Comparison of univariate and multivariate analyses for brain [18F]FDG PET data in α-synucleinopathies.

BACKGROUND: Brain imaging with [18F]FDG-PET can support the diagnostic work-up of patients with α-synucleinopathies. Validated data analysis approaches are necessary to evaluate disease-specific brain metabolism patterns in neurodegenerative disorders. This study compared the univariate Statistical Parametric Mapping (SPM) single-subject procedure and the multivariate Scaled Subprofile Model/Principal Component Analysis (SSM/PCA) in a cohort of patients with α-synucleinopathies. METHODS: We included [18F]FDG-PET scans of 122 subjects within the α-synucleinopathy spectrum: Parkinson's Disease (PD) normal cognition on long-term follow-up (PD - low risk to dementia (LDR); n = 28), PD who developed dementia on clinical follow-up (PD - high risk of dementia (HDR); n = 16), Dementia with Lewy Bodies (DLB; n = 67), and Multiple System Atrophy (MSA; n = 11). We also included [18F]FDG-PET scans of isolated REM sleep behaviour disorder (iRBD; n = 51) subjects with a high risk of developing a manifest α-synucleinopathy. Each [18F]FDG-PET scan was compared with 112 healthy controls using SPM procedures. In the SSM/PCA approach, we computed the individual scores of previously identified patterns for PD, DLB, and MSA: PD-related patterns (PDRP), DLBRP, and MSARP. We used ROC curves to compare the diagnostic performances of SPM t-maps (visual rating) and SSM/PCA individual pattern scores in identifying each clinical condition across the spectrum. Specifically, we used the clinical diagnoses ("gold standard") as our reference in ROC curves to evaluate the accuracy of the two methods. Experts in movement disorders and dementia made all the diagnoses according to the current clinical criteria of each disease (PD, DLB and MSA). RESULTS: The visual rating of SPM t-maps showed higher performance (AUC: 0.995, specificity: 0.989, sensitivity 1.000) than PDRP z-scores (AUC: 0.818, specificity: 0.734, sensitivity 1.000) in differentiating PD-LDR from other α-synucleinopathies (PD-HDR, DLB and MSA). This result was mainly driven by the ability of SPM t-maps to reveal the limited or absent brain hypometabolism characteristics of PD-LDR. Both SPM t-maps visual rating and SSM/PCA z-scores showed high performance in identifying DLB (DLBRP = AUC: 0.909, specificity: 0.873, sensitivity 0.866; SPM t-maps = AUC: 0.892, specificity: 0.872, sensitivity 0.910) and MSA (MSARP: AUC: 0.921, specificity: 0.811, sensitivity 1.000; SPM t-maps: AUC: 1.000, specificity: 1.000, sensitivity 1.000) from other α-synucleinopathies. PD-HDR and DLB were comparable for the brain hypo and hypermetabolism patterns, thus not allowing differentiation by SPM t-maps or SSM/PCA. Of note, we found a gradual increase of PDRP and DLBRP expression in the continuum from iRBD to PD-HDR and DLB, where the DLB patients had the highest scores. SSM/PCA could differentiate iRBD from DLB, reflecting specifically the differences in disease staging and severity (AUC: 0.938, specificity: 0.821, sensitivity 0.941). CONCLUSIONS: SPM-single subject maps and SSM/PCA are both valid methods in supporting diagnosis within the α-synucleinopathy spectrum, with different strengths and pitfalls. The former reveals dysfunctional brain topographies at the individual level with high accuracy for all the specific subtype patterns, and particularly also the normal maps; the latter provides a reliable quantification, independent from the rater experience, particularly in tracking the disease severity and staging. Thus, our findings suggest that differences in data analysis approaches exist and should be considered in clinical settings. However, combining both methods might offer the best diagnostic performance.

[18F]FDG PET in conditions associated with hyperkinetic movement disorders and ataxia: a systematic review.

