Abstract

Word finding symptoms are frequent early in the course of Alzheimer's disease and relate principally to functional changes in left posterior temporal cortex. In cognitively intact older adults, we examined whether amyloid load affects the network for language and associative-semantic processing. Fifty-six community-recruited subjects (52–74 years), stratified for apolipoprotein E and brain-derived neurotrophic factor genotype, received a neurolinguistic assessment, 18F-flutemetamol positron emission tomography, and a functional MRI of the associative-semantic system. The primary measure of amyloid load was the cerebral-to-cerebellar gray matter standardized uptake value ratio in a composite cortical volume of interest (SUVRcomp). The primary outcome analysis consisted of a whole-brain voxelwise linear regression between SUVRcomp and fMRI response during associative-semantic versus visuoperceptual processing. Higher activity in one region, the posterior left middle temporal gyrus, correlated positively with increased amyloid load. The correlation remained significant when only the word conditions were contrasted but not for pictures. According to a stepwise linear regression analysis, offline naming reaction times correlated positively with SUVRcomp. A binary classification into amyloid-positive and amyloid-negative cases confirmed our findings. The left posterior temporal activity increase may reflect higher demands for semantic control in the presence of a higher amyloid burden.

Introduction

Modern techniques such as amyloid positron emission tomography (PET) allow one to detect hallmark lesions related to Alzheimer's disease (AD) directly in vivo (Clark et al. 2011; Herholz and Ebmeier 2011; Clark et al. 2012; Vandenberghe, Adamczuk, Dupont et al. 2013; Vandenberghe, Adamczuk, Van Laere et al. 2013). Depending on mainly age and apolipoprotein E (APOE) genotype, 10–30% of cognitively intact older adults have a positive amyloid scan, which can be indistinguishable from what is seen in clinically probable AD (for review, see Chételat et al. 2013). Longitudinally, increased Aβ load is associated with greater risk of cognitive decline (Morris et al. 2009; Resnick et al. 2010; Villemagne et al. 2011; Doraiswamy et al. 2012) and gray matter volume loss (Chételat et al. 2012). Amyloid PET has become one of the principal ways to define the “preclinical” stage of AD, a term that refers to the AD-related pathogenetic processes that happen before clinical symptoms become apparent (Sperling et al. 2011). In this study, we used 18F-flutemetamol (Vandenberghe et al. 2010) as our ligand. Previous studies have revealed a high correlation between the cortical retention levels obtained with this ligand and those obtained with 11C-Pittsburgh Compound B (Vandenberghe et al. 2010; Hatashita et al. 2014) as well as with neuritic plaque density based on Bielschowsky silver staining (Thurfjell et al. 2014).

Word finding difficulties are frequent in clinically probable AD, even at a pre-dementia stage (Bayles and Tomoeda 1983; Huff et al. 1986; Chertkow and Bub 1990; Vandenbulcke et al. 2007; Apostolova et al. 2008; Clark et al. 2009; Sugarman et al. 2012). The first language area to become dysfunctional in early-stage AD and amnestic mild cognitive impairment (MCI) is the left posterior superior temporal sulcus (STS) (Nelissen et al. 2007; Vandenbulcke et al. 2007). Functional magnetic resonance imaging (fMRI) activity is lower in this region during associative-semantic compared with visuoperceptual processing in MCI patients (Vandenbulcke et al. 2007) and in clinically probable AD (Nelissen et al. 2007) compared with controls. In these populations, fMRI activity levels positively correlate with Boston Naming test scores (Nelissen et al. 2007) and with word identification speed (Vandenbulcke et al. 2007). Furthermore, in AD patients in whom naming is preserved, fMRI activity in the homotopical right-sided STS is increased compared with controls (Nelissen et al. 2007). Accordingly, we hypothesized that posterior temporal cortex may show adaptive changes in the presence of increased amyloid burden also in cognitively intact individuals. The study of functional changes related to amyloid burden in cognitively intact subjects is important because it could explain why some brains appear to be more resilient against Aβ-related injury than others. This factor may determine which individuals show clinical manifestations of underlying Alzheimer pathology and who remain cognitively intact despite the presence of Alzheimer pathology in the brain (Crystal et al. 1988; Katzman et al. 1988; Troncoso et al. 1996; Davis et al. 1999; Price and Morris 1999; Driscoll et al. 2006; Aizenstein et al. 2008). Even during the initial stages of neurodegenerative disease, the brain retains a potential for plasticity (Hyman et al. 1987; Nathan et al. 1994; Becker et al. 1996; Arendt et al. 1997; Mesulam 1999; Saykin et al. 1999; Grady et al. 2001; Grossman, Koenig, DeVita et al. 2003).

One of the genes that have been implicated in functional plasticity (Gorski et al. 2003; Webster et al. 2006) is brain-derived neurotrophic factor (BDNF), both in humans (Erickson et al. 2011) and in animal models (Okuno et al. 1999; Li et al. 2008; Osada et al. 2008). The presence of 1 or 2 met alleles on codon 66 is often considered to reduce the capacity for functional reorganisation. As our second hypothesis, we examined whether adaptive changes occurring in the language network in response to amyloid load differ between BDNF met carriers and non-carriers and how this interacts with APOE ϵ4 genotype (Adamczuk et al. 2013).

Materials and Methods

The protocol was approved by the Ethics Committee University Hospitals Leuven (EudraCT: 2009-014475-45), and written informed consent was obtained from all subjects in accordance with the latest version of the Declaration of Helsinki.

Participants

Subjects were recruited from the community via advertisement in local newspapers and via a website for seniors, asking for healthy volunteers between 50 and 75 years of age for participation in a scientific study at the University Hospital Leuven, Belgium, involving brain imaging. The relationship between genotype (APOE vs. BDNF) and amyloid levels in the present cohort has been described by Adamczuk et al. (2013).

At screening, subjects underwent blood sampling for genotyping, Mini Mental State Examination (MMSE), Clinical Dementia Rating (CDR) score, and a structured interview about medical history. Inclusion was stratified per age bin (50–59, 60–64, 65–69, and 70–75) for 2 genetic factors: BDNF (met allele present or absent) and APOE (ϵ4 allele present or absent). The cells of this 2 × 2 factorial design were prospectively matched for number of cases, gender, age, education, and handedness (Edinburgh Handedness Inventory) (Adamczuk et al. 2013). BDNF and APOE variants were genotyped by sequencing at the Genetic Service Facility (GSF, www.vibgeneticservicefacility.be) of the VIB Department of Molecular Genetics. The study exclusion criteria were an MMSE score below 27, a CDR score above 0, neurological or psychiatric history, brain lesions on structural MRI, left-handedness, non-native Dutch speaker, and below-normal test scores on conventional neuropsychological assessment (< 1.9 SD on published norms adapted for age, gender, and education) (Table 1). The conventional neuropsychological test protocol consisted of the Rey Auditory Verbal Learning Test, Boston Naming Test, Letter Verbal Fluency and Animal Verbal Fluency, Raven's Standard Progressive Matrices, and the Trail Making Test (Table 1).

Table 1

Demographic data and neuropsychological test scores

 Genetic groups
 
P 
BDNF met+ met− met+ met−  
APOE ϵ4+ ϵ4+ ϵ4− ϵ4− 
Gender (m/f) 7/7 7/4 7/7 10/7 0.9 
Age (years) 64.7 (5.9) 66.5 (4.7) 64.5 (6.0) 64.9 (5.5) 0.83 
Education (years) 13.1 (2.7) 12.7 (1.8) 13.8 (2.2) 14.4 (3.6) 0.47 
Handedness 94.3 (15.5) 100.0 (0.0) 96.2 (8.2) 100.0 (0.0) 0.24 
MMSE (/30) 28.9 (0.9) 28.7 (1.1) 29.3 (0.6) 28.9 (0.9) 0.47 
AVLT TL (/75) 48.7 (8.0) 47.5 (8.4) 51.2 (12.4) 50.0 (8.4) 0.79 
AVLT DR (/15) 11.6 (2.2) 9.0 (3.3) 11.4 (2.7) 10.8 (2.1) 0.07 
BNT (/60) 53.6 (4.6) 50.9 (7.4) 53.4 (3.9) 54.0 (3.3) 0.39 
AVF (# words) 18.6 (4.7) 19.7 (5.2) 21.9 (5.8) 21.3 (4.3) 0.3 
LVF (# words) 32.4 (12.1) 29.8 (7.9) 34.1 (10.3) 37.1 (10.0) 0.33 
RPM (/60) 39.1 (9.2) 39.8 (8.7) 45.7 (6.6) 46.5 (7.5) 0.03 
TMT B/A 2.9 (1.1) 2.4 (0.6) 2.5 (0.9) 2.5 (1.1) 0.5 
 Genetic groups
 
P 
BDNF met+ met− met+ met−  
APOE ϵ4+ ϵ4+ ϵ4− ϵ4− 
Gender (m/f) 7/7 7/4 7/7 10/7 0.9 
Age (years) 64.7 (5.9) 66.5 (4.7) 64.5 (6.0) 64.9 (5.5) 0.83 
Education (years) 13.1 (2.7) 12.7 (1.8) 13.8 (2.2) 14.4 (3.6) 0.47 
Handedness 94.3 (15.5) 100.0 (0.0) 96.2 (8.2) 100.0 (0.0) 0.24 
MMSE (/30) 28.9 (0.9) 28.7 (1.1) 29.3 (0.6) 28.9 (0.9) 0.47 
AVLT TL (/75) 48.7 (8.0) 47.5 (8.4) 51.2 (12.4) 50.0 (8.4) 0.79 
AVLT DR (/15) 11.6 (2.2) 9.0 (3.3) 11.4 (2.7) 10.8 (2.1) 0.07 
BNT (/60) 53.6 (4.6) 50.9 (7.4) 53.4 (3.9) 54.0 (3.3) 0.39 
AVF (# words) 18.6 (4.7) 19.7 (5.2) 21.9 (5.8) 21.3 (4.3) 0.3 
LVF (# words) 32.4 (12.1) 29.8 (7.9) 34.1 (10.3) 37.1 (10.0) 0.33 
RPM (/60) 39.1 (9.2) 39.8 (8.7) 45.7 (6.6) 46.5 (7.5) 0.03 
TMT B/A 2.9 (1.1) 2.4 (0.6) 2.5 (0.9) 2.5 (1.1) 0.5 

Note: Values represent means and standard deviations. Gender is expressed in number of individuals. m, male; f, female; MMSE, Mini Mental State Examination; AVLT, Rey Auditory Verbal Learning Test; TL, total learning; DR, delayed recall; BNT, Boston Naming Test; AVF, Animal Verbal Fluency Test; LVF, Letter Verbal Fluency Test; RPM, Raven's Progressive Matrices; TMT B/A, Trail Making Test B divided by A. Last column represents P-values for one-way between-groups ANOVA. Bonferroni-corrected threshold for significance P < 0.006 corresponding to Pcorrected < 0.05.

Fifty-six healthy, right-handed adults between 50 and 75 years of age (mean age = 65, SD = 5.5, range 52–74) who fulfilled all criteria were included in the study.

Experimental Language Tests

Given our a priori hypothesis of early involvement of left posterior STS and given its possible role in lexical-semantic retrieval (Vandenbulcke et al. 2007), the experimental language tests conducted outside the fMRI scanner consisted of confrontation naming, lexical decision, and speeded word identification (Table 2). Each of these tests was presented by Presentation 14.8 (NeuroBehavioural Systems) and was displayed on a 19-inch cathode ray tube monitor (resolution 1024 × 768 pixels, refresh rate 75 Hz) 60 cm from subjects' eyes.

