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The effect of semantic memory degeneration on creative thinking: A voxel-based
morphometry analysis
Tamara Paulin, Daniel Roquet, Yoed N. Kenett, Greg Savage, Muireann Irish
PII: S1053-8119(20)30559-0
DOI: https://doi.org/10.1016/j.neuroimage.2020.117073
Reference: YNIMG 117073
To appear in: NeuroImage
Received Date: 21 August 2019
Revised Date: 22 May 2020
Accepted Date: 16 June 2020
Please cite this article as: Paulin, T., Roquet, D., Kenett, Y.N., Savage, G., Irish, M., The effect of
semantic memory degeneration on creative thinking: A voxel-based morphometry analysis NeuroImage,
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Running Head: Creativity in semantic dementia
1
The effect of semantic memory degeneration on creative thinking:
A voxel-based morphometry analysis
Tamara Paulin
1,2
, Daniel Roquet
1
, Yoed N. Kenett
3
, Greg Savage
2
, Muireann Irish
1*
1
The University of Sydney, School of Psychology and Brain and Mind Centre, Camperdown,
NSW 2050, Australia.
2
Department of Psychology, Macquarie University, NSW 2109, Australia.
3
Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA
Corresponding author: Associate Professor Muireann Irish
Brain and Mind Centre,
94 Mallett Street
Camperdown, NSW 2050
Australia
Email: muireann.irish@sydney.edu.au
Ph: +61 2 9114 4165
For submission to NeuroImage – Special Issue on the Neuroscience of Creativity
Word Count : 6698 (excluding abstract and references)
Number of tables: 3
Number of figures: 2
Running Head: Creativity in semantic dementia
2
Abstract
Increasing attention is being directed towards explicating the neurocognitive mechanisms of
divergent thinking. While neuroimaging studies have tended to dominate the contemporary
creativity literature, lesion studies provide important converging evidence by revealing the
regions that are not only implicated in, but essential for, task performance. Here we explored
the capacity for divergent thinking in semantic dementia (SD), a neurodegenerative disorder
characterised by the progressive degeneration of the conceptual knowledge base. The
performance of 10 SD patients on a divergent thinking task was contrasted with that of 15
patients with the behavioural variant of frontotemporal dementia (bvFTD) and 20 healthy
control participants. In addition, all participants underwent neuropsychological testing and
structural MRI. Relative to controls, both patient groups generated significantly fewer
responses on the divergent thinking task, with disproportionate impairment in the SD group.
Further, the responses generated by patient groups were less original and reflected less
flexible thinking when compared with controls. For SD patients, fluency of responses
correlated with performance on a measure of semantic association, and originality of
responses correlated with semantic naming and comprehension ability. In bvFTD, originality
of ideas correlated with letter fluency and response inhibition. Voxel-based morphometry
analyses revealed two grey matter clusters consistently associated with diminished Fluency of
ideas, namely a left medial temporal lobe cluster centred on the left anterior hippocampus,
and a left middle frontal gyrus cluster. Our study highlights the importance of distinct
temporal and prefrontal contributions to divergent thinking via a lesion approach, and
underscores the pivotal role of semantic processes in creative cognition.
Keywords: creativity, semantic dementia, episodic memory, anterior temporal lobe,
hippocampus, cognitive flexibility
Running Head: Creativity in semantic dementia
3
1. Introduction
An important aspect of human cognition is the capacity to adjust one’s behaviour in
response to an ever-changing environment. Such cognitive flexibility allows us to override a
prepotent response, configure a new response, and implement this new response in a task at
hand (Dajani & Uddin, 2015). An inflexible cognitive style has been linked to poor outcomes
across a range of clinical populations including autism spectrum disorder and schizophrenia
(Champagne-Lavau, Charest, Anselmo, Rodriguez, & Blouin, 2012; Geurts, Corbett, &
Solomon, 2009; Nemoto, Kashima, & Mizuno, 2007). Here, we explore how the degradation
of anterior temporal and prefrontal brain regions in neurodegenerative disorders impacts the
capacity for flexible thought, as indexed by measures of divergent thinking.
Divergent thinking tasks are widely used to measure an individual’s capacity for
creativity and require individuals to find many varied and original solutions to problems
(Acar & Runco, 2019; Runco & Acar, 2012). The canonical example of this is the Alternate
Uses Task (AUT) during which participants generate as many alternate uses for an object as
possible (Gilhooly, Fioratou, Anthony, & Wynn, 2007). Successful performance on the AUT
relies upon a number of distinct, though interacting, cognitive mechanisms including bottom-
up episodic and semantic memory processes (Kenett & Faust, 2019; Madore, Addis, &
Schacter, 2015; Madore, Thakral, Beaty, Addis, & Schacter, 2019; Mednick, 1962; Volle,
2018), and the top-down implementation of executive control (Beaty, Silvia, Nusbaum, Jauk,
& Benedek, 2014; Benedek, Jauk, Sommer, Arendasy, & Neubauer, 2014); Leon, Altmann,
Abrams, Gonzalez Rothi, & Heilman, 2014). Accordingly, the retrieval of conceptual
knowledge and past episodic experiences provides the basic elements upon which executive
functions such as disengagement, set shifting, inhibition and working memory operate (Beaty
& Silvia, 2012; Benedek, Könen, & Neubauer, 2012; Nusbaum & Silvia, 2011). This
coordinated interplay between bottom-up and top-down processes ensures that the concepts
Running Head: Creativity in semantic dementia
4
generated are monitored and constrained according to task demands (Beaty, Benedek, Silvia,
& Schacter, 2016; Volle, 2018).
