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doi:10.1093/brain/awr173
Brain 2011: 134; 2502–2512
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BRAIN
A JOURNAL OF NEUROLOGY
Convergent grey and white matter evidence
of orbitofrontal cortex changes related to
disinhibition in behavioural variant
frontotemporal dementia
Michael Hornberger,1,2 John Geng1 and John R. Hodges1,2
1 Neuroscience Research Australia, Barker Street, Sydney NSW 2031, Australia
2 School of Medical Sciences, University of New South Wales, Sydney NSW 2052, Australia
Correspondence to: Dr Michael Hornberger,
Neuroscience Research Australia,
PO Box 1165,
Sydney, Australia
E-mail: [email protected]
Disinhibition is a common behavioural symptom in frontotemporal dementia but its neural correlates are still debated. In the
current study, we investigated the grey and white matter neural correlates of disinhibition in a sample of behavioural variant
frontotemporal dementia (n = 14) and patients with Alzheimer’s disease (n = 15). We employed an objective (Hayling Test of
inhibitory functioning) and subjective/carer-based (Neuropsychiatric Inventory) measure of disinhibition to reveal convergent
evidence of disinhibitory behaviour. Mean and overlap-based statistical analyses were conducted to investigate profiles of
performance in patients with behavioural variant frontotemporal dementia, Alzheimer’s disease and controls. Hayling Test
and Neuropsychiatric Inventory scores were entered as covariates in a grey matter voxel-based morphometry, as well as in a
white matter diffusion tensor imaging analysis to determine the underlying grey and white matter correlates. Patients with
behavioural variant frontotemporal dementia showed more disinhibition on both behavioural measures in comparison to patients
with Alzheimer’s disease and controls. Voxel-based morphometry results revealed that atrophy in orbitofrontal/subgenual,
medial prefrontal cortex and anterior temporal lobe areas covaried with total errors score of the Hayling Test. Similarly, the
Neuropsychiatric Inventory disinhibition frequency score correlated with atrophy in orbitofrontal cortex and temporal pole brain
regions. The orbitofrontal atrophy related to the objective (Hayling Test) and subjective (Neuropsychiatric Inventory) measures of
disinhibition was partially overlapping. Diffusion tensor imaging analysis revealed that white matter integrity fractional anisotropy values of the white matter tracts connecting the identified grey matter regions, namely uncinate fasciculus, forceps minor
and genu of the corpus callosum, correlated well with the total error score of the Hayling Test. Our results show that a network
of orbitofrontal, anterior temporal and mesial frontal brain regions and their connecting white matter tracts are involved in
inhibitory functioning. Further, we find convergent evidence for objective and subjective disinhibition measures that the orbitofrontal/subgenual brain region is critical for adapting and maintaining normal behaviour.
Keywords: behavioural variant frontotemporal dementia; disinhibition; orbitofrontal cortex; voxel-based morphometry; diffusion
tensor imaging
Abbreviations: FTD = frontotemporal dementia
Received April 13, 2011. Revised May 26, 2011. Accepted June 12, 2011. Advance Access publication July 23, 2011
ß The Author (2011). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.
For Permissions, please email: [email protected]
VBM and DTI correlates of disinhibition in bvFTD
Introduction
Frontotemporal dementia (FTD) is a common cause of young onset
dementia (565 years) after Alzheimer’s disease (Ratnavalli et al.,
2002). Clinical diagnostic criteria have been proposed (Neary
et al., 1998), but the differentiation from other dementias remains
difficult with standard neuropsychological and imaging tools
(Gregory et al., 1997; Torralva et al., 2009). This is particularly
true for the behavioural subtype of FTD (behavioural variant FTD),
in which patients present with changes in behaviour and personality (Knibb et al., 2006). Neuroimaging and pathological studies
have suggested that the grey matter regions most consistently
involved in behavioural variant FTD are mesial/orbitofrontal cortex
and anterior insula (Rosen et al., 2002; Davies et al., 2006), which
are affected from the very early disease stages (Seeley et al.,
2008). More recently, it has also become apparent that the underlying white matter tracts connecting these regions are also affected in behavioural variant FTD (Zhang et al., 2009; Whitwell
et al., 2010). Behaviourally, patients with behavioural variant FTD
present with a range of symptoms, such as reduced motivation
and inhibition with severe implications for management and carer
burden (Piguet et al., 2011).
Disinhibition is particularly important in terms of the impact on
carers but is difficult to quantify (Mendez et al., 1993; Gregory
and Hodges, 1996; Piguet et al., 2009) and its neural basis is still
debated (Peters et al., 2006; Zamboni et al., 2008). Behavioural
symptoms are typically assessed via carer-based questionnaires,
such as the Neuropsychiatric Inventory (Cummings et al., 1994)
or the Cambridge Behavioural Inventory (Wedderburn et al.,
2008). In one of the earliest studies employing the
Neuropsychiatric Inventory, Levy et al. (1996) reported a higher
incidence of disinhibition in FTD compared with Alzheimer’s disease and that 470% of patients could be correctly classified
on the disinhibition, apathy and depression Neuropsychiatric
Inventory scores alone. These findings were corroborated by
other studies (Kertesz and Munoz, 1998; Bozeat et al., 2000),
indicating that disinhibition can be an efficient discriminator
of patients with Alzheimer’s disease and patients with FTD, whereas other behavioural symptoms can overlap between the
conditions.