Table 2

Experimental language test scores

  Genetic groups
 
P
 
BDNF  met+ met− met+ met−    
APOE  ϵ4+ ϵ4+ ϵ4− ϵ4− BDNF APOE Interaction 
Conf naming RT (ms) 1595 (288) 1507 (237) 1471 (333) 1450 (317) 0.27 0.50 0.68 
Accu (%) 93.0 (3.3) 91.2 (8.1) 92.4 (5.3) 90.7 (5.0) 0.70 0.24 0.96 
Lexical decision RT (ms) 1033 (146) 1118 (238) 1138 (211) 1154 (352) 0.29 0.44 0.60 
Accu (A’) 0.99 (0.01) 0.99 (0.01) 0.99 (0.01) 0.98 (0.02) 0.95 0.38 0.45 
Speeded id W a (ms) 25.2 (17.5) 21.2 (9.7) 21.6 (12.2) 19.9 (9.1) 0.48 0.42 0.75 
b (ms) 17.4 (8.3) 25.5 (13.5) 22.7 (10.1) 19.2 (10.7) 0.85 0.42 0.05 
c (%) 99.1 (1.3) 98.2 (1.8) 99.6 (0.6) 99.0 (1.7) 0.09 0.05 0.77 
  Genetic groups
 
P
 
BDNF  met+ met− met+ met−    
APOE  ϵ4+ ϵ4+ ϵ4− ϵ4− BDNF APOE Interaction 
Conf naming RT (ms) 1595 (288) 1507 (237) 1471 (333) 1450 (317) 0.27 0.50 0.68 
Accu (%) 93.0 (3.3) 91.2 (8.1) 92.4 (5.3) 90.7 (5.0) 0.70 0.24 0.96 
Lexical decision RT (ms) 1033 (146) 1118 (238) 1138 (211) 1154 (352) 0.29 0.44 0.60 
Accu (A’) 0.99 (0.01) 0.99 (0.01) 0.99 (0.01) 0.98 (0.02) 0.95 0.38 0.45 
Speeded id W a (ms) 25.2 (17.5) 21.2 (9.7) 21.6 (12.2) 19.9 (9.1) 0.48 0.42 0.75 
b (ms) 17.4 (8.3) 25.5 (13.5) 22.7 (10.1) 19.2 (10.7) 0.85 0.42 0.05 
c (%) 99.1 (1.3) 98.2 (1.8) 99.6 (0.6) 99.0 (1.7) 0.09 0.05 0.77 

Note: Values represent means and standard deviations. Conf naming, confrontation naming task; Speeded id W, speeded identification task for words; RT, reaction times; Accu, accuracy. Last 3 columns represent significant values for the main effect of BDNF, APOE, and interaction between them. Bonferroni-corrected threshold for significance P < 0.007 corresponding to Pcorrected < 0.05.

Confrontation Naming Task

In a computerized version of the picture naming task from Laiacona and Capitani (2001), 60 white line drawings of concrete entities were presented on a black background (picture size 9.68 deg × 7.74 deg; Snodgrass and Vanderwart 1980). The 60 items comprised 3 living (10 animals, 10 fruits, and 10 vegetables) and 3 non-living (10 tools, 10 pieces of furniture, and 10 vehicles) categories. Item order was randomized for each individual. A trial started with the appearance of a fixation point displayed for 2 s before stimulus onset. A warning sound (177 ms duration) was presented 500 ms before stimulus onset. The stimulus was on the screen until the subject provided a response, for a maximum duration of 1 min.

Reaction times (RT) were measured for the correct responses from the onset of the stimulus to the onset of the naming response. Voice recordings were manually analyzed in the WavePad Sound Editor version 4.57 (http://www.nch.com.au/wavepad). Accuracy was measured as percentage correct responses. Responses were considered correct if they were the picture's dominant name, a synonym, the name of a subordinate to the entity designated by the dominant name, or else if it occurred in at least 3 out of 30 other healthy controls viewing the picture for 2 s. Spontaneous, immediate auto-corrections were allowed.

Lexical Decision Task

In a computerized version of the visual lexical decision test from the Dutch version of the Psycholinguistic Assessment of Language Processing in Aphasia (PALPA 24, Bastiaanse et al. 1995), words and non-words were presented as white letters (letter height: 1 deg) on a black background. Stimuli consisted of 40 words with high imageability (20 high- and 20 low-frequency words), 40 words with low imageability (20 high- and 20 low- frequency words) and 80 non-words, randomly divided into 4 blocks (literal transcription of PALPA 24 paper version). Each stimulus was preceded by a fixation point for 1 s. Subjects were instructed to use their dominant hand and respond by key press whether the stimulus was a word or non-word. The stimulus was on the screen until the subject responded, for a maximum duration of stimulus presentation of 30 s.

RTs were measured for correct responses from the onset of the stimulus to the time of the button press. A’ was used as our accuracy measure (Pallier 2002).

Speeded Word and Picture Identification

The purpose of the speeded word and picture identification task was to analyze written word and picture identification under varying time constraints (Vandenbulcke et al. 2007). We derived a time-accuracy curve for stimulus presentation durations varying between 30, 60, 90, 150, 200, 500, 800, and 2000 ms. Subjects were instructed to read the word or name the picture. A trial consisted of a warning sound, a forward mask (200 ms duration, 9.68 × 7.74 deg), followed by either a word (letter height 1 deg) or a picture (9.68 × 7.74 deg; Snodgrass and Vanderwart 1980), which was immediately followed by a backward mask (200 ms duration, 9.68 × 7.74 deg), and a fixation point for 3 s. For each individual subject, the onset (a), steepness of the curve (b), and asymptote (c) of the time-accuracy function for words and pictures were calculated by means of the equation: accuracy=c(1e(aΔt)/b) for Δt ≥ a (Verhaeghen et al. 1998; Vandenbulcke et al. 2007). Goodness of fit was estimated as the sum of squared differences between the measured and calculated values (sum of the squared errors).

Functional MRI

Stimuli and Tasks

Stimuli were projected onto a screen (resolution of 1024 × 768 pixels, refresh rate 60 Hz) using Presentation 14.8 (NeuroBehavioural Systems). The fMRI paradigm has been described in detail before (Vandenberghe et al. 1996; Vandenbulcke et al. 2005, 2006; Nelissen et al. 2007; Vandenbulcke et al. 2007; Nelissen et al. 2011; Vandenberghe, Wang et al. 2013). In summary, the experimental design was factorial (Vandenberghe et al. 1996). The first factor, task, had 2 levels: associative-semantic (Fig. 1, blue and purple) versus visuoperceptual judgment (Fig. 1, cyan and yellow). The second factor, input modality, also had 2 levels: printed words (Fig. 1, blue and cyan) versus pictures (Fig. 1, purple and yellow). The associative-semantic condition was derived from the Pyramids and Palm Trees test (Howard and Patterson 1992), a classical neuropsychological test of associative-semantic processing for words and pictures. During a trial, a triplet of stimuli was presented for 5250 ms, 1 stimulus on top (the sample stimulus) and 1 in each lower quadrant (the test stimuli) at 4.6 deg eccentricity (mean picture size was 3.7 deg and mean letter size 1.2 deg), followed by a 1500 ms of interstimulus interval. Subjects were asked to press a left- or right-hand key depending on which of the 2 test stimuli matched the sample stimulus more closely in meaning. A given triplet was presented in either the picture or the word format, and this was counterbalanced across subjects. In the visuoperceptual control condition, a picture or word stimulus was presented in 3 different sizes (mean picture size was 3.7 deg and mean letter size 1.2 deg). Subjects had to press a left- or right-hand key depending on which of the 2 test stimuli matched the sample stimulus more closely in size on the screen. An epoch, that is, a block of trials belonging to the same condition, consisted of 4 trials (total duration 27 s). The fifth condition consisted of a resting baseline condition during which a fixation point was presented in the center of the screen (Fig. 1, red). During each fMRI run (5 runs in total), a series of the 5 epoch types was replicated 3 times (Fig. 1, timeline). The order of conditions was pseudorandom and different across runs of the same subject.

Figure 1.

Stimuli and tasks in fMRI experiment. Associative-semantic task with words (blue) and with pictures (purple). Visuoperceptual task with words (cyan) or pictures (yellow). Resting baseline with fixation point (red). Subjects were asked to press a left- or right-hand key depending on which of the 2 lower stimuli matched the upper stimulus more closely in meaning (blue, purple) or in size on the screen (cyan, yellow). A given concept triplet was presented in either the word or the picture format, and this was counterbalanced across subjects. Arrow in the top of the figure shows a timeline of 1 fMRI run, with each condition indicated in its respective color. The order of conditions was randomized for each run and subject. Translation: deur = door, hek = fence, raam = window.

Figure 1.

Stimuli and tasks in fMRI experiment. Associative-semantic task with words (blue) and with pictures (purple). Visuoperceptual task with words (cyan) or pictures (yellow). Resting baseline with fixation point (red). Subjects were asked to press a left- or right-hand key depending on which of the 2 lower stimuli matched the upper stimulus more closely in meaning (blue, purple) or in size on the screen (cyan, yellow). A given concept triplet was presented in either the word or the picture format, and this was counterbalanced across subjects. Arrow in the top of the figure shows a timeline of 1 fMRI run, with each condition indicated in its respective color. The order of conditions was randomized for each run and subject. Translation: deur = door, hek = fence, raam = window.

Prior to the fMRI session, visual acuity was tested in each participant. Subjects were asked to read aloud a text written in font 12 at 40 cm distance from their eyes. In case a correction to normal vision was necessary, subjects received MR compatible glasses with lenses matched to the subjects’ sight defect. Following this, subjects performed an offline practice session of fMRI task. In this session, we determined which size difference (9%, 6%, 3%, or 1%) for the visuoperceptual conditions was needed for each individual subject to obtain comparable accuracies as for the associative-semantic conditions.

Image Acquisition

Twenty-eight subjects were scanned on a 3T Philips Intera system equipped with an 8-channel receive-only head coil (Philips SENSitivity Encoding head coil). Twenty-eight subjects could not undergo the fMRI in the Intera system because their body in the scanner lumen obstructed the beam from the projector to the screen. These subjects were scanned on a 3T Philips Achieva system equipped with a 32-channel receive-only head coil (Philips SENSitivity Encoding head coil), which used a screen placed behind the individual's head for the projection. There were no statistically significant differences of sex (P = 0.79) (chi-square test), genetic groups (P = 0.17), age (P = 0.49), or MMSE (P = 0.92) (Kolmogorov–Smirnov comparison of 2 datasets) between subjects scanned on the Intera versus the Achieva system. Scanner type was included as a covariate of no interest for all analyses.

Sequence parameters were the same for both scanners. A high-resolution T1-weighted structural scan was obtained using a 3D turbo field echo sequence (coronal inversion recovery prepared 3D gradient-echo images, inversion time 900 ms, TR = 9.6 ms, TE = 4.6 ms, flip angle 8°, field of view = 250 × 250 mm, 182 slices; voxel size 0.98 × 0.98 × 1.2 mm3). Functional MRIs were acquired using T2* echo-planar images (50 transverse slices, voxel size 2.5 × 2.5 × 2.5 mm3; TR = 3000 ms, TE = 30 ms, flip angle 90°, field of view 200 × 200 mm).

Image Analysis

All analyses were performed using Statistical Parametric Mapping 8 (SPM8, http://www.fil.ion.ucl.ac.uk/spm/). Functional MR scans of each subject were realigned to correct for potential head motion. The structural MR image was coregistered to the average of the realigned fMRI images. The structural MR image was then normalized to the SPM8 T1 template in Montreal Neurological Institute space. The same normalization matrix was applied to the coregistered fMRI scans. The normalized fMRI images (voxel size 3 × 3 × 3 mm3) were smoothed using a 6 × 6 × 6 mm3 Gaussian kernel. A high-pass filter with a Full Width at Half Maximum of 270 s and a low-pass filter consisting of a canonical hemodynamic response function (HRF) were applied. The epoch-related response was modeled by a canonical HRF convolved with a boxcar.

