ArticlePDF Available

Abstract and Figures

Spinocerebellarataxiatype2(SCA2) is an autosomal dominant neurodegenerative disease involving the cerebellum. The particular atrophy pattern results in some typical clinical features mainly including motor deficits. In addition, the presence of cognitive impairments, involving language, visuospatial and executive functions, has been also shown in SCA2 patients and it is now widely accepted as a feature of the disease. The aim of the study is to investigate the microstructural patterns and the anatomo-functional substrate that could account for the cognitive symptomatology observed in SCA2 patients. In the present study, Diffusion tensor imaging (DTI) based-tractography was performed to map the main cerebellar white matter bundles, such as Middle and Superior Cerebellar Peduncles, connecting cerebellum with higher-order cerebral regions. Damage-related diffusivity measures were used to determine the pattern of pathological changes of cerebellar white matter microstructure in patients affected by SCA2 and correlated with the patients' cognitive scores. Our results provide the first evidence that white matter (WM) diffusivity is altered in the presence of the cerebellar cortical degeneration associated with SCA2 thus resulting in a cerebello-cerebral dysregulation that may account for the specificity of cognitive symptomatology observed in patients.
Content may be subject to copyright.
Accepted Manuscript
Microstructural MRI basis of the cognitive functions in patients with Spinocer-
ebellar ataxia type 2
G. Olivito, M. Lupo, C. Iacobacci, S. Clausi, S. Romano, M. Masciullo, M.
Molinari, M. Cercignani, M. Bozzali, M. Leggio
PII: S0306-4522(17)30726-1
DOI: https://doi.org/10.1016/j.neuroscience.2017.10.007
Reference: NSC 18072
To appear in: Neuroscience
Received Date: 20 June 2017
Accepted Date: 5 October 2017
Please cite this article as: G. Olivito, M. Lupo, C. Iacobacci, S. Clausi, S. Romano, M. Masciullo, M. Molinari, M.
Cercignani, M. Bozzali, M. Leggio, Microstructural MRI basis of the cognitive functions in patients with
Spinocerebellar ataxia type 2, Neuroscience (2017), doi: https://doi.org/10.1016/j.neuroscience.2017.10.007
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers
we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and
review of the resulting proof before it is published in its final form. Please note that during the production process
errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1
Microstructural MRI basis of the cognitive functions in patients with
Spinocerebellar ataxia type 2
G. Olivito1,2, M. Lupo1, C. Iacobacci1,3, S. Clausi1,4, S. Romano5, M. Masciullo6, M. Molinari7, M.
Cercignani2,8, M. Bozzali2,8, M. Leggio1,4.
1. Ataxia Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy;
2. Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy;
3. PhD Program in Behavioral Neuroscience, Sapienza University of Rome, Rome, Italy
4.Department of Psychology, Sapienza University of Rome, Italy;
5. Department of Neurosciences, Mental Health and Sensory Organs (NESMOS), “Sapienza” University of Rome -
Sant'Andrea Hospital, Rome, Italy ;
6. SPInalREhabilitation Lab, IRCCS Fondazione Santa Lucia, Rome, Italy;
7. Neurorehabilitation 1 and Spinal Center, Robotic Neurorehabilitation Lab, IRCCS Santa Lucia Foundation, Rome,
Italy.
8. Clinical Imaging Science Center, Brighton and Sussex Medical School, Brighton, UK.
Keywords: DTI; Tractography; Cerebellum; Cerebellar Peduncles; White Matter; Cognition.
Corresponding Author
Dr. Giusy Olivito, PhD
Email: g.olivito@hsantalucia.it
Ataxia Laboratory, IRCCS Santa Lucia Foundation, Via Ardeatina 306, 00179, Rome, Italy;
Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Via Ardeatina 306, 00179, Rome, Italy.
Telephone number: #39-06-51501547
2
Abstract
Spinocerebellar ataxia type 2 (SCA2) is an autosomal dominant neurodegenerative disease
involving the cerebellum. The particular atrophy pattern results in some typical clinical features
mainly including motor deficits. In addition, the presence of cognitive impairments, involving
language, visuospatial and executive functions, has been also shown in SCA2 patients and it is now
widely accepted as a feature of the disease. The aim of the study is to investigate the
microstructural patterns and the anatomo-functional substrate that could account for the cognitive
symptomatology observed in SCA2 patients. In the present study, Diffusion tensor imaging (DTI)
based-tractography was performed to map the main cerebellar white matter bundles, such as Middle
and Superior Cerebellar Peduncles, connecting cerebellum with higher-order cerebral regions.
Damage-related diffusivity measures were used to determine the pattern of pathological changes of
cerebellar white matter microstructure in patients affected b y SCA2 and correlated with the
patients’ cognitive scores. Our results provide the first evidence that white matter (WM) diffusivity
is altered in the presence of the cerebellar cortical degeneration associated with SCA2 thus resulting
in a cerebello-cerebral dysregulation that may account for the specificity of cognitive
symptomatology observed in patients.
3
Introduction
Spinocerebellar ataxia type 2 (SCA2) is an autosomal dominant neurodegenerative disease
characterized by a progressive cerebellar syndrome, typically affecting motor functions (Takahashi
et al., 2010). The cognitive performances of SCA2 patients have been exhaustively investigated and
it has been shown that patients affected by SCA2 present not only motor impairment but also a
cognitive symptomatology (Klinke et al., 2010; Fancellu et al., 2013; Moriarty et al., 2016), mainly
involving visuospatial and executive functions (LePira et al., 2002; Kawai et al., 2008).
From a neuropathological point of view, SCA2 present with a macroscopic pattern
of olivopontocerebellar atrophy as well with a pattern of neuronal loss in several and in cerebellar
cortex, and a diffuse damage of the brainstem and cerebellar white matter (WM) (Durr et al.,
1995; Gilman et al., 1996; Iwabuchi et al., 1999; Estrada et al., 1999; Pang et al., 2002). These
features have been depicted in vivo by Magnetic Resonance Imaging (MRI) studies using voxel
based morphometry (VBM) and diffusion tensor imaging (DTI) (Mandelli et al., 2007; Della Nave
et al., 2008a,b). Specifically, the cerebellar vermis and hemispheres show a pattern of extensive GM
loss with sparing of the vermian lobules I,II (lingula) and X (nodulus) and of the hemispheric
lobules I,II (lingula) and Crus II. Cerebellar WM damage has been shown to affect mainly the
peridentate regions and middle cerebellar peduncle (MCP) (Della Nave et al., 2008b). Consistent
with the hypothesis that cerebellar atrophy may affect also the regions connected with the
cerebellum (Dayan et al., 2016), several supratentorial areas have been found to be altered in SCA2,
such as the right orbito-frontal cortex, right temporo-mesial cortex, the primary sensorimotor cortex
bilaterally, the right thalamus, the left precentral gyrus and inferior frontal operculum as well as
inferior parietal and post-central gyri (Brenneis et al., 2003; Della Nave et al., 2008a). The
supratentorial atrophy can be related to both a primary degenerative process associated to SCA2
disease and to secondary effect resulting from the cerebellar deafferentation (Brenneis et al., 2003).
Furthermore, the interruption of cerebello-thalamo-cortical pathways has been reported as the
4
mechanism responsible for crossed cerebello-cerebral diaschisis (Broich et al., 1987; Boni et al.,
1992; Komaba et al., 2000).
Thus, it is possible to hypothesize that a disruption of cerebello-cerebral pathway is responsible for
structural and functional alteration of cortical areas. Middle (MCP) and Superior cerebellar
peduncles (SCP) are respectively the feedback and feedforward limbs of the cerebello-cortical
system through which the cerebellum receives information from cerebral regions and then sends
back the cerebellar-processed information to accomplish functions successfully. Therefore it is
reasonable that white matter alterations of the peduncles may reflect alteration in the cerebello-
cortical interactions and may be responsible for patients’ cognitive symptomatology.
DTI has proven to be a valuable tool for investigating brain WM since it can probe tissue
microstructure by assessing the displacement of water molecules within specific WM tracts (Basser
et al., 1994). In the brain the motion of water molecules is hindered by the local microstructure, as
they tend to diffuse in preferred directions corresponding to white matter fiber bundles orientation.
The diffusion tensor (DT) model is a simplistic diffusion MRI (dMRI) model which assumes only
one fiber direction per voxel. It is commonly used to quantify the diffusion process with DT-derived
metrics such as fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial
diffusivity (AD), which relate to the tendency of water molecules to move in a particular direction
(Alexander et al., 2007; Feldman et al., 2010). The 3D connectivity patterns of WM could be
investigating by using WM tractography, a well-established approach which follows coherent
spatial patterns in the major eigenvectors of the diffusion tensor field (Alexander et al., 2007) thus
providing a model of brain connectivity, through which brain disconnection can be studied.
Using different tracing methods, tractography algorithms are capable of generating anatomically
plausible estimates of WM trajectories in the human brain (Alexander et al., 2000, 2007). In
particular, more advanced diffusion imaging methods that allow multiple fiber directions to be
estimated, such as QBall Imaging (QBI) (Tuch et al., 2004) and the persistent angular structure
(PAS) (Jansons and Alexander, 2003) may be particularly suitable in the case of the cerebellum
5
since they are able to better resolve intersecting crossing WM regions, such as MCP and SCP
(Alexander et al.,2007; see also Dayan et al., 2016). Alterations of MCP and SCP dMRI metrics
(Della Nave et al, 2008b, 2011; Vieira Karuta et al., 2015) have been demonstrated in degenerative
ataxia patients, but no studies specifically used tractography to reconstruct these tracts and assessed
voxel-wise diffusivity alterations and their impact on cognitive outcomes of SCA2 patients.
The aim of this work is to investigate the microstructural organization of MCP and SCP,
reconstructed via tractography and to investigate the relationship between dMRI metrics and
cognitive subscores of SCA2 patients thus providing a novel contribution to understanding the
relationship between cerebello-cerebral disconnection likely to be associated with SCA2
neurodegenerative processes and the specific cognitive symptomatology.
Experimental Procedures
Participants
Nine patients affected by SCA2 [F/M=6/3; mean age ± SD = 47,6± 10.2 years], were recruited from
the Ataxia Lab of Foundation Santa Lucia Hospital. Both in-patients (admitted for rehabilitation)
and out-patients (followed up at the clinic) were included. At the time of assessment, all patients
had more than 6 months of illness from the genetically confirmed diagnosis. T2-weighted MRI
scans, acquired as part of this research study, were visually inspected by an expert neuroradiologist
to ensure the absence of any extra-cerebellar lesion.