The contribution of semantic knowledge to creative thought is of particular interest in
this context (Kenett, 2018; Kenett & Faust, 2019; Kenett et al., 2018). Theoretical and
empirical research has demonstrated the role of semantic memory in the creative process,
whereby concepts are combined to form novel and useful ideas (Abraham, 2014; Kenett,
2018; Kenett & Faust, 2019; Mednick, 1962). Functional neuroimaging studies of creativity
suggest an important role for the temporal lobe in integrating semantic information to
establish novel associations. In addition, medial temporal regions enable individuals to draw
on personal experiences when engaging in creative cognition (Beaty, Christensen, Benedek,
Silvia, & Schacter, 2017; Beaty, Thakral, Madore, Benedek, & Schacter, 2018; Madore et al.,
2019; Shen, Yuan, Liu, & Luo, 2017). The prefrontal cortex is also consistently implicated in
mediating flexible thought and exerting top-down control processes to inhibit salient
responses and control creative thinking (Beaty, Seli, & Schacter, 2019; Benedek & Fink,
2019; Chrysikou, 2019; Gonen-Yaacovi et al., 2013). Moreover, recent meta-analyses have
concluded that both parieto-temporal and prefrontal regions work in concert to support
divergent thinking (Gonen-Yaacovi et al., 2013; Wu et al., 2015).
While functional neuroimaging studies have tended to dominate the contemporary
creativity literature, lesion studies continue to offer an important adjunct to neuroimaging
studies by demonstrating the regions that are not only implicated in but essential for task
performance (Abraham, 2018; Bendetowicz, Urbanski, Aichelburg, Levy, & Volle, 2017;
Irish & van Kesteren, 2018; Ovando-Tellez, Bieth, Bernard, & Volle, 2019). To date, most
lesion studies have focused on how frontal lobe damage disrupts creative thought. For
example, patients with varying degrees of lateral and medial prefrontal cortical damage have
been shown to generate fewer ideas on a divergent thinking task and the ideas produced are
Running Head: Creativity in semantic dementia
5
rated as lacking in originality (Abraham, Beudt, Ott, & Von Cramon, 2012). Similarly, in
Parkinson’s disease, frontal lobe dysfunction has been shown to disrupt the generation of
ideas on divergent thinking tasks (Tomer, Fisher, Giladi, & Aharon-Peretz, 2002).
Patients with frontal lobe atrophy, as a result of the behavioural variant of
frontotemporal dementia (bvFTD), have been observed to generate fewer ideas on verbal
divergent thinking tasks compared to controls (Hart & Wade, 2006). However, this study
pooled bvFTD with Alzheimer’s disease participants, limiting our capacity to make disease-
specific conclusions. A later study revealed that bvFTD patients performed in line with
control participants on a non-verbal figure-drawing task that involved divergent thinking
(Rankin et al., 2007). In contrast, a study by De Souza et al. (2010) revealed global
impairments in divergent thinking in bvFTD and implicated hypoperfusion of prefrontal
cortical regions in these deficits. Collectively, these studies provide important convergent
evidence for the role of prefrontal regions in divergent thinking, with the suggestion that
prefrontal damage impacts the originality of the ideas generated (Abraham et al., 2012).
In contrast, studies attempting to explicate the role of semantic processing in
divergent thinking using a lesion approach remain remarkably absent from the literature
(Ovando-Tellez et al., 2019). The syndrome of semantic dementia (SD) is particularly well-
suited to investigate the contribution of semantic knowledge to cognitive processes (Hodges
& Patterson, 2007; Irish, Piguet, & Hodges, 2012). The hallmark feature of SD is a pan-
modal deterioration of semantic knowledge due to anterior temporal lobe degeneration that
gradually spreads to include medial temporal and orbitofrontal regions (Gorno-Tempini et al.,
2011). Despite these profound semantic impairments, patients with SD perform in line with
controls on tests which bypass verbal and conceptual demands, such as tests of visual
memory (Bozeat, Lambon Ralph, Patterson, Garrard, & Hodges, 2000; Irish et al., 2016) and
spatial navigation (Pengas et al., 2010; Tu et al., 2015).
Running Head: Creativity in semantic dementia
6
Research involving SD patients has served to clarify the contribution of semantic
processes to a range of internally-driven cognitive functions including autobiographical
memory (Graham, Patterson, & Hodges, 1999; Irish et al., 2011), episodic future thinking
(Duval et al., 2012; Irish, Addis, Hodges, & Piguet, 2012a, 2012b) and scene construction
(Irish et al., 2017; reviewed by Irish & Piolino, 2016). As such, it has been suggested that
semantic memory provides the necessary scaffold for a host of flexible expressions of
cognition, most importantly that of imagination (Abraham & Bubic, 2015; Irish, 2016). To
our knowledge, only two studies to date have assessed creative cognition in SD. In a study
focusing on visual art production in dementia, Rankin et al. (2007) documented marked
impairments in 9 cases of SD on a non-verbal divergent thinking task. This finding is
interesting as it suggests a fundamental impairment in divergent thinking that is not primarily
driven by verbal deficits in this patient group. More recently, Ruggiero et al. (2019) used a
similar figure drawing task to reveal compromised divergent thinking in a mixed sample of 8
bvFTD and 3 SD patients, however, the precise nature of performance deficits in the SD
group was not explored.
The evidence to date converges to suggest marked impairments in the capacity for
divergent thought in SD, likely attributable to anterior temporal lobe atrophy, and in bvFTD
patients likely arising as a consequence of frontal lobe damage. Formal investigation of the
neural substrates of divergent thinking impairments in these syndromes is lacking. The
objective of this study, therefore, was to explore the capacity for divergent thinking in well-
characterised and separate cohorts of SD and bvFTD patients. In addition, both patient groups
completed a comprehensive neuropsychological battery covering the main cognitive domains
and underwent structural magnetic resonance imaging (MRI). This provided us with a rich
dataset to explore, for the first time, the cognitive and neural substrates of divergent thinking
performance in these unique patient groups.