Flutemetamol PET

Image Acquisition

As described before (Koole et al. 2009; Nelissen et al. 2009; Vandenberghe et al. 2010; Vandenberghe, Nelissen et al. 2013), images were acquired on a 16-slice Siemens Biograph PET/CT scanner (Siemens). The PET tracer was injected intravenously as a bolus (mean activity 151.2 MBq, SD 8.3, range 137.9–192.5 MBq) in an antecubital vein. Image acquisition started 90 min after tracer injection and lasted for 30 min. Prior to the PET scan, a low-dose computed tomography scan was performed for attenuation correction. Random and scatter corrections were also applied. Images were reconstructed using Ordered Subsets Expectation Maximization (4 iterations × 16 subsets).

Image Analysis

The PET data were reconstructed as 6 frames of 5 min and realigned to the first frame to correct for potential head motion. Subsequently, the 6 frames were summed to create 1 summed image. The individual's T1-weighted structural image was then coregistered to this PET summed image. This MR image was subsequently normalized to the SPM8 T1 template. The same normalization matrix was then applied to the individual's coregistered PET summed image. From the spatially normalized PET images (voxel size 2 × 2 × 2 mm3), standardized uptake value ratios (SUVR) were calculated in a voxelwise manner with cerebellar gray matter (GM) as reference region. The cerebellar GM reference region was defined as areas 91–108 of the Automated Anatomical Labelling atlas (AAL) (Tzourio-Mazoyer et al. 2002). The cerebellar reference region was resliced to each individual's normalized PET summed image. In order to exclude most of the white matter (WM) content, it was masked by the normalized and modulated subject-specific GM map, with the threshold for masking set at > 0.3.

Our primary PET outcome measure was the mean SUVR in a composite cortical volume of interest (VOI) (SUVRcomp). This composite VOI consisted of 5 bilateral cortical regions: frontal (AAL areas 3–10, 13–16, and 23–28), parietal (AAL 57–70), anterior cingulate (AAL 31–32), posterior cingulate (AAL 35–36), and lateral temporal (AAL 81–82 and 85–90). The composite cortical VOI was resliced to each individual's normalized PET summed image. In order to exclude most of the WM content, it was masked by the normalized and modulated subject-specific GM map, with the threshold for masking set at > 0.3.

While we used SUVRcomp as a continuous variable in our primary analysis, we also conducted a secondary analysis where amyloid load was treated as a binary variable and cases were classified as amyloid-positive versus amyloid-negative based on an SUVRcomp cutoff. Such a binary approach is closer to the way in which Sperling et al. (2011) conceptualized preclinical AD. The SUVRcomp cutoff for binary classification was derived from an independent dataset (Vandenberghe et al. 2010), which contained 27 scans from AD patients (mean age 70, SD 7.0) and 15 scans from healthy older controls (HC) (mean age 69, SD 7.6). 18F-flutemetamol scans from the Vandenberghe et al. (2010) study were re-analyzed using the MRI-informed PET analysis method described earlier. The cutoff was defined based on the statistical distance between the AD group and the HC as described in Vandenberghe et al. (2010). This gave an SUVRcomp cutoff equal to 1.38. Note that this cutoff is lower than the cutoff defined by Vandenberghe et al. (2010) or Thurfjell et al. (2014) for a purely PET-based approach, probably due to exclusion of more WM signal in the MRI-informed method in the amyloid-negative cases. Because of this difference, we also verified our binary case classification using the PET-based method and cutoff from Thurfjell et al. (2014) (cutoff equal to 1.57).

We verified our findings using partial volume corrected (PVC) data. PVC was based on the MRI using the modified Müller-Gärtner method (Müller-Gärtner et al. 1992; Adamczuk et al. 2013). This method makes use of probabilistic segmentation and determines tracer concentration per unit volume of GM. The normalized unmodulated GM and WM segmentations were used to estimate different tissue fractions per voxel. PVC was applied to the normalized PET summed images. The remaining procedures were identical to those outlined earlier.

Statistical Analysis

Analysis of Behavioral Data Obtained During fMRI

RTs and accuracies (% correct responses) were analyzed by means of a four-factor repeated-measures ANOVA, with stimulus modality (2 levels: pictures vs. words) and task (2 levels: associative-semantic vs. visuoperceptual) as within-subject factors and, as between-subject factors, BDNF (2 levels: codon 66 met carriers vs. non-carriers) and APOE (2 levels: ϵ4 carriers vs. non-carriers) genotype (Table 3). Pairwise comparisons were performed using Bonferroni post hoc tests.

Table 3

Performance during fMRI experiment

 RT (ms)
 
 Accuracy (% correct)
 
 
BDNF met+ met− met+ met− All groups met+ met− met+ met− All groups 
APOE ϵ4+ ϵ4+ ϵ4− ϵ4−  ϵ4+ ϵ4+ ϵ4− ϵ4−  
Sem W 2653 2852 2679 2725 2717 88.8 85.5 90.7 89.0 88.8 
(395) (326) (300) (449) (376) (7.4) (4.7) (4.2) (9.0) (7.0) 
Sem P 2885 2839 2771 2858 2840 80.2 83.5 82.6 81.3 81.7 
(530) (332) (293) (462) (417) (8.7) (7.9) (9.5) (9.0) (8.7) 
Visuo W 2343 2570 2474 2457 2451 81.2 75.7 75.1 80.7 78.5 
(404) (407) (381) (357) (382) (10.3) (15.8) (16.0) (15.6) (14.4) 
Visuo P 2633 2765 2534 2647 2636 76.3 71.7 81.2 85.0 79.3 
(611) (447) (426) (382) (468) (13.9) (17.8) (15.2) (14.5) (15.5) 
 RT (ms)
 
 Accuracy (% correct)
 
 
BDNF met+ met− met+ met− All groups met+ met− met+ met− All groups 
APOE ϵ4+ ϵ4+ ϵ4− ϵ4−  ϵ4+ ϵ4+ ϵ4− ϵ4−  
Sem W 2653 2852 2679 2725 2717 88.8 85.5 90.7 89.0 88.8 
(395) (326) (300) (449) (376) (7.4) (4.7) (4.2) (9.0) (7.0) 
Sem P 2885 2839 2771 2858 2840 80.2 83.5 82.6 81.3 81.7 
(530) (332) (293) (462) (417) (8.7) (7.9) (9.5) (9.0) (8.7) 
Visuo W 2343 2570 2474 2457 2451 81.2 75.7 75.1 80.7 78.5 
(404) (407) (381) (357) (382) (10.3) (15.8) (16.0) (15.6) (14.4) 
Visuo P 2633 2765 2534 2647 2636 76.3 71.7 81.2 85.0 79.3 
(611) (447) (426) (382) (468) (13.9) (17.8) (15.2) (14.5) (15.5) 

Note: Values represent means and standard deviations. Sem W, associative-semantic task with words; Sem P, associative-semantic task with pictures; Visuo W, visuoperceptual task with words; Visuo P, visuoperceptual task with pictures.

Whole-Brain Voxelwise Analysis

All voxelwise analyses were performed using SPM8. For each subject, parameter estimates were generated modeling each of the 5 conditions. We then created the following contrast images, averaging across runs: The first-level contrast images were then used for second-level whole-brain analysis.

  1. (Associative-semantic task with words + associative-semantic task with pictures) − (visuoperceptual task with words + visuoperceptual task with pictures)

  2. Associative-semantic task with words − visuoperceptual task with words

  3. Associative-semantic task with pictures − visuoperceptual task with pictures

  4. (Associative-semantic task with words − visuoperceptual task with words) − (associative-semantic task with pictures − visuoperceptual task with pictures) and inversely

  5. (Associative-semantic task with words + associative-semantic task with pictures) − baseline

  6. (Visuoperceptual task with words + visuoperceptual task with pictures) − baseline.

  7. Visuoperceptual task with words − baseline

  8. Visuoperceptual task with pictures − baseline

Our primary outcome analysis consisted of a whole-brain voxelwise linear regression analysis with SUVRcomp as independent variable, and fMRI response in Contrast 1 (main effect of task) as dependent variable. The statistical map was thresholded at a significance threshold of voxel-level Puncorrected of <0.001 combined with a cluster-level Pcorrected < 0.05, family-wise error (FWE) corrected for the whole-brain volume.

As a secondary outcome analysis, we examined for each of the 10 regions that constitute the composite cortical VOI, the correlation between regional SUVR and the main effect of task (Contrast 1) across the whole brain.

Furthermore, we examined whether any significant correlations with amyloid load were found for contrasts 2–8.

As a further secondary outcome analysis, we performed a whole-brain voxel-by-voxel linear regression between SUVR images and fMRI images representing associative-semantic minus visuoperceptual activity (Contrast 1) using Biological Parametric Mapping (BPM) (Casanova et al. 2007). The BPM is a toolbox for multimodal image analysis, which is based on a voxelwise use of the SPM's general linear model. This allows comparison of different imaging modalities within voxels.

As a further secondary analysis, we categorized the cases into amyloid-positive versus amyloid-negative and compared the main effect of task between the 2 groups (Contrast 1) using a two-sample t test.

We also tested whether there was any difference in fMRI response between the 4 genetic groups by means of a factorial ANOVA with BDNF (2 levels: met allele present vs. absent) and APOE (2 levels: ϵ4 allele present vs. absent) as between-subject factors and the main effect of task (Contrast 1) as dependent variable.

All whole-brain voxelwise analyses were thresholded at a significance threshold of voxel-level Puncorrected < 0.001 combined with a cluster-level Pcorrected < 0.05, FEW corrected for the whole brain volume. In the BPM analysis, we used threshold of voxel-level Puncorrected < 0.001 combined with cluster size of at least 10 voxels.

Relationship to Offline Measures of Linguistic Performance

When our primary analysis revealed clusters of significant correlation between SUVRcomp and fMRI response during associative-semantic versus visuoperceptual processing (Contrast 1), we examined in further detail whether mean fMRI response in these clusters correlated with a pre-specified set of offline measures of linguistic performance. Clusters of voxels exhibiting a significant correlation between SUVRcomp and fMRI response (Contrast 1) were extracted using the MarsBaR 0.43 toolbox (http://marsbar.sourceforge.net/). Given the proposed role of the posterior STS in lexical-semantic retrieval (Vandenbulcke et al. 2007), the principal measures that we selected a priori were 1) RT during the confrontation naming task, 2) RT during the lexical decision task, 3) The b parameter from the speeded word identification task. For each of these parameters, we performed a stepwise linear regression analysis with this parameter as dependent variable and the independent variables: fMRI response during the associative-semantic minus the visuoperceptual condition (Contrast 1), SUVRcomp, age, education level, BDNF genotype and APOE genotype. Probability to enter the model was set at P < 0.05 with probability to remove set to P > 0.1. This analysis was performed outside SPM in a VOI-based manner using STATISTICA 11 (http://www.statsoft.com/) as SPM software does not include stepwise linear regression.

In an additional, binary approach, we examined which of these neurolinguistic measures differed between the amyloid-positive and the amyloid-negative class (two-sample t test).

Results

Analysis of Behavioral Scores During fMRI

The main effect of task was significant: Subjects responded more accurately during the associative-semantic conditions than during the visuoperceptual conditions (F1,52 = 17.4, P = 0.0001), albeit with longer RTs (F1,52 = 24.9, P = 0.000007) (Table 3). The main effect of modality was also significant: Subjects responded more slowly (F1,52 = 21.3, P = 0.00003) and less accurately (F1,52 = 5.7, P = 0.02) for pictures than for words (Table 3). The interaction between task and modality was significant (F1,52 = 11, P = 0.002): The associative-semantic task was performed more accurately with words than with pictures (P = 0.00008), whereas there was no difference between words and pictures for the visuoperceptual task (P = 1). There was no main effect of BDNF and APOE genotypes on accuracy or RT (P > 0.2) (Table 3). The three-way interaction between task, modality and APOE genotype was significant for accuracies (F1,52 = 8.2, P = 0.006) (Table 3). According to a post hoc analysis, APOE ϵ4 non-carriers performed the associative-semantic task more accurately with words than with pictures (P = 0.0006), whereas there was no difference between the 2 input-modalities for the visuoperceptual task (P = 0.35). No such difference was seen in the APOE ϵ4 carriers (P = 0.23). We did not find any significant interactions for RT (P > 0.05).