The neurological examination of the patients showed that they all presented with a pure cerebellar
syndrome, except CA-3 (see Table 1) that presented the Babinski sign. A quantification of
cerebellar motor signs was also performed using the International Cooperative Ataxia Rating Scale
(ICARS, Trouillas et al., 1997), whose global score ranges from 0 (absence of any motor deficit) to
6
100 (presence of motor deficit at the highest degree). Demographic and clinical characteristics of
the patients are reported in Table 1.
A group of 25 healthy subjects (HS) [F/M=19/6] ranging from 40 to 60 years of age [mean age ±
SD = 53.8 ± 5.9 years] with no history of neurological or psychiatric illness were also recruited as
control group for the MRI protocol.
This research study was approved by the Ethics Committee of Santa Lucia Foundation, according to
the principles expressed in the Declaration of Helsinki. Written informed consent was obtained
from each subject.
Neuropsychological Assessment
SCA2 patients underwent a neuropsychological evaluation according to the evidence that in this
pathology specific cognitive domain are mainly involved, in particular visuospatial, executive and
attentional abilities (LePira et al., 2002; Kawai et al., 2008). For the cognitive assessment, the
following tests were used and then grouped by the functional domains that were measured: (Lezak,
1995):
- Wechsler Adult Intelligent Scale–revised Intelligent Quotient (Wechsler, 1981; Orsini and
Laicardi, 1997, 2003) and Raven’47 progressive matrices test (Raven, 1949) to analyze the
Intellectual level;
- Rey-Osterrieth Complex Figure Test (recall and copy) (Caffarra, 2002), forward and backword
Corsi (Corsi, 1972), and Wechsler Adult Intelligent Scale -revised block design subtest (Wechsler,
1981; Orsini and Laicardi, 1997, 2003) to analyze the visuospatial ability;
- Stroop Test (“time effect” and “error effect”) (Caffarra, 2002), semantic, phonological and verbal
fluency (Borkowskyet al., 1967), Wisconsinn Card Sorting Test (WCST) (Heaton et al., 2002), and
Tower of London procedure (TOL) (Krikorian et al., 1994), to analyze the executive functions;
-Trail Making Test B-A (Giovagnoli et al., 1996) to analyze the attention abilities.
The results of the neuropsychological assessment are reported in Table 2.
7
MRI acquisition protocol
The MRI examination was performed by using a 3T scanner (Magnetom Allegra, Siemens,
Erlangen, Germany) and the following scans were acquired: 1) dual-echo turbo spin echo [TSE]
(TR = 6190 ms, TE = 12/109 ms); 2) fast-FLAIR (TR = 8170 ms, 204TE = 96 ms, TI = 2100 ms);
3) 3D Modified Driven Equilibrium Fourier Transform (MDEFT) scan (TR = 1338 ms, TE = 2.4
ms, Matrix = 256 × 224×176, in-plane FOV=250×250mm2, slice thickness=1 mm); 4) diffusion
weighted Spin-Echo Echo Planar Imaging (SE EPI) along 61 non-collinear directions (TR=7 s,
TE=85 ms, b factor=1000 s/mm2, 45 contiguous slices volumes with a 2.3mm3 isotropic
reconstructed voxel size). Nine volumes without diffusion weighting (b=0) were also acquired.
MRI imaging and data analyses
DTI processing
Affine registration to the first non-diffusion weighted volume using FSL was done on DTI volumes
to correct for eddy currents and small head movements (Smith et al., 2004). After brain
segmentation with the BET utility (Smith, 2002), the diffusion tensor (DT) coefficients were
computed in Camino (Cook et al., 2006) to generate whole brain maps of the dMRI metrics,
including FA and MD. Additionally, to better characterize the tissue microstructure changes AD
and RD were also analyzed. Each FA volume was registered to the native space MDEFT volume
with a linear registration first, followed by a non-linear transformation. The target for the linear
registration was the skull-stripped MDEFT, while the original volume (including skull). was the
target for the non-linear transformation. The registration was achieved using the tools FLIRT
(Jenkinson et al., 2002) and FNIRT (Andersson et al., 2008) from FSL. This “FA to MDEFT”
transformation was combined with each individual “MDEFT to MNI” transformation, obtained by
non-linear registration of the MDEFT to the ICBM152 MNI template. This resulted in the final
transformation from each participant’s DTI space to the ICBM152 MNI template.
8
diffusion MRI based Tractography
It has been pointed out previously (Ye et al., 2013) that tractography based on DTI is not able to
adequately segment the SCP, and particularly the decussation of the SCP. Here MCP and SCP were
reconstructed using tractography based on two multi-fiber models implemented in Camino.
Specifically, QBall (Tuch, 2004) was used for MCP, as it provides less false positive fiber
components while PAS MRI (Janson and Alexander, 2003) was used for left (LSCP) and right
(RSCP) SCP, as it deals more effectively than QBall with fiber crossing. This procedure was
optimized in a previous study from our group (Dayan et al., 2016).
Once the multi-fiber directions were estimated, probabilistic tractography was carried out based on
these data using the PICo algorithm. N = 10000 tracking iterations were performed from each voxel
of the seed Region of Interest (ROI) with stopping criteria of FA 0:1 and curving angle 80°.
Five ROIs were manually drawn on the FA map images for MCP tracking. Cerebellar tract
reconstruction was performed using the same approach as in Dayan and colleagues (2016). The
SCP was segmented separately for each cerebellar hemisphere and two endpoint ROIs were chosen
so as to select all the fibers that continue posteriorly to the seed ROI, centered in the dentate
nucleus, and to include both the red nucleus and its medial area, contralaterally, where the SCP is
known to decussate (see Dayan et al., 2016).
In order to obtain a binary map of the “average tract”, every subject’s reconstructed MCP, LSCP
and RSCP maps were binarised using a probability threshold for probability index of connectivity
(PICo) maps computed by in-house software to minimize the amount of tract volume variation with
PICo threshold. These images were then warped into standard space using the FA to ICBM152
MNI space transformation previously calculated, and averaged. The resulting maps were
thresholded to retain only those voxels that were common to at least 50% of subjects.
9
Statistical Analysis
Neuropsychological assessment
For each tests, individual raw scores were converted to obtain a mean Z-score for each functional
domain. For the tests that lacked published normative data, individual z-scores were calculated with
reference to specific control groups using the following formula: (subject raw score population
mean)/population standard deviation (SD). Demographic and performance data of control groups
are reported in Table 3.
Published normative data were used for the following tests: Rey-Osterrieth Complex Figure Test,
(recall and copy versions), Raven’47 progressive matrices and Trail Making Test. No control
subject had history of neurological or psychiatric illness, and all controls were well matched with
regard to age and education (independent-sample t-test: p= not significant).
Voxel-wise analysis on white matter tracts
A voxel-wise analysis was performed in order to compare FA and MD changes differences in the
white matter between SCA2 patients and HS, restricting the comparison to the voxels of the MCP
and SCP, based on the average tract masks obtained as described above. T-contrasts were evaluated
with voxel significance set at p < 0.001 and corrected for family-wise error (FWE) at cluster level
with significance level chosen for p < 0.05. In order to better characterize the tissue microstructure
both FA and MD were used, while AD and RD were analyzed to help the interpretation of changes
to FA and MD (Alexander et al., 2007).
To remove the effect of confounding variables, the analysis was adjusted for age, since statistically
significant difference was found between patients and controls as assessed by the t-test analysis
(T=-2.23422; p=0.03). Although there was no difference in gender distribution between groups
(chi-square= 0.2962, df=1, p=0.58), sex was also set as covariate.
In order to investigate the relationship between WM damage and cognitive impairment Spearman
rank-order correlation coefficient was used to analyze possible correlations between individual
10
values of WM diffusivity, extracted using FSL command line from the FMRIB software library
(FSL, www.fmrib.ox.ac.uk/fsl/) and the correspondent neuropsychological scores.
Results
Subjects with cerebellar damage had negative Z-scores for all cognitive domain except for
Attention (0.14) (Fig 1).
The results of tractography were visually evaluated in every participant. In order to be deemed
successful, the segmentation had to fulfill the following criteria: the MCP included the transverse
pontine fibers both posterior and anterior to the corticospinal tracts and the SCP decussation was
visible at the level of the midbrain, as expected from known anatomy (see also Dayan et al., 2016).
Based on this procedure, MCP and SCPs were successfully reconstructed in all patients and HS. Fig
2 shows the 3D fiber reconstruction for the average MCP and SCP of both groups of subjects.
Voxel-wise comparisons between patients and HS were performed for each diffusion metric
separately in each tract (MCP, LSCP, RSCP). WM analysis showed a widespread pattern of WM
diffusivity alterations to affect MCP, LSCP and RSCP. Indeed, when compared to controls, SCA2
patients showed a significant decrease of FA and a significant increase of MD in all tracts examined.
When compared to controls, SCA2 patients also showed a significant increase of both AD and RD
to affect both the MCP and SCP, bilaterally.
Results are illustrated in Fig 3 and detailed statistics are reported in Table 4.
Regarding the relationship between WM damage and patients’ cognitive scores, Spearman’s
correlation analysis showed mean LSCP MD to be negatively correlated with the Visuospatial
11
ability (R= -0.67; p=0.05) and mean RSCP MD to be negatively correlated with Executive function
(R= -0.67; p=0.05).
No correlation was detected between FA and cognitive impairment.
Discussion
In the present study we aimed to investigate the pattern of WM changes associated with cerebellar
degeneration in SCA2 patients. dMRI based tractography was used to reconstruct the main
cerebellar WM tracts, namely MCP and SCP, and then to evaluate DTI metrics within those tracts.
Specifically, FA decrease and MD increase were found bilaterally in MCP and SCP of SCA2
patients compared to controls. This pattern is consistent with the presence of microstructural white
matter damage, although at this stage we can only speculate on the underlying pathology. Since the
examination of multiple DTI measures may provide more specific information about the tissue
microstructure (Alexander et al., 2007), AD and RD were also examined, in order to investigate the
combination of AD and RD changes that may underlie the decreased FA in the examined tracts. In
the present study, an increase of both AD and RD was also found to affect bilaterally MCP and SCP
of SCA2 patients.
