The Role of Deep Learning and Gait Analysis in Parkinson's Disease: A Systematic Review.

Parkinson's disease (PD) is the second most common movement disorder in the world. It is characterized by motor and non-motor symptoms that have a profound impact on the independence and quality of life of people affected by the disease, which increases caregivers' burdens. The use of the quantitative gait data of people with PD and deep learning (DL) approaches based on gait are emerging as increasingly promising methods to support and aid clinical decision making, with the aim of providing a quantitative and objective diagnosis, as well as an additional tool for disease monitoring. This will allow for the early detection of the disease, assessment of progression, and implementation of therapeutic interventions. In this paper, the authors provide a systematic review of emerging DL techniques recently proposed for the analysis of PD by using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The Scopus, PubMed, and Web of Science databases were searched across an interval of six years (between 2018, when the first article was published, and 2023). A total of 25 articles were included in this review, which reports studies on the movement analysis of PD patients using both wearable and non-wearable sensors. Additionally, these studies employed DL networks for classification, diagnosis, and monitoring purposes. The authors demonstrate that there is a wide employment in the field of PD of convolutional neural networks for analyzing signals from wearable sensors and pose estimation networks for motion analysis from videos. In addition, the authors discuss current difficulties and highlight future solutions for PD monitoring and disease progression.

Kinematic and Kinetic Gait Features Associated With Mild Cognitive Impairment in Parkinson's Disease.

Mild cognitive impairment (MCI) and gait deficits are commonly associated with Parkinson's disease (PD). Early detection of MCI associated with Parkinson's disease (PD-MCI) and its biomarkers is critical to managing disability in PD patients, reducing caregiver burden and healthcare costs. Gait is considered a surrogate marker for cognitive decline in PD. However, gait kinematic and kinetic features in PD-MCI patients remain unknown. This study was designed to explore the difference in gait kinematics and kinetics during single-task and dual-task walking between PD patients with and without MCI. Kinematic and kinetic data of 90 PD patients were collected using 3D motion capture system. Differences in gait kinematic and kinetic gait features between groups were identified by using: first, univariate statistical analysis and then a supervised machine learning analysis. The findings of this study showed that the presence of MCI in PD patients is coupled with kinematic and kinetic deviations of gait cycle which may eventually identify two different phenotypes of the disease. Indeed, as shown by the demographical and clinical comparison between the two groups, PD-MCI patients were older and more impaired. Moreover, PD-MCI kinematic results showed that cognitive dysfunction coexists with more severe axial symptoms and an increase postural flexion. A lack of physiological distal-to-proximal shift in joint kinetics was evidenced in the PD phenotype associated with cognitive impairments.

Direct Current Stimulation of Prefrontal Cortex Is Not Effective in Progressive Supranuclear Palsy: A Randomized Trial.

BACKGROUND: Progressive supranuclear palsy (PSP) is a rare 4R-tauopathy. Transcranial direct current stimulation (tDCS) may improve specific symptoms. OBJECTIVES: This randomized, double-blinded, sham-controlled trial aimed at verifying the short-, mid-, and long-term effect of multiple sessions of anodal tDCS over the left dorsolateral prefrontal cortex (DLPFC) cortex in PSP. METHODS: Twenty-five patients were randomly assigned to active or sham stimulation (2 mA for 20 minute) for 5 days/week for 2 weeks. Participants underwent assessments at baseline, after the 2-week stimulation protocol, then after 45 days and 3 months from baseline. Primary outcomes were verbal and semantic fluency. The efficacy was verified with analysis of covariance. RESULTS: We failed to detect a significant effect of active stimulation on primary outcomes. Stimulation was associated to worsening of specific behavioral complaints. CONCLUSIONS: A 2-week protocol of anodal left DLPFC tDCS is not effective in PSP. Specific challenges in running symptomatic clinical trials with classic design are highlighted. © 2024 International Parkinson and Movement Disorder Society.