Running Head: Creativity in semantic dementia
7
2. Materials and Methods
2.1 Participants
A total of 45 participants were recruited through the FRONTIER frontotemporal dementia
research group at the Brain and Mind Centre, The University of Sydney, Australia. Of those,
15 individuals met clinical criteria for probable bvFTD (Rascovsky et al., 2011), 10 met
clinical criteria for SD (Gorno-Tempini et al., 2011), and 20 were healthy control
participants. Diagnosis was established by consensus between a senior neurologist and a
neuropsychologist based on the results of clinical investigation, comprehensive cognitive
assessment, and evidence of atrophy on structural neuroimaging.
Patients diagnosed with bvFTD were characterised by marked changes in behaviour,
executive dysfunction, loss of insight, socioemotional dysfunction, apathy, and functional
decline. In addition, prominent bilateral prefrontal and anterior temporal atrophy was evident
on MRI. Patients diagnosed with SD presented with marked language disturbances
manifesting in impaired naming and comprehension, in the context of intact phonology and
fluency of speech. The majority of SD patients (n = 7) displayed the classic left-lateralised
presentation, with focal language disturbances reflecting atrophy commencing in the left
anterior temporal lobe and evolving to a left-predominant, yet bilateral pattern of atrophy on
structural MRI. Notably, 3 cases were diagnosed with the less prevalent right-sided SD
syndrome, presenting clinically with prosopagnosia and behavioural changes, and
characterised by predominant right-lateralised anterior temporal atrophy, which encroached
into the contralateral hemisphere to a lesser degree. SD patients were combined into a single
cohort to maximise power. Disease severity in all patients was measured using the Clinical
Dementia Rating Frontotemporal Lobar Degeneration Scale (CDR-FTLD; Knopman et al.,
2008) and the Frontotemporal dementia Rating Scale (FRS; Mioshi, Hsieh, Savage,
Running Head: Creativity in semantic dementia
8
Hornberger, & Hodges, 2010). Controls were recruited through the FRONTIER research
volunteer panel and all scored 88 or above on the Addenbrooke’s Cognitive Examination –
Third Edition (ACE-III; Hsieh, Schubert, Hoon, Mioshi, & Hodges, 2013; So et al., 2018).
Exclusion criteria for all participants included a history of significant head injury,
presence of another neurological or psychiatric condition, substance abuse, and limited
English proficiency. Ethics approval was obtained from the University of New South Wales
and the South Eastern Sydney Health Service ethics committee. Informed consent was
provided by all participants, or by the person responsible for their care. Participants
volunteered their time and were reimbursed for any travel expenses incurred.
2.2 Assessment of Divergent Thinking
The Alternate Uses Task (AUT) was used to index divergent thinking and was derived from a
commonly used measure in recent literature (Gilhooly et al., 2007). Briefly, participants were
provided with the name of an everyday object and the usual use for that object. They were
then required to generate as many alternative uses for that object as possible. One example
item was given with the instructions (i.e., newspaper: used for reading) along with suggested
alternative uses (i.e., swatting flies, to line drawers, to make a paper hat). Prior to
commencing the task, participants were provided with an opportunity to ask questions and to
clarify task instructions. Once they indicated that they understood the task requirements, six
test items were presented one at a time (brick, car tyre, barrel, pencil, shoe, hanger).
Throughout the task, the experimenter checked the responses made by participants to ensure
they were adhering to the task requirements. Participants were encouraged to be creative and
to generate as many ideas as possible. At the start of each trial, participants received a short
reminder of the task instructions and the name of the object was shown on a computer screen
Running Head: Creativity in semantic dementia
9
(see also Madore, Jing, & Schacter, 2016). The cue remained on screen for the duration of
each trial.
Participants had two minutes to complete each item, although they were not advised
of the time limit and were automatically moved on to the next item if required. Two minutes
was chosen as an appropriate time limit that would allow enough time for older adults to
respond whilst minimising the potential for fatigue in the patient groups over the entire
testing session. Participants provided all responses verbally, and these were digitally recorded
by the experimenter for subsequent transcription and scoring.
2.3 Scoring
AUT Responses were scored in line with standard scoring methods (Barbot, Hass, & Reiter-
Palmon, 2019) focusing on three main outcome measures: Fluency, Originality and
Flexibility. (i) Fluency represents our primary measure of interest and refers to the total
number of adequate uses produced by each participant across the six trials; (ii) Originality
was measured by rating the uniqueness of each use provided on a scale from 1 to 4 (lower
scores denoted more commonplace responses and higher scores signified more unique
responses). To control for potential confounds of fluency and generativity, an average
Originality score was computed for each participant (Silvia et al., 2008); (iii) Flexibility
reflected the total number of distinct categories under which each use could be subsumed.
Responses were excluded if they were vague, implausible or a repetition of a previous
response. Responses were scored by the first author (TP), who was blind to diagnoses. A
second rater (GS) scored a subset (n=10) of AUT responses blind to diagnoses and study
hypotheses. High inter-rater reliability was achieved for Originality (Cronbach’s alpha = .98)
and Flexibility (Cronbach’s alpha = .80). Fluency was not scored by the second rater as it was
simply a sum of responses provided.
Running Head: Creativity in semantic dementia
10
2.4 Neuropsychological testing
All participants completed the ACE-III (Hsieh et al., 2013) as a global measure of cognition
covering the domains of attention and orientation, memory, fluency, language, and
visuospatial abilities. Letter fluency was assessed using the letters F, A, and S (Strauss,
Sherman, & Spreen, 2006). Digit Span Forward and Backward subtests of the WAIS-III were
used as measures of attention and working memory, respectively (Wechsler, 1997). The Trail
Making Test Part B (TMT-B; Reitan, 1958) was used as a measure of executive function.
