medical Association,283(12), 1571–1577.

Nordberg, A. (1992). Neuroreceptor changes in Alzheimer disease. Cerebrovascularand Brain Metabolism Reviews, 4(4), 303–328.

Nordberg, A. (1994). Human nicotinic receptors—Their role in aging and dementia.Neurochemistry International, 25(1), 93–97.

Nordberg, A., Alafuzoff, I., & Winblad, B. (1992). Nicotinic and muscarinic subtypesin the human brain: Changes with aging and dementia. Journal of NeuroscienceResearch, 31(1), 103–111.

Nordberg, A., Hartvig, P., Lilja, A., Viitanen, M., Amberla, K., Lundqvist, H.,et al. (1990). Decreased uptake and binding of 11C-nicotine in brain ofAlzheimer patients as visualized by positron emission tomography. Journalof Neural Transmission. Parkinson’s Disease and Dementia Section, 2(3),215–224.

Nordberg, A., Lundqvist, H., Hartvig, P., Andersson, J., Johansson, M., Hellstrom-Lindahl, E., et al. (1997). Imaging of nicotinic and muscarinic receptors inAlzheimer’s disease: Effect of tacrine treatment. Dementia and GeriatricCognitive Disorders, 8(2), 78–84.

Nordberg, A., Lundqvist, H., Hartvig, P., Lilja, A., & Langstrom, B. (1995). Kineticanalysis of regional (S)(�)11C-nicotine binding in normal and Alzheimer brains-in vivo assessment using positron emission tomography. Alzheimer Disease andAssociated Disorders, 9(1), 21–27.

Nyback, H., Halldin, C., Ahlin, A., Curvall, M., & Eriksson, L. (1994). PET studies of theuptake of (S)- and (R)-[11C] nicotine in the human brain: Difficulties invisualizing specific receptor binding in vivo. Psychopharmacology (Berlin),115(1–2), 31–36.

O’Brien, J. T., Colloby, S. J., Pakrasi, S., Perry, E. K., Pimlott, S. L., Wyper, D. J., et al.(2007). Alpha4beta2 nicotinic receptor status in Alzheimer’s disease using 123I-5IA-85380 single-photon-emission computed tomography. Journal of Neurology,Neurosurgery, and Psychiatry, 78(4), 356–362.

O’Brien, J. T., Wiseman, R., Burton, E. J., Barber, B., Wesnes, K., Saxby, B., et al. (2002).Cognitive associations of subcortical white matter lesions in older people.Annals of the New York Academy of Sciences, 977, 436–444.

Pantel, J., Schonknecht, P., Essig, M., & Schroder, J. (2004). Distribution of cerebralatrophy assessed by magnetic resonance imaging reflects patterns ofneuropsychological deficits in Alzheimer’s dementia. Neuroscience Letters,361(1–3), 17–20.

Pardo, J. V., Fox, P. T., & Raichle, M. E. (1991). Localization of a human system forsustained attention by positron emission tomography. Nature, 349(6304),61–64.

Patterson, M. B., Mack, J. L., Geldmacher, D. S., & Whitehouse, P. J. (1996). Executivefunctions and Alzheimer’s disease: Problems and prospects. European Journal ofNeurology, 3, 5–15.

Perry, R. J., & Hodges, J. R. (1999). Attention and executive deficits in Alzheimer’sdisease. A critical review. Brain, 122(Pt. 3), 383–404.

Perry, E. K., Martin-Ruiz, C. M., & Court, J. A. (2001). Nicotinic receptor subtypes inhuman brain related to aging and dementia. Alcohol, 24(2), 63–68.

Perry, E. K., Morris, C. M., Court, J. A., Cheng, A., Fairbairn, A. F., McKeith, I. G., et al.(1995). Alteration in nicotine binding sites in Parkinson’s disease, Lewy bodydementia and Alzheimer’s disease: Possible index of early neuropathology.Neuroscience, 64(2), 385–395.

Phelps, E. A., Hyder, F., Blamire, A. M., & Shulman, R. G. (1997). FMRI of theprefrontal cortex during overt verbal fluency. Neuroreport, 8(2), 561–565.