PURPOSE: To give a comprehensive literature overview of alterations in regional cerebral glucose metabolism, measured using [18F]FDG PET, in conditions associated with hyperkinetic movement disorders and ataxia. In addition, correlations between glucose metabolism and clinical variables as well as the effect of treatment on glucose metabolism are discussed. METHODS: A systematic literature search was performed according to PRISMA guidelines. Studies concerning tremors, tics, dystonia, ataxia, chorea, myoclonus, functional movement disorders, or mixed movement disorders due to autoimmune or metabolic aetiologies were eligible for inclusion. A PubMed search was performed up to November 2021. RESULTS: Of 1240 studies retrieved in the original search, 104 articles were included. Most articles concerned patients with chorea (n = 27), followed by ataxia (n = 25), dystonia (n = 20), tremor (n = 8), metabolic disease (n = 7), myoclonus (n = 6), tics (n = 6), and autoimmune disorders (n = 5). No papers on functional movement disorders were included. Altered glucose metabolism was detected in various brain regions in all movement disorders, with dystonia-related hypermetabolism of the lentiform nuclei and both hyper- and hypometabolism of the cerebellum; pronounced cerebellar hypometabolism in ataxia; and striatal hypometabolism in chorea (dominated by Huntington disease). Correlations between clinical characteristics and glucose metabolism were often described. [18F]FDG PET-showed normalization of metabolic alterations after treatment in tremors, ataxia, and chorea. CONCLUSION: In all conditions with hyperkinetic movement disorders, hypo- or hypermetabolism was found in multiple, partly overlapping brain regions, and clinical characteristics often correlated with glucose metabolism. For some movement disorders, [18F]FDG PET metabolic changes reflected the effect of treatment.

Altered brain connectivity in hyperkinetic movement disorders: A review of resting-state fMRI.

BACKGROUND: Hyperkinetic movement disorders (HMD) manifest as abnormal and uncontrollable movements. Despite reported involvement of several neural circuits, exact connectivity profiles remain elusive. OBJECTIVES: Providing a comprehensive literature review of resting-state brain connectivity alterations using resting-state fMRI (rs-fMRI). We additionally discuss alterations from the perspective of brain networks, as well as correlations between connectivity and clinical measures. METHODS: A systematic review was performed according to PRISMA guidelines and searching PubMed until October 2022. Rs-fMRI studies addressing ataxia, chorea, dystonia, myoclonus, tics, tremor, and functional movement disorders (FMD) were included. The standardized mean difference was used to summarize findings per region in the Automated Anatomical Labeling atlas for each phenotype. Furthermore, the activation likelihood estimation meta-analytic method was used to analyze convergence of significant between-group differences per phenotype. Finally, we conducted hierarchical cluster analysis to provide additional insights into commonalities and differences across HMD phenotypes. RESULTS: Most articles concerned tremor (51), followed by dystonia (46), tics (19), chorea (12), myoclonus (11), FMD (11), and ataxia (8). Altered resting-state connectivity was found in several brain regions: in ataxia mainly cerebellar areas; for chorea, the caudate nucleus; for dystonia, sensorimotor and basal ganglia regions; for myoclonus, the thalamus and cingulate cortex; in tics, the basal ganglia, cerebellum, insula, and frontal cortex; for tremor, the cerebello-thalamo-cortical circuit; finally, in FMD, frontal, parietal, and cerebellar regions. Both decreased and increased connectivity were found for all HMD. Significant spatial convergence was found for dystonia, FMD, myoclonus, and tremor. Correlations between clinical measures and resting-state connectivity were frequently described. CONCLUSION: Key brain regions contributing to functional connectivity changes across HMD often overlap. Possible increases and decreases of functional connections of a specific region emphasize that HMD should be viewed as a network disorder. Despite the complex interplay of physiological and methodological factors, this review serves to gain insight in brain connectivity profiles across HMD phenotypes.

Alzheimer's disease pattern derived from relative cerebral flow as an alternative for the metabolic pattern using SSM/PCA.

BACKGROUND: 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer's disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. RESULTS: In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. CONCLUSION: rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA.

A resting-state fMRI pattern of spinocerebellar ataxia type 3 and comparison with 18F-FDG PET.