Non-verbal memory was measured using the 3-minute delayed recall of the Rey-Osterrieth
Complex Figure (Rey, 1941). For bvFTD patients only, verbal memory was assessed using
the Rey Auditory Verbal Learning Test (RAVLT; Schmidt, 1996) and inhibition was
measured using the Hayling Sentence Completion Task (Burgess & Shallice, 1997). These
tasks were not administered to SD patients, due to their heavy semantic loading (see
Supplementary Materials Table 1). SD patients, however, completed additional tests of
language function including the naming, repetition, comprehension and semantic association
subtests from the Sydney Language Battery (SYDBAT; Savage et al., 2013).
2.5 Statistical analyses
Behavioural data were analysed using SPSS version 25.0. Group differences on categorical
variables (e.g., sex) were examined using chi-square tests. For continuous variables,
normality of data distribution was assessed using a combination of Shapiro-Wilk tests and
box-and-whisker plots. Where data were normally distributed (e.g., demographic data and
AUT Fluency scores), group differences were assessed using a between-subjects ANOVA
with Sidak correction for post-hoc comparisons adjusting for small sample sizes. Effect sizes
for all ANOVA statistics are denoted using partial eta-squared values (
). For non-normally
Running Head: Creativity in semantic dementia
11
distributed data (e.g., ACE-III measures and AUT Flexibility and Originality scores),
Kruskal-Wallis tests were used to examine group differences with Bonferroni-adjusted post-
hoc pairwise comparisons. Finally, two-tailed Pearson’s correlation analyses were conducted
to examine associations between general neuropsychological performance and the AUT
measures in the patient groups, and between ACE-III subscales and AUT performance in
controls.
2.6 Image Acquisition
Participants underwent whole-brain structural MRI on a GE Discovery MR750 3Tesla
scanner equipped with an 8-channel head coil. High resolution 3D BRAVO T1-weighted
images were acquired using the following parameters: imaging matrix of 256 × 256 × 200,
1mm isotropic voxel resolution, echo time = 2.5ms, repetition time = 6.7ms, inversion time =
900ms, flip angle = 8°. Structural MRI data were available for all patients and a subset of
control participants (n = 15).
2.7 Data Pre-processing
Voxel-based morphometry (VBM) was conducted using SPM12 (Wellcome Department of
Cognitive Neurology, London, UK), in Matlab R2017b (Mathworks, Natick, Massachusetts,
USA). First, T1-weighted images were segmented into five tissue probability maps in the
native space. Both the original T1-weighted and the segmented maps were screened by DR
during image quality control to ensure that no artefact (such as head motion during
acquisition or bad contrast between brain tissues) or image processing errors biased the
output images and could impact the statistical results. One bvFTD patient was removed from
analysis due to excessive head movement during image acquisition. A Diffeomorphic
Anatomical Registration using Exponentiated Lie (DARTEL) algebra template was computed
Running Head: Creativity in semantic dementia
12
using the grey and white matter probability maps of healthy control participants, then grey
and white matter probability maps of patients were warped to the template. Grey matter
probability maps of patients and control participants were spatially normalized to the
Montreal National Institute (MNI) space according to the transformation parameters from the
corresponding DARTEL template. Images were modulated and smoothed with a Gaussian
filter of full width at half maximum of 8 mm.
2.8 Voxel-based Morphometry Analysis
Patterns of grey matter atrophy were explored using a whole-brain general linear model
comprising bvFTD and SD patients as well as control participants, with age, sex and total
intracranial volume (to account for individual differences in head size) as regressors of non-
interest. The total intracranial volume was assessed in the patient’s space prior to spatial
normalization by summing thresholded grey matter, white matter and corticospinal fluid
probability maps (threshold = 0.2) and counting non-zero voxels. Voxel-wise differences in
grey matter intensity between groups were assessed across the entire brain using t-tests,
where statistical analyses combined a p
uncorrected
< .001 at the voxel level with a cluster size
threshold of 500 contiguous voxels, followed by a multiple comparison correction (Family
Wise Error or FWE) of P
FWE
< .05 at the cluster level.
Next, correlation analyses were performed between grey matter intensity and each of
the three main outcome measures on the AUT (Fluency, Originality, Flexibility) using
separate models. These analyses were corrected for age, sex and total intracranial volume,
and bvFTD, SD and control groups were considered separately in the statistical model (i.e.,
one vector per group) to account for atrophy between groups. The clusters that consistently
emerged across the three correlation analyses at a statistical threshold of p
uncorrected
< .001 at
Running Head: Creativity in semantic dementia
13
the voxel level were extracted as regions of interest, with a cluster size threshold of 500
contiguous voxels.
Finally, since a correlation could be significant across- but not within-groups, within-
group correlation analyses were conducted between grey matter intensity of each of the
selected clusters (corrected for age, sex, total intracranial volume) and the total Fluency
subscore of the AUT in bvFTD and SD patient groups separately. Correlations were corrected
for multiple comparisons using Bonferroni correction (corrected p value: .05/4 = .0125).