FA is widely recognized as a marker of so-called white matter integrity and thus it is used as the
primary measure of tissue microstructural damage. Both demyelination and axonal loss can result in
reduced FA (Beaulieu, 2002; Song et al., 2002): indeed, when axons packing is not sufficiently
dense, more intercellular water will result in a less restriction of diffusion and therefore lowering
FA (Feldman et al., 2010). Although FA is a highly sensitive measure of tissue microstructure, it is
a non-specific biomarker of neuropathology. Further insight can be gained from the evaluation of
MD. Conversely to FA, MD has been shown to negatively correlate with fiber integrity (Beaulieu,
2002; Song et al., 2002). Although the exact pathological correlates of increased MD cannot be
established, it has been proposed that it predominantly reflects wallerian degeneration. Present
12
findings of MD increase thus might reflect fiber degeneration within the cerebellar peduncle as
often reported in SCA2 patients (Durr et al., 1995; Gilman et al., 1996; Iwabuchi et al., 1999;
Estrada et al., 1999; Pang et al., 2002).
While RD increase is largely accepted to correlate with myelin disruption (Alexander et al., 2007;
Feldman et al., 2010), human studies found increased AD in association with axonal degeneration
(Hasan et al., 2008; Roosendaal et al., 2009; Metwalli et al., 2010). Consistently, our data suggest
an increase in AD of SCA2 patients, which may reflect fiber degeneration. Similar results were
observed in patients affected by Friedriech’s ataxia (FRDA) (Della Nave et al., 2011). Indeed, it
has been postulated that the RD values increase with loss of myelin integrity in chronic
pathological conditions while the AD values increase in areas with reduced axonal density or
caliber (Hasan et al., 2008; Kumar et al., 2008, 2010; Della Nave et al., 2011). Further support to
this interpretation comes from DTI studies on murine models of acute lesions (Song et al., 2003;
Budde et al., 2007, 2009; Kim et al., 2010) suggesting that AD changes are characterized by a
time-dependent course with initial decrease during the acute phase followed by normalization or
increase in more advanced stages as axon fragments are cleared (Concha et al., 2006).
Consistently, increases of AD have been shown in chronically degenerated white matter bundles in
humans (Pierpaoli et al., 2001; Glenn et al., 2003). Thus, a significant increase of AD may feature
either in direct WM damage, i.e stroke and Multiple Sclerosis, (Bammer et al., 2000; Pierpaoli et
al., 2001) or in the more advanced stage of wallerian degeneration (Mandelli et al., 2007). DTI
metrics modifications have been already reported in the inferior, middle and superior cerebellar
peduncles of SCA2 patients (Della Nave et al., 2008b; Hernandez-Castillo et al., 2015). Those
studies, however, were based on tract-based spatial statistics (TBSS) (Smith et al., 2006), thus
investigating voxel-wise differences of the WM along the core of tracts. By contrast, we evaluated
the DTI Metrics for the whole tract, restricting the analysis to the fibers of interest tracked in each
subject (see also Roine et at., 2015).
13
A further element of novelty in this study is the observed relationship between cerebellar
microstructural damage and cognitive abilities in SCA2 patients, which was not investigated
previously. Interestingly, we found that cognitive functions typically altered in SCA2, i.e executive
and visuospatial functions (LePira et al., 2002; Kawai et al., 2008), correlate with damage of right
and left SCP respectively. This datum is in line with cerebellar lateralization of functions (Stoodley
and Schmahmann, 2008). According to the crossed cerebello-cerebral projections, negative Z-
scores of visuospatial functions negatively correlated with increased MD values in the left SCP, the
main cerebellar output tract connecting the cerebellum with right cerebral cortex, known to be
predominantly involved in visuospatial processing (Baillieux et al., 2010). The correlation between
executive functions and MD values in the right SCP is consistent with the evidence that left
prefrontal cortex plays a crucial role in many critical aspects of executive processing such as
strategy (Grafman et al., 2005; Vallesi et al., 2012), hypothesis generation (Reverberi et al., 2005),
and manipulations of goal hierarchies (Kaller, et al., 2011; Reverberi et al., 2005; Crescentini et al.,
2011; Langdon and Warrington, 2000).
Overall, our results show a specific pattern of white matter microstructural damage, likely to be
associated with SCA2 neurodegenerative processes, as expressed by the decrease of FA and the
increase of MD affecting bilateral MCP and SCP. This suggests that in SCA2 the cerebellar
atrophy also affects the diffusivity of the main cerebellar white matter tracts thus resulting in a
cerebello-cerebral dysregulation that may account for the cognitive symptomatology of SCA2
patients. Consistent with this interpretation, a previous DTI study in FDRA individuals (Zalensky et
al., 2014) has specifically shown that the interruption of the cerebellar afferent and efferent
connections leads to secondary functional effects in distant cortical and subcortical regions, a
phenomenon referred to as reverse cerebellar diaschisis, thus resulting in the cerebellar cognitive
affective syndrome (Schmahmann and Sherman 1998).
14
Furthermore, the fact that we found a precise lateralization of cognitive functions and structural
alterations indicating significant correlations of visuospatial functions with RSCP MD and
executive functions with LSCP MD, provides additional support to our conclusions.
In light of our results, we hypothesize a combination of demyelination, as expressed by increased
RD, and axonal changes, as expressed by AD increase, to affect the tracts examined. Taken
together our data suggest some heterogeneity of microstructural WM damage in SCA2 as
suggested also by Della Nave and colleagues (2008b).
However, it has to be considered that in the case of more complex diseases, where a combination
of demyelination, axon loss, gliosis, and inflammation may affect brain regions, the use of
integrated approaches with other imaging measures (e.g., T1, T2, magnetization transfer,
perfusion, fast/slow diffusion, spectroscopy) could improve the DTI information on the
neuropathology and the interpretation of diffusivity changes (Alexander et al., 2007). According
to this evidence, our interpretation of combined diffusivity changes in SCA2 patients needs
further investigation and should be confirmed in future studies.
It is also important to discuss some methodological limitations. First of all, it is important to
reiterate that typically diffusion MRI data are acquired with a resolution of 2-3 mm3, which is too
coarse to capture fine anatomical details. In addition, all tractography algorithms are at high risk
of both false positives and false negatives. Furthermore, reconstructing the SCP is notoriously
difficult because of the crossing occurring at their decussation. Several tractographic
reconstructions have failed (Zhang et al., 2008; Ye et al., 2012). Ye and colleagues (2013) have
proposed a method based on random forest classification, which can be trained to segment the
SCPs based on the shape of the diffusion tensor in every voxel. Instead, we used two
sophisticated models of diffusion, namely Q-ball and PAS MRI to rely exclusively on
tractography for the segmentation. Overall, this approach allowed us to independently analyze
which voxels along the tracts presented with DTI metrics changes.
15
The present findings are largely consistent with MRI studies that have investigated dMRI metrics
in patients affected by cerebellar atrophy of different etiology. Indeed, patterns of diffusivity WM
changes to affect FA and MD of MCP and/or SCP have been evidenced in SCA1, SCA2
(Mandelli et al., 2007) and SCA6 (Ying et al., 2006; Ye et al., 2013) patients. With the exception
of the study from Ye and colleagues (2013), that examines the FA and MD in SCA6 within the
whole volumes of the MCP and SCPs, all these studies measured dMRI metrics of the MCP and
SCPs in a Regions of Interest (ROI) limited to a single slice. The use of single slice can introduce
important bias and variations in the metric averaged over that region, depending on the particular
ROI position (Dayan et al., 2016). The use of tractography allows the whole bundle to be taken
into account, overcoming this limitation.
Furthermore, the present study demonstrates the sensitivity of dMRI to detect the microstructural
alterations linked to cognitive symptomatology in SCA2 patients. The additional correlation with
cognitive scores further support the idea that DTI metrics may serve as clinical imaging
biomarker to differentiate between different kinds of cerebellar neurodegenerative diseases, as
previously suggested in another study o f our group with mixed cerebellar ataxias (Dayan et al.,
2016).
In conclusion, we advance the hypothesis that microstructural WM damage in cerebellar
peduncles may account for the specificity of the cognitive impairment observed in SCA2 patients.
16
Acknowledgements
This work was supported by the Ministry of Education, Universities and Research (MIUR).-
(Grant Number C26A1329AR) to ML, and Ministry of Health (Grant Number RF-2011-
02348213) to MM and (Grant Number GR-2013-02354888) to SC.
Authors’ Contribution
Giusy Olivito, Maria Leggio, Marco Molinari and Marco Bozzali contributed to the study
conception and design and supervised development of work;
Marcella Masciullo and Silvia Romano contributed to recruitment and enrollment of patients;
Michela Lupo, Claudia Iacobacci and Silvia Clausi contributed to the acquisition and
interpretation of neuropsyhological data;
Michela Lupo contributed to the analysis of neuropsychological data;
Mara Cercignani contributed to the implementation of MRI protocol and analysis;
Giusy Olivito contributed to acquisition of MRI protocol, preprocessing and analysis of MRI
data.
Giusy Olivito contributed to the writing of the original manuscript;
All co-authors contributed to final editing and critical revision of the original manuscript.
Conflict of Interest
Conflicts of interest: none'.
17
References
Alexander AL, Hasan K, Kindlmann G, Parker DL, Tsuruda JS (2000), A geometric comparison of
diffusion anisotropy measures. Magn Reson Med 44:283–291.
Alexander AL, Lee JE, Lazar M, Field AS (2007), Diffusion Tensor Imaging of the Brain.
Neurotherapeutics 4(3): 316–329.
Andersson J, Smith S, Jenkinson M (2008), Fnirt-fmrib’s non-linear 24 image registration tool. In:
14th Annual Meeting of the Organization for Human Brain Mapping; 15–9.
Baillieux H, De Smet HJ, Dobbeleir A, Paquier PF, De Deyn PP, Mariën P (2010), Cognitive and
affective disturbances following focal cerebellar damage in adults: a neuropsychological and
SPECT study. Cortex 46(7):869-79.
Bammer R, Augustin M, Strasser-Fuchs S, Seifert T, Kapeller P, Stollberger, R, Ebner F, Hartung
HP, Fazekas F (2000), Magnetic resonance diffusion tensor imaging for characterizing diffuse and
focal abnormalities in multiple sclerosis. Magn Reson Med 44:583–591.
Basser PJ, Mattiello J, LeBihan D (1994), MR diffusion tensor spectroscopy and imaging. Biophys
Jl 66:259-67.
Beaulieu C (2002), The basis of anisotropic water diffusion in the nervous system - a technical
review. NMR Biomed 15:435–55.
Boni S, Valle G, Ciuffi RP, Sonetti MG, Perrone E, Tofani A, et al. (1992), Crossed cerebello-
cerebral diaschisis: a SPECT study. Nucl Med Commun 13:824–831.
Borkowsky JG, Benton AL, Spreen O (1967), Word fluency and brain-damage. Neuropsychologia
5: 135-140.