Spinocerebellar ataxia type 3 (SCA3) is a rare genetic neurodegenerative disease. The neurobiological basis of SCA3 is still poorly understood, and up until now resting-state fMRI (rs-fMRI) has not been used to study this disease. In the current study we investigated (multi-echo) rs-fMRI data from patients with genetically confirmed SCA3 (n = 17) and matched healthy subjects (n = 16). Using independent component analysis (ICA) and subsequent regression with bootstrap resampling, we identified a pattern of differences between patients and healthy subjects, which we coined the fMRI SCA3 related pattern (fSCA3-RP) comprising cerebellum, anterior striatum and various cortical regions. Individual fSCA3-RP scores were highly correlated with a previously published 18F-FDG PET pattern found in the same sample (rho = 0.78, P = 0.0003). Also, a high correlation was found with the Scale for Assessment and Rating of Ataxia scores (r = 0.63, P = 0.007). No correlations were found with neuropsychological test scores, nor with levels of grey matter atrophy. Compared with the 18F-FDG PET pattern, the fSCA3-RP included a more extensive contribution of the mediofrontal cortex, putatively representing changes in default network activity. This rs-fMRI identification of additional regions is proposed to reflect a consequence of the nature of the BOLD technique, enabling measurement of dynamic network activity, compared to the more static 18F-FDG PET methodology. Altogether, our findings shed new light on the neural substrate of SCA3, and encourage further validation of the fSCA3-RP to assess its potential contribution as imaging biomarker for future research and clinical use.

Serotonergic system in vivo with [11C]DASB PET scans in GTP-cyclohydrolase deficient dopa-responsive dystonia patients.

GTP-cyclohydrolase deficiency in dopa-responsive dystonia (DRD) patients impairs the biosynthesis of dopamine, but also of serotonin. The high prevalence of non-motor symptoms suggests involvement of the serotonergic pathway. Our study aimed to investigate the serotonergic system in vivo in the brain of`DRD patients and correlate this to (non-)motor symptoms. Dynamic [11C]DASB PET scans, a marker of serotonin transporter availability, were performed. Ten DRD, 14 cervical dystonia patients and 12 controls were included. Univariate- and network-analysis did not show differences in binding between DRD patients compared to controls. Sleep disturbances were correlated with binding in the dorsal raphe nucleus (all participants: rs = 0.45, p = 0.04; patients: rs = 0.64, p = 0.05) and participants with a psychiatric disorder had a lower binding in the hippocampus (all participants: p = 0.00; patients: p = 0.06). Post-hoc analysis with correction for psychiatric co-morbidity showed a significant difference in binding in the hippocampus between DRD patients and controls (p = 0.00). This suggests that psychiatric symptoms might mask the altered serotonergic metabolism in DRD patients, but definite conclusions are difficult as psychiatry is considered part of the phenotype. We hypothesize that an imbalance between different neurotransmitter systems is responsible for the non-motor symptoms, and further research investigating multiple neurotransmitters and psychiatry in DRD is necessary.

Neural coupling between upper and lower limb muscles in Parkinsonian gait.

OBJECTIVE: To explore to what extent neuronal coupling between upper and lower limb muscles during gait is preserved or affected in patients with Parkinson's Disease (PD). METHODS: Electromyography recordings were obtained from the bilateral deltoideus anterior and bilateral rectus femoris and biceps femoris muscles during overground gait in 20 healthy participants (median age 69 years) and 20 PD patients (median age 68.5 years). PD patients were able to walk independently (Hoehn and Yahr scale: Stage 2-3), had an equally distributed symptom laterality (6 left side, 7 both sides and 7 right side) and no cognitive problems or tremor dominant PD. Time-dependent directional intermuscular coherence analysis was employed to compare the neural coupling between upper and lower limb muscles between healthy participants and PD patients in three different directions: zero-lag (i.e. common driver), forward (i.e. shoulders driving the legs) and reverse component (i.e. legs driving the shoulders). RESULTS: Compared to healthy participants, PD patients exhibited (i) reduced intermuscular zero-lag coherence in the beta/gamma frequency band during end-of-stance and (ii) enhanced forward as well as reverse directed coherence in the alpha and beta/gamma frequency bands around toe-off. CONCLUSIONS: PD patients had a reduced common cortical drive to upper and lower limb muscles during gait, possibly contributing to disturbed interlimb coordination. Enhanced bidirectional coupling between upper and lower limb muscles on subcortical and transcortical levels in PD patients suggests a mechanism of compensation. SIGNIFICANCE: These findings provide support for the facilitating effect of arm swing instructions in PD gait.