Several studies have investigated the neural correlates of disinhibition as measured by carer questionnaires. For example, Peters
et al. (2006) showed that the disinhibition score of the
Neuropsychiatric Inventory covaried with the PET metabolic activity in posterior orbitofrontal cortex in patients with FTD. They
concluded that dysfunction in this region most likely contributed
to the disinhibited symptoms. This finding was recently replicated
(Krueger et al., 2011) in a large sample of neurodegenerative
patients (including behavioural variant FTD) using cortical thickness as a measure of orbitofrontal cortex grey matter integrity. In
contrast, another study (Zamboni et al., 2008) using scores of the
Frontal Systems Behaviour Scale showed no correlation with orbitofrontal cortex atrophy using voxel-based morphometry analysis,
instead the right nucleus accumbens and temporal lobe structures
were related to disinhibition on this measure. These discrepant
findings highlight the inherent problems of employing subjective
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(e.g. carer) information alone to establish behavioural symptoms in
FTD.
More objective measures of disinhibition have been applied to
behavioural variant FTD, notably the Stroop, Go/No-go and Stop
Signal tasks. Although impaired on the Stroop test, patients with
behavioural variant FTD perform at an equivalent level to patients
with Alzheimer’s disease (Pachana et al., 1996; Perry and Hodges,
2000; Collette et al., 2007) emphasizing the multidimensional
nature of this task. Go/No-go tasks are potentially more specific.
Mendez et al. (2005) contrasted sociopathic versus non-sociopath
patients with FTD and found a difference in the performance of
the Go/No-go and Alternate Tapping subtests of the Frontal
Assessment Battery. Using a short version of a Go/No-go paradigm, Torralva et al. (2009) found a significant difference between
behavioural variant FTD and Alzheimer’s disease. In contrast,
Collette et al. (2007) found no difference in Go/No-go performance between patients with FTD in contrast to controls or patients
with Alzheimer’s disease. Inhibitory performance of patients with
FTD has also been explored using a Stop-Signal task (Logan et al.,
1984), in which participants are trained to respond as quickly as
possible in a reaction time task but on a proportion of trials, a
‘stop signal’ is sounded shortly after the presentation of the usual
stimulus, which indicates that the subject has to inhibit its response
on that particular trial. The presentation lag of the stop signal is
varied across trials and longer delays making it harder to inhibit
responses than that for shorter delays. Patients with FTD were
only marginally impaired on this task (Dimitrov et al., 2003).
It becomes obvious that these tasks designed to assess inhibitory
responses do not reliably distinguish between patients with FTD
and other dementias or healthy controls, either because of their
lack of specificity (Stroop test) or low sensitivity (Go/No-go). In
contrast, the Hayling Test of inhibitory function (Burgess and
Shallice, 1997) was specifically developed to assess impulsive
and stimulus bound behaviour. The task consists of two parts:
part A requires participants to complete a last word of a sentence
with a correct word (e.g. ‘He sent the letter without a . . .’; correct
answer: ‘stamp’), while in part B participants are asked to complete a new set of sentences, this time with a completely unrelated
word (e.g. ‘The captain stayed with the sinking . . .’; wrong
answer: ‘ship’; possible correct answer: ‘cucumber’). The second
part of the Hayling Test, therefore, requires participants to inhibit
a prepotent response set up in the first part. Lough et al. (2006)
found that patients with behavioural variant FTD were severely
impaired on the Hayling Test. A retrospective study on a larger
behavioural variant FTD sample further found that performance
on the Hayling Test together with reverse Digit Span best discriminated real patients with behavioural variant FTD from the
so-called behavioural variant FTD phenocopy cases (Hornberger
et al., 2008), despite indistinguishable behavioural presentations.
A short version of the Hayling Test was incorporated into the The
Institute of Cognitive and Behavioural Neurology (INECO) frontal
screening test (Torralva et al., 2009), which appears extremely
useful in detecting cognitive dysfunction in behavioural variant
FTD, with the Hayling component being a subtest that best discriminated behavioural variant FTD from Alzheimer’s disease. A
recent study (Hornberger et al., 2010) corroborated these behavioural findings and established that a combination of orbitofrontal
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M. Hornberger et al.
cortex atrophy (as assessed by visual rating) and inhibition error
scores could discriminate 490% of behavioural variant FTD and
patients with Alzheimer’s disease.
The neural correlates of performance in the Hayling Test, which
appears sensitive and specific to behavioural variant FTD, have not
been explored using automated methods of structural brain analysis, such as voxel-based morphometry or diffusion tensor imaging. Such analysis would not only allow the establishment of grey
matter regions associated with objective disinhibition measures in
behavioural variant FTD, but also which white matter tracts are
associated with the inhibition performance. Finally, the link between objective and subjective disinhibition measures still remains
to be established.