Whole-Brain Voxelwise Analysis

Univariate Contrast Between fMRI Conditions

The contrast between the associative-semantic minus the visuoperceptual conditions (main effect of task, Contrast 1) revealed a distributed semantic network consistent with previous findings (Vandenberghe et al. 1996; Vandenbulcke et al. 2007; Nelissen et al. 2007) (Fig. 2A). The interaction between task and input modality (Contrast 4) revealed word-specific activation during the semantic compared with the visuoperceptual task in left STS, extending from posterior to more anterior portions of the STS (cluster peak coordinates −66, −36, 9, extent (ext) = 113 voxels, cluster-level Pcorrected = 0.0001) (Fig. 2B). Picture-specific semantic activation (inverse of Contrast 4) occurred bilaterally in ventral occipitotemporal cortex extending to superior occipital gyrus (right cluster peak coordinates 33, −45, −21, ext = 1756 voxels, cluster-level Pcorrected < 0.0001 and left cluster peak coordinates −39, −51, −15, ext = 1286 voxels, cluster-level Pcorrected < 0.0001) and in right inferior frontal gyrus (cluster peak coordinates 48, 12, 27, ext = 141 voxels, cluster-level Pcorrected < 0.0001) (Fig. 2C).

Figure 2.

(A) Main effect of associative-semantic task minus visuopercetual task (Contrast 1). (B) Interaction effect of task and modality: effect of semantic words (Contrast 4, i.e., [associative-semantic task with words − visuoperceptual task with words] – [associative-semantic task with pictures − visuoperceptual task with pictures]). (C) Interaction effect of task and modality: effect of semantic pictures (inverse of Contrast 4, i.e., [associative-semantic task with pictures − visuoperceptual task with pictures] – [associative-semantic task with words − visuoperceptual task with words]). Shown activations are significant at the threshold of voxel-level Puncorrected = 0.001 combined with cluster-level Pcorrected = 0.05. The color scales indicate the T-values for the contrasts. MNI coordinates are indicated in the left upper corner and orientation of the brain in the right upper corner.

Figure 2.

(A) Main effect of associative-semantic task minus visuopercetual task (Contrast 1). (B) Interaction effect of task and modality: effect of semantic words (Contrast 4, i.e., [associative-semantic task with words − visuoperceptual task with words] – [associative-semantic task with pictures − visuoperceptual task with pictures]). (C) Interaction effect of task and modality: effect of semantic pictures (inverse of Contrast 4, i.e., [associative-semantic task with pictures − visuoperceptual task with pictures] – [associative-semantic task with words − visuoperceptual task with words]). Shown activations are significant at the threshold of voxel-level Puncorrected = 0.001 combined with cluster-level Pcorrected = 0.05. The color scales indicate the T-values for the contrasts. MNI coordinates are indicated in the left upper corner and orientation of the brain in the right upper corner.

Linear Regression Between fMRI Response and Amyloid Load

In a whole-brain analysis, the posterior third of the left middle temporal gyrus (MTG) (Fig. 3A) exhibited a significant positive correlation between fMRI response during the associative-semantic versus the visuoperceptual task (Contrast 1) and SUVRcomp: Activity levels were higher with a higher amyloid load (−57, −45, 9, ext = 64 voxels, cluster-level Pcorrected = 0.006) (Fig. 3AE). No other regions showed a correlation, even when we lowered the significance threshold to cluster-level Pcorrected < 0.25. The MTG belonged to the amodal network, as evidenced by the conjunction analysis of Contrasts 2 and 3 (Fig. 4A–C).

Figure 3.

(A) Area in the left posterior MTG of significant correlation between SUVRcomp and fMRI response during associative-semantic minus visuoperceptual condition (Contrast 1) (cluster peak −57, −45, 9, ext = 64 voxels, cluster-level Pcorrected = 0.006). The color scale indicates the T-values. MNI coordinates are indicated in the left upper corner and orientation of the brain in the right upper corner. (B) Plot of correlation between SUVRcomp (X-axis) and mean fMRI contrast values in the left MTG VOI during associative-semantic minus visuoperceptual condition (Contrast 1) (Y-axis) (r = 0.63, P < 0.0001). (C) Bar plot depicting mean fMRI contrast values (Y-axis) in the left posterior MTG during each condition (X-axis). Error bars: standard error; Sem W: associative-semantic task with words (blue); Sem P: associative-semantic task with pictures (purple); Visuo W: visuoperceptual task with words (cyan); Visuo P: visuoperceptual task with pictures (yellow); Rest: resting baseline condition (red). (D) Correlation of SUVRcomp (X-axis) with mean fMRI contrast values during associative-semantic word processing (Contrast 2) in the left MTG VOI (Y-axis) (r = 0.59, P < 0.0001). (E) Correlation of SUVRcomp (X-axis) with mean fMRI contrast values during associative-semantic picture processing (Contrast 3) in the left MTG VOI (Y-axis) (r = 0.47, P = 0.00025). Black lines, linear regressions; red triangles, BDNF met+ve/APOE ϵ4+ve; blue squares, BDNF met-ve/APOE ϵ4+ve; red circles, BDNF met+ve/APOE ϵ4-ve; blue diamonds, BDNF met-ve/APOE ϵ4-ve.

Figure 3.

(A) Area in the left posterior MTG of significant correlation between SUVRcomp and fMRI response during associative-semantic minus visuoperceptual condition (Contrast 1) (cluster peak −57, −45, 9, ext = 64 voxels, cluster-level Pcorrected = 0.006). The color scale indicates the T-values. MNI coordinates are indicated in the left upper corner and orientation of the brain in the right upper corner. (B) Plot of correlation between SUVRcomp (X-axis) and mean fMRI contrast values in the left MTG VOI during associative-semantic minus visuoperceptual condition (Contrast 1) (Y-axis) (r = 0.63, P < 0.0001). (C) Bar plot depicting mean fMRI contrast values (Y-axis) in the left posterior MTG during each condition (X-axis). Error bars: standard error; Sem W: associative-semantic task with words (blue); Sem P: associative-semantic task with pictures (purple); Visuo W: visuoperceptual task with words (cyan); Visuo P: visuoperceptual task with pictures (yellow); Rest: resting baseline condition (red). (D) Correlation of SUVRcomp (X-axis) with mean fMRI contrast values during associative-semantic word processing (Contrast 2) in the left MTG VOI (Y-axis) (r = 0.59, P < 0.0001). (E) Correlation of SUVRcomp (X-axis) with mean fMRI contrast values during associative-semantic picture processing (Contrast 3) in the left MTG VOI (Y-axis) (r = 0.47, P = 0.00025). Black lines, linear regressions; red triangles, BDNF met+ve/APOE ϵ4+ve; blue squares, BDNF met-ve/APOE ϵ4+ve; red circles, BDNF met+ve/APOE ϵ4-ve; blue diamonds, BDNF met-ve/APOE ϵ4-ve.

Figure 4.

(A) Functional left MTG VOI belongs to the amodal associative-semantic network (conjunction of Contrasts 2 and 3) (MTG cluster pick −63, −45, 3, ext = 51 voxels, voxel-level Pcorrected = 0.000002). Overlap is shown in purple. (B) Left MTG VOI did not belong to the word-specific associative-semantic areas (Contrast 4) (voxel-level Pcorrected > 0.16) and (C) neither to the picture-specific semantic areas (inverse of Contrast 4) (voxel-level Pcorrected > 0.18). The left MTG VOI is shown in blue. The hot color scales indicate the T-values of associative-semantic network (A), word-specific associative-semantic regions (B), and picture-specific associative-semantic regions (C). Orientation of the brain is indicated in the right upper corner. All P-values were FWE corrected for multiple comparisons in a small volume.

Figure 4.

(A) Functional left MTG VOI belongs to the amodal associative-semantic network (conjunction of Contrasts 2 and 3) (MTG cluster pick −63, −45, 3, ext = 51 voxels, voxel-level Pcorrected = 0.000002). Overlap is shown in purple. (B) Left MTG VOI did not belong to the word-specific associative-semantic areas (Contrast 4) (voxel-level Pcorrected > 0.16) and (C) neither to the picture-specific semantic areas (inverse of Contrast 4) (voxel-level Pcorrected > 0.18). The left MTG VOI is shown in blue. The hot color scales indicate the T-values of associative-semantic network (A), word-specific associative-semantic regions (B), and picture-specific associative-semantic regions (C). Orientation of the brain is indicated in the right upper corner. All P-values were FWE corrected for multiple comparisons in a small volume.

When we restricted the contrast between the associative-semantic and the visuoperceptual task to the words (Contrast 2) and examined the correlation with amyloid load in the whole-brain analysis, SUVRcomp correlated positively with fMRI response during the associative-semantic minus visuoperceptual control condition for words in the same region (−60, −48, 9, ext = 49 voxels, cluster-level Pcorrected = 0.02). For pictures, there was no correlation (Contrast 3) (cluster-level Pcorrected > 0.6). No other regions showed a correlation, even when we lowered the significance threshold to cluster-level Pcorrected < 0.10. Neither were any correlations with SUVRcomp found for Contrasts 4–8.

Analysis of PVC data confirmed these results. PVC SUVRcomp positively correlated with fMRI response during the associative-semantic minus the visuoperceptual condition (Contrast 1) in the posterior third of the left MTG (−54, −39, 12, ext = 87 voxels, cluster-level Pcorrected = 0.001). Analysis restricted only to the word conditions showed that SUVRcomp correlated positively with fMRI response during the associative-semantic minus visuoperceptual control condition for words (Contrast 2) in the same region (−54, −36, 9, ext = 45 voxels, cluster-level Pcorrected = 0.028). No correlation was found between SUVRcomp and the fMRI response during the associative-semantic minus visuoperceptual condition when only pictures were used (Contrast 3) (cluster-level Pcorrected > 0.07).

Among the regions which constituted the composite cortical VOI, average SUVR in each of the regions besides the left and right anterior cingulate and left lateral frontal region contributed to the correlation of fMRI response during Contrast 1 and SUVRcomp (cluster-level Pcorrected< 0.038).

BPM indicated a significant correlation within-voxels between fMRI activity and SUVR in the posterior left MTG (cluster peak coordinates −60, −54, 12, ext = 18 voxels, voxel-level Puncorrected = 0.0001, Z = 3.65, r = 0.50).

Binary Classification

We evaluated whether similar results would be obtained had we used a binary approach: amyloid-positive versus amyloid-negative group (Fig. 5). Eight subjects (14%) were classified as positive (Fig. 5). fMRI performance parameters did not differ between the amyloid-positive and the amyloid-negative group (Table 4). In a whole-brain voxelwise analysis, the amyloid-positive group exhibited a higher fMRI response compared with the amyloid-negative group during the associative-semantic minus visuoperceptual conditions (Contrast 1) in the posterior third of the MTG (−54, −42, 9, ext = 55 voxels, cluster-level Pcorrected = 0.013) (Fig. 5B, red cluster). This was also true for the contrast between the associative-semantic minus visuoperceptual task presented as words (Contrast 2) (−57, −45, 6, ext = 59 voxels, cluster-level Pcorrected = 0.008) (Fig. 5B, green cluster). Overlap between clusters is shown in dark orange (Fig. 5B). We did not find any significant differences elsewhere and neither did we find any significant between-group differences for other contrasts. When we applied the Thurfjell et al. (2014) method and cutoff for binary classification, 4 cases were positive. The between-group differences remained essentially the same: The amyloid-positive group had higher fMRI response compared with the amyloid-negative group during the associative-semantic versus visuoperceptual condition (−60, −48, 9, ext = 54 voxels, cluster-level Pcorrected = 0.014).