Validation of the Italian version of the Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease-Rating Scale (QUIP-RS) in an Italian Parkinson's disease cohort.

INTRODUCTION: Impulse control disorders (ICDs) frequently occur in Parkinson's disease (PD), and an early identification is essential to prevent severe psychosocial consequences. The Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease-Rating Scale (QUIP-RS) has been developed to evaluate the severity of ICDs along with a range of impulsive-compulsive behaviors (ICBs) in PD; however, its Italian version has not yet been validated. METHODS: One hundred consecutive outpatients with PD were administered an Italian version of the QUIP-RS and a brief neuropsychological assessment to evaluate global cognitive status and scales to measure depression, apathy and impulsive disorders. We evaluated the internal consistency, convergent and divergent validity, and factorial structure of QUIP-RS. We also explored the possible association between QUIP-RS scores and clinical factors and dopaminergic medication. RESULTS: Subsyndromal ICDs manifestations were observed in 54% of the patients, and one in four (22%) reported two or more ICDs or related behaviors. The QUIP-RS demonstrated good internal consistency (Cronbach's alpha = 0.806) and construct validity, and its factorial structure reflected different ICDs and ICBs domains. No association emerged between QUIP-RS scores and the clinical aspects of PD and dopaminergic medication. CONCLUSION: We provided, for the first time, an Italian translation of the QUIP-RS and demonstrated its feasibility in clinical and research settings. Severity of ICDs was independent of clinical factors and dopaminergic medication, underlining the need to adopt a broader perspective on their etiopathology in PD.

Psychometric properties of the Caregiver's inventory neuropsychological diagnosis dementia (CINDD) in mild cognitive impairment and dementia.

OBJECTIVES: The Caregiver's Inventory Neuropsychological Diagnosis Dementia (CINDD) is an easy tool designed to quantify cognitive, behavioural and functional deficits of patients with cognitive impairment. Aim of the present study was to analyse the psychometric properties of the CINDD in Mild Cognitive Impairment (MCI) and Dementia (D). DESIGN, SETTING AND PARTICIPANTS: The CINDD, composed by 9 sub-domains, was administered to fifty-six caregivers of patients with different types of dementia (D) and 44 caregivers of patients with MCI. All patients underwent an extensive neuropsychological assessment, the Neuropsychiatric Inventory (NPI) and functional autonomy scales. The reliability, convergent construct validity and possible cut-off of CINND were measured by Cronbach's alpha (α), Pearson's correlation and ROC analysis, respectively. RESULTS: The D and MCI patients differed only for age (p=0.006). The internal consistency of CINDD was high (α= 0.969). The α-value for each CINDD domain was considered acceptable, except the mood domain (α=0.209). The CINDD total score correlated with cognitive screening tests; each domain of the CINDD correlated with the corresponding score from either tests or NPI (p<0.05), except for visuo-spatial perception skills and apathy. A screening cut-off equal to 59, can be used discriminate D from MCI (Sensitivity=0.70, Specificity=0.57). CONCLUSION: The CINDD is a feasible, accurate and reliable tool for the assessment of cognitive and behavioural difficulties in patients with different degree of cognitive impairment. It may be used to quantify and monitor caregiver-reported ecological data in both clinical and research settings.

Theory of mind in mild cognitive impairment and Parkinson's disease: The role of memory impairment.