Time-dependent directional intermuscular coherence analysis reveals that forward and backward arm swing equally drive the upper leg muscles during gait initiation.

BACKGROUND: Human bipedal gait benefits from arm swing, as it drives and shapes lower limb muscle activity in healthy participants as well as patients suffering from neurological impairment. Also during gait initiation, arm swing instructions were found to facilitate leg muscle recruitment. RESEARCH QUESTION: The aim of the present study is to exploit the directional decomposition of coherence to examine to what extent forward and backward arm swing contribute to leg muscle recruitment during gait initiation. METHODS: Ambulant electromyography (EMG) from shoulder muscles (deltoideus anterior and posterior) and upper leg muscles (biceps femoris and rectus femoris) was analysed during gait initiation in nineteen healthy participants (median age of 67 ± 12 (IQR) years). To assess to what extent either deltoideus anterior or posterior muscles were able to drive upper leg muscle activity during distinct stages of the gait initiation process, time dependent intermuscular coherence was decomposed into directional components based on their time lag (i.e. forward, reverse and zero-lag). RESULTS: Coherence from the forward directed components, representing shoulder muscle signals leading leg muscle signals, revealed that deltoideus anterior (i.e. forward arm swing) and deltoideus posterior (i.e. backward arm swing) equally drive upper leg muscle activity during the gait initiation process. SIGNIFICANCE: The presently demonstrated time dependent directional intermuscular coherence analysis could be of use for future studies examining directional coupling between muscles or brain areas relative to certain gait (or other time) events. In the present study, this analysis provided neural underpinning that both forward and backward arm swing can provide neuronal support for leg muscle recruitment during gait initiation and can therefore both serve as an effective gait rehabilitation method in patients with gait initiation difficulties.

Enhanced arm swing improves Parkinsonian gait with EEG power modulations resembling healthy gait.

BACKGROUND: The supplementary motor area (SMA) is implicated in stereotypic multi-limb movements such as walking with arm swing. Gait difficulties in Parkinson's Disease (PD) include reduced arm swing, which is associated with reduced SMA activity. OBJECTIVE: To test whether enhanced arm swing improves Parkinsonian gait and explore the role of the SMA in such an improvement. METHODS: Cortical activity and gait characteristics were assessed by ambulant EEG, accelerometers and video recordings in 27 PD patients with self-reported gait difficulties and 35 healthy participants when walking normally. Within these two groups, 19 PD patients additionally walked with enhanced arm swing and 30 healthy participants walked without arm swing. Power changes across the EEG frequency spectrum were assessed by Event Related Spectral Perturbation analysis of recordings from Fz over the putative SMA and gait analysis was performed. RESULTS: Baseline PD gait, characterized by reduced arm swing among other features, exhibited reduced within-step Event Related Desynchronization (ERD)/Synchronization (ERS) alternation (Fz; 20-50Hz), accompanied by a reduced step length and walking speed. All became similar to normal gait when patients walked with enhanced arm swing. When healthy controls walked without arm swing, their alternating ERD-ERS pattern decreased, mimicking baseline PD gait. CONCLUSION: Enhanced arm swing may serve as a driving force to overcome impaired gait control in PD patients by restoring reduced ERD-ERS alternation over the putative SMA. Accompanied by increased step length and walking speed, this provides a neural underpinning of arm swing as an effective rehabilitation concept for improving Parkinsonian gait.

Amble Gait EEG Points at Complementary Cortical Networks Underlying Stereotypic Multi-Limb Co-ordination.