Brenneis C, Bosch SM, Schocke M, Wenning GK, Poewe W (2003), Atrophy pattern in SCA2
determined by voxel-based morphometry. Neuroreport 14:1799-1802.
Broich K, Hartmann A, Biersack HJ, Horn R (1987), Crossed cerebello-cerebral diaschisis in a
patient with cerebellar infarction. Neurosci Lett 83(1-2):7-12.
Budde MD, Kim JH, Liang HF et al. (2007), Toward accurate diagnosis of white matter pathology
using diffusion tensor imaging. Magn Reson Med 57:688–695.
Budde MD, Xie M, Cross AH et al. (2009), Axial diffusivity is the primary correlate of axonal
injury in the EAE spinal cord: a quantitative pixelwise analysis. J Neurosci 29:2805–2813.
Caffarra P, Vezzadini G, Dieci F, Zonato F, Venneri A (2002), Rey-Osterrieth complex figure:
normative values in an Italian population sample. Neurol Sci 22:443-7.
Concha L, Gross DW, Wheatley M et al. (2006), Diffusion tensor imaging of time dependent
axonal and myelin degradation after corpus callosotomy in epilepsy patients. NeuroImage 32:1090–
1099.
18
Cook PA, Bai Y, Gilani NS, Seunarine KK, Hall MG, Parker GJ, et al. (2006), Camino: Open-
source diffusion-MRI reconstruction and processing. In: 14th Scientific Meeting of the International
Society for Magnetic Resonance in Medicine; Seattle, USA.
Corsi PM (1972), Human memory and the medial temporal regions of the brain. Dissert Abst Int
34:891.
Crescentini C, Seyed-Allaei S, de Pisapia N, Jovicich J, Amati D, Shallice T (2011), Mechanisms of
rule acquisition and rule following in inductive reasoning. Journal of Neuroscience 31:7763-7774.
Dayan M, Olivito G, Molinari M, Cercignani M, Bozzali M, Leggio M (2016), Impact of cerebellar
atrophy on cortical gray matter and cerebellar peduncles as assessed by voxel-based morphometry
and high angular resolution diffusion imaging. Funct Neurol 31(4):239-248.
Della Nave R, Ginestroni A, Diciotti S, Salvatore E, Soricelli A, Mascalchi M (2011), Axial
diffusivity is increased in the degenerating superior cerebellar peduncles of Friedreich's ataxia.
Neuroradiology 53(5):367-72.
Della Nave R, Ginestroni A, Tessa C, Cosottini M, Giannelli M, Salvatore E, Sartucci F, De
Michele G, Dotti MT, Piacentini S, Mascalchi M (2008a), Brain structural damage in
spinocerebellar ataxia type 2. A voxel-based morphometry study. Mov Disord 23(6):899-903.
Della Nave R, Ginestroni A, Tessa C, Salvatore E, De Grandis D, Plasmati R, Salvi F, De Michele
G, Dotti MT, Piacentini S, Mascalchi M (2008b), Brain white matter damage in SCA1 and SCA2.
An in vivo study using voxel-based morphometry, histogram analysis of mean diffusivity and tract-
based spatial statistics. Neuroimage. 43(1):10-9.
Durr A, Smadja D, Cancel G, Lezin A, Stevanin G, Mikol J, et al. (1995), Autosomal dominant
cerebellar ataxia type I in Martinique (French West Indies),. Clinical and neuropathological analysis
of 53 patients from three unrelated SCA2 families. Brain 118:1573–81.
Estrada R, Galarraga J, Orozco G, Nodarse A, Auburger G (1999), Spinocerebellar ataxia 2
(SCA2),: morphometric analyses in 11 autopsies. Acta Neuropathol (Berl) 97: 306–10.
Fancellu R, Paridi D, Tomasello C, Panzeri M, Castaldo A, Genitrini S, Soliveri P, Girotti F (2013),
Longitudinal study of cognitive and psychiatric functions in spinocerebellar ataxia types 1 and 2. J
Neurol 260: 3134-43.
Feldman HM, Yeatman JD, Lee ES, Barde LHF, Gaman-Bean S (2010), Diffusion Tensor Imaging:
A Review for Pediatric Researchers and Clinicians. J Dev Behav Pediatr 31(4): 346–356.
Gilman S, Sima AA, Junck L, Kluin KJ, Koeppe RA, Lohman ME, et al. (1996), Spinocerebellar
ataxia type1 with multiple system degeneration and glial cytoplasmic inclusions. Ann Neurol 39:
241–55.
Giovagnoli AR, Del Pesce M, Mascheroni S, Simoncelli M, Laiacona M, Capitani E (1996), Trail
making test: normative values from 287 normal adult controls. Ital J Neurol Sci 17:305-9.
Glenn OA, Henry RG, Berman JI, Chang PC, Miller SP, Vigneron DB, et al. (2003), DTI-based
three-dimensional tractography detects differences in the pyramidal tracts of infants and children
with congenital hemiparesis. J Magn Reson Imaging 18:641– 648.
19
Grafman J, Spector L, Rattermann M J (2005), Planning and the brain. In R. Morris & G. Ward
(Eds.), The cognitive psychology of planning. Psychology Press 181-188.
Hasan KM, Halphen C, Boska MD, Narayana PA (2008), Diffusion tensor metrics, T2 relaxation,
and volumetry of the naturally aging human caudate nuclei in healthy young and middle-aged
adults: possible implications for the neurobiology of human brain aging and disease. Magn Reson
59(1):7-13.
Heaton RK, Chelune GJ, Talley JL, Kay GG, Curtiss G (2000), WCST: Wisconsin Card Sorting
Test. Forma completa revisionata. Adattamento italiano a cura di Hardoy MC, Carta MG, Hardoy
MJ e Cabras PL. Ed. It. O.S. Organizzazioni Speciali. Firenze.
Hernandez-Castillo CR, Galvez V, Mercadillo R, Diaz R, Campos-Romo A, Fernandez-Ruiz J.
(2015), Extensive White Matter Alterations and Its Correlations with Ataxia Severity in SCA 2
Patients. PLoS One, 10, e0135449.
Iwabuchi K, Tsuchiya K, Uchihara T, Yagishita S (1999), Autosomal dominant spinocerebellar
degenerations. Clinical, pathological, and genetic correlations. Rev Neurol (Paris) 155:255–70.
Janson KM, Alexander DC (2003), Persistent angular structure: new insights from diffusion
magnetic resonance imaging data. Inf Process Med Imaging 19:1031-1046.
Jenkinson M, Bannister P, Brady M, et al. (2002), Improved optimization for the robust and
accurate linear registration and motion correction of brain images. NeuroImage 17:825-41.
Kaller CP, Rahm B, Spreer J, Weiller C, Unterrainer JM (2011), Dissociable contributions of left
and right dorsolateral prefrontal cortex in planning. Cerebral Cortex 21:307-317.
Kawai Y, Suenaga M, Watanabe H, Sobue G (2009), Cognitive impairment in spinocerebellar
degeneration. Review. Eur Neurol 61(5):257-68.
Kim JH, Loy DN, Wang Q et al. (2010), Diffusion tensor imaging at 3 hours after traumatic spinal
cord injury predicts long-term locomotory recovery. J Neurotrauma 27:587–598.
Klinke I, Minnerop M, Schmitz-Hübsch T, Hendriks M, Klockgether T, Wüllner U, Helmstaedter C
(2010), Neuropsychological features of patients with Spinocerebellar Ataxia (SCA), Types 1,2,3,
and 6. Cerebellum 9:433-442.
Komaba Y, Osono E, Kitamura S, Katayama Y (2000), Crossed cerebellocerebral diaschisis in
patients with cerebellar stroke. Acta Neurol Scand 101(1):8-12.
Krikorian R, Bartok J, Gay N (1994), Tower of London procedure: a standard method and
developmental data. J Clin Exp Neuropsychol 16(6):840-50.
Kumar R, Macey PM, Woo MA, Alger JR, Harper RM (2008), Diffusion tensor imaging
demonstrates brainstem and cerebellar abnormalities in congenital central hypoventilation
syndrome. Pediatr Res 64(3):275–280.
Kumar R, Macey PM, Woo MA, Harper RM (2010), Rostral brain axonal injury in congenital
central hypoventilation syndrome. J Neurosci Res 88(10):2146–2154.
20
Langdon D, Warrington EK (2000), The role of the left hemisphere in verbal and spatial reasoning
tasks. Cortex 36:691-702.
Le Pira F, Zappalà G, Saponara R, Domina E, Restivo D, Reggio E, Nicoletti A, Giuffrida S (2002),
Cognitive findings in spinocerebellar ataxia type 2: relationship to genetic and clinical variables. J
Neurol Sci 201(1-2):53-7.
Lezak MD (1995), Neurpsychological assessment. 3rd edition. New York: Oxford University Press.
Mandelli ML, De Simone T, Minati L, Bruzzone MG, Mariotti C, Fancellu R, Savoiardo M, Grisoli
M (2007), Diffusion tensor imaging of spinocerebellar ataxias types 1 and 2. AJNR Am J
Neuroradiol 28(10):1996-2000.
Metwalli NS, Benatar M, Nair G, Usher S, Hu X, Carew JD (2010), Utility of axial and radial
diffusivity from diffusion tensor MRI as markers of neurodegeneration in amyotrophic lateral
sclerosis. Brain Research 1348:156-164.
Moriarty A, Cook A, Hunt H, Adams ME, Cipolotti L, Giunti P (2016), A longitudinal investigation
into cognition and disease progression in spinocerebellar ataxia types 1, 2, 3, 6, and 7. Orphanet J
Rare Dis 11: 82.
Orsini A, Laicardi C (1997), WAIS-R. Contributo alla taratura Italiana, Firenze Organizzazioni
Speciali.
Orsini A, Laicardi C (2003), Wais-r e terza età, Firenze Organizzazioni Speciali.
Pang JT, Giunti P, Chamberlain S, An SF, Vitaliani R, Scaravilli T, Martinian L, Wood NW,
Scaravilli F, Ansorge O (2002), Neuronal intranuclear inclusions in SCA2: a genetic, morphological
and immunohistochemical study of two cases. Brain 125:656–663.
Pierpaoli C, Barnett A, Pajevic S, Chen R, Penix Virta A, Basser P (2001), Water diffusion changes
in Wallerian degeneration and their dependance on white matter architecture. NeuroImage 13:1174–
1185.
Raven JC (1949), Progressive matrices, Sets A, Ab, B: Board and Book forms, LondonLewis.
Reverberi C, Lavaroni A, Gigli GL, Skrap M, Shallice T (2005), Specific impairments of rule
induction in different frontal lobe subgroups. Neuropsychologia 43:460-472.