BACKGROUND: Social cognition is impaired in Parkinson's disease (PD). Whether social cognitive impairment (iSC) is a by-product of the underlying cognitive deficits in PD or a process independent of cognitive status is unknown. To this end, the present study was designed to investigate the weight of specific cognitive deficits in social cognition, considering different mild cognitive impairment subtypes of PD (PD-MCI). METHODS: Fifty-eight PD patients underwent a neuropsychological battery assessing executive functions, memory, language, and visuospatial domains, together with social cognitive tests focused on theory of mind (ToM). Patients were divided into subgroups according to their clinical cognitive status: amnestic PD-MCI (PD-aMCI, n = 18), non-amnestic PD-MCI (PD-naMCI, n = 16), and cognitively unimpaired (PD-CU, n = 24). Composite scores for cognitive and social domains were computed to perform mediation analyses. RESULTS: Memory and language impairments mediated the effect of executive functioning in social cognitive deficits in PD patients. Dividing by MCI subgroups, iSC occurred more frequently in PD-aMCI (77.8%) than in PD-naMCI (18.8%) and PD-CU (8.3%). Moreover, PD-aMCI performed worse than PD-CU in all social cognitive measures, whereas PD-naMCI performed worse than PD-CU in only one subtype of the affective and cognitive ToM tests. CONCLUSIONS: Our findings suggest that ToM impairment in PD can be explained by memory dysfunction that mediates executive control. ToM downsides in the amnesic forms of PD-MCI may suggest that subtle changes in social cognition could partly explain future transitions into dementia. Hence, the evaluation of social cognition in PD is critical to characterize a possible behavioral marker of cognitive decline.

Agreement between Optoelectronic System and Wearable Sensors for the Evaluation of Gait Spatiotemporal Parameters in Progressive Supranuclear Palsy.

The use of wearable sensors for calculating gait parameters has become increasingly popular as an alternative to optoelectronic systems, currently recognized as the gold standard. The objective of the study was to evaluate the agreement between the wearable Opal system and the optoelectronic BTS SMART DX system for assessing spatiotemporal gait parameters. Fifteen subjects with progressive supranuclear palsy walked at their self-selected speed on a straight path, and six spatiotemporal parameters were compared between the two measurement systems. The agreement was carried out through paired data test, Passing Bablok regression, and Bland-Altman Analysis. The results showed a perfect agreement for speed, a very close agreement for cadence and cycle duration, while, in the other cases, Opal system either under- or over-estimated the measurement of the BTS system. Some suggestions about these misalignments are proposed in the paper, considering that Opal system is widely used in the clinical context.

Validity and diagnostics of the Italian version of the Montreal Cognitive Assessment (MoCA) in non-demented Parkinson's disease patients.

BACKGROUND: This study aimed at: (1) assessing, in an Italian cohort of non-demented Parkinson's disease (PD) patients, the construct validity of the Montreal Cognitive Assessment (MoCA) against both first- and second-level cognitive measures; (2) delivering an exhaustive and updated evaluation of its diagnostic properties. METHODS: A retrospective cohort of N = 237 non-demented PD patients having been administered the MoCA was addressed, of whom N = 169 further underwent the Mini-Mental State Examination (MMSE) and N = 68 the Parkinson's Disease Cognitive Rating Scale (PD-CRS). A subsample (N = 60) also underwent a second-level cognitive battery encompassing measures of attention/executive functioning, language, memory, praxis and visuo-spatial abilities. Construct validity was assessed against both the PD-CRS and the second-level cognitive battery. Diagnostics were tested via receiver-operating characteristics analyses against a below-cut-off MMSE score. RESULTS: The MoCA was associated with both PD-CRS scores (p < .001) and the vast majority of second-level cognitive measures (ps < .003). Both raw and adjusted MoCA scores proved to be highly accurate to the aim of identifying patients with MMSE-confirmed cognitive dysfunctions. A MoCA score adjusted for age and education according to the most recent normative dataset and < 19.015 is herewith suggested as indexing cognitive impairment in this population (AUC = .92; sensitivity = .92; specificity = .80). DISCUSSION: The Italian MoCA is a valid and diagnostically sound screener for global cognitive inefficiency in non-demented PD patients. Further studies are nevertheless needed that confirm its diagnostic values against a measure other than the MMSE.

Unawareness of Apathy in Parkinson's Disease: The Role of Executive Dysfunction on Symptom Recognition.