This prospective study examined the relationship between performance on the Hayling Test and grey and white matter brain
atrophy. We investigated: (i) how atrophy in grey matter areas
correlates with the Hayling inhibition performance; and (ii) how
white matter changes, as indicated via fractional anisotropy on
diffusion tensor imaging, related to inhibitory control. We predicted that orbitofrontal grey matter areas and connecting white
matter tracts would be directly correlated with the degree of disinhibition in behavioural variant FTD. To establish a link between
objective and subjective measures of disinhibition, we explored the
neural correlates of carer-based scores of disinhibition using the
Neuropsychiatric Inventory. We hypothesized that if objective and
subjective measures tap into the same dysfunction, then similar
neural correlates should be identified.
Patients and methods
Case selection
Patients were selected from the FRONTIER database (www.ftdrg.org)
resulting in a sample of 14 patients with behavioural variant FTD,
15 with Alzheimer’s disease and 18 controls. All patients with behavioural variant FTD met current consensus criteria for FTD (Neary et al.,
1998; Rascovsky et al., 2007) with insidious onset, decline in social
behaviour and personal conduct, emotional blunting and loss of insight. In light of the recent recognition of the phenocopy syndrome
(Hornberger et al., 2008, 2009), only patients with behavioural variant
FTD with evidence of clear decline as reported by the caregivers and
atrophy on MRI scans were included in the study. All patients with
Alzheimer’s disease met NINCDS-ADRDA diagnostic criteria (McKhann
et al., 1984) for probable Alzheimer’s disease. Demographic details are
presented in Table 1. Age- and education-matched healthy controls
were selected from a healthy volunteer panel or were spouses/carers
of patients.
Behavioural testing
The Hayling Test (Burgess and Shallice, 1997) evaluates inhibition of a
prepotent response by employing a sentence completion task. In the
first section of the test, consisting of 15 sentences, participants are
required to complete a sentence with a word that gives a meaningful
sense to the sentence. The second section of the test, again consisting
of 15 sentences, requires the participant to complete a sentence with a
word that is unconnected to the sentence, which requires inhibiting an
automatic response. Errors are recorded for words that do not follow
these rules. In addition, the time taken to respond is recorded, which
together with the error scores results in an overall score. In the current
study, we report the scaled score B, total error score and the overall
scaled score of the Hayling Test, which have been shown to be most
sensitive to discriminate behavioural variant FTD and Alzheimer’s disease (Hornberger et al., 2010).
As independent measure of behavioural disturbance, we used
the Neuropsychiatric Inventory (Cummings et al., 1994). The
Neuropsychiatric Inventory screens for a range of symptoms including
apathy, agitation, anxiety, irritability, dysphoria, aberrant motor behaviour, disinhibition, delusions, hallucinations and euphoria, which
are all scored on a frequency scale of 1 (occasionally, less than once
a week) to 4 (very frequently, once or more per day or continuously).
Table 1 Mean (SD) scores for behavioural variant FTD and controls on demographics and general cognitive tests
Demographics,
cognitive and
behavioural tests
Behavioural
variant FTD
(n = 14)
Alzheimer’s
disease
(n = 15)
Controls
(n = 18)
F-values
Behavioural
variant FTD
versus control
Alzheimer’s
disease versus
control
Behavioural
variant FTD
versus Alzheimer’s
disease
Sex (M/F)
Handedness (R/L)
Education
Mean age at scan (years)
Length of disease (years)
ACE (max. score = 100)
MMSE (max. score = 30)
Hayling
Scaled score B
Total error score
Overall scaled score
Neuropsychiatric Inventory
Disinhibition frequency
10/4
13/0
11.8 (3.4)
59.3 (7.9)
3.7 (2.6)
75.6 (11.4)
24.9 (3.8)
11/4
13/1
13.1 (3.6)
63.8 (7.7)
2.7 (1.7)
80.1 (11.4)
26 (2.8)
9/9
18/0
13.6 (2.5)
64.8 (5.3)
–
95.4 (2.9)
29.2 (.8)
NS
NS
NS
NS
NS
***
***
–
–
–
–
–
***
***
–
–
–
–
–
***
**
–
–
–
–
–
NS
NS
4.14 (2.3)
42 (26.9)
2.6 (1.9)
4.2 (2)
11.9 (10.5)
3.9 (2)
6 (0)
2.3 (4.2)
6.4 (.6)
**
***
***
*
***
***
*
NS
***
NS
***
NS
1.57 (1.6)
.27 (.46)
–
**
–
–
–
F-values indicate significant differences across groups; Tukey post hoc tests compare differences between group pairs. *P 5 0.05; **P 5 0.01; ***P 5 0.001.
ACE = Addenbrooke’s Cognitive Examination; MMSE = Mini-Mental State Examination; NS = non-significant.
VBM and DTI correlates of disinhibition in bvFTD
We employed the subscore of disinhibition of the Neuropsychiatric
Inventory as a carer measure of disinhibition.