BACKGROUND: Walking is characterized by stable antiphase relations between upper and lower limb movements. Such bilateral rhythmic movement patterns are neuronally generated at levels of the spinal cord and brain stem, that are strongly interconnected with cortical circuitries, including the Supplementary Motor Area (SMA). OBJECTIVE: To explore cerebral activity associated with multi-limb phase relations in human gait by manipulating mutual attunement of the upper and lower limb antiphase patterns. METHODS: Cortical activity and gait were assessed by ambulant EEG, accelerometers and videorecordings in 35 healthy participants walking normally and 19 healthy participants walking in amble gait, where upper limbs moved in-phase with the lower limbs. Power changes across the EEG frequency spectrum were assessed by Event Related Spectral Perturbation analysis and gait analysis was performed. RESULTS: Amble gait was associated with enhanced Event Related Desynchronization (ERD) prior to and during especially the left swing phase and reduced Event Related Synchronization (ERS) at final swing phases. ERD enhancement was most pronounced over the putative right premotor, right primary motor and right parietal cortex, indicating involvement of higher-order organization and somatosensory guidance in the production of this more complex gait pattern, with an apparent right hemisphere dominance. The diminished within-step ERD/ERS pattern in amble gait, also over the SMA, suggests that this gait pattern is more stride driven instead of step driven. CONCLUSION: Increased four-limb phase complexity recruits distributed networks upstream of the primary motor cortex, primarily lateralized in the right hemisphere. Similar parietal-premotor involvement has been described to compensate impaired SMA function in Parkinson's disease bimanual antiphase movement, indicating a role as cortical support regions.

Amyloid burden quantification depends on PET and MR image processing methodology.

Quantification of amyloid load with positron emission tomography can be useful to assess Alzheimer's Disease in-vivo. However, quantification can be affected by the image processing methodology applied. This study's goal was to address how amyloid quantification is influenced by different semi-automatic image processing pipelines. Images were analysed in their Native Space and Standard Space; non-rigid spatial transformation methods based on maximum a posteriori approaches and tissue probability maps (TPM) for regularisation were explored. Furthermore, grey matter tissue segmentations were defined before and after spatial normalisation, and also using a population-based template. Five quantification metrics were analysed: two intensity-based, two volumetric-based, and one multi-parametric feature. Intensity-related metrics were not substantially affected by spatial normalisation and did not significantly depend on the grey matter segmentation method, with an impact similar to that expected from test-retest studies (≤10%). Yet, volumetric and multi-parametric features were sensitive to the image processing methodology, with an overall variability up to 45%. Therefore, the analysis should be carried out in Native Space avoiding non-rigid spatial transformations. For analyses in Standard Space, spatial normalisation regularised by TPM is preferred. Volumetric-based measurements should be done in Native Space, while intensity-based metrics are more robust against differences in image processing pipelines.

Intermuscular coherence analysis in older adults reveals that gait-related arm swing drives lower limb muscles via subcortical and cortical pathways.

KEY POINTS: Gait-related arm swing in humans supports efficient lower limb muscle activation, indicating a neural coupling between the upper and lower limbs during gait. Intermuscular coherence analyses of gait-related electromyography from upper and lower limbs in 20 healthy participants identified significant coherence in alpha and beta/gamma bands indicating that upper and lower limbs share common subcortical and cortical drivers that coordinate the rhythmic four-limb gait pattern. Additional directed connectivity analyses revealed that upper limb muscles drive and shape lower limb muscle activity during gait via subcortical and cortical pathways and to a lesser extent vice versa. The results provide a neural underpinning that arm swing may serve as an effective rehabilitation therapy concerning impaired gait in neurological diseases. ABSTRACT: Human gait benefits from arm swing, as it enhances efficient lower limb muscle activation in healthy participants as well as patients suffering from neurological impairment. The underlying neuronal mechanisms of such coupling between upper and lower limbs remain poorly understood. The aim of the present study was to examine this coupling by intermuscular coherence analysis during gait. Additionally, directed connectivity analysis of this coupling enabled assessment of whether gait-related arm swing indeed drives lower limb muscles. To that end, electromyography recordings were obtained from four lower limb muscles and two upper limb muscles bilaterally, during gait, of 20 healthy participants (mean (SD) age 67 (6.8) years). Intermuscular coherence analysis revealed functional coupling between upper and lower limb muscles in the alpha and beta/gamma band during muscle specific periods of the gait cycle. These effects in the alpha and beta/gamma bands indicate involvement of subcortical and cortical sources, respectively, that commonly drive the rhythmic four-limb gait pattern in an efficiently coordinated fashion. Directed connectivity analysis revealed that upper limb muscles drive and shape lower limb muscle activity during gait via subcortical and cortical pathways and to a lesser extent vice versa. This indicates that gait-related arm swing reflects the recruitment of neuronal support for optimizing the cyclic movement pattern of the lower limbs. These findings thus provide a neural underpinning for arm swing to potentially serve as an effective rehabilitation therapy concerning impaired gait in neurological diseases.