Altered self-awareness or anosognosia may impact patients' everyday life by interfering with their safe and independent functioning. Symptom awareness has been linked to executive dysfunctions caused by damage to frontal regions. Apathy is a frequent neuropsychiatric manifestation of Parkinson's disease (PD) and is considered a consequence of altered functioning of cortico-subcortical circuitries connecting the prefrontal cortex (PFC) with the basal ganglia. Thus, apathetic PD patients may be not be fully aware of their condition due to shared neuropathophysiological mechanisms. The present study aimed to explore the awareness of apathy in PD patients by comparing the self-reported evaluations with their caregivers' ratings. Moreover, we explored the clinical predictors of possible discrepancies and their consequences on patients' self-reported evaluation of quality of life (QoL). We found a fair agreement between patients' self-reports and caregivers' ratings on apathy scores, with patients reporting less severe apathetic symptoms, especially those related to executive and auto-activation processing, compared to their caregivers' reports. Executive functioning was found to mediate the relationship between disease stage and awareness of the apathetic state. Awareness of executive apathy impacted patients' self-reported QoL. Therefore, PD patients might be unaware of their apathetic symptoms, especially those with worse executive functioning, which plays a key role in metacognitive processes such as self-monitoring and error detection. Anosognosia for apathy in PD patients may affect their QoL perception and leads to misleading self-report evaluations that delay diagnosis and treatment.

Clinimetrics and feasibility of the Italian version of the Frontal Assessment Battery (FAB) in non-demented Parkinson's disease patients.

BACKGROUND: This study aimed at assessing the cross-sectional and longitudinal clinimetrics and feasibility of the Frontal Assessment Battery (FAB) in non-demented Parkinson's disease (PD) patients. METHODS: N = 109 PD patients underwent the FAB and the Montreal Cognitive Assessment (MoCA). A subsample of patients further underwent a thorough motor, functional and behavioral evaluation (the last including measures of anxiety, depression and apathy). A further subsample was administered a second-level cognitive battery tapping on attention, executive functioning, language, memory, praxis and visuo-spatial abilities. The following properties of the FAB were tested: (1) concurrent validity and diagnostics against the MoCA; (2) convergent validity against the second-level cognitive battery; (4) association with motor, functional and behavioral measures; (5) capability to discriminate patients from healthy controls (HCs; N = 96); (6) assessing its test-retest reliability, susceptibility to practice effects and predictive validity against the MoCA, as well as deriving reliable change indices (RCIs) for it, at a ≈ 6-month interval, within a subsample of patients (N = 33). RESULTS: The FAB predicted MoCA scores at both T0 and T1, converged with the vast majority of second-level cognitive measures and was associated with functional independence and apathy. It accurately identified cognitive impairment (i.e., a below-cut-off MoCA score) in patients, also discriminating patients from HCs. The FAB was reliable at retest and free of practice effects; RCIs were derived according to a standardized regression-based approach. DISCUSSION: The FAB is a clinimetrically sound and feasible screener for detecting dysexecutive-based cognitive impairment in non-demented PD patients.

Wearable sensors for assessing disease severity and progression in Progressive Supranuclear Palsy.

INTRODUCTION: Progressive supranuclear palsy (PSP) is an atypical parkinsonism characterized by prominent gait and postural impairment. The PSP rating scale (PSPrs) is a clinician-administered tool to evaluate disease severity and progression. More recently, digital technologies have been used to investigate gait parameters. Therefore, object of this study was to implement a protocol using wearable sensors evaluating disease severity and progression in PSP. METHODS: Patients were evaluated with the PSPrs as well as with three wearable sensors located on the feet and lumbar area. Spearman coefficient was used to assess the relationship between PSPrs and quantitative measurements. Furthermore, sensor parameters were included in a multiple linear regression model to assess their ability in predicting the PSPrs total score and sub-scores. Finally, differences between baseline and three-month follow-up were calculated for PSPrs and each quantitative variable. The significance level in all analyses was set at ≤ 0.05. RESULTS: Fifty-eight evaluations from thirty-five patients were analyzed. Quantitative measurements showed multiple significant correlations with the PSPrs scores (r between 0.3 and 0.7; p < 0.05). Linear regression models confirmed the relationships. After three months visit, significant worsening from baseline was observed for cadence, cycle duration and PSPrs item 25, while PSPrs item 10 showed a significant improvement. CONCLUSION: We propose wearable sensors can provide an objective, sensitive quantitative evaluation and immediate notification of gait changes in PSP. Our protocol can be easily introduced in outpatient and research settings as a complementary tool to clinical measures as well as an informative tool on disease severity and progression in PSP.