3. Results
3.1 Demographic and clinical information
As displayed in Table 1, participants did not differ in terms of age [F(2, 42) = 1.22; p = .31;
= .055] or years of education [F(2, 42) = 0.93; p = .40;
= .04], however a marginally
significant group difference was evident for sex distribution [χ² = 6.13; p = .047]. Disease
duration (years elapsed since onset of symptoms) did not differ between the patient groups
[F(1, 21) = 0.998, p =.33;
= .045] nor did disease severity [CDR-FTLD SoB: F(1, 22) =
0.56, p = .46,
= .03]. Both bvFTD and SD patient groups displayed significant
impairments on the global measure of cognitive function relative to Controls [ACE-III total:
F(2, 42) = 37.01; p < .001;
=.64], with SD patients showing significant impairments
relative to bvFTD, due to the heavy semantic loading of this task (p = .01). Importantly,
however, bvFTD patients demonstrated disproportionate functional impairment relative to the
SD group [FRS Rasch score: F(1, 18) = 6.33; p = .02;
=.26], suggesting a comparable level
of disease severity.
Running Head: Creativity in semantic dementia
14
Table 1. Demographic and clinical profile of study groups (standard deviation in
parentheses)
Note - n.s. = not significant (p > .05); bvFTD = behavioural variant of frontotemporal
dementia; SD = semantic dementia; ACE-III = Addenbrooke’s Cognitive Examination –
Third Edition. Data missing for 1 bvFTD and 1 SD patient on disease duration (years since
symptom onset). Data missing for 1 SD patient on CDR-FTLD SoB. Data missing for 1
bvFTD and 4 SD patients on FRS Rasch Score.
a
Denotes milder functional impairment in SD
relative to bvFTD patients.
3.2 Cognitive profiles
Controls bvFTD SD Group effect
(p value)
Post hoc
(direction of effect)
N 20 15 10
Sex (M: F) 7:13 10:5 2:8 .047 -
Age (years) 66.8
(7.8) 62.9
(7.2) 64.9
(6.2) n.s. -
Education (years) 13.6
(3.0) 12.3
(3.2) 12.4
(3.5) n.s. -
Disease duration
(years since onset) - 5.8
(3.0) 4.7
(1.7) n.s. -
Disease severity
(CDR-FTLD SoB) - 5.8
(4.6) 4.6
(2.8) n.s. -
Disease severity
(FRS Rasch Score) - -0.59
(1.20) 1.05
(1.65) .022 SD > bvFTD
a
ACE-III Attention 17.0
(1.2) 14.5
(2.8) 15.6
(1.6) .006 Controls, SD > bvFTD
ACE-III Memory 24.5
(1.8) 18.1
(4.6) 15.3
(6.2) <.001 Controls > bvFTD, SD
ACE-III Fluency 12.3
(1.3) 9.0
(2.7) 6.2
(3.4) < .001 Controls > bvFTD, SD
ACE-III Language 25.2
(0.9) 22.8
(3.5) 15.4
(5.3) < .001 Controls, bvFTD > SD
ACE-III
Visuospatial 15.5
(0.8) 13.9
(1.9) 15.1
(1.3) .007 Controls, SD > bvFTD
ACE-III Total 94.4
(3.3) 78.3
(8.4) 67.6
(14.2) < .001 Controls > bvFTD > SD
Running Head: Creativity in semantic dementia
15
Characteristic profiles of cognitive impairment were evident across the subscales of the ACE-
III in the patient groups relative to controls (Table 1). Briefly, bvFTD patients displayed
significant impairments in attention and orientation (p = .01), memory (p < .001), fluency (p
= .003), and visuospatial function (p = .006), in the context of relatively intact language
function (p = .11). In contrast, SD patients displayed significant impairments on memory,
fluency, and language (all p-values < .001) while attention and orientation (p = .16), and
visuospatial function (p = 1.0) were largely intact. Direct comparison of the patient groups
revealed disproportionately poorer language function in SD relative to bvFTD (p < .02), with
no other differences evident between the patient groups (all p-values > .08).
3.3 Assessment of Divergent Thinking
A summary of the three outcome measures of interest on the AUT for all three groups is
displayed in Table 2.
3.3.1 Fluency
Fluency represents the total number of adequate responses generated by each participant on
the AUT, and is the primary measure of interest in this study. A between-subjects ANOVA
revealed a significant main effect of group on AUT Fluency, F(2, 42) = 38.40; p < .001;
=
.65, reflecting significant impairments in both bvFTD and SD groups relative to controls (all
p values < .001). Sidak-corrected comparisons between the patient groups revealed
disproportionate impairments on AUT Fluency in SD relative to the bvFTD group (Mean
difference = 8.1; 95% CI for mean difference = 0.65, 15.48; p = .03).
Table 2. Mean performance on the Alternate Uses Task in participant groups (standard
deviation in parentheses)
Running Head: Creativity in semantic dementia
16
Note: Fluency = total number of ideas produced across all trials; Flexibility = total number of
categories the generated ideas fell under; Originality = average rating for ideas produced.
Figure 1. Performance across participant groups on the Alternate Uses Task. Fluency
measured as total number of alternate uses produced over the six trials; Originality measured
as the average rating for ideas produced; Flexibility measured as the total number of
categories the uses fell under. *significant difference p < .05. ** significant difference p <
.01; bvFTD = behavioural variant of frontotemporal dementia; SD = semantic dementia.
Error bars represent minimum and maximum scores.
3.3.2 Originality
Controls
(n = 20)
bvFTD
(n = 15)
SD
(n = 10)
Group effect
(p value)
Posthoc
(Direction of Effect)
Fluency 30.45 (7.44) 15.27 (7.50) 7.20 (6.70) p < .001 Controls > bvFTD >
SD
Originality 2.03 (0.23) 1.61 (0.33) 1.48 (0.44) p < .001 Controls > bvFTD, SD
Flexibility 8.45 (1.36) 5.07 (1.10) 2.70 (1.95) p < .001 Controls > bvFTD, SD
Running Head: Creativity in semantic dementia
17
A Kruskal-Wallis test revealed a significant main effect of group on Originality ratings, H
(2,42) = 16.44; p < .001. Bonferroni adjusted post-hoc pairwise comparisons revealed that, on
average, bvFTD and SD patients produced ideas that were less original compared to controls
(both p-values = .001). Originality of ideas did not differ significantly between the patient
groups (p = .54).