Feasibility of pharmacokinetic parametric PET images in scaled subprofile modelling using principal component analysis.

Scaled subprofile model using principal component analysis (SSM/PCA) is a multivariate analysis technique used, mainly in [18F]-2-fluoro-2-deoxy-d-glucose (FDG) PET studies, for the generation of disease-specific metabolic patterns (DP) that may aid with the classification of subjects with neurological disorders, like Alzheimer's disease (AD). The aim of this study was to explore the feasibility of using quantitative parametric images for this type of analysis, with dynamic [11C]-labelled Pittsburgh Compound B (PIB) PET data as an example. Therefore, 15 AD patients and 15 healthy control subjects were included in an SSM/PCA analysis to generate four AD-DPs using relative cerebral blood flow (R1), binding potential (BPND) and SUVR images derived from dynamic PIB and static FDG-PET studies. Furthermore, 49 new subjects with a variety of neurodegenerative cognitive disorders were tested against these DPs. The AD-DP was characterized by a reduction in the frontal, parietal, and temporal lobes voxel values for R1 and SUVR-FDG DPs; and by a general increase of values in cortical areas for BPND and SUVR-PIB DPs. In conclusion, the results suggest that the combination of parametric images derived from a single dynamic scan might be a good alternative for subject classification instead of using 2 independent PET studies.

Altered Posterior Midline Activity in Patients with Jerky and Tremulous Functional Movement Disorders.

Objective: To explore changes in resting-state networks in patients with jerky and tremulous functional movement disorders (JT-FMD). Methods: Resting-state functional magnetic resonance imaging data from seventeen patients with JT-FMD and seventeen age-, sex-, and education-matched healthy controls (HC) were investigated. Independent component analysis was used to examine the central executive network (CEN), salience network, and default mode network (DMN). Frequency distribution of network signal fluctuations and intra- and internetwork functional connectivity were investigated. Symptom severity was measured using the Clinical Global Impression-Severity scale. Beck Depression Inventory and Beck Anxiety Inventory scores were collected to measure depression and anxiety in FMD, respectively. Results: Compared with HC, patients with JT-FMD had significantly decreased power of lower range (0.01-0.10 Hz) frequency fluctuations in a precuneus and posterior cingulate cortex component of the DMN and in the dorsal attention network (DAN) component of the CEN (false discovery rate-corrected p < 0.05). No significant group differences were found for intra- and internetwork functional connectivity. In patients with JT-FMD, symptom severity was not significantly correlated with network measures. Depression scores were weakly correlated with intranetwork functional connectivity in the medial prefrontal cortex, while anxiety was not found to be related to network connectivity. Conclusions: Given the changes in the posterodorsal components of the DMN and DAN, we postulate that the JT-FMD-related functional alterations found in these regions could provide support for the concept that particularly attentional dysregulation is a fundamental disturbance in these patients. Impact statement In this study, we explored static brain network functional connectivity in patients with jerky and tremulous functional movement disorders (JT-FMD) and healthy controls. We studied network functioning by analyzing functional connectivity measures, and also time course frequency spectra, which is novel compared with previous studies. We discovered aberrations in the frequency distribution of a posterior component of the default mode network (precuneus/posterior cingulate) and the dorsal attention network in patients with JT-FMD relative to controls. Conclusively, our findings could provide support for impaired attentional control as a fundamental disturbance in JT-FMD and contribute to the growing conceptualization of this disorder.

An application of generalized matrix learning vector quantization in neuroimaging.