Roine U, Salmi J, Roine T, Wendt TN, Leppämäki S, Rintahaka P, Tani P, Leemans A, Sams M
(2015), Constrained spherical deconvolution-based tractography and tract-based spatial statistics
show abnormal microstructural organization in Asperger syndrome. Mol Autism 6:4
Roosendaal SD, Geurts JJG, Vrenken H, Hulst HE, Cover KS, Castelijns JA, Pouwels PJW,
Barkhof F (2009), Regional DTI differences in multiple sclerosis patients. Neuroimage 44(4):1397-
1403.
Schmahmann JD, Sherman JC (1998), The cerebellar cognitive affective syndrome. Brain 121:561–
579.
21
Smith S, Jenkinson M, Woolrich M, Beckmann C, Behrens T, Johansen-Berg H, et al. (2004),
Advances in functional and structural MR image analysis and implementation as fsl. Neuroimage
23, S208–Conference on Mathematics in Brain Imaging, Jul 12-23, Los Angeles, CA.
Smith SM (2002), Fast robust automated brain extraction. Hum Brain Mapp 17:143-55.
Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, et al. (2006),
Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31:
1487-505.
Song SK, Sun SW, Ramsbottom MJ, Chang C, Russell J, Cross AH (2002), Dysmyelination
revealed through MRI as increased radial (but unchanged axial), diffusion of water. Neuroimage
17(3):1429-36.
Song SK, Sun SW, Ju WK et al. (2003), Diffusion tensor imaging detects and differentiates axon
and myelin degeneration in mouse optic nerve after retinal ischemia. NeuroImage 20:1714–1722.
Takahashi T, Katada S, Onodera O (2010), Polyglutamine diseases: wheredoes toxicity come from?
what is toxicity? where are we going? J Mol Cell Biol 2:180-191.
Trouillas P, Takayanagi T, Hallett M, Currier RD, Subramony SH, Wessel K, Bryer A, Diener HC,
Massaquoi S, Gomez CM, Coutinho P, Ben Hamida M, Campanella G, Filla A, Schut L, Timann D,
Honnorat J, Nighoghossian N, Manyam B (1997), International Cooperative Ataxia Rating Scale
for pharmacological assessment of the cerebellar syndrome. The Ataxia Neuropharmacology
Committee of the World Federation of Neurology. J Neurol Sci 145:205-11.
Tuch DS (2004), Q-ball imaging. Magn Reson Med 52:1358-1372.
Vallesi A (2012), Organisation of executive functions: Hemispheric asymmetries, Journal of
Cognitive Psychology 24(4):367-386.
Vieira Karuta SC, Raskin S, de Carvalho Neto A, Gasparetto EL, Doring T, Teive HA (2015),
Diffusion tensor imaging and tract-based spatial statistics analysis in Friedreich's ataxia patients.
Parkinsonism Relat Disord 21(5):504-8.
Zalesky A, Akhlaghi H, Corben LA, Bradshaw JL, Delatycki MB, Storey E, Georgiou-Karistianis
N, Egan GF (2014), Cerebello-cerebral connectivity deficits in Friedreich ataxia. Brain Structure
and Function 219(3):969-81.
Wechsler D (1981), Scala di intelligenza Wechsler per adulti rivisitata (WAIS-R), Manuale, Firenze
Organizzazioni Speciali.
Ye C, Bazin PL, Bogovic JA, Ying SH, Prince JL (2012), Labeling of the cerebellar peduncles
using a supervised Gaussian classifier with volumetric tract segmentation. Proceedings of SPIE
Medical Imaging 8314:143.
Ye C, Bogovic JA, Ying SH, Prince JL (2013), Segmentation of the complete superior cerebellar
peduncles using a multi-object geometric deformable model. 2013 IEEE 10th International
Symposium on Biomedical Imaging (ISBI) 49–52.
22
Ying SH, Choi SI, Perlman SL, Baloh RW, Zee DS, Toga AW (2006), Pontine and cerebellar
atrophy correlate with clinical disability in SCA2. Neurology 66:424-426.
Zhang H, Avants BB, Yushkevich PA, Woo JH, Wang S, McCluskey LF, Elman LB, Melhem ER,
Gee JC (2007), High-dimensional spatial normalization of diffusion tensor images improves the
detection of white matter differences: an example study using amyotrophic lateral sclerosis. IEEE
Transactions on Medical Imaging 26(11):1585–1597.
23
Figure Captions
Fig.1 Neuropsychological assessment. Mean and Standard Error of cognitive functions in the SCA
2 group expressed in Z-scores (mean Z-scores are reported). Neuropsychological functions
are grouped according to the cognitive domains assessed.
Fig.2 DTI-based tractography of middle and superior cerebellar peduncles. 3D reconstruction
of the average tract of MCP (red) LSCP (green) and RSCP (blue) with voxels belonging to at least
50% of the subjects. Reconstructed tracts are superimposed on the Spatially Unbiased Template of
the Cerebellum and Braistem (SUIT) (Diedrichsen et al., 2009). The decussation of the SCPs at
level of the ventral brainstem is clearly visible. A: anterior view; P: posterior view; S: superior
view.
Fig.3 Voxel-wise analysis of white matter tracts. Regions showing altered Fractional Anisotropy
(FA), Mean Diffusivity (MD) , Axial Diffusivity (AD) and Radial diffusivity (RD) in patients
compared to controls. Only clusters of significant diffusivity changes that survived after correction
for multiple comparisons are reported. Results are shown in different colors for the middle
cerebellar peduncle (red), left superior cerebellar peduncle (green), and right superior cerebellar
peduncle (blue), Clusters are superimposed on MNI (the Montreal Neurological Institute) template
in coronal, sagittal and axial slices.
*FWE uncorrected at p<0.001 at cluster level
24
Highlights
1) Cerebellar microstructural damage affects Middle and Superior Cerebellar Peduncle in
SCA2 patients.
2) Diffusivity changes predominantly reflect the white matter degeneration typically observed
in cerebellar atrophies
3) Diffusivity changes may reflect a dysregulation of cerebello-cerebral interaction
4) The pattern of cerebellar white matter damage is associated with impaired cognitive
performances of patients
25
26
Table 1. Demographic characteristics and motor deficit scores of the patients.
Case
code Age
Education Gender Years of illness CGA Repeats ICARS TOTAL
SCORES
(0-100)
CA-1
42
13 F
1 22/39
47
CA-2
42
18 F
1 22/39
28
CA-3
54
18 F
1 22/37
27
CA-4
36
13 F
8 22/42
37
CA-5
65
17 M
3 22/35
27
CA-6
44
13 F
13 -
28
CA-7
62
8 F
4
22/37
31
CA-8
41
8 M
3
22/38
18
CA-9
42
11 M
1 14/47
24
Mean(SD)
47.6(10.2)
13.2(3.8)
-
3.8 (4.1)
29.6(8.2)
Table 1. The table reports for each patients age, education, gender, years of illness, CGA repeats
and total motor scores as assessed by the International Cooperative Ataxia Rating Scale (ICARS)
(Trouillas et al., 1997) Means scores and standard deviations (SD) are also reported.
27
Table 2. Patients’ Neuropsychological raw scores.
TESTs
STROOP WCST
Cas
e
cod
e
TI
Q
P
M
fRE
Y
copy
fREY
delaye
d
F
C
B
C
B
D
Time
effec
t
Erro
r
effect
S
F
F
F
V
F
PEr
r
TEr
r
TO
L
TM
T B-
A
CA1 74 30 34 4.5 4 - 12 37.5 0
1
9 39 15 9 19 25 2
CA2 81 29 33 13 5 4 12 15.5 0 2
5 27 19 28 48 25 -
CA3 85 33 32 6.5 6 4 16 14.0
8 -0.5 1
9 44 24 7 18 24 45
CA4 91 35 31 13.5 4 4 22
19.7
3 0
2
1 29 13 4 7 30 48
CA5 82 30 27 8.5 5 4 8 31 0 2
3 27 12 8 16 32 49
CA6 98 29 28 8.5 5 5 28 9.5 0 3
0 42 19 5 8 27 68
CA7 75 30 30 9.5 6 6 10 25.5 1
2
2 23 6 18 44 27 156
CA8 91 34 33 22 6 5 23 12.5 0 1
8 19 10 6 18 34 192
CA9 84 34 35 16 7 6 21 39.5 0 2
1 24 10 15 29 34 66
TIQ : Total Intellectual Quotient; PM: Progressive matrices; fRey: Rey-Osterrieth Complex Figure;
FC: forward Corsi; BC: backword Corsi; BD: block design subtest; SF: semantic fluency; FF:
phonological fluency; VF: verbal fluency ; WCST: Wisconsinn Card Sorting Test (PErr:
perseverative errors; TErr: total errors); TOL: Tower of London; TMT : Trail Making Test.
28
Table 3. Demographic and performances data of the different control groups for each test.
T
est
A
ge (years)
E
ducation
Raw score
QI WAIS
-
r
96
45,18 (14,70)
11,65 (3,80)
104,45 (11,83)
Forward digit span
93
43,31
(14,
47
)
1
1
,
42
(3,7
6
)
5,86
(1,2
3
)
Back
ward digit span
93
43,31
(14,
47
)
1
1
,
42
(3,7
6
)
4,45 (
1,02
)
Forward Corsi
125
45,26
(
16,05
)
13,32 (4,44)
5,
82
(1,
1
9)
Backward Corsi
125
45,26
(
16,05
)
13,32 (4,44)
5,
34
(1,0
9
)
Semantic fluency
72
48,14
(
12,70
)
13,42
(
3,66
)
29,53
(
8,50
)
Phonological fluenc
y
72
48,14
(
12,70
)
13,42
(
3,66
)
40,77
(
10,18
)
Verbal fluency
43
47,44
(
12,11
)
13,91
(
3,48
)
18,09
(5,
13
)
Tower of London
43
47,44
(
12,11
)
13,91
(
3,48
)
31,02
(
2,50
)
Stroop Time effect
43
47,44
(
12,11
)
13,91
(
3,48
)
19,17
(1
0,00
)
Error
effe
ct
43
47,44
(
12,11
)
13,91
(
3,48
)
0,31
(
1,57
)
WCST n° errors
43
47,44
(
12,11
)
13,91
(
3,48
)
16,69
(
15,30
)
“ n° perseverative errors
43
47,44
(
12,11
)
13,91
(
3,48
)
7,95
(6,
85
)
29
Table 4. Statistics of whole brain voxel-wise analysis within the reconstructed tracts
FA (SCA2<HS)
Cluster
Size
Coordinates (mm)
Cluster
Peak
Z
-
score
x
y
z
MCP
LSCP
RSCP
984
10
-
42
-
36
7.71
104
-
10
-
46
-
28
7.53
72
12
-
44
-
34
6.85
MD (SCA2>HS)
AD(SCA2
>HS)
RD(SCA2
>HS)
(FWE
uncorrecte
d at p<
0.001)
MCP
668
16
-
36
-
30
6.83
575
-
14
-
38
-
30
6.69
LSCP
191
-
14
46
-
32
7.53
RSCP
140
20
-
52
-
32
6.93
MCP
392
14
-
38
-
28
6.47
299
-
14
-
38
-
28
6.16
LSCP
182
-
8
-
42
-
30
6.87
RSCP
141
-
10
-
42
-
26
6.13
MCP
1421
-
14
-
38
-
32
7.37
LSCP
187
-
14
-
36
-
32
7.63
RSCP
128
20
-
52
-
32
6.81
... The DN alteration is of particular interest, given the cerebellar anatomy. Indeed, the DN is the major cerebellar output channel connecting to the cerebral cortex (8), and modifications in functional connectivity (FC) within specific cerebello-cortical networks have already been described in patients affected by other forms of cerebellar atrophy (9)(10)(11)(12) and linked to motor, cognitive, and behavioral symptoms (13)(14)(15)(16)(17)(18)(19)(20)(21)(22). ...