Identification of a Gait Pattern for Detecting Mild Cognitive Impairment in Parkinson's Disease.

The aim of this study was to determine a gait pattern, i.e., a subset of spatial and temporal parameters, through a supervised machine learning (ML) approach, which could be used to reliably distinguish Parkinson's Disease (PD) patients with and without mild cognitive impairment (MCI). Thus, 80 PD patients underwent gait analysis and spatial-temporal parameters were acquired in three different conditions (normal gait, motor dual task and cognitive dual task). Statistical analysis was performed to investigate the data and, then, five ML algorithms and the wrapper method were implemented: Decision Tree (DT), Random Forest (RF), Naïve Bayes (NB), Support Vector Machine (SVM) and K-Nearest Neighbour (KNN). First, the algorithms for classifying PD patients with MCI were trained and validated on an internal dataset (sixty patients) and, then, the performance was tested by using an external dataset (twenty patients). Specificity, sensitivity, precision, accuracy and area under the receiver operating characteristic curve were calculated. SVM and RF showed the best performance and detected MCI with an accuracy of over 80.0%. The key features emerging from this study are stance phase, mean velocity, step length and cycle length; moreover, the major number of features selected by the wrapper belonged to the cognitive dual task, thus, supporting the close relationship between gait dysfunction and MCI in PD.

Psychometrics and diagnostics of the Italian version of the Beck Depression Inventory-II (BDI-II) in Parkinson's disease.

INTRODUCTION: Depression is one of the most disabling neuropsychiatric manifestations of Parkinson's disease (PD) and requires proper screening and diagnosis because it affects the overall prognosis and quality of life of patients. This study aimed to assess the psychometric and diagnostic properties of the Beck Depression Inventory-II (BDI-II) in an Italian PD cohort. MATERIALS AND METHODS: Fifty consecutive outpatients with PD underwent the Italian version of the BDI-II and other questionnaires to evaluate anxiety and apathetic symptoms. Patients' caregivers completed the depression/dysphoria domain of the Neuropsychiatric Inventory (NPI-D). We evaluated the internal consistency, convergent and divergent validity, and factorial structure of BDI-II. Sensitivity, specificity, positive and negative predictive values, and likelihood ratios were computed using ROC analyses, and an optimal cutoff was defined using the Youden index. RESULTS: The BDI-II proved to be internally consistent (Cronbach's α = 0.840) and substantially met the bi-factorial structure. Regarding construct validity, the BDI-II was substantially related to anxiety measures, but not to apathy. With the combination of the NPI-D and anxiety score used as the gold standard, the BDI-II overall showed good accuracy (AUC = 0.859) with adequate sensitivity (75%) and specificity (87%). The optimal cutoff point was defined at 14.50. CONCLUSIONS: We provide evidence of the psychometric and diagnostic properties of the Italian version of the BDI-II as a screening tool for depression in patients with PD. The BDI-II was found to be reliable and valid for the measurement of depression in patients with PD; therefore, it is available for use in clinical research and practice.

Screening performances of an 8-item UPSIT Italian version in the diagnosis of Parkinson's disease.