Pimlott, S. L., Piggott, M., Owens, J., Greally, E., Court, J. A., Jaros, E., et al. (2004).Nicotinic acetylcholine receptor distribution in Alzheimer’s disease, dementiawith Lewy bodies, Parkinson’s disease, and vascular dementia: In vitro bindingstudy using 5-[(125)i]-a-85380. Neuropsychopharmacology, 29(1), 108–116.

Pirozzolo, F. J., Christensen, K. J., Ogle, K. M., Hansch, E. C., & Thompson, W. G.(1981). Simple and choice reaction time in dementia: Clinical implications.Neurobiology of Aging, 2(2), 113–117.

Rosen, W. G. (1980). Verbal fluency in aging and dementia. Journal of ClinicalNeuropsychology, 2, 135–146.

Sabbagh, M. N., Shah, F., Reid, R. T., Sue, L., Connor, D. J., Peterson, L. K., et al. (2006).Pathologic and nicotinic receptor binding differences between mild cognitiveimpairment, Alzheimer disease, and normal aging. Archives of Neurology, 63(12),1771–1776.

Sahakian, B., Jones, G., Levy, R., Gray, J., & Warburton, D. (1989). The effects ofnicotine on attention, information processing, and short-term memory inpatients with dementia of the Alzheimer type. British Journal of Psychiatry, 154,797–800.

Saxton, J., Ratcliff, G., Munro, C. A., Coffey, E. C., Becker, J. T., Fried, L., et al. (2000).Normative data on the Boston Naming Test and two equivalent 30-item shortforms. The Clinical Neuropsychologist, 14(4), 526–534.

Saykin, A. J., Johnson, S. C., Flashman, L. A., McAllister, T. W., Sparling, M., Darcey, T.M., et al. (1999). Functional differentiation of medial temporal and frontalregions involved in processing novel and familiar words: An fMRI study. Brain,122(Pt. 10), 1963–1971.

Schliebs, R., & Arendt, T. (2006). The significance of the cholinergic system in thebrain during aging and in Alzheimer’s disease. Journal of Neural Transmission,113(11), 1625–1644.

Seidenberg, M., Geary, E., & Hermann, B. (2005). Investigating temporal lobecontribution to confrontation naming using MRI quantitative volumetrics.Journal of the International Neuropsychological Society, 11(4), 358–366.

Sihver, W., Nordberg, A., Langstrom, B., Mukhin, A. G., Koren, A. O., Kimes, A. S., et al.(2000). Development of ligands for in vivo imaging of cerebral nicotinicreceptors. Behavioural Brain Research, 113(1–2), 143–157.

Spitzer, R. L., Williams, J. B., Kroenke, K., Linzer, M., deGruy, F. V., 3rd, Hahn, S. R.,et al. (1994). Utility of a new procedure for diagnosing mental disorders inprimary care. The PRIME-MD 1000 study. The Journal of the American MedicalAssociation, 272(22), 1749–1756.

Sternberg, S. (1966). High-speed scanning in human memory. Science, 153(736),652–654.

412 J.R. Ellis et al. / Neurobiology of Learning and Memory 90 (2008) 404–412

Sun, W., Ginovart, N., Ko, F., Seeman, P., & Kapur, S. (2003). In vivo evidence fordopamine-mediated internalization of D2-receptors after amphetamine:Differential findings with [3H]raclopride versus [3H]spiperone. MolecularPharmacology, 63(2), 456–462.

Swanberg, M. M., Tractenberg, R. E., Mohs, R., Thal, L. J., & Cummings, J. L. (2004).Executive dysfunction in Alzheimer disease. Archives of Neurology, 61(4),556–560.

Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix,N., et al. (2002). Automated anatomical labeling of activations in SPM using amacroscopic anatomical parcellation of the MNI MRI single-subject brain.Neuroimage, 15(1), 273–289.

Valette, H., Bottlaender, M., Dolle, F., Coulon, C., Ottaviani, M., & Syrota, A.(2003). Long-lasting occupancy of central nicotinic acetylcholine receptorsafter smoking: A PET study in monkeys. Journal of Neurochemistry, 84(1),105–111.