... Thus, in view of these data, the verbal memory and language impairment shown by our SPG7 patients might be related to the atrophy in the cerebellar posterior lobules and in the lingual gyrus, while the "theory of mind" alterations might be linked to the atrophy in the precuneus and superior frontal gyrus, supporting the relevance of the functional alteration of cerebellocerebral networks implicated in different cognitive and social functions (10,12,66). ...
Article
Full-text available
Spastic paraplegia type 7 (SPG7), which represents one of the most common forms of autosomal recessive spastic paraplegia (MIM#607259), often manifests with a complicated phenotype, characterized by progressive spastic ataxia with evidence of cerebellar atrophy on brain MRI. Recent studies have documented the presence of peculiar dentate nucleus hyperintensities on T2-weighted images and frontal executive dysfunction in neuropsychological tests in SPG7 patients. Therefore, we decided to assess whether any particular MRI pattern might be specifically associated with SPG7 mutations and possibly correlated with patients' cognitive profiles. For this purpose, we evaluated six SPG7 patients, studying the cerebello-cortical network by MRI voxel-based morphometry and functional connectivity techniques, compared to 30 healthy control subjects. In parallel, we investigated the cognitive and social functioning of the SPG7 patients. Our results document specific cognitive alterations in language, verbal memory, and executive function in addition to an impairment of social task and emotional functions. The MRI scans showed a diffuse symmetric reduction in the cerebellar gray matter of the right lobule V, right Crus I, and bilateral lobule VI, together with a cerebral gray matter reduction in the lingual gyrus, precuneus, thalamus, and superior frontal gyrus. The evidence of an over-connectivity pattern between both the right and left cerebellar dentate nuclei and specific cerebral regions (the lateral occipital cortex, precuneus, left supramarginal gyrus, and left superior parietal lobule) confirms the presence of cerebello-cortical dysregulation in different networks involved in cognition and social functioning in SPG7 patients.
... Diffusion MR imaging, using regions of interest, histogram analyses or tractography or tract-based spatial statistics, allows one to quantitatively measure the symmetric distributed microstructural damage of the T2 hyperintense or normal white matter in the brainstem, cerebellar peduncles, cerebellum and corticospinal tracts of SCA2 gene carriers [9,17,[19][20][21][22][23] (Figure 4).Additional areas of increased diffusivity and decreased fractional anisotropy can be observed in the thalamus, corpus callosum and cerebral hemispheric white matter [17,20,21,23]. ...
... Generally, modifications of diffusion properties in the brain of SCA2 gene carriers correlated with ataxia severity [9,17,20,21], cognitive scores [22] and disease duration [17]. ...
Article
Full-text available
A variety of Magnetic Resonance (MR) and nuclear medicine (NM) techniques have been used in symptomatic and presymptomatic SCA2 gene carriers to explore,in vivo, the physiopathological biomarkers of the neurological dysfunctions characterizing the associated progressive disease that presents with a cerebellar syndrome, or less frequently, with a levodopa-responsive parkinsonian syndrome. Morphometry performed on T1-weighted images and diffusion MR imaging enable structural and microstructural evaluation of the brain in presymptomatic and symptomatic SCA2 gene carriers, in whom they show the typical pattern of olivopontocerebellar atrophy observed at neuropathological examination. Proton MR spectroscopy reveals, in the pons and cerebellum of SCA2 gene carriers,a more pronounced degree of abnormal neurochemical profile compared to other spinocerebellar ataxias with decreased NAA/Cr and Cho/Cr, increased mi/Cr ratios, and decreased NAA and increased mI concentrations. These neurochemical abnormalities are detectable also in presymtomatic gene carriers. Resting state functional MRI (rsfMRI) demonstrates decreased functional connectivity within the cerebellum and of the cerebellum with fronto-parietal cortices and basal ganglia in symptomatic SCA2 subjects. 18F-fluorodeoxyglucose Positron Emission Tomography (PET) shows a symmetric decrease of the glucose uptake in the cerebellar cortex, the dentate nucleus, the brainstem and the parahippocampal cortex. Single photon emission tomography and PET using several radiotracers have revealed almost symmetric nigrostriatal dopaminergic dysfunction irrespective of clinical signs of parkinsonism which are already present in presymtomatic gene carriers. Longitudinal small size studies have proven that morphometry and diffusion MR imaging can track neurodegeneration in SCA2, and hence serve as progression biomarkers. So far, such a capability has not been reported for proton MR spectroscopy, rsfMRI and NM techniques. A search for the best surrogate marker for future clinical trials represents the current challenge for the neuroimaging community.
... An extensive cerebellar volume loss was detected from early stages in Tg-69Q-ATXN3 mice and in MJD patients, accompanied by decrease of both cerebellar white and grey matter, and a clear increase of the fourth ventricle volume. These observations are in accordance with previous human MJD patients reports over atrophy of the cerebella [33][34][35], changes of white matter microstructure [36][37][38], as well as enlargement of the fourth ventricle documented from the initial disease stages [29,30] Machado-Joseph disease causes chronic axonal damage and extensive myelin degeneration in MJD [39]. Accordingly, we found pronounced loss of both white and grey matter in the cerebellum, irrespectively of the gender in human patients [37]. ...
Article
Full-text available
Machado-Joseph disease (MJD) or Spinocerebellar ataxia type 3 (SCA3) is the most common form of dominant SCA worldwide. Magnetic Resonance Imaging (MRI) and Proton Magnetic Resonance Spectroscopy (¹H-MRS) provide promising non-invasive diagnostic and follow-up tools, also serving to evaluate therapies efficacy. However, pre-clinical studies showing relationship between MRI-MRS based biomarkers and functional performance are missing, which hampers an efficient clinical translation of therapeutics. This study assessed motor behaviour, neurochemical profiles, and morphometry of the cerebellum of MJD transgenic mice and patients aiming at establishing magnetic-resonance-based biomarkers. ¹H-MRS and structural MRI measurements of MJD transgenic mice were performed with a 9.4 Tesla scanner, correlated with motor performance on rotarod and compared with data collected from human patients. We found decreased cerebellar white and grey matter and enlargement of the fourth ventricle in both MJD mice and human patients as compared to controls. N-acetylaspartate (NAA), NAA + N-acetylaspartylglutamate (NAA + NAAG), Glutamate, and Taurine, were significantly decreased in MJD mouse cerebellum regardless of age, whereas myo-Inositol (Ins) was increased at early time-points. Lower neurochemical ratios levels (NAA/Ins and NAA/total Choline), previously correlated with worse clinical status in SCAs, were also observed in MJD mice cerebella. NAA, NAA + NAAG, Glutamate, and Taurine were also positively correlated with MJD mice motor performance. Importantly, these ¹H-MRS results were largely analogous to those found for MJD in human studies and in our pilot data in human patients. We have established a magnetic resonance-based biomarker approach to monitor novel therapies in preclinical studies and human clinical trials.
... The presence of subtle neuropsychological impairment in the setting of significant GM atrophy of the posterior cerebellum along with the spectrum of neuropsychiatric features in our cohort supports the possibility of CCAS as an underlying pathogenic mechanism in SCA2. This is also supported by the observations of Olivito and colleagues [25,26]. ...
Article
Introduction Cognitive impairment is reported but is poorly explored in spinocerebellar ataxia 2 (SCA2). This study was undertaken to evaluate and classify cognitive impairment (CI) in patients with SCA2 and to identify their grey matter (GM) correlates. Methods We evaluated the neurocognitive profile of 35 SCA2 and 30 age-, gender- and education-matched healthy controls using tests for attention, executive functions, learning and memory, language and fluency, and visuomotor constructive ability. Patients were classified into SCA2 with and without CI based on normative data from population and healthy controls. Furthermore, patients with CI were sub-classified based on the number of impaired domains into multi-domain CI (≥3 domains; MDCI) and limited domain CI (≤2 domains; LDCI). The underlying GM changes were identified using voxel based morphometry. Results The mean age at onset, duration of disease, and ataxia score was 28.7 ± 8.51 years, 66.7 ± 44.1 months, and 16.1 ± 4.9 points, respectively. CI was present in 71.4 % of SCA2 subjects (MDCI: 42.7 %; LDCI: 28.5 %). Patients with CI had significant atrophy of the posterior cerebellum, sensorimotor cortex, and superior frontal gyrus (FWE p-value <0.05). Patients with MDCI had significant GM atrophy of the angular gyrus compared to LDCI (FWE p-value <0.05). Conclusion Patients with CI had significant GM involvement of the posterior cerebellum and frontal lobe, suggestive of impairment in the cerebello-fronto-cortical circuitry.
... Cognitive assessment was performed using a battery of cognitive tests including: Mini Mental State Examination Test (MMSE), digit span forward, copy and delayed recall of the Rey-Osterrieth complex figure (ROCF), phonemic (letters F-P-L) and semantic fluency tests (animals-fruits-car brands), and Symbol Digit Modalities Test (SDMT) (23)(24)(25). Scores were corrected for age, sex and education, according to the normative data. Disease duration was calculated based on subject's age at enrolment and age of ataxia manifestation. ...