Hyposmia is a common finding in Parkinson's disease (PD) and is usually tested through the University of Pennsylvania Smell Identification Test (UPSIT). The aim of our study is to provide a briefer version of the Italian-adapted UPSIT test, able to discriminate between PD patients and healthy subjects (HS). By means of several univariate and multivariate (machine-learning-based) statistical approaches, we selected 8 items by which we trained a partial-least-square discriminant analysis (PLS-DA) and a decision tree (DT) model: class predictions of both models performed better with the 8-item version when compared to the 40-item version. An area under the receiver operating characteristic (AUC-ROC) curve built with the selected 8 odors showed the best performance (sensitivity 86.8%, specificity 82%) in predicting the PD condition at a cut-off point of ≤ 6. These performances were higher than those previously calculated for the 40-item UPSIT test (sensitivity 82% and specificity 88.2 % with a cut-off point of ≤ 21). Qualitatively, our selection contains one odor (i.e., apple) which is Italian-specific, supporting the need for cultural adaptation of smell testing; on the other hand, some of the selected best discriminating odors are in common with existing brief smell test versions validated on PD patients of other cultures, supporting the view that disease-specific odor patterns may exist and deserve a further evaluation.

Magnetic Resonance T1w/T2w Ratio in the Putamen and Cerebellum as a Marker of Cognitive Impairment in MSA: a Longitudinal Study.

The exact pathophysiology of cognitive impairment in multiple system atrophy (MSA) is unclear. In our longitudinal study, we aimed to analyze (I) the relationships between cognitive functions and some subcortical structures, such as putamen and cerebellum assessed by voxel-based morphometry (VBM) and T1-weighted/T2-weighted (T1w/T2w) ratio, and (II) the neuroimaging predictors of the progression of cognitive deficits. Twenty-six patients with MSA underwent a comprehensive neuropsychological battery, motor examination, and brain MRI at baseline (T0) and 1-year follow-up (T1). Patients were then divided according to cognitive status into MSA with normal cognition (MSA-NC) and MSA with mild cognitive impairment (MCI). At T1, we divided the sample according to worsening/non worsening of cognitive status compared to baseline evaluation. Logistic regression analysis showed that age (ß = - 9.45, p = .02) and T1w/T2w value in the left putamen (ß = 230.64, p = .01) were significant predictors of global cognitive status at T0, explaining 65% of the variance. Logistic regression analysis showed that ∆-values of WM density in the cerebellum/brainstem (ß = 2188.70, p = .02) significantly predicted cognitive worsening at T1, explaining 64% of the variance. Our results suggest a role for the putamen and cerebellum in the cognitive changes of MSA, probably due to their connections with the cortex. The putaminal T1w/T2w ratio may deserve further studies as a marker of cognitive impairment in MSA.

Machine learning can predict mild cognitive impairment in Parkinson's disease.

Background: Clinical markers of cognitive decline in Parkinson's disease (PD) encompass several mental non-motor symptoms such as hallucinations, apathy, anxiety, and depression. Furthermore, freezing of gait (FOG) and specific gait alterations have been associated with cognitive dysfunction in PD. Finally, although low cerebrospinal fluid levels of amyloid-ß42 have been found to predict cognitive decline in PD, hitherto PET imaging of amyloid-ß (Aß) failed to consistently demonstrate the association between Aß plaques deposition and mild cognitive impairment in PD (PD-MCI). Aim: Finding significant features associated with PD-MCI through a machine learning approach. Patients and methods: Patients were assessed with an extensive clinical and neuropsychological examination. Clinical evaluation included the assessment of mental non-motor symptoms and FOG using the specific items of the MDS-UPDRS I and II. Based on the neuropsychological examination, patients were classified as subjects without and with MCI (noPD-MCI, PD-MCI). All patients were evaluated using a motion analysis system. A subgroup of PD patients also underwent amyloid PET imaging. PD-MCI and noPD-MCI subjects were compared with a univariate statistical analysis on demographic data, clinical features, gait analysis variables, and amyloid PET data. Then, machine learning analysis was performed two times: Model 1 was implemented with age, clinical variables (hallucinations/psychosis, depression, anxiety, apathy, sleep problems, FOG), and gait features, while Model 2, including only the subgroup performing PET, was implemented with PET variables combined with the top five features of the former model. Results: Seventy-five PD patients were enrolled (33 PD-MCI and 42 noPD-MCI). PD-MCI vs. noPD-MCI resulted in older and showed worse gait patterns, mainly characterized by increased dynamic instability and reduced step length; when comparing amyloid PET data, the two groups did not differ. Regarding the machine learning analyses, evaluation metrics were satisfactory for Model 1 overcoming 80% for accuracy and specificity, whereas they were disappointing for Model 2. Conclusions: This study demonstrates that machine learning implemented with specific clinical features and gait variables exhibits high accuracy in predicting PD-MCI, whereas amyloid PET imaging is not able to increase prediction. Additionally, our results prompt that a data mining approach on certain gait parameters might represent a reliable surrogate biomarker of PD-MCI.