Valette, H., Bottlaender, M., Dolle, F., Guenther, I., Fuseau, C., Coulon, C., et al. (1999).Imaging central nicotinic acetylcholine receptors in baboons with [18F]fluoro-A-85380. Journal of Nuclear Medicine, 40(8), 1374–1380.

Van Kampen, M., Selbach, K., Schneider, R., Schiegel, E., Boess, F., &Schreiber, R. (2004). AR-R 17779 improves social recognition in rats byactivation of nicotinic alpha7 receptors. Psychopharmacology (Berlin),172(4), 375–383.

Vaupel, D. B., Mukhin, A. G., Kimes, A. S., Horti, A. G., Koren, A. O., & London, E. D.(1998). In vivo studies with [125I]5-I-A-85380, a nicotinic acetylcholine receptorradioligand. Neuroreport, 9(10), 2311–2317.

Vogel, A., Gade, A., Stokholm, J., & Waldemar, G. (2005). Semantic memoryimpairment in the earliest phases of Alzheimer’s disease. Dementia andGeriatric Cognitive Disorders, 19(2–3), 75–81.

Wang, H. Y., Lee, D. H., D’Andrea, M. R., Peterson, P. A., Shank, R. P., & Reitz, A. B.(2000). Beta-amyloid(1–42) binds to alpha7 nicotinic acetylcholine receptorwith high affinity. Implications for Alzheimer’s disease pathology. The Journal ofBiological Chemistry, 275(8), 5626–5632.

Wang, H. Y., Lee, D. H., Davis, C. B., & Shank, R. P. (2000). Amyloid peptide Abeta(1–42) binds selectively and with picomolar affinity to alpha7 nicotinicacetylcholine receptors. Journal of Neurochemistry, 75(3), 1155–1161.

Warpman, U., & Nordberg, A. (1995). Epibatidine and ABT 418 reveal selective lossesof alpha 4 beta 2 nicotinic receptors in Alzheimer brains. Neuroreport, 6(17),2419–2423.

Wesnes, K. A., Ward, T., McGinty, A., & Petrini, O. (2000). The memory enhancingeffects of a Ginkgo biloba/Panax ginseng combination in healthy middle-agedvolunteers. Psychopharmacology (Berlin), 152(4), 353–361.

White, H. K., & Levin, E. D. (1999). Four-week nicotine skin patch treatment effectson cognitive performance in Alzheimer’s disease. Psychopharmacology (Berlin),143(2), 158–165.

Whitehouse, P. J. (1987). Neurotransmitter receptor alterations in Alzheimerdisease: A review. Alzheimer Disease and Associated Disorders, 1(1), 9–18.

Whitehouse, P. J., Martino, A. M., Wagster, M. V., Price, D. L., Mayeux, R., Atack, J. R.,et al. (1988). Reductions in [3H]nicotinic acetylcholine binding in Alzheimer’sdisease and Parkinson’s disease: An autoradiographic study. Neurology, 38(5),720–723.

Wiggs, C. L., Weisberg, J., & Martin, A. (1999). Neural correlates of semantic andepisodic memory retrieval. Neuropsychologia, 37(1), 103–118.

Wood, A. G., Saling, M. M., Abbott, D. F., & Jackson, G. D. (2001). A neurocognitiveaccount of frontal lobe involvement in orthographic lexical retrieval: An fMRIstudy. Neuroimage, 14(1, Pt. 1), 162–169.

Woodruff-Pak, D. S., & Gould, T. J. (2002). Neuronal nicotinic acetylcholinereceptors: Involvement in Alzheimer’s disease and schizophrenia. Behavioraland Cognitive Neuroscience Reviews, 1(1), 5–20.

Young, J. W., Finlayson, K., Spratt, C., Marston, H. M., Crawford, N., Kelly, J. S., et al.(2004). Nicotine improves sustained attention in mice: Evidence forinvolvement of the alpha7 nicotinic acetylcholine receptor.Neuropsychopharmacology, 29(5), 891–900.

Zigmond, A. S., & Snaith, R. P. (1983). The hospital anxiety and depression scale. ActaPsychiatrica Scandinavica, 67(6), 361–370.