Patients also underwent general cognitive screening using the
Addenbrooke’s Cognitive Examination Revised (Mathuranath et al.,
2000; Mioshi et al., 2006) and Mini-Mental State Examination to determine their overall cognitive functioning. Only data from the first
clinical presentation of the patients were included in all analyses.
Behavioural analyses
Data were analysed using SPSS 17.0 (SPSS Inc.). Parametric demographic (age, education), neuropsychological (Hayling and general
cognitive tests) and behavioural (Neuropsychiatric Inventory) data
were compared across the three groups (behavioural variant FTD,
Alzheimer’s disease and controls) via one-way ANOVAs followed by
Tukey post hoc tests. A priori, variables were plotted and checked for
normality of distribution by Kolmogorov–Smirnov tests. Variables revealing non-normal distributions were log transformed and the appropriate log values were used in the analyses. Variables showing
non-parametric distribution after log transformation were analysed
via chi-square, Kruskal–Wallis and Mann–Whitney U tests.
Imaging acquisition
All patient and controls underwent the same imaging protocol with
whole-brain T1- and diffusion tensor imaging-weighted images using
a 3T Philips MRI scanner with standard quadrature head coil (eight
channels).
The 3D T1-weighted sequences were acquired as follows: coronal
orientation, matrix 256 256, 200 slices, 1 1 mm2 in-plane resolution, slice thickness 1 mm, echo time/repetition time = 2.6/5.8 ms.
The diffusion tensor imaging-weighted sequences were acquired as
follows: 32 gradient direction diffusion tensor imaging sequence (repetition time/echo time/inversion time: 8400/68/90 ms; b-value =
1000 s/mm2; 55 2.5 mm horizontal slices, end resolution: 2.5 2.5
2.5 mm3; field of view 240 240 mm, 96 96 matrix; repeated
twice). Two diffusion tensor imaging sequences were acquired for
each participant, which were in a first step averaged. All scans were
then visually checked for field inhomogeneity distortions and corrected
for eddy current distortions. The diffusion tensor models were then
fitted at each voxel via the FMRIB’s Diffusion toolbox in the FMRIB
software
library
(http://www.fmrib.ox.ac.uk/fsl/fdt/index.html),
resulting in maps of three eigenvalues (1, 2, 3) that allowed
calculation of fractional anisotropy maps for each subject.
Voxel-based morphometry analysis
Three-dimensional T1-weighted sequences were analysed with FSL-VBM,
a voxel-based morphometry analysis (Ashburner and Friston, 2000;
Good et al., 2001), which is part of the FMRIB software library package (http://www.fmrib.ox.ac.uk/fsl/fslvbm/index.html) (Smith et al.,
2004). First, tissue segmentation was carried out using FMRIB’s
Automatic Segmentation Tool (FAST) (Zhang et al., 2001) from
brain extracted images. The resulting grey matter partial volume
maps were then aligned to the Montreal Neurological Institute standard space (MNI152) using the non-linear registration approach FNIRT
(Andersson et al., 2007a, b), which uses a b-spline representation of
the registration warp field (Rueckert et al., 1999). The registered partial volume maps were then modulated (to correct for local expansion
or contraction) by dividing them by the Jacobian of the warp field.
The modulated images were then smoothed with an isotropic
Gaussian kernel with a standard deviation of 3 mm (full width half
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maximum = 8 mm). Finally, a voxel-wise general linear model was applied and permutation-based non-parametric testing was used to form
clusters with the threshold-free cluster enhancement method (Smith
and Nichols, 2009), tested for significance at P 5 0.05, corrected for
multiple comparisons by family-wise error correction across space.
Diffusion tensor imaging analysis
Tract-based Spatial Statistics (Smith et al., 2006) from the FMRIB software library were used to perform a skeleton-based analysis of white
matter fractional anisotropy. Fractional anisotropy maps of each individual subject were eddy current corrected and co-registered using
non-linear registration FNIRT (Andersson et al., 2007a, b) to the MNI
standard space using the FMRIB58 fractional anisotropy template,
which is available as part of the FMRIB library software. The template
was subsampled at 2 2 2 mm3 due to the coarse resolution of
native diffusion tensor imaging data (i.e. 2.5 2.5 2.5 mm3). After
image registration, fractional anisotropy maps were averaged to produce a group mean fractional anisotropy image. A skeletonization algorithm (Smith et al., 2006) was applied to the group mean fractional
anisotropy image to define a group template of the lines of maximum
fractional anisotropy, assumed to correspond to centres of white matter
tracts. Fractional anisotropy values for each individual subject were
then projected onto this group template skeleton. Clusters were
tested using permutation-based non-parametric testing as described for
the voxel-based morphometry analysis. Clusters reported have significance at P 5 0.05, corrected for multiple comparisons across by
family-wise error correction space, unless otherwise stated.
Results
Demographics and global cognitive
functioning
Demographics and general cognitive scores are shown in Table 1.
Participant groups did not differ in terms of age, education, handedness or sex (all P 4 0.1). More importantly, behavioural variant
FTD and patients with Alzheimer’s disease did not differ in disease
duration (P 4 0.1).