Combined regional T1w/T2w ratio and voxel-based morphometry in multiple system atrophy: A follow-up study.

Several MRI techniques have become available to support the early diagnosis of multiple system atrophy (MSA), but few longitudinal studies on both MSA variants have been performed, and there are no established MRI markers of disease progression. We aimed to characterize longitudinal brain changes in 26 patients with MSA (14 MSA-P and 12 MSA-C) over a 1-year follow-up period in terms of local tissue density and T1w/T2w ratio in a-priori regions, namely, bilateral putamen, cerebellar gray matter (GM), white matter (WM), and substantia nigra (SN). A significant GM density decrease was found in cerebellum and left putamen in the entire group (10.7 and 33.1% variation, respectively) and both MSA subtypes (MSA-C: 15.4 and 33.0% variation; MSA-P: 7.7 and 33.2%) and in right putamen in the entire group (19.8% variation) and patients with MSA-C (20.9% variation). A WM density decrease was found in the entire group (9.3% variation) and both subtypes in cerebellum-brainstem (MSA-C: 18.0% variation; MSA-P: 5% variation). The T1w/T2w ratio increase was found in the cerebellar and left putamen GM (6.6 and 24.9% variation), while a significant T1w/T2w ratio decrease was detected in SN in the entire MSA group (31% variation). We found a more progressive atrophy of the cerebellum in MSA-C with a similar progression of putaminal atrophy in the two variants. T1w/T2w ratio can be further studied as a potential marker of disease progression, possibly reflecting decreased neuronal density or iron accumulation.

The impact of executive dysfunctions on Theory of Mind abilities in Parkinson's disease.

Theory of Mind (ToM) is the ability to infer and reason about others' mental states, a process impaired by Parkinson's disease (PD). ToM performance in PD seems to be strongly related to executive functioning but the exact nature of this relationship is still unclear. We aim to investigate the direct impact of several executive dysfunctions on ToM deficits (Affective and Cognitive ToM) in PD patients. Sixty-eight PD patients underwent neuropsychological tests evaluating executive control such as inhibition, cognitive flexibility, processing speed or working memory and Cognitive and Affective ToM. We divided participants into two groups based on their performance on executive tests: PD patients with poor executive functioning (PD-EF-) and those with preserved executive functioning (PD-EF+). To explore the direct impact of executive subdomains on ToM abilities, two mediation models were executed in the whole sample. We found that PD patients with poor executive functioning reported poorer scores on Affective and Cognitive ToM tasks than PD patients with preserved executive functions, controlling for age and education. Moreover, parallel mediation models, conducted in the whole sample, indicated that performance on phonological fluency mediated the relationships between educational level and both Affective and Cognitive ToM, controlling the effect of other executive tests. These findings further support the idea that executive functions are crucial in ToM processes. Particularly, phonological fluency, whose execution requires both verbal abilities and cognitive flexibility, mediated ToM performance controlling the effect of other executive functions. The identification of neuropsychological processes underpinning ToM abilities might represent a plausible target for cognitive training to strengthen ToM abilities in PD.