Pattern Of Parkinson's Disease Research Articles

Functional MRI for the Assessment of Brain Connectivity in Neurodegenerative Diseases: An Observational Study in Mexico City

Introduction: Neurodegenerative diseases are characterized by progressive brain dysfunction and structural changes. Functional MRI (fMRI), a non-invasive imaging technique, offers the potential to assess brain connectivity and identify early biomarkers of these diseases. Methods: This observational study included patients with Alzheimer's disease (AD), Parkinson's disease (PD), and healthy controls in Mexico City. Resting-state fMRI data was acquired, and brain connectivity was analyzed using independent component analysis (ICA) and seed-based correlation analysis (SCA). Results: fMRI revealed altered brain connectivity patterns in AD and PD compared to healthy controls. In AD, decreased connectivity was observed within the default mode network (DMN), while PD patients showed reduced connectivity in the motor network. Conclusion: fMRI provides valuable insights into brain connectivity changes in neurodegenerative diseases. These findings contribute to the development of early diagnostic tools and potential therapeutic targets for AD and PD.

Longitudinal brain changes in Parkinson's disease with severe olfactory deficit

IntroductionOlfactory dysfunction and REM sleep behavior disorder (RBD) are associated with distinct cognitive trajectories in the course of Parkinson's disease (PD). The underlying neurobiology for this relationship remains unclear but may involve distinct patterns of neurodegeneration. This study aimed to examine longitudinal cortical atrophy and thinning in early-stage PD with severe olfactory deficit (anosmia) without and with concurrent probable RBD. MethodsLongitudinal MRI data over four years of 134 de novo PD and 49 healthy controls (HC) from the Parkinson Progression Marker Initiative (PPMI) cohort were analyzed using a linear mixed-effects model. Patients were categorized into those with anosmia by the University of Pennsylvania Smell Identification Test (UPSIT) score ≤ 18 (AO+) and those without (UPSIT score > 18, AO-). The AO+ group was further subdivided into AO+ with probable RBD (AO+RBD+) and without (AO+RBD-) for subanalysis. ResultsCompared to subjects without baseline anosmia, the AO+ group exhibited greater longitudinal declines in both volume and thickness in the bilateral parahippocampal gyri and right transverse temporal gyrus. Patients with concurrent anosmia and RBD showed more extensive longitudinal declines in cortical volume and thickness, involving additional brain regions including the bilateral precuneus, left inferior temporal gyrus, right paracentral gyrus, and right precentral gyrus. ConclusionsThe atrophy/thinning patterns in early-stage PD with severe olfactory dysfunction include regions that are critical for cognitive function and could provide a structural basis for previously reported associations between severe olfactory deficit and cognitive decline in PD. Concurrent RBD might enhance the dynamics of cortical changes.

Association between major dietary patterns and Parkinson's disease risk: a case-control study.

There has been emerging attention to investigate the possible role of some dietary factors in the pathogenesis of Parkinson's disease (PD); however, evidence about the relationship between dietary components and the risk of PD is limited. The aim of this study was to determine the association between major dietary patterns and the risk of PD. This case-control study was performed on 105 patients with newly diagnosed PD and 215 healthy controls. Diagnosis of Parkinson's disease was made based on the UK Brain Bank criteria. Usual dietary intakes were collected by a validated semi-quantitative food frequency questionnaire. Dietary patterns were detected by principal component analysis. Four dietary patterns, including traditional, healthy, western, and light dietary patterns, were identified. After considering all potential confounders, individuals with the highest tertile of traditional dietary pattern scores had a lower risk of PD than those with the lowest tertile (OR: 0.002; 95% CI: 0.000-0.016). A similar inverse association between the healthy pattern (OR: 0.314; 95% CI: 0.131-0.750) and light pattern (OR: 0.282; 95% CI: 0.121-0.654) and risk of PD was revealed. In contrast, adherence to the western dietary pattern was associated with PD incidence (OR: 7.26; 95% CI: 2.76-19.09). The findings of this study suggest that adherence to western dietary pattern could increase the risk of PD by approximately seven times. However, the traditional, healthy, and light dietary patterns had an inverse relationship with PD risk.