Hayling Test
The behavioural variant FTD group were impaired on all scores derived from part B of the Hayling Test: scaled score B (P 5 0.05);
total error score (P 5 0.001); overall scaled score (P 5 0.001).
Patients with Alzheimer’s disease were also significantly impaired
on scaled score B and overall score of the Hayling Test in comparison to controls but not on the total error score (P 4 0.1).
Crucially, however, patients with behavioural variant FTD and
Alzheimer’s disease differed on the total error score (P 5 0.001)
(Fig. 1). A logistic regression using the Enter method and employing only behavioural variant FTD and Alzheimer’s disease, revealed
that 75% of the participating patients could be correctly classified
into behavioural variant FTD and Alzheimer’s disease on this score
alone.
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M. Hornberger et al.
Figure 1 Box plot for the Hayling Test total error score across all
three groups: behavioural variant FTD (bvFTD), Alzheimer’s
disease (AD) and controls. Whiskers indicate minimum and
maximum values.
Neuropsychiatric Inventory disinhibition
subscore
The average disinhibition frequency score ascribed by carers of
patients with behavioural variant FTD (Table 1) was significantly
higher than that for patients with Alzheimer’s disease (P 5 0.01).
Voxel-based morphometry group
analysis
In a first step of the voxel-based morphometry analysis, we contrasted our participant groups to reveal the pattern of overall brain
atrophy. Patients with behavioural variant FTD showed grey matter
atrophy in anterior cingulate, orbitofrontal, anterior insula and anterior temporal lobe regions in comparison to controls (Supplementary
Table 1 and Fig. 1). The patients with Alzheimer’s disease showed
a more widespread atrophy pattern (Supplementary Table 1 and
Fig. 2), including the hippocampus and posterior cingulate/
precuneus brain regions. Comparison of patient groups showed
significantly greater atrophy of the orbitofrontal cortex regions in
behavioural variant FTD versus Alzheimer’s disease (Table 2). The
reverse contrast revealed no significant differences after correction for multiple comparisons; however, at P 5 0.001 uncorrected,
the Alzheimer’s disease group showed significantly greater atrophy
of medial parietal (i.e. precuneus) and lateral occipital cortices
(Table 2).
Voxel-based morphometry—
correlations with disinhibition
In a second step, we entered the Total Error score of the Hayling
Test as a covariate in the design matrix of the voxel-based morphometry analysis. This analysis was conducted on the patients with
behavioural variant FTD and with Alzheimer’s disease only. As can
be seen in Fig. 2 and Table 3, atrophy in three brain regions
(ventromedial orbitofrontal/subgenual anterior cingulate, anterior
cingulate and temporal pole) was correlated with the Hayling Total
Error score at P 5 0.001 uncorrected. An additional analysis
Figure 2 Voxel-based morphometry analysis showing brain
areas which positively correlate with the Hayling total error
score variable in behavioural variant FTD and patients with
Alzheimer’s disease. Clusters are overlaid on the MNI standard
brain (t 4 2.41). Coloured voxels show regions that were
significant in the analyses for P 5 0 .001 uncorrected and
a cluster threshold of 70 contiguous voxels.
investigated whether the temporal pole findings were due to the
semantic nature of the task. We entered, therefore, the patients’
performance in a semantic (naming) task as a covariate in the
analysis, which did not change the earlier results.
Similarly, we entered the disinhibition score of the Neuropsychiatric
Inventory as a covariate in the voxel-based morphometry analysis,
which showed a positive correlation with atrophy in the ventromedial orbitofrontal/subgenual cingulate and temporal pole brain
regions (Table 3). Importantly, the atrophy related to both measures partially overlapped for the ventromedial orbitofrontal cortex
(Fig. 3).
Diffusion tensor imaging
Analysis of whole brain fractional anisotropy measures across
groups replicated the voxel-based morphometry findings.
Patients with behavioural variant FTD showed a decrease in fractional anisotropy for mostly frontal and anterior temporal brain
regions, while patients with Alzheimer’s disease showed diffuse
fractional anisotropy white matter changes for the white matter
of the precuneus brain region (Supplementary Table 2).
We investigated fractional anisotropy values of white matter
tracts connecting the grey matter regions found to correlate
with performance on the Hayling Test. Masks for the following
white matter tracts taken from the Johns Hopkins probabilistic
white matter tract atlas (Mori et al., 2005) were created: uncinate
fasciculus (connecting orbitofrontal and anterior temporal brain
regions); cingulum fasciculus (corpus callosum part); and forceps
minor fasciculus (connecting medial and lateral prefrontal regions
VBM and DTI correlates of disinhibition in bvFTD
Brain 2011: 134; 2502–2512
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Table 2 Voxel-based morphometry results showing regions of significant grey matter intensity decrease for the contrasts of
behavioural variant FTD and Alzheimer’s disease patient groups
Regions
Hemisphere
MNI
coordinates
x
T-score
Number
of voxels
y
z
Behavioural variant FTD versus Alzheimer’s disease
Orbitofrontal cortex
Bilateral
12
16
22
1204
Temporal pole
Left
46
24
32
23
2.5
1.67
Alzheimer’s disease versus behavioural variant FTD
Precuneus
Bilateral
2
90
8
2250
3.03
Supramarginal gyrus
Left
48
42
58
276
3.03
Lateral occipital cortex
Left
46
78
20
219
2.77
Precentral gyrus
Left
28
6
62
124
2.77
Behavioural variant FTD versus Alzheimer’s disease contrast corrected for multiple comparisons (family-wise error) at P 5 0.05; Alzheimer’s disease versus behavioural
variant FTD contrast uncorrected at P 5 0.001 with at least 100 contiguous voxels.