Article
Full-text available
Spinocerebellar ataxias type 2 (SCA2) is an autosomal dominant inherited disease caused by expanded trinucleotide repeats (≥32 CAG) within the coding region of ATXN2 gene. Age of disease onset primarily depends on the length of the expanded region. The majority of subjects carrying the mutation remain free of clinical signs for few decades (“pre-symptomatic” stage), but in proximity of disease onset subtle neurophysiological, cognitive, and structural brain imaging changes may occur. Aims of the present study are to determine the time-window in which early clinical and neurodegenerative MRI changes may be identified, and to evaluate the rate of the disease progression in both preclinical and early disease phases. We performed a 1-year longitudinal study in 42 subjects: 14 SCA2 patients (mean age 39 years, disease duration 7 years, SARA score 9 points), 13 presymptomatic SCA2 subjects (preSCA2, mean age 39 years, expected time to disease onset 16 years), and 15 gene-negative healthy controls (mean age 33 years). All participants underwent genetic test, neurological examination, cognitive tests, and brain MRI. Evaluations were repeated at 1-year interval. Baseline MRI evaluations in SCA2 patients showed significant atrophy in cerebellum, brainstem, basal ganglia and cortex compared to controls, while preSCA2 subjects had isolated volume loss in the pons, and cortical thinning in specific frontal and parietal areas, namely rostral-middle-frontal and precuneus. One-year longitudinal follow-up demonstrated, in SCA2 patients, volume reduction in cerebellum, pons, superior cerebellar peduncles, and midbrain, and only in the cerebellum in preSCA2 subjects. No progression in clinical or cognitive measures was observed in preSCA2 subjects. The rate of volume loss in the cerebellum and subcortical regions greatly differed between patients and preSCA2. In conclusion, our pilot study demonstrated that MRI measures are highly sensitive to identify longitudinal structural changes in SCA2 patients, and in preSCA2 up to a decade before expected disease onset. These findings may contribute in the understanding of early neurodegenerative processes and may be useful in future therapeutical trials.
... The former, located in the anterior lobe (Lobules III-VI, and VIII), has connections with motor, somatosensory, visual, and auditory cortices (Schmahmann 1996(Schmahmann , 2004Kelly and Strick, 2003;Buckner, 2013), while the latter, in the posterior lobe (Lobules VIIa, Crus I, and II), has connections with prefrontal and posterior-parietal cortices related to cognition and emotion (Kelly andStrick, 2003, Ramnani, 2006). Accordingly, in addition to typical motor deficits (Takahashi et al., 2010), the presence of cognitive impairment has been shown in subjects with focal or degenerative cerebellar damage (Olivito et al., 2017aStoodley et al., 2016;Tedesco et al., 2011;Schmahmann, 1998). ...
Article
Alzheimer's disease (AD) is a chronic neurodegenerative disorder characterized by specific patterns of gray and white matter damage and cognitive/behavioral manifestations. The cerebellum has also been implicated in the pathophysiology of AD. Because the cerebellum is known to have strong functional connectivity (FC) with associative cerebral cortex regions, it is possible to hypothesize that it is incorporated into intrinsic FC networks relevant to cognitive manifestation of AD. In the present study, the cerebellar dentate nucleus, the largest cerebellar nucleus and the major output channel to the cerebral cortex, was chosen as the region of interest to test potential cerebellocerebral FC alterations and correlations with patients' memory impairment in a group of patients with AD. Compared to controls, patients with AD showed an increase in FC between the dentate nucleus and regions of the lateral temporal lobe. This study demonstrates that lower memory performances in AD may be related to altered FC within specific cerebellocortical functional modules, thus suggesting the cerebellar contribution to AD pathophysiology and typical memory dysfunctions.
Article
Clinical studies described emotional and social behaviour alterations in patients with cerebellar diseases, proposing a role of specific cerebello-cerebral circuits in social cognition. However, for a long time these difficulties were underestimated, and no studies have addressed the correlation between social cognition deficits and topography of the cerebellar damage. The present study aims to investigate the social cognition impairment and the neuroanatomical alterations in patients with spinocerebellar ataxia type 2 (SCA2) and to analyze their relationship. To this purpose a social cognition battery composed by three tests, and a MRI protocol were administered to 13 SCA2 patients and 26 healthy subjects. The pattern of gray matter (GM) atrophy was analyzed by voxel-based morphometry, and the GM volumes of each altered area were correlated with the behavioral scores to investigate anatomo-functional relationships. In addition, we investigated the relationship between social deficits and damage to the cerebellar peduncles using DTI diffusivity indices.Our patients showed impairment of the immediate perceptual component of the mental state recognition (i.e. to recognize feelin gs and thoughts from the eyes expression), and difficulties in anger attribution, and in the understanding of false or mistaken beliefs. They showed a pattern of GM reduction in specific cerebellar regions, including lobules IX and VIIIb and Crus II, all of which are involved in specific components of the mentalizing process. Interestingly, the behavioral performance, in which SCA2 patients showed impairments compared to controls, correlated with the degree of cerebellar GM reduction and with the presence of microstructural abnormalities in the cerebellar peduncles. The present study provides the first characterization of some areas of the social cognition deficits in a homogenous cohort SCA2 patients and demonstrates that alterations in specific cerebellar regions should represent the neurobiological underpinning of their social behavior difficulties. Our results offer a new point of view in considering these aspects in the clinical practice.
Book
This edited volume provides the first presentation of the state-of-the-art in the application of modern Neuroscience research in predicting, preventing and alleviating the negative sequelae of neurodevelopmental, acquired, or neurodegenerative conditions on speech and language. It brings together contributions from several leading experts in a markedly broad range of disciplines, including Speech and Language Therapy, Neuropsychology and Neurology, but also Neurosurgery, Neuroimaging and Neurostimulation, as well as Engineering and Genetics.
Chapter
Approaches to thinking about the cerebellum have historically been overshadowed by the view that it is a structure mainly involved in the regulation and coordination of motor control. During the past decades, neuroanatomical, neuroimaging, and clinical studies have substantially modified this traditional view and provided new insights and a body of evidence for cerebellar involvement in a wide range of nonmotor processes, such as cognitive, affective, and social processes. Within the broad range of functions in which the cerebellum is involved, several clinical studies have shown the occurrence of different types of speech and language impairments subsequent to cerebellar damage. In the first part of the present chapter, we briefly summarize the motor and nonmotor language impairments that have been reported after cerebellar damage in adults and the associated cerebello-cerebral network alterations. Starting from these clinical and neuroimaging data about the “linguistic cerebellum,” in the second part of the chapter, we provide an overview of the studies that used noninvasive transcranial neuromodulation techniques to further investigate the cerebellar role in speech and language domains. Furthermore, we show the current state of the art and translational potential of the use of cerebellar neuromodulation to improve speech and language functions after cortical and subcortical damage.
Article
Full-text available
In recent years, increasing evidence of the cerebellar role in social cognition has emerged. The cerebellum has been shown to modulate cortical activity of social brain regions serving as a regulator of function-specific mentalizing and mirroring processes. In particular, a mentalizing area in the posterior cerebellum, specifically Crus II, is preferentially recruited for more complex and abstract forms of social processing, together with mentalizing cerebral areas including the dorsal medial prefrontal cortex (dmPFC), the temporo-parietal junction (TPJ), and the precuneus. In the present study, the network-based statistics approach was used to assess functional connectivity (FC) differences within this mentalizing cerebello-cerebral network associated with a specific cerebellar damage. To this aim, patients affected by spinocerebellar ataxia type 2 (SCA2), a neurodegenerative disease specifically affecting regions of the cerebellar cortex, and age-matched healthy subjects have been enrolled. The dmPFC, left and right TPJ, the precuneus, and the cerebellar Crus II were used as regions of interest to construct the mentalizing network to be analyzed and evaluate pairwise functional relations between them. When compared with controls, SCA2 patients showed altered internodal connectivity between dmPFC, left (L-) and right (R-) TPJ, and right posterior cerebellar Crus II. The present results indicate that FC changes affect a function-specific mentalizing network in patients affected by cerebellar damage. In particular, they allow to better clarify functional alteration mechanisms driven by the cerebellar damage associated with SCA2 suggesting that selective cortico-cerebellar functional disconnections may underlie patients’ social impairment in domain-specific complex and abstract forms of social functioning.
Article
Full-text available
Background: The natural history of clinical symptoms in the spinocerebellar ataxias (SCA)s has been well characterised. However there is little longitudinal data comparing cognitive changes in the most common SCA subtypes over time. The present study provides a preliminary longitudinal characterisation of the clinical and cognitive profiles in patients with SCA1, SCA2, SCA3, SCA6 and SCA7, with the aim of elucidating the role of the cerebellum in cognition. Methods: 13 patients with different SCAs all caused by CAG repeat expansion (SCA1, n = 2; SCA2, n = 2; SCA3, n = 2; SCA6, n = 4; and SCA7, n = 3) completed a comprehensive battery of cognitive and mood assessments at two time points, a mean of 7.35 years apart. All patients were evaluated clinically using the Scale for the Rating and Assessment of Ataxia (SARA) and the Inventory of Non-Ataxia Signs (INAS). Patients underwent structural MRI imaging at follow-up. Results: Clinical scale scores increased in all patients over time, most prominently in the SCA1 (SARA) and SCA3 (INAS) groups. New impairments on neuropsychological tests were most commonly observed with executive functions, speed, attention, visual memory and Theory of Mind. Results suggest possible differences in cognitive decline in SCA subtypes, with the most rapid cognitive decline observed in the SCA1 patients, and the least in the SCA6 patients, congruent with observed patterns of motor deterioration. Minimal changes in mood were observed, and MRI measures of atrophy did not correlate with cognitive decline. Conclusion: As well as increasing physical impairment, cognitive decline over time appears to be a distinct aspect of the SCA phenotype, in keeping with the cerebellar cognitive-affective syndrome. Our data suggest a trend of cognitive decline that is different for each SCA subtype, and for the majority is related to the severity of cerebellar motor impairment.