Atypical brain FDG-PET patterns increase the risk of long-term cognitive and motor progression in Parkinson's disease

IntroductionBrain hypometabolism patterns have been previously associated with cognitive decline in Parkinson's disease (PD). Our aim is to evaluate the impact of single-subject fluorodeoxyglucose (FDG)-PET brain hypometabolism on long-term cognitive and motor outcomes in PD. MethodsForty-nine non-demented PD patients with baseline brain FDG-PET data underwent an extensive clinical follow-up for 8 years. The ability of FDG-PET to predict long-term cognitive and motor progression was evaluated using Cox regression and mixed ANCOVA models. ResultsParticipants were classified according to FDG-PET pattern in PD with typical (n = 26) and atypical cortical metabolism (n = 23). Patients with atypical brain hypometabolic patterns showed higher incidence of dementia (60% vs 3%; HR = 18.3), hallucinations (56% vs 7%, HR = 7.3) and faster motor decline compared to typical pattern group. ConclusionThis study argues for specific patterns of FDG-PET cortical hypometabolism in PD as a prognostic marker for long term cognitive and motor outcomes at single-subject level.

Machine learning screening for Parkinson's disease-related cuproptosis-related typing development and validation and exploration of personalized drugs for cuproptosis genes.

Parkinson's disease (PD) is a common, degenerative disease of the nervous system that is characterized by the death of dopaminergic neurons in the substantia nigra densa (SNpc). There is growing evidence that copper (Cu) is involved in myelin formation and is involved in cell death through modulation of synaptic activity as well as neurotrophic factor-induced excitotoxicity. This study aimed to explore potential cuproptosis-related genes (CRGs) and immune infiltration patterns in PD and the development of Cu chelators relevant for PD treatment. The PD datasets GSE7621, GSE20141, and GSE49036 were downloaded from the Gene Expression Omnibus (GEO) database. The consensus clustering method was used to classify the specimens of PD. Using weighted gene co-expression network analysis (WGCNA) and random forest (RF) tree model, support vector machine (SVM) learning model, extreme gradient boosting (XGBoost) model, and general linear model (GLM) algorithms to screen disease progression-related models, the column charts were created to verify the accuracy of these CRGs in predicting PD progression. Single sample genomic enrichment analysis (ssGSEA) was used to estimate the correlation between genes associated with copper poisoning and genes associated with immune cells and immune function. Molecular docking was used to verify interactions with copper chelating agents associated with cuproptosis for PD treatment. Through ssGSEA, we identified three copper poisoning related genes ATP7A, NFE2L2 and MTF1, which are related to immune cells in PD. We also verified that LAGASCATRIOL can bind to NFE2L2 through molecular docking. Consistent cluster analysis identified two subtypes, among which C2 subtype was just enriched in PD. And to more accurately diagnose PD progression, patients can benefit from a feature map based on these genes. CRGs such as NFE2L2, MTF1, and ATP7B were identified to be associated with the pathogenesis of PD and provide a possible new direction for the treatment of PD, which needs further in-depth study.

Single- and dual-task gait performance and their diagnostic value in early-stage Parkinson's disease.

BackgroundGait parameters are considered potential diagnostic markers of Parkinson's disease (PD). We aimed to 1) assess the gait impairment in early-stage PD and its related factors in the single-task (ST) and dual-task (DT) walking tests and 2) evaluate and compare the diagnostic value of gait parameters for early-stage PD under ST and DT conditions.MethodsA total of 97 early-stage PD patients and 41 healthy controls (HC) were enrolled at Hwa Mei hospital. Gait parameters were gathered and compared between the two groups in the ST and DT walking test, controlling for covariates. Utilizing the receiver operating characteristic curve, diagnostic parameters were investigated.ResultsIn the ST walking test, significantly altered gait patterns could be observed in early-stage PD patients in all domains of gait, except for asymmetry (P < 0.05). Compared to the ST walking test, the early-stage PD group performed poorly in the DT walking test in the pace, rhythm, variability and postural control domain (P < 0.05). Older, heavier subjects, as well as those with lower height, lower level of education and lower gait velocity, were found to have a poorer gait performance (P < 0.05). Stride length (AUC = 0.823, sensitivity, 68.0%; specificity, 85.4%; P < 0.001) and heel strike angle (AUC = 0.796, sensitivity, 71.1%; specificity, 80.5%; P < 0.001) could distinguish early-stage PD patients from HCs with moderate accuracy, independent of covariates. The diagnostic accuracy of gait parameters under ST conditions were statistically noninferior to those under DT conditions(P>0.05). Combining all gait parameters with diagnostic values under ST and DT walking test, the predictive power significantly increased with an AUC of 0.924 (sensitivity, 85.4%; specificity, 92.7%; P < 0.001).ConclusionGait patterns altered in patients with early-stage PD but the gait symmetry remained preserved. Stride length and heel strike angle were the two most prominent gait parameters of altered gait in early-stage of PD that could serve as diagnostic markers of early-stage PD. Our findings are helpful to understand the gait pattern of early-stage PD and its related factors and can be conducive to the development of new diagnostic tools for early-stage PD.