Table 3 Voxel-based morphometry results showing regions of significant grey matter intensity decrease that covary with
disinhibition performance
Regions
Hemisphere
MNI coordinates
x
Hayling Test—total error score
Temporal pole
Left
Temporal pole
Right
Medial prefrontal cortex
Bilateral
Orbitofrontal cortex
Bilateral
Neuropsychiatric Inventory—disinhibition frequency score
Temporal pole
Left
Orbitofrontal cortex
Bilateral
y
z
Number
of voxels
T-score
40
32
2
2
6
22
58
24
46
44
0
18
1668
1582
371
365
3.03
3.03
3.03
3.03
20
2
2
18
48
26
228
74
2.47
2.47
All results uncorrected at P 5 0.001; only clusters with at least 70 contiguous voxels included.
Figure 3 Overlap of Hayling Test total error score and Neuropsychiatric Inventory (NPI) disinhibition frequency grey matter atrophy in
patients with behavioural variant FTD and Alzheimer’s disease. Clusters are overlaid on the MNI standard brain (t 4 2.41). Coloured voxels
show regions that were significant in the analyses for P 5 0.001 uncorrected and a cluster threshold of 70 contiguous voxels.
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| Brain 2011: 134; 2502–2512
via the genu of the corpus callosum). Non-parametric permutation
tests were run on the fractional anisotropy maps masked for the
selected tracts. Fractional anisotropy values were extracted from
the tracts at P 5 0.001, uncorrected and exported into SPSS.
Fractional anisotropy and Hayling Total Errors were entered into
a linear regression for each tract, separately. Note, only fractional
anisotropy values and Hayling Total Errors of the two patient
groups (behavioural variant FTD, Alzheimer’s disease) were entered into the linear regression. As can be seen in Fig. 4, the
degree of fractional anisotropy decrease was negatively correlated
with the inhibition performance on the Hayling task. In particular,
fractional anisotropy values of the uncinate fasciculus were highly
correlated with Hayling Error scores (P 5 0.001), as well as fractional anisotropy values for the forceps minor (P 5 0.001) and cingulum (P 5 0.001) fasciculi. Similarly, the Neuropsychiatric Inventory
disinhibition frequency score showed a statistical trend (P = 0.07)
for a negative correlation with the fractional anisotropy values of
the uncinate fasciculus.
Discussion
The principal finding of our study was that ventromedial orbitofrontal, medial frontal and anterior temporal lobe grey matter
M. Hornberger et al.
atrophy is directly related to the degree of disinhibition shown
by patients with behavioural variant FTD. In addition, the integrity
of white matter tracts connecting these regions appears critical.
Atrophy of the ventromedial orbitofrontal/subgenual brain region
was related both as an objective measure of inhibitory functioning
and a carer-based assessment of disinhibition. These findings have
clinical and theoretical implications.
The behavioural data replicated our previous findings (Hornberger
et al., 2008, 2010). Patients with behavioural variant FTD showed
substantial deficits on the Hayling Test of inhibitory control and
were distinguishable from patients with Alzheimer’s disease by the
total errors score. Using logistic regression, the total error score
could discriminate 75% of patients on their first assessment. Not
surprisingly, carers of patients with behavioural variant FTD reported a significantly greater frequency of disinhibition than caregivers of patients with Alzheimer’s disease on the Neuropsychiatric
Inventory. These findings confirm previous reports of a higher incidence of disinhibited behaviour in behavioural variant FTD
in comparison to Alzheimer’s disease (Levy et al., 1996; Bozeat
et al., 2000). Similar to our previous findings (Hornberger et al.,
2010), the Hayling total error score emerged as a sensitive measure to distinguish both groups, with patients with behavioural variant FTD showing on average nearly four times more inhibitory errors
on the sentence completion task. The Hayling Test is a simple but
Figure 4 Correlations of fractional anisotropy (FA) and Hayling total error scores for (A) uncinate fasciculus and (B) forceps minor.
VBM and DTI correlates of disinhibition in bvFTD
sensitive measure that detects disinhibition in FTD. Other objective
disinhibition measures, such as Go/No-go and Stroop tasks have not
shown the same level of discrimination of FTD and patients with
Alzheimer’s disease (Perry and Hodges, 2000; Collette et al., 2007).
Nevertheless, development of a test of disinhibition, equivalent in
some way to the Hayling, but based upon non-verbal stimuli,
might be even better as it would allow the inclusion of aphasic
patients with FTD.