Table 4

Differences between amyloid-positive and amyloid-negative subjects

 Age (year) Gender (m/f) Education (year) MMSE (/30) AVTL TL (/75) AVLT DR (/15) BNT (/60) AVF (# words) LVF (# words) RPM (/60) 
Amyloid+ 67.9 (5.2) 3/5 13.1 (3.5) 28.5 (0.9) 44.1 (6.8) 10.5 (1.8) 52.8 (4.1) 18.4 (4.2) 30.0 (13.8) 39.3 (12.1) 
Amyloid− 64.8 (5.5) 28/20 13.8 (2.7) 29.1 (0.9) 50.0 (9.7) 10.8 (2.8) 53.3 (4.9) 20.8 (5.1) 34.5 (9.7) 43.7 (7.7) 
P 0.14 0.27 0.55 0.10 0.10 0.81 0.78 0.21 0.26 0.17 
 BDNF APOE Conf naming Lexical decision Speeded id W  
 met+/met− ϵ4+/ϵ4− RT (ms) Accu (%) RT (ms) Accu (A’) a (ms) b (ms) c (ms)  
Amyloid+ 5/3 6/2 2203 (441) 92.3 (0.0) 1109 (322) 98.0 (0.0) 21.3 (9.9) 21.4 (10.9) 98.6 (1.3)  
Amyloid− 23/25 19/29 1978 (258) 91.9 (0.1) 1106 (231) 98.9 (0.0) 22.4 (13.4) 20.7 (10.8) 99.1 (1.5)  
P 0.45 0.06 0.047 0.84 0.97 0.11 0.83 0.86 0.42  
 Sem W Sem P Visuo W Visuo P   
 RT (ms) Accu (%) RT (ms) Accu (%) RT (ms) Accu (%) RT (ms) Accu (%)   
Amyloid+ 2885 (416) 89.4 (4.0) 2883 (564) 83.5 (9.3) 2571 (443) 82.3 (11.0) 2856 (686) 74.8 (15.7)   
Amyloid− 2689 (367) 88.7 (7.4) 2833 (395) 81.4 (8.7) 2431 (372) 77.9 (14.9) 2599 (420) 80.1 (15.5)   
P 0.17 0.79 0.76 0.53 0.34 0.43 0.15 0.38   
 Age (year) Gender (m/f) Education (year) MMSE (/30) AVTL TL (/75) AVLT DR (/15) BNT (/60) AVF (# words) LVF (# words) RPM (/60) 
Amyloid+ 67.9 (5.2) 3/5 13.1 (3.5) 28.5 (0.9) 44.1 (6.8) 10.5 (1.8) 52.8 (4.1) 18.4 (4.2) 30.0 (13.8) 39.3 (12.1) 
Amyloid− 64.8 (5.5) 28/20 13.8 (2.7) 29.1 (0.9) 50.0 (9.7) 10.8 (2.8) 53.3 (4.9) 20.8 (5.1) 34.5 (9.7) 43.7 (7.7) 
P 0.14 0.27 0.55 0.10 0.10 0.81 0.78 0.21 0.26 0.17 
 BDNF APOE Conf naming Lexical decision Speeded id W  
 met+/met− ϵ4+/ϵ4− RT (ms) Accu (%) RT (ms) Accu (A’) a (ms) b (ms) c (ms)  
Amyloid+ 5/3 6/2 2203 (441) 92.3 (0.0) 1109 (322) 98.0 (0.0) 21.3 (9.9) 21.4 (10.9) 98.6 (1.3)  
Amyloid− 23/25 19/29 1978 (258) 91.9 (0.1) 1106 (231) 98.9 (0.0) 22.4 (13.4) 20.7 (10.8) 99.1 (1.5)  
P 0.45 0.06 0.047 0.84 0.97 0.11 0.83 0.86 0.42  
 Sem W Sem P Visuo W Visuo P   
 RT (ms) Accu (%) RT (ms) Accu (%) RT (ms) Accu (%) RT (ms) Accu (%)   
Amyloid+ 2885 (416) 89.4 (4.0) 2883 (564) 83.5 (9.3) 2571 (443) 82.3 (11.0) 2856 (686) 74.8 (15.7)   
Amyloid− 2689 (367) 88.7 (7.4) 2833 (395) 81.4 (8.7) 2431 (372) 77.9 (14.9) 2599 (420) 80.1 (15.5)   
P 0.17 0.79 0.76 0.53 0.34 0.43 0.15 0.38   

Note: Values represent means and standard deviations. Gender, APOE, and BDNF genotypes are expressed in number of individuals. Abbreviations are explained in Tables 1, 2, and 3. P-values represent significance for two-sample t test or chi-square test (gender, APOE, BDNF). Bold values significant at P< 0.05.

Figure 5.

(A) Older healthy amyloid-positive subjects had higher amyloid deposition compared with amyloid-negative subjects in typical regions for increased amyloid load (precuneus, anterior and posterior cingulate, lateral prefrontal, lateral parietal, and lateral temporal, ext = 39779 voxels, cluster-level Pcorrected < 0.0001). The hot color scale indicates the T-values for the differences. (B) Older healthy amyloid-positive subjects had increased fMRI response compared with amyloid-negative subjects during the associative-semantic minus visuoperceptual conditions (Contrast 1) in the posterior third of the MTG (−54, −42, 9, ext = 55 voxels, cluster-level Pcorrected = 0.013; in red), and during the associative-semantic minus visuoperceptual task presented as words (Contrast 2) also in the MTG (−57, −45, 6, ext = 59 voxels, cluster-level Pcorrected = 0.008; in green). Overlap between clusters is shown in dark orange. Results are thresholded at voxel-level Puncorrected = 0.001 combined with cluster-level Pcorrected = 0.05. MNI coordinates are indicated in the left upper corner and orientation of the brain in the right upper corner.

Figure 5.

(A) Older healthy amyloid-positive subjects had higher amyloid deposition compared with amyloid-negative subjects in typical regions for increased amyloid load (precuneus, anterior and posterior cingulate, lateral prefrontal, lateral parietal, and lateral temporal, ext = 39779 voxels, cluster-level Pcorrected < 0.0001). The hot color scale indicates the T-values for the differences. (B) Older healthy amyloid-positive subjects had increased fMRI response compared with amyloid-negative subjects during the associative-semantic minus visuoperceptual conditions (Contrast 1) in the posterior third of the MTG (−54, −42, 9, ext = 55 voxels, cluster-level Pcorrected = 0.013; in red), and during the associative-semantic minus visuoperceptual task presented as words (Contrast 2) also in the MTG (−57, −45, 6, ext = 59 voxels, cluster-level Pcorrected = 0.008; in green). Overlap between clusters is shown in dark orange. Results are thresholded at voxel-level Puncorrected = 0.001 combined with cluster-level Pcorrected = 0.05. MNI coordinates are indicated in the left upper corner and orientation of the brain in the right upper corner.

Genotype Effect on fMRI Response and Relationship Between fMRI Response and SUVR

APOE and BDNF genotype did not affect the activity patterns during the associative-semantic versus visuoperceptual conditions (cluster-level Pcorrected > 0.8). Nor was there an effect of BDNF or APOE genotype on the correlation between mean fMRI response in the left posterior MTG (Contrast 1) and SUVRcomp (P > 0.1) (BDNF met carriers r = 0.64, P = 0.0002; BDNF non-carriers r = 0.61, P = 0.0005; APOE ϵ4 carriers r = 0.71, P = 0.00006; APOE ϵ4 non-carriers r = 0.40, P = 0.03) (Fig. 6).

Figure 6.

(A) The difference between correlations for BDNF met carriers (red full circles) and non-carriers (blue full circles) (P = 0.86). (B) The difference between correlations for APOE ϵ4 carriers (red empty circles) and non-carriers (blue empty circles) (P = 0.11). Y-axes: mean fMRI response during the associative-semantic minus the visuoperceptual condition (Contrast 1) in functional left MTG VOI. X-axes: SUVRcomp. Lines show linear regressions.

Figure 6.

(A) The difference between correlations for BDNF met carriers (red full circles) and non-carriers (blue full circles) (P = 0.86). (B) The difference between correlations for APOE ϵ4 carriers (red empty circles) and non-carriers (blue empty circles) (P = 0.11). Y-axes: mean fMRI response during the associative-semantic minus the visuoperceptual condition (Contrast 1) in functional left MTG VOI. X-axes: SUVRcomp. Lines show linear regressions.

Relationship with Offline Language Measures

According to a stepwise regression analysis, variance in RT during the confrontation naming task was partly explained by SUVRcomp (r = 0.27, P = 0.04), rather than fMRI response (Contrast 1; P = 0.62), age (P = 0.34), education (P = 0.57), BDNF (P = 0.21), or APOE status (P = 0.42) (Fig. 7).

Figure 7.

Results of a stepwise regression analysis. RT during the confrontation naming task (Y-axis) was best predicted by the SUVRcomp (r = 0.27, P = 0.04), and not by fMRI response from Contrast 1 (P = 0.62), age (P = 0.34), education (P = 0.57), BDNF (P = 0.21), or APOE (P = 0.42) status. X-axis represents values of the predictor variables. Gray dashed line = SUVRcomp cutoff of 1.38.

Figure 7.

Results of a stepwise regression analysis. RT during the confrontation naming task (Y-axis) was best predicted by the SUVRcomp (r = 0.27, P = 0.04), and not by fMRI response from Contrast 1 (P = 0.62), age (P = 0.34), education (P = 0.57), BDNF (P = 0.21), or APOE (P = 0.42) status. X-axis represents values of the predictor variables. Gray dashed line = SUVRcomp cutoff of 1.38.

Response latencies during confrontation naming were longer in the amyloid-positive compared with the amyloid-negative group (P = 0.047) (Table 4). There were no differences for any of the other experimental language tests and neither did the conventional neuropsychological test scores differ between the amyloid-positive and amyloid-negative class (Table 4).

Discussion

In cognitively intact older adults, a higher amyloid burden was associated with subclinical alterations of the network for language and associative-semantic processing. Activity in left posterior MTG was higher with a higher amyloid load (Fig. 3A,B). Higher amyloid levels were correlated with slower confrontation naming (Fig. 7). Our posterior temporal findings are based on a whole-brain search without prior restriction of the search volume. They were in agreement with our a priori hypothesis about posterior temporal cortex, although the exact location was in the amodal posterior MTG (Fig. 4A) adjacent to the word-specific posterior STS found before in MCI (Vandenbulcke et al. 2007) and AD (Nelissen et al. 2007) patients.

While we used the SUVRcomp as a continuous variable for the primary outcome analysis, we also conducted a secondary analysis where amyloid load was treated as a binary variable and cases were classified as amyloid-positive versus amyloid-negative based on an SUVRcomp cutoff. Such a binary approach is closer to the way in which Sperling et al. (2011) conceptualize preclinical AD. The findings based on a binary approach were entirely in line with the findings obtained with the linear regression approach (Fig. 5).

During the visuoperceptual control conditions, subjects engaged in an active comparison of the size-on-the-screen of a picture or a word. It is highly plausible that the meaning of this word or picture is automatically activated to some degree during the visuoperceptual condition too. A lower-level control condition with consonant letter strings or scrambled pictures (Ricci et al. 1999) would have been necessary had we wanted to isolate the regions activated during word and picture processing in the visuoperceptual condition. In any case, we did not find a correlation between amyloid load and the activity pattern during the visuoperceptual control conditions minus fixation baseline. This could suggest that the network underlying activation of word and picture meaning during the visuoperceptual condition is relatively intact in preclinical AD and that the principal changes are at the level of explicit associative-semantic processing.

Our findings are based on observational cross-sectional data, analyzed by means of correlational analysis and between-group comparisons. One therefore has to be careful in drawing conclusions about a causal link between the increase in amyloid burden, the increase in left posterior temporal activity, and the decrease in confrontation naming latencies. To adequately resolve this fundamental limitation, one would need to conduct interventional studies. This is difficult since there are no proven amyloid-lowering interventions available. Transcranial magnetic stimulation targeting the left posterior temporal cortex could be an option to examine how altering activity within a subject affects naming latencies and whether this depends on amyloid load.