The role of NOTCH2NLC in Parkinson's disease: A clinical, neuroimaging, and pathological study.

Recently, the pathogenic and intermediate GGC repeat expansion in NOTCH2NLC was detected in Parkinson's disease (PD). However, detailed clinical, neuroimaging, and pathological information of clinically diagnosed PD patients with pathogenic GGC repeat expansion in NOTCH2NLC remains scarce. Thus, we aimed to elucidate the clinical, neuroimaging, and pathological characteristics of PD patients carrying the pathogenic GGC repeat expansion in NOTCH2NLC. The NOTCH2NLC GGC repeat expansion was screened in 941 sporadic PD patients and 244 unrelated probands. Comprehensive assessments were performed in three PD patients with pathogenic GGC repeat expansion in NOTCH2NLC. The repeat expansion length was estimated using CRISPR/Cas9-based targeted long-read sequencing. The three patients (two PD patients from Family 1 and one sporadic PD) carrying the pathogenic NOTCH2NLC expansion were reconfirmed with a diagnosis of clinically established PD. Although they lacked the typical neuronal intranuclear inclusion disease (NIID) magnetic resonance imaging (MRI) feature, the typical PD pattern of striatal dopamine transporter loss was detected. Notably, all three patients presented with systemic areflexia, and other secondary causes of polyneuropathy were excluded. Skin biopsy showed intranuclear inclusions and an absence of phosphorylated alpha-synuclein deposition in the skin nerve fibers of all three patients. Although these clinically diagnosed PD patients with pathogenic GGC repeat expansion in NOTCH2NLC were hardly distinguishable from idiopathic PD based on clinical course and neuroimaging features, the pathological findings indicated that their phenotype was a PD phenocopy of NIID. Systemic areflexia may be an important and unique clinical clue suggesting further genetic testing and skin biopsy examination to confirm the diagnosis of NIID in patients presenting with a PD phenocopy.

Combined GCASE/ALPHA-synuclein pattern may identify specific prodomal PD patterns in GBA carriers: A cluster analysis study

Glucocerebrosidase (GBA) gene mutations are the most frequent genetic risk factor for Parkinson's disease (PD). Relationship between GBA status and increased risk for GBA-PD is still unclear. We investigated whether glucocerebrosidase activity (GCase) and α-synuclein levels in blood cells in asymptomatic subjects carrying GBA mutations (GBA carriers) are associated with a more severe prodromal PD profile.

Parkinson Disease-Related Brain Metabolic Patterns and Neurodegeneration in Isolated REM Sleep Behavior Disorder.

To elucidate the role of Parkinson disease (PD)-related brain metabolic patterns as a biomarker in isolated REM sleep behavior disorder (iRBD) for future disease conversion. This is a prospective cohort study consisting of 30 patients with iRBD, 25 patients with de novo PD with a premorbid history of RBD, 21 patients with longstanding PD on stable treatment, and 24 healthy controls. The iRBD group was longitudinally followed up. All participants underwent 18F-fluorodeoxyglucose (FDG) PET and were evaluated with olfaction, cognition, and the Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) at baseline. From FDG-PET scans, we derived metabolic patterns from the longstanding PD group (PD-RP) and de novo PD group with RBD (dnPDRBD-RP). Subsequently, we calculated the PD-RP and dnPDRBD-RP scores in patients with iRBD. We validated the metabolic patterns in each PD group and separate iRBD cohort (n = 14). The 2 patterns significantly correlated with each other and were spatially overlapping yet distinct. The MDS-UPDRS motor scores significantly correlated with PD-RP (p = 0.013) but not with dnPDRBD-RP (p = 0.076). In contrast, dnPDRBD-RP correlated with olfaction in butanol threshold test (p = 0.018) in patients with iRBD, but PD-RP did not (p = 0.21). High dnPDRBD-RP in patients with iRBD predicted future phenoconversion with all cutoff ranges from 1.5 to 3 SD of the control value, whereas predictability of PD-RP was only significant in a partial range of cutoff. The dnPDRBD-RP is an efficient neuroimaging biomarker that reflects prodromal features of PD and predicts phenoconversion in iRBD that can be applied individually. This study provides Class IV evidence that a de novo PD pattern on FDG-PET predicts future conversion to neurodegenerative disease in patients with iRBD.