Both patients with behavioural variant FTD and Alzheimer’s
disease showed the classic pattern of grey matter brain atrophy
commonly reported (Seeley, 2008; Whitwell et al., 2009); in behavioural variant FTD, medial frontal/anterior cingulate, orbitofrontal, anterior insula and temporal lobe atrophy was present.
In contrast, patients with Alzheimer’s disease showed atrophy of
medial temporal, including parahippocampal and hippocampal
areas, as well as involvement of posterior cingulate/precuneus
brain regions. A direct comparison revealed that patients with behavioural variant FTD could be discriminated from patients with
Alzheimer’s disease on orbitofrontal atrophy, whereas regional atrophy of the precuneus was indicative of an Alzheimer’s disease
presentation. Our findings corroborate previous results, highlighting the differential atrophy in typical Alzheimer’s disease and behavioural variant FTD, with Alzheimer’s disease showing more
parietal (Rusinek et al., 1991; Jones et al., 2006) and FTD more
frontal atrophy (Rosen et al., 2002; Seeley, 2008), while both
patient groups can show temporal atrophy (Whitwell and Jack,
2005; Whitwell et al., 2009). It is clear that ventromedial frontal
and medial parietal regions are key for differential diagnosis of
these dementias (Womack et al., 2011).
More importantly, the differential atrophy mapped onto the
clinical symptoms. The degree of ventromedial orbitofrontal/subgenual cingulate atrophy covaried with the level of disinhibition. In
particular, the Hayling Error scores correlated with the ventromedial orbitofrontal cortex/subgenual brain regions as well as anterior temporal and medial frontal grey matter atrophy. Crucially,
the disinhibition scores on the Neuropsychiatric Inventory also
correlated with the ventromedial orbitofrontal cortex region.
Thus, we have convergent evidence from both an objective measure (i.e. the Hayling Test) and a carer-based assessment (i.e.
Neuropsychiatric Inventory) that this region is critical for the genesis of disinhibited behaviour.
Interestingly, as mentioned above, atrophy in two other brain
regions covaried with the disinhibition error score of the Hayling
Test, the anterior temporal pole and the medial frontal/anterior
cingulate cortex. Importantly, the medial frontal/anterior cingulate
region was not evident in the analysis with the carer disinhibition
information. The correlation with the grey matter atrophy of the
anterior temporal pole may reflect the verbal nature of the Hayling
task. The anterior temporal pole has been shown to be critically
involved in semantic processing (e.g. Patterson et al., 2007;
Lambon Ralph et al., 2010). It should not be surprising that patients with atrophy in this region would perform poorly on the
Hayling task, which requires patients to understand the sentence
fragments for successful completion. Nevertheless, inclusion of a
semantic naming covariate in the Hayling Test analysis did not
change the initial results. Further, the carer evaluation of disinhibited behaviour also showed a correlation with the left temporal
Brain 2011: 134; 2502–2512
| 2509
pole, though not overlapping and more medial to the Hayling
atrophy correlates. It is currently not clear why the carer-based
assessment should be related to temporal pole degeneration. One
possibility, which should be explored in the future, is that atrophy
in this region might reflect more verbal disinhibition (e.g. inappropriate comments) instead of a purely behavioural disinhibition (e.g.
perseverative behaviour). It is also possible that temporal pole
pathology has a role in the genesis of behavioural disinhibition
as overlapping symptoms are reported by caregivers of patients
with behavioural variant FTD and semantic dementia (Bozeat
et al., 2000) that are typically attributed to accompanying frontal
pathology. This notion is further supported by findings in monkeys
with temporal pole lesions and patients with Klüver–Bucy syndrome, which involves mainly the temporal pole, who show grossly abnormal social behaviours (for review see Olson et al., 2007).
Further, Zahn et al. (2009) have shown that combined temporal
pole and orbitofrontal cortex atrophy is associated with disinhibited social behaviour, as indicated on the Neuropsychiatric
Inventory, which corroborates with our findings. The interaction of
the orbitofrontal cortex with temporal regions via the uncinate
fasciculus might be crucial in maintaining normal behaviour and
in particular inhibitory performance (see also Green et al., 2010
for related findings).
The atrophy in the medial frontal/anterior cingulate region is
more difficult to explain. This frontal region is important for
Theory of Mind processing (Eslinger, 1998; Gregory et al., 2002)
and perspective taking (Kipps et al., 2009; Shamay-Tsoory et al.,
2009). Other studies report the importance of this region in cognitive control (Kerns et al., 2004). It is not clear which of those
functions might have affected the performance on the Hayling
Test, but cognitive control appears the most plausible candidate,
as previous studies have found that this region is implicated in
error detection and correction on Go/No-go tasks (Hester et al.,
2009). Future investigations are needed to identify the overlap of
inhibition and cognitive control processes to address this finding.
Importantly, findings from the diffusion tensor imaging analysis
revealed that integrity of the white matter tracts connecting orbitofrontal cortex with temporal pole and medial frontal brain regions also correlated with the Hayling performance, suggesting
that a network of regions is involved in the performance of this
task.