We also observed right-hemispheric inferior frontal activation during the associative-semantic versus the visuoperceptual task (Fig. 2A), and this was particularly pronounced for the pictures (Fig. 2C). The right inferior frontal activation could be related to the older age range of our individuals, in line with the Hemispheric Asymmetry Reduction in Older Adults model (Cabeza 2002; Cabeza et al. 2005). However, one would need fMRI data over a wider age range including also young adults to confirm this. In any case, no increase in right-hemispheric activation was found as a consequence of increasing amyloid load in our dataset, contrary to our original hypothesis (Nelissen et al. 2007).

Previous studies have investigated changes in task-related fMRI in AD principally within the episodic memory domain. AD patients consistently show lower hippocampal activation in episodic memory encoding tasks in comparison with controls and/or MCI subjects (Small et al. 1999; Machulda et al. 2003; Sperling et al. 2003; Golby et al. 2005; Celone et al. 2006; Sperling 2007). Subjects with late MCI also have decreased hippocampal activity during episodic memory encoding (Machulda et al. 2003; Johnson, Schmitz, Moritz et al. 2006) whereas subjects with early MCI compared with controls show an increase in hippocampal activity during memory encoding (Dickerson et al. 2005; Johnson, Schmitz, Trivedi et al. 2006). Young healthy presenilin 1 mutation carriers destined for early-onset AD exhibit higher activity in the hippocampal formation in comparison with the non-carrier controls (Mondadori et al. 2006; Reiman et al. 2012). Subjects with a higher risk for AD due to family history and APOE ϵ4 carrier status also have higher hippocampal activation during encoding compared with non-carrier controls (Fleisher et al. 2005). These studies led to a model where the direction of functional changes in medial temporal cortex is stage-dependent: In the preclinical AD stage and the early MCI stage, activity during memory encoding in the hippocampus is increased compared with controls, whereas in the late MCI and the clinically probable AD stage, activity is decreased compared with controls. Our findings indicate that a similar sequence may occur in the language domain in left posterior temporal cortex. The current data show increased activity during associative-semantic processing in preclinical AD according to the National Institute on Aging and Alzheimer's Association criteria (Sperling et al. 2011). In a previous study in amnestic MCI, activity in left posterior STS was decreased and correlated with the speed of written word identification (Vandenbulcke et al. 2007). In clinically probable AD, the same region also showed lower activity levels (Nelissen et al. 2007). Our study is the first to report an increase in left posterior temporal cortex in a stage that has been referred to as preclinical AD (Fig. 3), similarly to what has been described in the hippocampal formation for episodic memory (Sperling 2007). Taken together, this series of studies may suggest a similar sequence of increased activity in posterior temporal cortex followed by activity decreases as Alzheimer's disease progresses to the clinical stages.

Initial functional imaging studies of language and semantic memory in clinically probable AD have emphasized prefrontal increases which correlated positively with task performance (Becker et al. 1996; Saykin et al. 1999; Grady et al. 2003). These AD-related prefrontal increases generalized across episodic and semantic memory tasks (Grady et al. 2003) and presumably reflect general adaptive strategic processes (Becker et al. 1996; Grady et al. 2003). A series of studies revealed functional changes also in temporal cortex, most notably left inferior temporal cortex (Grossman, Koenig, Glosser et al. 2003; Grossman, Koenig, DeVita et al. 2003), left and right MTG (Grossman, Koenig, Glosser et al. 2003; Grossman, Koenig, DeVita et al. 2003; Seidenberg et al. 2009), and left posterior STS (Nelissen et al. 2007; Vandenbulcke et al. 2007). Functional differentiation exists within left temporal cortex even within nearby areas. For instance, the posterior third of the left STS is activated during semantic processing specifically for words (Vandenberghe et al. 1996; Vandenbulcke et al. 2007). It has been principally implicated in lexical-semantic (Vandenbulcke et al. 2007) or lexical-phonological retrieval (Binder et al. 2000; Price and Mechelli 2005). In contrast, an adjacent more inferior region, the posterior third of the left MTG, is activated during semantic processing for both words and pictures (Fig. 4A,B,C, Fig. 3D,E). The left posterior MTG is 1 of the most consistent hubs in the associative-semantic network (Buckner et al. 2005; Vandenberghe, Wang et al. 2013). It has been implicated in amodal semantic processing (Vandenberghe et al. 1996; Vandenbulcke et al. 2007) as well as in semantic control (Whitney et al. 2011, 2012). In the current study, the correlation principally occurred within the amodal posterior MTG region rather than the word-specific STS (Fig. 3A and Fig. 4A). Our findings can be readily integrated in current hypotheses that attribute to posterior MTG a role in cognitive control: Regions involved in semantic control may be the prime candidates for compensatory processes in response to increases in amyloid load. Increased amyloid burden in cortical areas may hamper normal neuronal functioning due to its neurotoxic effects. In order to cope with such functional changes at the neuronal level, demands for cognitive control may increase and this may account for the increase in MTG activity levels. Cognitively normal older persons may have increased Aβ levels yet intact neuropsychological performance (Driscoll et al. 2006; Aizenstein et al. 2008), possibly due to ongoing compensatory processes. As the disease advances, mechanisms responsible for maintaining constant level of increased activation may become exhausted, resulting in the first cognitive symptoms. Thus, early word finding difficulties in the course of AD might arise due to failure of semantic control processes, followed by a gradual activity decrease in other language areas, for example, areas directly involved in word processing like posterior STS.

We did not find any effect of genetic polymorphisms of APOE or BDNF on the language network in our cohort. In AD, APOE ϵ4 status has been associated more closely with episodic memory deficits than with language symptoms (Lehtovirta et al. 1996; Rasmusson et al. 1996; Mendez 2012; Mez et al. 2013). HC with a family history of Alzheimer's disease and that at least 1 APOE ϵ4 allele have increased fMRI activation during a semantic memory task (famous vs. unfamiliar names) in bilateral temporoparietal areas, posterior cingulate and precuneus, posterior middle and superior temporal regions, and left hippocampal complex (Woodard et al. 2009). It is not that we did not find any effect of APOE. As reported before, APOE genotype exerted an effect on the amyloid burden in our cohort: A higher amyloid load in APOE ϵ4 carriers was present in posterior cingulate; a region outside the network that our paradigm is activating (Adamczuk et al. 2013).

As of yet, the relationship between BDNF and language has been principally studied during development and early adulthood (Freundlieb et al. 2012; Simmons et al. 2010; Li and Bartlett 2012) and in schizophrenia (Kebir et al. 2009). Contrary to our hypothesis, the regression between fMRI response and amyloid load was not influenced by BDNF status. In the same cohort, we previously reported that BDNF exerted a direct effect on amyloid load in interaction with APOE: BDNF met carriers had increased levels of Aβ in typical regions of predilection in comparison with the BDNF met non-carriers with APOE ϵ4 (Adamczuk et al. 2013). In summary, contrary to our prediction, the effect of BDNF in our cohort is situated at the level of amyloid aggregation rather than at the level of fMRI response.

Our findings highlight the critical role of left posterior temporal cortex in AD-related processes. Changes in left posterior STS lead to lexical-semantic retrieval deficits, which may explain the word finding difficulties in clinical AD (Nelissen et al. 2007) and the subclinical slowing in word identification speed in MCI (Vandenbulcke et al. 2007). The changes we observed in this study in the posterior MTG may reflect higher demands for semantic control in those subjects who are cognitively intact despite a high amyloid burden.

To conclude, our cross-sectional data indicate that a higher amyloid load in cognitively intact individuals has functional consequences for the network mediating language and associative-semantic processing. The converging evidence obtained in cognitively intact older adults, amnestic MCI and AD may suggest a sequence of events similar to that proposed for the hippocampal formation in episodic memory. The initial compensatory role of increased neuronal activity may precede later deterioration.

Funding

This work was supported by the Foundation for Alzheimer Research SAO-FRMA (09013, 11020, 13007); Research Foundation Flanders (G.0660.09); KU Leuven (OT/08/056, OT/12/097); IWT VIND; IWT TGO BioAdapt AD; Belspo IAP (P7/11); Research Foundation Flanders senior clinical investigator grant to R.V. and K.V.L.; and Research Foundation Flanders doctoral fellowship to K.A. 18F-flutemetamol was provided by GE Healthcare free of charge for this academic investigator-driven trial.

Notes

We thank the staff of Nuclear Medicine, Radiology, and the Memory Clinic at the University Hospitals Leuven, and the staff of the Genetic Service Facility at the University of Antwerp—VIB Department of Molecular Genetics. Conflict of Interest: R.V. has been the PI of the phase 1 and the phase 2 18F-flutemetamol studies and his institution had a consultancy agreement with GEHC.