Shared imaging biomarkers across Alzheimer’s and Parkinson’s disease

AbstractBackgroundAlzheimer's disease (AD) and Parkinson's disease (PD) are the two of the most common neurodegenerative diseases [1]. In previous studies, AD and PD demonstrate overlap in clinical syndromes, including presence of cognitive impairment, dementia in PD, and post‐mortem studies with regional atrophy and amyloid and tau deposition [2][3]. Here, we propose a novel morphometric‐feature based machine learning model to explore shared degenerative patterns in AD and PD on neuroimaging.MethodWe used T1‐weighted (T1w) MRI data from (PPMI) 166 controls/356 de novo PD patients, and (ADNI‐1) 242 controls/199 AD patients. As a baseline model we trained sparse spatially regularized (TV‐L1) logistic regression [6][7] using subcortical shape and cortical thickness [4][5] from T1w MRI. To train the two models jointly, we constrain the optimization with a cross‐disorder (CD) agreement term: the L2 model difference, weighted by the models’ local normalized mutual information (MI). The CD‐MI term allows the models to guide each other’s optimization, dynamically amplifying information sharing where degenerative patterns are most similar and minimizing sharing where they are dissimilar. We evaluate all models’ ROC area‐under‐the‐curve (ROC AUC) using nested cross‐validation and a shuffle‐split bootstrap test to assess model stability. For subcortical regions, we trained models using all regions, as well as individual models for each region (L/R thalamus, putamen, caudate, pallidum, hippocampus, amygdala, accumbens).ResultInformation sharing significantly improved predictive power for cortical thickness‐based, L amygdala, L caudate, and bilateral putamen models (Table 1, Figure 4). Weight maps of AD and PD models (Figures 1a,b,2) show areas of similar degenerative patterns in frontal and parietal association areas, thalamus caudate and putamen, confirmed by the mutual information maps (Figures 1c,3).ConclusionWe designed a novel machine learning model to explore joint imaging biomarkers between Alzheimer's and Parkinson’s disease. Our findings on neuroimaging suggest shared topography of frontal, parietal, temporal, and cingulate changes for AD and PD. This may signify overlap of underlying pathologies with co‐existent amyloid and tau burden in both AD and PD.

Longitudinal change in dopamine transporter availability in idiopathic REM sleep behavior disorder.

To elucidate longitudinal changes in the dopamine transporter (DAT) availability in association with the prodromal markers in idiopathic REM sleep behavior disorder (iRBD), we analyzed a longitudinal prospective iRBD cohort data. The study cohort consisted of patients with iRBD, individuals with Parkinson disease (PD), and healthy controls. All participants were evaluated for olfaction, neuropsychological tests, and the Movement Disorders Society-Unified Parkinson's Disease Rating Scale and underwent 18F-FP-CIT PET scans every 2 years. We calculated the DAT pattern by performing the principal component analysis of tracer uptakes in 6 striatal regions. DAT patterns in patients with iRBD with baseline hyposmia, constipation, and mild parkinsonian signs distributed toward the PD pattern and clearly distinguished from the healthy control pattern. The DAT pattern moved toward the PD pattern over time in some patients with iRBD during the follow-up, and baseline hyposmia was the only biomarker significantly associated with this change. Baseline PD pattern of DAT predicted 58% of disease converters (hazard ratio 4.95 [95% confidence interval 1.16-21.08]). The combination of hyposmia and baseline PD pattern of DAT predicted 67% of the conversion (hazard ratio 7.89 [confidence interval 1.85-33.69]). The estimated sample size required for a simulated neuroprotective clinical trial was 63 per group when the annual change of DAT pattern was used as an outcome in the subgroup with baseline DAT PD pattern and hyposmia, which is the smallest number reported so far. Baseline and longitudinal monitoring of the DAT pattern can be a useful biomarker in identifying individuals with a high risk of disease conversion and in selecting the potential population for clinical trials in iRBD.