Article
Full-text available
Background: Previous studies of SCA2 have revealed significant degeneration of white matter tracts in cerebellar and cerebral regions. The motor deficit in these patients may be attributable to the degradation of projection fibers associated with the underlying neurodegenerative process. However, this relationship remains unclear. Statistical analysis of diffusion tensor imaging enables an unbiased whole-brain quantitative comparison of the diffusion proprieties of white matter tracts in vivo. Methods: Fourteen genetically confirmed SCA2 patients and aged-matched healthy controls participated in the study. Tract-based spatial statistics were performed to analyze structural white matter damage using two different measurements: fractional anisotropy (FA) and mean diffusivity (MD). Significant diffusion differences were correlated with the patient's ataxia impairment. Results: Our analysis revealed decreased FA mainly in the inferior/middle/superior cerebellar peduncles, the bilateral posterior limb of the internal capsule and the bilateral superior corona radiata. Increases in MD were found mainly in cerebellar white matter, medial lemniscus, and middle cerebellar peduncle, among other regions. Clinical impairment measured with the SARA score correlated with FA in superior parietal white matter and bilateral anterior corona radiata. Correlations with MD were found in cerebellar white matter and the middle cerebellar peduncle. Conclusion: Our findings show significant correlations between diffusion measurements in key areas affected in SCA2 and measures of motor impairment, suggesting a disruption of information flow between motor and sensory-integration areas. These findings result in a more comprehensive view of the clinical impact of the white matter degeneration in SCA2.
Article
Full-text available
Background The aim of this study was to investigate potential differences in neural structure in individuals with Asperger syndrome (AS), high-functioning individuals with autism spectrum disorder (ASD). The main symptoms of AS are severe impairments in social interactions and restricted or repetitive patterns of behaviors, interests or activities. Methods Diffusion weighted magnetic resonance imaging data were acquired for 14 adult males with AS and 19 age, sex and IQ-matched controls. Voxelwise group differences in fractional anisotropy (FA) were studied with tract-based spatial statistics (TBSS). Based on the results of TBSS, a tract-level comparison was performed with constrained spherical deconvolution (CSD)-based tractography, which is able to detect complex (for example, crossing) fiber configurations. In addition, to investigate the relationship between the microstructural changes and the severity of symptoms, we looked for correlations between FA and the Autism Spectrum Quotient (AQ), Empathy Quotient and Systemizing Quotient. Results TBSS revealed widely distributed local increases in FA bilaterally in individuals with AS, most prominent in the temporal part of the superior longitudinal fasciculus, corticospinal tract, splenium of corpus callosum, anterior thalamic radiation, inferior fronto-occipital fasciculus (IFO), posterior thalamic radiation, uncinate fasciculus and inferior longitudinal fasciculus (ILF). CSD-based tractography also showed increases in the FA in multiple tracts. However, only the difference in the left ILF was significant after a Bonferroni correction. These results were not explained by the complexity of microstructural organization, measured using the planar diffusion coefficient. In addition, we found a correlation between AQ and FA in the right IFO in the whole group. Conclusions Our results suggest that there are local and tract-level abnormalities in white matter (WM) microstructure in our homogenous and carefully characterized group of adults with AS, most prominent in the left ILF.
Article
Full-text available
Introduction Diffusion-MRI is a rapidly evolving research field that has produced a wealth of algorithms for the analysis of white matter fibre architecture and disorders in the brain. Camino is a free, open-source toolkit designed to make a selection of this technology available and convenient to use for the diffusion MRI research community. Camino implements a data processing pipeline, which allows for easy scripting and flexible integration with other software. This abstract summarises the features of Camino at each stage of the pipeline from the raw data to the statistics used by clinicians and researchers. Design Camino is written in Java, and designed for a Unix-style interface. The user documentation is in the form of Unix manual pages, and each program has a shell wrapper, so users do not require any knowledge of Java. The data pipeline provides flexibility, by allowing data to be imported and exported to other software, and transparency, because the output of each Camino program can be analyzed in detail. Fig. 1 illustrates the pipeline. Camino processes all data in voxel order, where the measurements for each voxel are stored together. This ordering facilitates the data pipeline model and allows each voxel to be processed independently, which simplifies parallel processing. All of Camino's output is in a documented raw binary format. The tractography module optionally outputs Analyze images for easy integration with visualisation software. Data The data source for Camino can be raw data from a scanner or from Camino's data synthesiser. The data synthesiser emulates scanner sequences and provides synthetic data from a range of customisable test functions. Data from scanners is not typically in voxel order, so Camino contains tools for rearranging data into the correct format. Associated with each data file is the scheme file, which is a text file that describes the acquisition parameters for each measurement.
Article
Full-text available
This address provides a review of evidence for a deconstruction of executive functions, the set of cognitive operations which allow goal-directed behaviour. The underlying working hypothesis is that some complementary and computationally diverse executive functions are dissociable not only functionally but also temporally and anatomically, along the left-right axis of prefrontal cortex and related neural networks. In particular, criterion setting—the capacity to flexibly set up and select task rules—is more left-lateralised; monitoring—the process of continuously evaluating the internal or external contingencies to optimise behaviour—is more right-lateralised; finally, superior medial prefrontal regions, including dorsal anterior cingulate cortex, play a role in energising weakly activated but relevant processes. Several lines of empirical evidence, including neuroimaging and neuropsychological findings, are presented to support this tripartite model of executive functions. Evidence which is difficult to explain with this model and some future directions are also discussed.
Article
In recent years the cerebellum has been attributed amore important role in higher-level functions than previously believed. We examined a cohort of patients suffering from cerebellar atrophy resulting in ataxia, with two main objectives: first to investigate which regions of the cerebrum were affected by the cerebellar degeneration, and second to assess whether diffusion magnetic resonance imaging (dMRI) metrics within the medial (MCP) and superior cerebellar peduncle (SCP) - namely fractional anisotropy (FA) and radial diffusivity (RD) - could be used as a biomarker in patients with this condition. Structural and dMRI data of seven patients with cerebellar atrophy (2 with spinocerebellar atrophy type 2, 1 with Friedreich's ataxia, 4 with idiopathic cerebellar ataxia) and no visible cortical lesions or cortical atrophy were investigated with Freesurfer and voxel-based morphometry (VBM) of gray matter (GM) as well as MCP and SCP FA maps. Correlations of MCP and SCP mean FA with ataxia scores and subscores were also evaluated. Freesurfer showed that patients had significantly reduced volume of the thalamus, ventral diencephalon and pallidum. VBM also demonstrated significantly lower local GM volumes in patients, notably in the head of the caudate nucleus, posterior cingulate gyrus and orbitofrontal cortex bilaterally, as well as in Broca's area in the left hemisphere, and a significant increase in RD in the MCP and SCP of both hemispheres. A significant correlation was found between MCP mean FA and total ataxia score (R=-0.7, p=0.03), and subscores for kinetic functions (R=-0.74, p=0.03) and oculomotor disorders (R=-0.70, p=0.04). The regions of the cerebrum found to have significantly lower local GM volumes have been described to be involved in higher-level cerebellar functions such as initiation of voluntary movements, emotional control, memory retrieval and general cognition. Our findings corroborate recent research pointing to a more extensive corticocerebellar system than previously thought. The significant difference in the MCP and SCP dMRI metrics between patients and controls as well as the significant correlation with ataxia total score and subscores support the use of dMRI metrics as an imaging biomarker for cerebellar degeneration and ataxia.
Article
The superior cerebellar peduncles (SCPs) are white matter tracts that serve as the major efferent pathways from the cerebellum to the thalamus. With diffusion tensor images (DTI), tractography algorithms or volumetric segmentation methods have been able to reconstruct part of the SCPs. However, when the fibers cross, the primary eigenvector (PEV) no longer represents the primary diffusion direction. Therefore, at the crossing of the left and right SCP, known as the decussation of the SCPs (dSCP), fiber tracts propagate incorrectly. To our knowledge, previous methods have not been able to segment the SCPs correctly. In this work, we explore the diffusion properties and seek to volumetrically segment the complete SCPs. The non-crossing SCPs and dSCP are modeled as different objects. A multi-object geometric deformable model is employed to define the boundaries of each piece of the SCPs, with the forces derived from diffusion properties as well as the PEV. We tested our method on a software phantom and real subjects. Results indicate that our method is able to the resolve the crossing and segment the complete SCPs with repeatability.
Article
The cerebellar peduncles are white matter tracts that play an important role in the communication of the cerebellum with other regions of the brain. They can be grouped into three fiber bundles: inferior cerebellar peduncle middle cerebellar peduncle, and superior cerebellar peduncle. Their automatic segmentation on diffusion tensor images would enable a better understanding of the cerebellum and would be less time-consuming and more reproducible than manual delineation. This paper presents a method that automatically labels the three fiber bundles based on the segmentatin results from the diffusion oriented tract segmentation (DOTS) algorithm, which achieves volume segmentation of white matter tracts using a Markov random field (MRF) framework. We use the DOTS labeling result as a guide to determine the classification of fibers produced by wild bootstrap probabilistic tractography. Mean distances from each fiber to each DOTS volume label are defined and then used as features that contribute to classification. A supervised Gaussian classifier is employed to label the fibers. Manually delineated cerebellar peduncles serve as training data to determine the parameters of class probabilities for each label. Fibers are labeled ad the class that has the highest posterior probability. An outlier detection ste[ re,pves fober tracts that belong to noise of that are not modeled by DOTS. Experiments show a successful classification of the cerebellar peduncles. We have also compared results between successive scans to demonstrate the reproducibility of the proposed method.
Article
The role of the cerebellum in cognition, both in healthy subjects and in patients with cerebellar diseases, is debated. Neuropsychological studies in spinocerebellar ataxia type 1 (SCA1) and type 2 (SCA2) demonstrated impairments in executive functions, verbal memory, and visuospatial performances, but prospective evaluations are not available. Our aims were to assess progression of cognitive and psychiatric functions in patients with SCA1 and SCA2 in a longitudinal study. We evaluated at baseline 20 patients with SCA1, 22 patients with SCA2 and 17 matched controls. Two subgroups of patients (9 SCA1, 11 SCA2) were re-evaluated after 2 years. We tested cognitive functions (Mini Mental State Examination, digit span, Corsi span, verbal memory, attentional matrices, modified Wisconsin Card Sorting Test, Raven Progressive Matrices, Benton test, phonemic and semantic fluency), psychiatric status (Scales for Assessment of Negative and Positive Symptoms, Hamilton Depression and Anxiety Scales), neurological conditions (Scale for Assessment and Rating of Ataxia), and functional abilities (Unified Huntington Disease Rating Scale-part IV). At baseline, SCA1 and SCA2 patients had significant deficits compared to controls, mainly in executive functions (phonemic and semantic fluencies, attentional matrices); SCA2 showed further impairment in visuospatial and visuoperceptive tests (Raven matrices, Benton test, Corsi span). Both SCA groups had higher depression and negative symptoms, particularly apathy, compared to controls. After 2 years, motor and functional disability worsened, while only attentive performances deteriorated in SCA2. This longitudinal study showed dissociation in progression of motor disability and cognitive impairment, suggesting that in SCA1 and SCA2 motor and cognitive functions might be involved with different progression rates.