References

Adamczuk
K
De Weer
AS
Nelissen
N
Chen
K
Sleegers
K
Bettens
K
Van Broeckhoven
C
Vandenbulcke
M
Thiyyagura
P
Dupont
P
et al
2013
.
Polymorphism of brain derived neurotrophic factor influences β amyloid load in cognitively intact apolipoprotein E ϵ4 carriers
.
Neuroimage Clin
 .
2
:
512
520
.
Aizenstein
HJ
Nebes
RD
Saxton
JA
Price
JC
Mathis
CA
Tsopelas
ND
Ziolko
SK
James
JA
Snitz
BE
Houck
PR
et al
2008
.
Frequent amyloid deposition without significant cognitive impairment among the elderly
.
Arch Neurol
 .
65
:
1509
1517
.
Apostolova
LG
Lu
P
Rogers
S
Dutton
RA
Hayashi
KM
Toga
AW
Cummings
JL
Thompson
PM
.
2008
.
3D mapping of language networks in clinical and pre-clinical Alzheimer's disease
.
Brain Lang
 .
104
:
33
41
.
Arendt
T
Schindler
C
Brückner
MK
Eschrich
K
Bigl
V
Zedlick
D
Marcova
L
.
1997
.
Plastic neuronal remodeling is impaired in patients with Alzheimer's disease carrying apolipoprotein epsilon 4 allele
.
J Neurosci
 .
17
:
516
529
.
Bastiaanse
R
Bosje
M
Visch-Brink
E
.
1995
.
Psycholinguïstische testbatterij voor de taalverwerking van Afasiepatiënten (PALPA)
 .
Hove
(
UK
):
Lawrence Erlbaum Associates
.
Bayles
KA
Tomoeda
CK
.
1983
.
Confrontation naming impairment in dementia
.
Brain Lang
 .
19
:
98
114
.
Becker
JT
Mintun
MA
Aleva
K
Wiseman
MB
Nichols
T
DeKosky
ST
.
1996
.
Compensatory reallocation of brain resources supporting verbal episodic memory in Alzheimer's disease
.
Neurology
 .
46
:
692
700
.
Binder
JR
Frost
JA
Hammeke
TA
Bellgowan
PS
Springer
JA
Kaufman
JN
Possing
ET
.
2000
.
Human temporal lobe activation by speech and nonspeech sounds
.
Cereb Cortex
 .
10
:
512
528
.
Buckner
RL
Snyder
AZ
Shannon
BJ
LaRossa
G
Sachs
R
Fotenos
AF
Sheline
YI
Klunk
WE
Mathis
CA
Morris
JC
et al
2005
.
Molecular, structural, and functional characterization of Alzheimer's disease: evidence for a relationship between default activity, amyloid, and memory
.
J Neurosci
 .
25
:
7709
7717
.
Cabeza
R
.
2002
.
Hemispheric asymmetry reduction in older adults: the HAROLD model
.
Psychol Aging
 .
17
:
85
100
.
Cabeza
R
Nyberg
L
Park
DC
.
2005
.
Cognitive Neuroscience of Aging
 .
New York
(
NY
):
Oxford University Press
.
Casanova
R
Srikanth
R
Baer
A
Laurienti
PJ
Burdette
JH
Hayasaka
S
Flowers
L
Wood
F
Maldjian
JA
.
2007
.
Biological parametric mapping: a statistical toolbox for multimodality brain image analysis
.
Neuroimage
 .
34
:
137
143
.
Celone
KA
Calhoun
VD
Dickerson
BC
Atri
A
Chua
EF
Miller
SL
DePeau
K
Rentz
DM
Selkoe
DJ
Blacker
D
et al
2006
.
Alterations in memory networks in mild cognitive impairment and Alzheimer's disease: an independent component analysis
.
J Neurosci
 .
26
:
10222
10231
.
Chertkow
H
Bub
D
.
1990
.
Semantic memory loss in dementia of Alzheimer's type. What do various measures measure?
Brain
 .
113
:
397
417
.
Chételat
G
La Joie
R
Villain
N
Perrotin
A
de La Sayette
V
Eustache
F
Vandenberghe
R
.
2013
.
Amyloid imaging in cognitively normal individuals, at-risk populations and preclinical Alzheimer's disease
.
Neuroimage Clin
 .
2
:
356
365
.
Chételat
G
Villemagne
VL
Villain
N
Jones
G
Ellis
KA
Ames
D
Martins
RN
Masters
CL
Rowe
CC
.
2012
.
Accelerated cortical atrophy in cognitively normal elderly with high β-amyloid deposition
.
Neurology
 .
78
:
477
484
.
Clark
CM
Pontecorvo
MJ
Beach
TG
Bedell
BJ
Coleman
RE
Doraiswamy
PM
Fleisher
AS
Reiman
EM
Sabbagh
MN
Sadowsky
CH
et al
2012
.
Cerebral PET with florobetapir compared with neuropathology at autopsy for detection of neuritic amyloid-β plaques: a prospective cohort study
.
Lancet Neurol
 .
11
:
669
678
.
Clark
CM
Schneider
JA
Bedell
BJ
Beach
TG
Bilker
WB
Mintun
MA
Pontecorvo
MJ
Hefti
F
Carpenter
AP
Flitter
ML
et al
2011
.
Use of florobetapir-PET for imaging beta-amyloid pathology
.
JAMA
 .
305
:
275
283
.
Clark
LJ
Gatz
M
Zheng
L
Chen
YL
McCleary
C
Mack
WJ
.
2009
.
Longitudinal verbal fluency in normal aging, preclinical, and prevalent Alzheimer's disease
.
Am J Alzheimers Dis Other Demen
 .
24
:
461
468
.
Crystal
H
Dickson
D
Fuld
P
Masur
D
Scott
R
Mehler
M
Masdeu
J
Kawas
C
Aronson
M
Wolfson
L
.
1988
.
Clinico-pathologic studies in dementia: nondemented subjects with pathologically confirmed Alzheimer's disease
.
Neurology
 .
38
:
1682
1687
.
Davis
DG
Schmitt
FA
Wekstein
DR
Markesbery
WR
.
1999
.
Alzheimer neuropathologic alterations in aged cognitively normal subjects
.
J Neuropathol Exp Neurol
 .
58
:
376
388
.
Dickerson
BC
Salat
DH
Greve
DN
Chua
EF
Rand-Giovannetti
E
Rentz
DM
Bertram
L
Mullin
K
Tanzi
RE
Blacker
D
et al
2005
.
Increased hippocampal activation in mild cognitive impairment compared to normal aging and AD
.
Neurology
 .
65
:
404
411
.
Doraiswamy
PM
Sperling
RA
Coleman
RE
Johnson
KA
Reiman
EM
Davis
MD
Grundman
M
Sabbagh
MN
Sadowsky
CH
Fleisher
AS
et al
2012
.
Amyloid-β assessed by florobetapir F 18 PET and 18-month cognitive decline: a multicenter study
.
Neurology
 .
79
:
1636
1644
.
Driscoll
I
Resnick
SM
Troncoso
JC
An
Y
O'Brien
R
Zonderman
AB
.
2006
.
Impact of Alzheimer's pathology on cognitive trajectories in nondemented elderly
.
Ann Neurol
 .
60
:
688
695
.
Erickson
KI
Voss
MW
Prakash
RS
Basak
C
Szabo
A
Chaddock
L
Kim
JS
Heo
S
Alves
H
White
SM
et al
2011
.
Exercise training increases size of hippocampus and improves memory
.
Proc Natl Acad Sci USA
 .
108
:
3017
3022
.
Fleisher
AS
Houston
WS
Eyler
LT
Frye
S
Jenkins
C
Thal
LJ
Bondi
MW
.
2005
.
Identification of Alzheimer disease risk by functional magnetic resonance imaging
.
Arch Neurol
 .
62
:
1881
1888
.
Freundlieb
N
Philipp
S
Schneider
SA
Brüggemann
N
Klein
C
Gerloff
C
Hummel
FC
.
2012
.
No association of the BDNF val66met polymorphism with implicit associative vocabulary and motor learning
.
PLoS One
 .
7
:
e48327
.
Golby
A
Silverberg
G
Race
E
Gabrieli
S
O'Shea
J
Knierim
K
Stebbins
G
Gabrieli
J
.
2005
.
Memory encoding in Alzheimer's disease: an fMRI study of explicit and implicit memory
.
Brain
 .
128
:
773
787
.
Gorski
JA
Zeiler
SR
Tamowski
S
Jones
KR
.
2003
.
Brain-derived neurotrophic factor is required for the maintenance of cortical dendrites
.
J Neurosci
 .
23
:
6856
6865
.
Grady
CL
Furey
ML
Pietrini
P
Horwitz
B
Rapoport
SI
.
2001
.
Altered brain functional connectivity and impaired short-term memory in Alzheimer's disease
.
Brain
 .
124
:
739
756
.
Grady
CL
McIntosh
AR
Beig
S
Keightley
ML
Burian
H
Black
SE
.
2003
.
Evidence from functional neuroimaging of a compensatory prefrontal network in Alzheimer's disease
.
J Neurosci
 .
23
:
986
993
.
Grossman
M
Koenig
P
DeVita
C
Glosser
G
Moore
P
Gee
J
Detre
J
Alsop
D
.
2003
.
Neural basis for verb processing in Alzheimer's disease: an fMRI study
.
Neuropsychology
 .
17
:
658
674
.
Grossman
M
Koenig
P
Glosser
G
DeVita
C
Moore
P
Rhee
J
Detre
J
Alsop
D
Gee
J
.
2003
.
Neural basis for semantic memory difficulty in Alzheimer's disease: an fMRI study
.
Brain
 .
126
:
292
311
.
Hatashita
S
Yamasaki
H
Suzuki
Y
Tanaka
K
Wakebe
D
Hayakawa
H
.
2014
.
[18F]Flutemetamol amyloid-beta PET imaging compared with [11C]PIB across the spectrum of Alzheimer's disease
.
Eur J Nucl Med Mol Imaging
 .
41
:
290
300
.
Herholz
K
Ebmeier
K
.
2011
.
Clinical amyloid imaging in Alzheimer's disease
.
Lancet Neurol
 .
10
:
667
670
.
Howard
D
Patterson
KE
.
1992
.
The Pyramids and Palm Trees Test: A Test of Semantic Access from Words and Pictures
 .
Bury St. Edmunds
(
UK
):
Thames Valley Test Company
.
Huff
FJ
Corkin
S
Growdon
JH
.
1986
.
Semantic impairment and anomia in Alzheimer's disease
.
Brain Lang
 .
28
:
235
249
.
Hyman
BT
Kromer
LJ
Van Hoesen
GW
.
1987
.
Reinnervation of the hippocampal perforant pathway zone in Alzheimer's disease
.
Ann Neurol
 .
21
:
259
267
.
Johnson
SC
Schmitz
TW
Moritz
CH
Meyerand
ME
Rowley
HA
Alexander
AL
Hansen
KW
Gleason
CE
Carlsson
CM
Ries
ML
et al
2006
.
Activation of brain regions vulnerable to Alzheimer's disease: the effect of mild cognitive impairment
.
Neurobiol Aging
 .
27
:
1604
1612
.
Johnson
SC
Schmitz
TW
Trivedi
MA
Ries
ML
Torgerson
BM
Carlsson
CM
Asthana
S
Hermann
BP
Sager
MA
.
2006
.
The influence of Alzheimer disease family history and apolipoprotein E epsilon4 on mesial temporal lobe activation
.
J Neurosci
 .
26
:
6069
6076
.
Katzman
R
Terry
R
DeTeresa
R
Brown
T
Davies
P
Fuld
P
Renbing
X
Peck
A
.
1988
.
Clinical, pathological, and neurochemical changes in dementia: a subgroup with preserved mental status and numerous neocortical plaques
.
Ann Neurol
 .
23
:
138
144
.
Kebir
O
Mouaffak
F
Chayet
M
Leroy
S
Tordjman
S
Amado
I
Krebs
MO
.
2009
.
Semantic but not phonological verbal fluency associated with BDNF Val66Met polymorphism in schizophrenia
.
Am J Med Genet B Neuropsychiatr Genet
 .
150B
:
441
442
.
Koole
M
Lewis
DM
Buckley
C
Nelissen
N
Vandenbulcke
M
Brooks
DJ
Vandenberghe
R
Van Laere
K
.
2009
.
Whole-body biodistribution and radiation dosimetry of 18F-GE067: a radioligand for in vivo brain amyloid imaging
.
J Nucl Med
 .
50
:
818
822
.
Laiacona
M
Capitani
E
.
2001
.
A case of prevailing deficit of nonliving categories or a case of prevailing sparing of living categories?
Cogn Neuropsychol
 .
18
:
39
70
.
Lehtovirta
M
Soininen
H
Helisalmi
S
Mannermaa
A
Helkala
EL
Hartikainen
P
Hänninen
T
Ryynänen
M
Riekkinen
PJ
.
1996
.
Clinical and neuropsychological characteristics in familial and sporadic Alzheimer's disease: relation to apolipoprotein E polymorphism
.
Neurology
 .
46
:
413
419
.
Li
N
Bartlett
CW
.
2012
.
Defining the genetic architecture of human developmental language impairment
.
Life Sci
 .
90
:
469
475
.
Li
Y
Luikart
BW
Birnbaum
S
Chen
J
Kwon
CH
Kernie
SG
Bassel-Duby
R
Parada
LF
.
2008
.
TrkB regulates hippocampal neurogenesis and governs sensitivity to antidepressive treatment
.
Neuron
 .
59
:
399
412
.
Machulda
MM
Ward
HA
Borowski
B
Gunter
JL
Cha
RH
O'Brien
PC
Petersen
RC
Boeve
BF
Knopman
D
Tang-Wai
DF
et al
2003
.