3.3.3 Flexibility
A Kruskal-Wallis test revealed a significant main effect of group on Flexibility, H (2, 42) =
34.69; p < .001. Bonferroni adjusted post-hoc pairwise comparisons indicated that bvFTD
and SD patients produced ideas that fell into fewer categories compared to controls (both p-
values < .001), with no significant difference between the patient groups (p = .19).
3.4 Correlations with Neuropsychological Measures
Next, we examined potential associations between the AUT scores and performance on
neuropsychological tests of interest in the two patient groups. For SD patients, AUT Fluency
was strongly associated with performance on the semantic association subtest of the
SYDBAT (r = .81, p < .01), while AUT Originality correlated with the naming (r = .784, p =
.01) and comprehension (r = .686, p < .05) subtests of the SYDBAT. No other significant
associations were evident in SD (all r < .5, all p-values > .1). For bvFTD patients, AUT
Fluency and Flexibility were not found to correlate with performance on any
neuropsychological measures (all r < .5, all p-values > .09). AUT Originality correlated with
letter fluency performance (r = .52, p < .05) and response inhibition on the Hayling test (r =
.679, p = .01), with no other significant associations found (all r < .5, all p-values > .06).
Controls did not complete the comprehensive neuropsychological test battery administered to
patients. When we explored potential associations between AUT performance and subscales
Running Head: Creativity in semantic dementia
18
of the ACE-III screening tool in controls, no significant correlations were found (all r < .5, all
p-values >.06).
3.5 Voxel-based morphometry analyses
3.5.1 Patterns of Atrophy
Relative to controls, patient groups displayed patterns of atrophy consistent with their clinical
diagnoses (see Supplementary Materials Figure 1 and Table 3). Briefly, bvFTD patients
showed decreased grey matter intensity in the right frontoinsular cortex, putamen and
temporal pole as well as in the left middle and superior frontal gyri. In contrast, SD patients
showed characteristic atrophy predominantly in the anterior temporal lobe bilaterally,
extending to the medial temporal lobe including the anterior and posterior parts of the
hippocampus, as well as the insula, basal ganglia, and orbitofrontal cortex. Although
bilateral, the burden of atrophy exhibited a left > right predominance, in keeping with
previous studies (Irish, Hodges, & Piguet, 2014; Nestor, Fryer, & Hodges, 2006). Direct
comparison of the patient groups revealed disproportionate atrophy in SD relative to bvFTD
patients in the bilateral anterior temporal lobe, medial temporal lobe including anterior
hippocampus, parahippocampal gyrus and amygdala, as well as insula, basal ganglia and
orbitofrontal cortex, more pronounced in the left than right hemisphere. The reverse contrast
failed to reveal any significant clusters (i.e., bvFTD relative to SD; see Supplementary
Materials Figure 2 and Table 3).
3.5.2 Neural correlates of divergent thinking performance
Voxel-wise whole-brain correlations across the entire sample were conducted to
explore associations between grey matter intensity and the three AUT measures (Fluency,
Originality, Flexibility; see Supplementary Materials Figure 3 and Table 4). Fluency of
Running Head: Creativity in semantic dementia
19
responses was associated with a left medial temporal cluster comprising the anterior
hippocampus and parahippocampal gyrus, as well as a left middle frontal gyrus cluster.
Flexibility of responses correlated with the left anterior hippocampus, the amygdala, and the
left middle frontal gyrus. Finally, Originality of responses correlated with the amygdala,
putamen, pallidum, and the same left middle frontal gyrus cluster.
As such, two main clusters were implicated across the AUT measures: (i) a left
medial temporal cluster including the anterior hippocampus, parahippocampal gyrus, and
amygdala, and (ii) the left middle frontal gyrus (Figure 2).
Figure 2. Convergence across AUT scores: overlapping voxel-wise correlations between
grey matter intensity and Fluency, Originality, and Flexibility measures. Separate models
exploring correlations between each AUT measure and grey matter intensity were run across
all participants (n = 39). Coloured regions show significant clusters extracted using a
statistical threshold of p
uncorrected
< .001 with a cluster size extent of 500 voxels (in MNI
space).
Running Head: Creativity in semantic dementia
20
3.5.3 Within-group region of interest correlations
Focusing on AUT Fluency as the primary measure of interest, we next explored within-group
correlations between grey matter intensity in the left medial temporal and left middle frontal
gyrus clusters and AUT Fluency in the bvFTD and SD groups separately (Table 3). In
bvFTD, the left middle frontal gyrus cluster was significantly associated with AUT Fluency,
while an association with the left medial temporal lobe cluster failed to survive conservative
Bonferroni correction. In SD, the left medial temporal cluster was correlated with AUT
Fluency and no significant associations emerged with the left middle frontal gyrus. Post hoc
power calculations were run using G*Power 3.1 and revealed an achieved power of 0.77 in
bvFTD and 0.81 in SD.
Table 3. Correlations between grey matter intensity and AUT Fluency performance.
Note – Left column: voxel-wise correlations across groups between grey matter intensity and
AUT Fluency, using a statistical threshold of p
uncorrected
< .001 with a cluster extent size of 500
voxels (in MNI space). t-values refer to the maximal t-values of the clusters. Right column:
Voxel-wise analysis: Region-based analysis:
across group correlations within group correlations
size in
mm3 t-value Coordinates (x, y, z) bvFTD SD
r p
r p
Left Medial
Temporal
Lobe
AUT
Fluency 1478 5.39 -26 -18 -9 .54 .05 .80 .006
Left Middle
Frontal Gyrus
AUT
Fluency 2700 4.77 -31 36 -13 .69 .007 .58 .08
Running Head: Creativity in semantic dementia
21
within-group Pearson’s correlations in bvFTD and SD groups between the mean grey matter
intensity (corrected for age, sex, total intracranial volume) and AUT Fluency. r = Pearson’s
correlation coefficient. Bold values indicate correlations that survive Bonferroni correction
for multiple comparisons (corrected threshold: p = .0125).