BACKGROUND AND OBJECTIVE: Neurodegenerative diseases like Parkinson's disease often take several years before they can be diagnosed reliably based on clinical grounds. Imaging techniques such as MRI are used to detect anatomical (structural) pathological changes. However, these kinds of changes are usually seen only late in the development. The measurement of functional brain activity by means of [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) can provide useful information, but its interpretation is more difficult. The scaled sub-profile model principal component analysis (SSM/PCA) was shown to provide more useful information than other statistical techniques. Our objective is to improve the performance further by combining SSM/PCA and prototype-based generalized matrix learning vector quantization (GMLVQ). METHODS: We apply a combination of SSM/PCA and GMLVQ as a classifier. In order to demonstrate the combination's validity, we analyze FDG-PET data of Parkinson's disease (PD) patients collected at three different neuroimaging centers in Europe. We determine the diagnostic performance by performing a ten times repeated ten fold cross validation. Additionally, discriminant visualizations of the data are included. The prototypes and relevance of GMLVQ are transformed back to the original voxel space by exploiting the linearity of SSM/PCA. The resulting prototypes and relevance profiles have then been assessed by three neurologists. RESULTS: One important finding is that discriminative visualization can help to identify disease-related properties as well as differences which are due to center-specific factors. Secondly, the neurologist assessed the interpretability of the method and confirmed that prototypes are similar to known activity profiles of PD patients. CONCLUSION: We have shown that the presented combination of SSM/PCA and GMLVQ can provide useful means to assess and better understand characteristic differences in FDG-PET data from PD patients and HCs. Based on the assessments by medical experts and the results of our computational analysis we conclude that the first steps towards a diagnostic support system have been taken successfully.

Structural Network Analysis Using Diffusion MRI Tractography in Parkinson's Disease and Correlations With Motor Impairment.

Functional impairment of spatially distributed brain regions in Parkinson's disease (PD) suggests changes in integrative and segregative network characteristics, for which novel analysis methods are available. To assess underlying structural network differences between PD patients and controls, we employed MRI T1 gray matter segmentation and diffusion MRI tractography to construct connectivity matrices to compare patients and controls with data originating from two different centers. In the Dutch dataset (Data-NL), 14 PD patients, and 15 healthy controls were analyzed, while 19 patients and 18 controls were included in the Canadian dataset (Data-CA). All subjects underwent T1 and diffusion-weighted MRI. Patients were assessed with Part 3 of the Unified Parkinson's Disease Rating Scale (UPDRS). T1 images were segmented using FreeSurfer, while tractography was performed using ExploreDTI. The regions of interest from the FreeSurfer segmentation were combined with the white matter streamline sets resulting from the tractography, to construct connectivity matrices. From these matrices, both global and local efficiencies were calculated, which were compared between the PD and control groups and related to the UPDRS motor scores. The connectivity matrices showed consistent patterns among the four groups, without significant differences between PD patients and control subjects, either in Data-NL or in Data-CA. In Data-NL, however, global and local efficiencies correlated negatively with UPDRS scores at both the whole-brain and the nodal levels [false discovery rate (FDR) 0.05]. At the nodal level, particularly, the posterior parietal cortex showed a negative correlation between UPDRS and local efficiency, while global efficiency correlated negatively with the UPDRS in the sensorimotor cortex. The spatial patterns of negative correlations between UPDRS and parameters for network efficiency seen in Data-NL suggest subtle structural differences in PD that were below sensitivity thresholds in Data-CA. These correlations are in line with previously described functional differences. The methodological approaches to detect such differences are discussed.

The chronnectome as a model for Charcot's 'dynamic lesion' in functional movement disorders.

This exploratory study set out to investigate dynamic functional connectivity (dFC) in patients with jerky and tremulous functional movement disorders (JT-FMD). The focus in this work is on dynamic brain states, which represent distinct dFC patterns that reoccur in time and across subjects. Resting-state fMRI data were collected from 17 patients with JT-FMD and 17 healthy controls (HC). Symptom severity was measured using the Clinical Global Impression-Severity scale. Depression and anxiety were measured using the Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI), respectively. Independent component analysis was used to extract functional brain components. After computing dFC, dynamic brain states were determined for every subject using k-means clustering. Compared to HC, patients with JT-FMD spent more time in a state that was characterized predominantly by increasing medial prefrontal, and decreasing posterior midline connectivity over time. They also tended to visit this state more frequently. In addition, patients with JT-FMD transitioned significantly more often between different states compared to HC, and incorporated a state with decreasing medial prefrontal, and increasing posterior midline connectivity in their attractor, i.e., the cyclic patterns of state transitions. Altogether, this is the first study that demonstrates altered functional brain network dynamics in JT-FMD that may support concepts of increased self-reflective processes and impaired sense of agency as driving factors in FMD.