On a theoretical level, our findings further establish the ventromedial orbitofrontal cortex region as crucial in maintaining normal
behaviour and adapting responses to changed contingencies in the
environment. Classically, orbitofrontal cortex damage has been
attributed with drastic changes in behaviour, as most famously
described in the case of Phineas Gage (Harlow, 1868). Gage
showed disinhibition as indicated by inflexible and perseverative
behaviour as well as risky decision making after a tamping iron
traversed his orbitofrontal cortex. Such behavioural changes have
also been observed in monkeys with ventromedial orbitofrontal
cortex lesions (Mishkin, 1964; Izquierdo et al., 2004;
Kringelbach and Rolls, 2004), who fail or are slow to adapt their
responses when the cue–outcome associations in tasks are changed. Thus, the intactness of the ventromedial orbitofrontal cortex
appears crucial for flexible behaviour and adapting the response to
a changed environment. Rahman et al. (1999) showed that
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| Brain 2011: 134; 2502–2512
patients with FTD are impaired on the reversal stages of a visual
discrimination task, i.e. they fail to adapt their behaviour when the
contingencies changed, while they perform normally when the
contingencies are maintained. Rahman et al. (1999) concluded
that the known ventromedial damage in FTD likely contributed
to these deficits, although volumetric neuroimaging data were
not available in the eight patients tested. They further concluded
that the results are consistent with current theories that damage to
this cortical region results in the inability to reform stimulus–reinforcement associations when contingencies change. Our findings
are concordant. The Hayling Test requires that participants change
their response contingencies from part A to part B of the test. The
results further suggest that disinhibited behaviour in behavioural
variant FTD may be based on a failure to adapt behaviour flexibly,
although there may be a number of different and interrelated
processes that contribute to this disinhibited behaviour (Murray
et al., 2007). Along with the ventromedial orbitofrontal cortex,
other prefrontal brain regions also have been implicated in inhibitory functioning, in particular the lateral orbitofrontal cortex/right
inferior frontal cortex (for a review see Aron, 2007). The inferior
frontal cortex is consistently activated in functional neuroimaging
studies of inhibitor functioning in healthy young participants
(Garavan et al., 1999; Konishi et al., 1999; Rubia et al., 2003)
and also affects stop-signal performance in stroke patients with
right inferior frontal cortex lesions (Aron et al., 2003). The same
region, however, is conspicuously absent in any atrophy disinhibition correlations in neurodegenerative diseases. One potential
reason might be that most functional neuroimaging tasks
employ stop-signal tasks, while patient studies often use Go/
No-go type task, like the Hayling Test. Recent evidence suggests
that stop-signal task performance, which relies on response completion inhibition, can be dissociated from Go/No-go task performance, which is dependent on response selection inhibition
(Eagle et al., 2008). These two related but separable processes
might, therefore, rely on different neural substrates (e.g. inferior
frontal cortex versus orbitofrontal cortex). Another potential
reason for an absence of inferior frontal cortex atrophy being
correlated with disinhibition performance could be that the inferior
frontal cortex is not as affected in behavioural variant FTD as the
ventromedial orbitofrontal cortex and thus there might still be a
relation but below the statistical threshold.
On a clinical level, it becomes obvious that the ventromedial
orbitofrontal cortex region is crucial for the maintenance of
intact behaviour. As previous studies have shown (Peters et al.,
2006; Hornberger et al., 2010), atrophy in this region is related to
behavioural deficits in FTD. A prior study established that a simple
visual magnetic resonance rating of the orbitofrontal cortex, in
conjunction with the Hayling Test, could discriminate behavioural
variant FTD and patients with Alzheimer’s disease in 490% of
instances (Hornberger et al., 2010). In the present study, 75%
of patients with behavioural variant FTD and with Alzheimer’s
disease could be distinguished on the basis of their behavioural
scores alone. This becomes particularly relevant in the light of
recent findings of impaired episodic memory in patients with behavioural variant FTD that can be of a similar magnitude to that
seen in patients with Alzheimer’s disease (Hornberger et al., 2010;
Pennington et al., 2011). The differentiation is further complicated
M. Hornberger et al.
by the fact that patients with Alzheimer’s disease can present with
prominent dysexecutive symptoms (Gleichgerrcht et al., 2010;
Dickerson and Wolk, 2011). Measures of disinhibition emerge as
a powerful diagnostic tool, that target the function of a brain
region specifically impaired in behavioural variant FTD. The caregivers of patients with behavioural variant FTD report high level of
stress and burden in excess of that reported for patients with
Alzheimer’s disease (Mioshi et al., 2009). Attempts to understand
the cognitive and neural basis of disinhibition, one of the leading
symptoms in behavioural variant FTD, is clearly of considerable
practical importance.
Funding
Australian Research Council Federation Fellowship (FF0776229 to
J.R.H.; Australian Research Council Research Fellowship
(DP110104202 to M.H.).
Supplementary material
Supplementary material is available at Brain online.
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