4. Discussion
The objective of this study was to explore the capacity for divergent thinking, and its
neural substrates, in a well-characterised cohort of patients with semantic dementia (SD) to
provide unique insights into the contribution of semantic processing to acts of creative
cognition. Our main finding was that, relative to controls, SD patients and a disease control
group of behavioural-variant FTD patients showed marked impairments on the AUT,
generating significantly fewer responses and uses that lacked originality and diversity. Voxel-
based morphometry analyses based on structural MRI enabled us to elucidate the neural bases
of these impairments, revealing a central role for medial temporal and prefrontal brain
regions in divergent thinking. Here, we discuss our findings in relation to the extant
functional neuroimaging literature on creativity, and emphasise the importance of lesion
studies in advancing our fundamental understanding of creative cognition.
The most striking finding from this study is our observation of profound impairments
in divergent thinking in SD, manifesting in a paucity of responses on the AUT and the
provision of responses which were less original and less diverse relative to controls. Looking
at the potential underlying cognitive mechanisms, the Fluency of responses in SD correlated
robustly with an independent measure of semantic association, which measures the ability to
make links between semantic concepts (Savage et al., 2013). Originality of responses in SD
was associated with measures of semantic naming and comprehension (Savage et al., 2013).
These findings are consistent with the idea that degeneration of the semantic knowledge base
Running Head: Creativity in semantic dementia
22
results in a narrowed repository from which AUT responses can be configured (Hass, 2017;
Kenett & Faust, 2019; Volle, 2018). By this view, the limited store of conceptual knowledge
in SD may result in a less flexible semantic memory structure that further hinders declarative
search processes (Kenett, Gold, & Faust, 2016; Kenett et al., 2018); Leon et al., 2014).
Divergent thinking performance in bvFTD was also found to be significantly
compromised across all AUT subscales relative to controls, converging with previous studies
(Ruggiero et al., 2019). This marked incapacity to generate uses that differ from the canonical
exemplar of an item dovetails with well-documented difficulties in set-shifting, taking the
perspectives of others, and disengaging from the immediate sensorium in this syndrome
(O'Callaghan, Shine, Hodges, Andrews-Hanna, & Irish, 2019), ultimately resulting in an
increasingly rigid and inflexible style of interacting with the world. In terms of cognitive
mechanisms, the originality of the responses generated by bvFTD patients correlated with
letter fluency and response inhibition, suggestive of difficulties with disengagement. Previous
studies have established the role of the prefrontal cortex in exerting top-down control to guide
the creative process (Benedek & Fink, 2019; Chrysikou, 2019; Gonen-Yaacovi et al., 2013).
The degeneration of the prefrontal cortex in this population may disrupt a number of
executive processes that support the strategic retrieval of information from memory, the
capacity to disengage from the exemplar item, and the ability to override or inhibit prepotent
responses when required to generate creative solutions (Chrysikou, 2019).
Our voxel-based morphometry analyses revealed important insights regarding the
neural bases of divergent thinking deficits in SD and bvFTD. Of note, we found two clusters
that were predominantly implicated in the Fluency of ideas generated on the AUT; namely a
left medial temporal lobe cluster centred on the left anterior hippocampus, and a left middle
frontal gyrus cluster. Current theories on the neural mechanisms that relate to the creative
process posit a frontal function that mediates flexibility and exertion of cognitive control
Running Head: Creativity in semantic dementia
23
(Benedek & Fink, 2019), and a temporal function that supports semantic integration and
insight (Shen et al., 2017). The left middle frontal gyrus cluster correlated strongly with AUT
performance in bvFTD, resonating with a large body of work implicating the frontal lobes in
the creative process (Beaty et al., 2016; Beaty et al., 2017; Beaty et al., 2019; Benedek &
Fink, 2019; Gonen-Yaacovi et al., 2013) and supporting the associations we found on the
behavioural level between divergent thinking performance and neuropsychological indices of
frontal lobe function.
In contrast, the left medial temporal cluster was found to correlate robustly with AUT
performance in the SD group. Our finding of a predominantly left anterior hippocampal
contribution to total Fluency of responses in SD resonates strongly with the proposal that the
hippocampus plays a critical role in creative and flexible forms of cognition (Beaty et al.,
2018; Madore et al., 2019; Rubin, Watson, Duff, & Cohen, 2014). Patients with hippocampal
lesions have been shown to perform poorly across figural and verbal creativity tasks (Duff,
Kurczek, Rubin, Cohen, & Tranel, 2013), and are unable to imagine new experiences
(Hassabis, Kumaran, Vann, & Maguire, 2007). Notably, the anterior hippocampus has been
suggested to support coarse global information (i.e., event gist) versus the fine-grained
representation of perceptual details in posterior subregions (i.e., specific event details; Brunec
et al., 2018). In the context of divergent thinking, anterior hippocampal atrophy may disrupt
the capacity to invoke abstracted features that generalise across different settings (Irish &
Vatansever, 2020). Looking at the nature of items generated on the AUT, SD patients often
defaulted to the canonical exemplar of the test item (e.g., for brick: ‘building’), and some
displayed a marked inability to deviate or move from the specific item category (e.g., ‘you
just use bricks to build all sorts of things like houses, apartment buildings and shopping
centres’). This was also evident to a lesser extent in the bvFTD group, aligning with their
characteristic perseverative tendencies. Importantly, however, SD patients relied heavily on
Running Head: Creativity in semantic dementia
24
their own previous experiences with the cue item (e.g., ‘what I find great that you can do is
just turn bricks into steps’) resonating strongly with recent studies suggesting a role for
episodic memory in creative thinking (Beaty et al., 2018; Madore et al., 2016; Madore et al.,
2019). This converges with findings on future simulation tasks, whereby SD patients
recapitulate or “recast” past episodic experiences in their entirety and appear unable to
construct novel or new experiences from scratch (Irish et al., 2012a, 2012b). As event-driven
representations come to dominate the mental landscape of SD, we therefore see an increase in
concrete, experience-dependent information on any open-ended cognitive task in which the
transfer of knowledge is required (see Irish & Vatansever, 2020). Here we demonstrate that
this preference for the familiar and concrete, driven by intact recent epsiodic memory,
extends to the arena of creative thinking and suggests a domain-general mechanism by which
SD patients compensate for their prominent semantic impairments (reviewed by Irish, 2020;
Irish & Vatansever, 2020).