Pre-Movement Cortico-Muscular Dynamics Underlying Improved Parkinson Gait Initiation after Instructed Arm Swing.

BACKGROUND: The supplementary motor area (SMA) is implicated in both motor initiation and stereotypic multi-limb movements such as walking with arm swing. Gait in Parkinson's disease exhibits starting difficulties and reduced arm swing, consistent with reduced SMA activity. OBJECTIVE: We tested whether enhanced arm swing could improve Parkinson gait initiation and assessed whether increased SMA activity during preparation might facilitate such improvement. METHODS: Effects of instructed arm swing on cortical activity, muscle activity and kinematics were assessed by ambulant EEG, EMG, accelerometers and video in 17 Parkinson patients and 19 controls. At baseline, all participants repeatedly started walking after a simple auditory cue. Next, patients started walking at this cue, which now meant starting with enhanced arm swing. EEG changes over the putative SMA and leg motor cortex were assessed by event related spectral perturbation (ERSP) analysis of recordings at Fz and Cz. RESULTS: Over the putative SMA location (Fz), natural PD gait initiation showed enhanced alpha/theta synchronization around the auditory cue, and reduced alpha/beta desynchronization during gait preparation and movement onset, compared to controls. Leg muscle activity in patients was reduced during preparation and movement onset, while the latter was delayed compared to controls. When starting with enhanced arm swing, these group differences virtually disappeared. CONCLUSION: Instructed arm swing improves Parkinson gait initiation. ERSP normalization around the cue indicates that the attributed information may serve as a semi-internal cue, recruiting an internalized motor program to overcome initiation difficulties.

Intrastriatal gradient analyses of 18F-FDOPA PET scans for differentiation of Parkinsonian disorders.

AIM: L -3,4-dihydroxy-6-18F-fluorophenylalanine (18F-DOPA PET may be used to distinguish subjects with Parkinsonism from those with symptoms not originating from impaired dopaminergic transmission. However, it is not routinely utilized to discriminate Idiopathic Parkinson's disease (IPD) from Atypical Parkinsonian Disorders (APD). We investigated the potential of FDOPA PET to discriminate between IPD and APD, with a focus on the anterior-to-posterior decline in het striatum, considered to be more specific for IPD. MATERIALS AND METHODS: 18F-DOPA PET data from a total of 58 subjects were retrospectively analyzed. 28 subjects had idiopathic Parkinson's disease (14 male, 14 female; age at scan 61 +- 11,5), 13 atypical Parkinsonian disease (7 male, 6 females; age at scan: 69,6 +- 6,4) and 17 were controls (6 male, 11 female; age at scan 65,3 +-8,6). Regional striatal-to-occipital ratio's (RSOR's) were calculated, as well as multiple in-line VOI's from the caudate nucleus to the posterior part of the putamen. The linearity of anteroposterior decline was determined by a linear regression fit and associated R squared values. ROC curves were calculated to assess the diagnostic performance of these measurements. Data contralateral to the clinically most affected side were used for analysis. RESULTS: ROC curve analysis for differentiation between controls and Parkinsonism patients showed the highest AUC for the caudate nucleus-to-posterior putamen ratio (AUC = 0.930; p < 0.00) and for the R squared value for the linear regression fit (AUC = 0.948; p = 0.006). For discrimating IPD from APD, the highest AUC was found for the caudate nucleus-to-anterior putamen ratio (0.824; p < 0.001) CONCLUSIONS: Subregional analysis of the striatum in F-DOPA PET scans may provide additional diagnostic information in patients screened for a  presynaptic dopaminergic deficit. A more linear decrease from the head of the caudate nucleus to the posterior putamen was  present in patients with IPD, although this feature did not have additional diagnostic value over the RSOR analysis.