Comparison of memory fMRI response among normal, MCI, and Alzheimer's patients
.
Neurology
 .
61
:
500
506
.
Mendez
MF
.
2012
.
Early-onset Alzheimer's disease: nonamnestic subtypes and type 2 AD
.
Arch Med Res
 .
43
:
677
685
.
Mesulam
MM
.
1999
.
Neuroplasticity failure in Alzheimer's disease: bridging the gap between plaques and tangles
.
Neuron
 .
24
:
521
529
.
Mez
J
Cosentino
S
Brickman
AM
Huey
ED
Mayeux
R
.
2013
.
Different demographic, genetic, and longitudinal traits in language versus memory Alzheimer's subgroups
.
J Alzheimers Dis
 .
37
:
137
146
.
Mondadori
CR
Buchmann
A
Mustovic
H
Schmidt
CF
Boesiger
P
Nitsch
RM
Hock
C
Streffer
J
Henke
K
.
2006
.
Enhanced brain activity may precede the diagnosis of Alzheimer's disease by 30 years
.
Brain
 .
129
:
2908
2922
.
Morris
JC
Roe
CM
Grant
EA
Head
D
Storandt
M
Goate
AM
Fagan
AM
Holtzman
DM
Mintun
MA
.
2009
.
Pittsburgh compound B imaging and prediction of progression from cognitive normality to symptomatic Alzheimer disease
.
Arch Neurol
 .
66
:
1469
1475
.
Müller-Gärtner
HW
Links
JM
Prince
JL
Bryan
RN
McVeigh
E
Leal
JP
Davatzikos
C
Frost
JJ
.
1992
.
Measurement of radiotracer concentration in brain gray matter using positron emission tomography: MRI-based correction for partial volume effects
.
J Cereb Blood Flow Metab
 .
12
:
571
583
.
Nathan
BP
Bellosta
S
Sanan
DA
Weisgraber
KH
Mahley
RW
Pitas
RE
.
1994
.
Differential effects of apolipoproteins E3 and E4 on neuronal growth in vitro
.
Science
 .
264
:
850
852
.
Nelissen
N
Dupont
P
Vandenbulcke
M
Tousseyn
T
Peeters
R
Vandenberghe
R
.
2011
.
Right hemisphere recruitment during language processing in frontotemporal lobar degeneration and Alzheimer's disease
.
J Mol Neurosci
 .
45
:
637
647
.
Nelissen
N
Vandenbulcke
M
Fannes
K
Verbruggen
A
Peeters
R
Dupont
P
Van Laere
K
Bormans
G
Vandenberghe
R
.
2007
.
Abeta amyloid deposition in the language system and how the brain responds
.
Brain
 .
130
:
2055
2069
.
Nelissen
N
Van Laere
K
Thurfjell
L
Owenius
R
Vandenbulcke
M
Koole
M
Bormans
G
Brooks
DJ
Vandenberghe
R
.
2009
.
Phase 1 study of the Pittsburgh compound B derivative 18F-flutemetamol in healthy volunteers and patients with probable Alzheimer disease
.
J Nucl Med
 .
50
:
1251
1259
.
Okuno
H
Tokuyama
W
Li
YX
Hashimoto
T
Miyashita
Y
.
1999
.
Quantitative evaluation of neurotrophin and trk mRNA expression in visual and limbic areas along the occipito-temporo-hippocampal pathway in adult macaque monkeys
.
J Comp Neurol
 .
408
:
378
398
.
Osada
T
Adachi
Y
Kimura
HM
Miyashita
Y
.
2008
.
Towards understanding of the cortical network underlying associative memory
.
Philos Trans R Soc Lond B Biol Sci
 .
363
:
2187
2199
.
Pallier
C
.
2002
.
Computing discriminability and bias with the R software
.
URL
Available from: URL .
Price
CJ
Mechelli
A
.
2005
.
Reading and reading disturbance
.
Curr Opin Neurobiol
 .
15
:
231
238
.
Price
JL
Morris
JC
.
1999
.
Tangles and plaques in nondemented aging and “preclinical” Alzheimer's disease
.
Ann Neurol
 .
45
:
358
368
.
Rasmusson
DX
Dal Forno
G
Brandt
J
Warren
AC
Troncoso
J
Lyketsos
C
.
1996
.
Apo-E genotype and verbal deficits in Alzheimer's disease
.
J Neuropsychiatry Clin Neurosci
 .
8
:
335
337
.
Reiman
EM
Quiroz
YT
Fleisher
AS
Chen
K
Velez-Pardo
C
Jimenez-Del-Rio
M
Fagan
AM
Shah
AR
Alvarez
S
Arbelaez
A
et al
2012
.
Brain imaging and fluid biomarker analysis in young adults at genetic risk for autosomal dominant Alzheimer's disease in the presenilin 1 E280A kindred: a case-control study
.
Lancet Neurol
 .
11
:
1048
1056
.
Resnick
SM
Sojkova
J
Zhou
Y
An
Y
Ye
W
Holt
DP
Dannals
RF
Mathis
CA
Klunk
WE
Ferrucci
L
et al
2010
.
Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [11C]PiB
.
Neurology
 .
74
:
807
815
.
Ricci
PT
Zelkowicz
BJ
Nebes
RD
Meltzer
CC
Mintun
MA
Becker
JT
.
1999
.
Functional neuroanatomy of semantic memory: recognition of semantic associations
.
Neuroimage
 .
9
:
88
96
.
Saykin
AJ
Flashman
LA
Frutiger
SA
Johnson
SC
Mamourian
AC
Moritz
CH
O'Jile
JR
Riordan
HJ
Santulli
RB
Smith
CA
et al
1999
.
Neuroanatomic substrates of semantic memory impairment in Alzheimer's disease: patterns of functional MRI activation
.
J Int Neuropsychol Soc
 .
5
:
377
392
.
Seidenberg
M
Guidotti
L
Nielson
KA
Woodard
JL
Durgerian
S
Antuono
P
Zhang
Q
Rao
SM
.
2009
.
Semantic memory activation in individuals at risk for developing Alzheimer disease
.
Neurology
 .
73
:
612
620
.
Simmons
TR
Flax
JF
Azaro
MA
Hayter
JE
Justice
LM
Petrill
SA
Bassett
AS
Tallal
P
Brzustowicz
LM
Bartlett
CW
.
2010
.
Increasing genotype-phenotype model determinism: application to bivariate reading/language traits and epistatic interactions in language-impaired families
.
Hum Hered
 .
70
:
232
244
.
Small
SA
Perera
GM
DeLaPaz
R
Mayeux
R
Stern
Y
.
1999
.
Differential regional dysfunction of the hippocampal formation among elderly with memory decline and Alzheimer's disease
.
Ann Neurol
 .
45
:
466
472
.
Snodgrass
JG
Vanderwart
M
.
1980
.
A standardized set of 260 pictures: norms for name agreement, image agreement, familiarity, and visual complexity
.
J Exp Psychol Hum Learn
 .
6
:
174
215
.
Sperling
R
.
2007
.
Functional MRI studies of associative encoding in normal aging, mild cognitive impairment, and Alzheimer's disease
.
Ann N Y Acad Sci
 .
1097
:
146
155
.
Sperling
RA
Aisen
PS
Beckett
LA
Bennett
DA
Craft
S
Fagan
AM
Iwatsubo
T
Jack
CR
Jr
Kaye
J
Montine
TJ
et al
2011
.
Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease
.
Alzheimers Dement
 .
7
:
280
292
.
Sperling
RA
Bates
JF
Chua
EF
Cocchiarella
AJ
Rentz
DM
Rosen
BR
Schacter
DL
Albert
MS
.
2003
.
fMRI studies of associative encoding in young and elderly controls and mild Alzheimer's disease
.
J Neurol Neurosurg Psychiatry
 .
74
:
44
50
.
Sugarman
MA
Woodard
JL
Nielson
KA
Seidenberg
M
Smith
JC
Durgerian
S
Rao
SM
.
2012
.
Functional magnetic resonance imaging of semantic memory as a presymptomatic biomarker of Alzheimer's disease risk
.
Biochim Biophys Acta
 .
1822
:
442
456
.
Thurfjell
L
Lilja
J
Lundqvist
R
Buckley
C
Smith
A
Vandenberghe
R
Sherwin
P
.
2014
.
Automated quantification of 18F-flutemetamol PET activity for categorizing scans as negative or positive for brain amyloid: concordance with visual image reads
.
J Nucl Med
 .
55
:
1623
1628
.
Troncoso
JC
Martin
LJ
Dal Forno
G
Kawas
CH
.
1996
.
Neuropathology in controls and demented subjects from the Baltimore Longitudinal Study of Aging
.
Neurobiol Aging
 .
17
:
365
371
.
Tzourio-Mazoyer
N
Landeau
B
Papathanassiou
D
Crivello
F
Etard
O
Delcroix
N
Mazoyer
B
Joliot
M
.
2002
.
Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain
.
Neuroimage
 .
15
:
273
289
.
Vandenberghe
R
Adamczuk
K
Dupont
P
Van Laere
K
Chételat
G
.
2013
.
Amyloid PET in clinical practice: its place in the multidimensional space of Alzheimer's disease
.
Neuroimage Clin
 .
2
:
497
511
.
Vandenberghe
R
Adamczuk
K
Van Laere
K
.
2013
.
The interest of amyloid PET imaging in the diagnosis of Alzheimer's disease
.
Curr Opin Neurol
 .
26
:
646
655
.
Vandenberghe
R
Nelissen
N
Salmon
E
Ivanoiu
A
Hasselbalch
S
Andersen
A
Korner
A
Minthon
L
Brooks
DJ
Van Laere
K
et al
2013
.
Binary classification of 18F-flutemetamol PET using machine learning: comparison with visual reads and structural MRI
.
Neuroimage
 .
64
:
517
525
.
Vandenberghe
R
Price
C
Wise
R
Josephs
O
Frackowiak
RS
.
1996
.
Functional anatomy of a common semantic system for words and pictures
.
Nature
 .
383
:
254
256
.
Vandenberghe
R
Van Laere
K
Ivanoiu
A
Salmon
E
Bastin
C
Triau
E
Hasselbalch
S
Law
I
Andersen
A
Korner
A
et al
2010
.
18F-flutemetamol amyloid imaging in Alzheimer disease and mild cognitive impairment: a phase 2 trial
.
Ann Neurol
 .
68
:
319
329
.
Vandenberghe
R
Wang
Y
Nelissen
N
Vandenbulcke
M
Dhollander
T
Sunaert
S
Dupont
P
.
2013
.
The associative-semantic network for words and pictures: effective connectivity and graph analysis
.
Brain Lang
 .
127
:
264
272
.
Vandenbulcke
M
Peeters
R
Dupont
P
Van Hecke
P
Vandenberghe
R
.
2007
.
Word reading and posterior temporal dysfunction in amnestic mild cognitive impairment
.
Cereb Cortex
 .
17
:
542
551
.
Vandenbulcke
M
Peeters
R
Fannes
K
Vandenberghe
R
.
2006
.
Knowledge of visual attributes in the right hemisphere
.
Nat Neurosci
 .
9
:
964
970
.
Vandenbulcke
M
Peeters
R
Van Hecke
P
Vandenberghe
R
.
2005
.
Anterior temporal laterality in primary progressive aphasia shifts to the right
.
Ann Neurol
 .
58
:
362
370
.
Verhaeghen
P
Vandenbroucke
A
Dierckx
V
.
1998
.
Growing slower and less accurate: adult age differences in time-accuracy functions for recall and recognition from episodic memory
.
Exp Aging Res
 .
24
:
3
19
.
Villemagne
VL
Pike
KE
Chételat
G
Ellis
KA
Mulligan
RS
Bourgeat
P
Ackermann
U
Jones
G
Szoeke
C
Salvado
O
et al
2011
.
Longitudinal assessment of Aβ and cognition in aging and Alzheimer disease
.
Ann Neurol
 .
69
:
181
192
.
Webster
MJ
Herman
MM
Kleinman
JE
Shannon Weickert
C
.
2006
.
BDNF and trkB mRNA expression in the hippocampus and temporal cortex during the human lifespan
.
Gene Expr Patterns
 .
6
:
941
951
.
Whitney
C
Kirk
M
O'Sullivan
J
Lambon Ralph
MA
Jefferies
E
.
2011
.
The neural organization of semantic control: TMS evidence for a distributed network in left inferior frontal and posterior middle temporal gyrus
.
Cereb Cortex
 .
21
:
1066
1075
.
Whitney
C
Kirk
M
O'Sullivan
J
Lambon Ralph
MA
Jefferies
E
.
2012
.
Executive semantic processing is underpinned by a large-scale neural network: revealing the contribution of left prefrontal, posterior temporal, and parietal cortex to controlled retrieval and selection using TMS
.
J Cogn Neurosci
 .
24
:
133
147
.
Woodard
JL
Seidenberg
M
Nielson
KA
Antuono
P
Guidotti
L
Durgerian
S
Zhang
Q
Lancaster
M
Hantke
N
Butts
A
et al
2009
.
Semantic memory activation in amnestic mild cognitive impairment
.
Brain
 .
132
:
2068
2078
.