As the undifferentiated repository of conceptual knowledge, semantic memory can be
harnessed at many different levels of abstraction and applied across contexts resulting in a
flexible system that is highly conducive to creative thought (Abraham, 2014; Irish, 2020;
Kenett & Faust, 2019). For this system to be efficient, elements from episodic and semantic
memory need to be extracted and recombined into a flexible representation that can be
deployed across multiple contexts (Addis, 2018). The hippocampus has a well-established
role in supporting the binding of arbitrary relations between elements into representations that
can be flexibly deployed across different contexts (Rubin et al., 2014). In this light,
hippocampal atrophy in SD may disrupt the relational binding of content derived from recent
episodic experiences and residual semantic concepts, resulting in increasingly inflexible and
rigid forms of thought (Irish & Vatansever 2020). We suggest that the degeneration of the
Running Head: Creativity in semantic dementia
25
semantic knowledge base in SD not only disrupts access to relevant conceptual information
but also the capacity to make appropriate associative links between concepts, a cognitive
process that is essential for arriving upon unique and creative responses (Kenett, 2018; Kenett
& Faust, 2019; Mednick, 1962; Volle, 2018). It will be important for future studies to
systematically test how the degradation of conceptual knowledge versus the disruption of
relational binding relates to divergent thinking impairments in SD.
Several methodological issues warrant consideration in the current context. Our
neuropsychological test battery was constrained due to the nature of these syndromes and the
need to minimise the risk of patient fatigue over what was already a lengthy testing session.
Future studies might consider exploring the role of disengagement in divergent thinking
further, by including measures such as those from the Wisconsin Card Sorting Test (Heaton,
Chelune, Talley, Kay, & Curtiss, 1993). Similarly, it would be interesting to continue to
explore how disruption to the binding of concepts influences divergent thinking by including
tests such as the Similarities subtest of the WAIS-IV (Wechsler, 2008) or Raven’s
Progressive Matrices (Raven & Raven, 2003). In addition, it will be important for future
studies to consider using non-verbal divergent thinking tasks to complement the outcomes on
the AUT, given variable profiles of loss and sparing observed in SD when verbal versus non-
verbal cognitive tasks are employed (Irish, 2020; Rankin et al., 2007).
Given the rarity of the SD syndrome, we combined left- and right-SD cases in the
current sample to maximise power. Although all of the SD cases showed bilateral anterior
temporal lobe atrophy at the time of this study, it remains unclear whether the lateralisation of
anterior temporal lobe damage observed in the early stages of the disease trajectory plays a
modulating role in divergent thinking disruption (see Supplementary Materials Table 2 for
individual SD patient scores). This will be important to address given reports of increased
rigidity and behavioural disturbances in the less prevalent right-sided presentation of SD
Running Head: Creativity in semantic dementia
26
(Kamminga et al., 2015). From a clinical perspective, understanding how rigidity of thought
relates to behavioural changes will prove particularly informative for carers, given
observations of increasingly rigid behaviours in SD and bvFTD, including strict adherence to
routines, fixed food preferences, and stereotypical and inflexible behaviours (Bozeat,
Gregory, Ralph, & Hodges, 2000; Kamminga, O'Callaghan, Hodges, & Irish, 2014). To equip
carers to deal with these behavioural changes, longitudinal studies will be essential to chart
how cognitive inflexibility potentially relates to behavioural disturbances, and the temporal
unfolding of these symptoms.
In summary, this study is the first, to our knowledge, to systematically explore the
cognitive and neural mechanisms underlying compromised divergent thinking capacity in SD
and bvFTD patients. Using SD as a lesion model for semantic memory, our findings
underscore the importance of the conceptual knowledge base for creative cognition. Notably,
the progressive deterioration of semantic knowledge in SD not only precludes access to
appropriate semantic constructs, but impairs the capacity to draw novel associations between
concepts in the service of divergent thinking. Future studies exploring the neurocognitive
mechanisms of semantic association will be important to refine our understanding of the
mechanisms by which humans arrive upon unique and creative ideas.
Acknowledgements
The authors are grateful to the study participants and their families for their continued
support of our research. This work forms a component of a PhD dissertation by TP who is
supported by a Research Training Program Scholarship from Macquarie University. DR is
supported by an ARC Discovery Project (DP180101548). MI is supported by an ARC Future
Fellowship (FT160100096). These funding sources were not involved in the study design, in
Running Head: Creativity in semantic dementia
27
the collection, analysis and interpretation of data, in the writing of the report, or in the
decision to submit the manuscript for publication.
Running Head: Creativity in semantic dementia
28
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