Structural white matter alterations as compensatory mechanisms in Parkinson's disease: A systematic review of diffusion tensor imaging studies.

Compensation is described as normal or near to normal performance in Parkinson's disease (PD), despite the ongoing neural loss. Functional compensation typically proceeds in an inverse U-shaped manner: compensation initiates in the prodromal phase, followed by an increasing episode until plateauing and diminishes in the advanced stages of the disease. The first evidence of the structural compensation was reported by functional magnetic resonance imaging studies. Recent studies, which have used diffusion tensor imaging (DTI) as the basis for their investigation, have shown improved white matter diffusional properties both in motor- and non-motor-related structures in association with improved clinical scores in patients with PD. The majority of DTI studies have demonstrated microstructural compensation in the prodromal/early stages of PD at the regional scale. However, there have been reports of compensation in later stages of the disease and the whole-brain/network scale that are probably due to the heterogeneous nature of PD. Although serving as a promising beginning to characterize compensation, lots remain to be clarified in understanding the underlying mechanisms of compensation and its structural pattern in PD. The existing knowledge gap necessitates studies that their main research questions are focused on structural compensation. This requirement becomes more apparent because structural compensation evidence has mostly emerged from the post hoc analysis of data and incidental findings of studies. Thus, future studies are required to investigate compensatory microstructural changes in PD to clarify the exact underlying mechanisms. These studies would also provide a basis to develop clinical improvements in the early diagnosis and management of PD.

Subcortical atrophy and perfusion patterns in Parkinson disease and multiple system atrophy

BackgroundThe clinical differentiation between Parkinson disease (PD) and multiple system atrophy (MSA) is difficult. ObjectivesArterial spin labeling (ASL) is an advanced MRI technique that obviates the use of an exogenous contrast agent for the estimation of cerebral perfusion. We explored the value of ASL in combination with structural MRI for the differentiation between PD and MSA. MethodsNinety-four subjects (30 PD, 30 MSA and 34 healthy controls) performed a morphometric and ASL-MRI to measure volume and perfusion values within basal ganglia and cerebellum. A region-of-interest analysis was performed to test for structural atrophy and regional blood flow differences between groups. ResultsMSA patients showed higher subcortical atrophy than both PD patients and HC, while no differences were observed between the latter. MSA and PD showed lower volume-corrected perfusion values than HC in several cerebellar areas (Crus I, Crus II, right VIIb, right VIIIa, right VIIIb), right caudate and both thalami. MSA and PD patients displayed similar perfusion values in all aforementioned areas, but the right cerebellar area VIIIb (lower in MSA) and right caudate and both thalami (lower in PD). Similar results were obtained when comparing PD and MSA patients with the parkinsonian variant. ConclusionsA perfusion reduction was equally observed in both MSA and PD patients in cerebellar areas that are putatively linked to cognitive (i.e., executive) rather than motor functions. The observed hypo-perfusion could not be explained by atrophy, suggesting the involvement of the cerebellum in the pathophysiology of both MSA and PD.

Uncovering the Heterogeneity and Temporal Complexity of Progressive Supranuclear Palsy and Parkinson's Disease with Subtype and Stage Inference [Presidential Award Proceedings

In this study, subtype and stage inference analysis (SuStaIn) was performed based on the data obtained from cross-sectional brain structure magnetic resonance imaging, in order to clarify the differences in the temporal progression pattern of brain atrophy for progressive supranuclear palsy (PSP) and Parkinson's disease (PD). SuStaIn was able to estimate the spatial brain atrophy progression pattern in PD and PSP and was useful for the classification of these diseases.

Distinct Autoimmune Anti-α-Synuclein Antibody Patterns in Multiple System Atrophy and Parkinson's Disease.

Aggregation of alpha-synuclein (α-syn) is considered to be the major pathological hallmark and driving force of Multiple System Atrophy (MSA) and Parkinson's disease (PD). Immune dysfunctions have been associated with both MSA and PD and recently we reported that the levels of natural occurring autoantibodies (NAbs) with high-affinity/avidity toward α-synuclein are reduced in MSA and PD patients. Here, we aimed to evaluate the plasma immunoglobulin (Ig) composition binding α-syn and other amyloidogenic neuropathological proteins, and to correlate them with disease severity and duration in MSA and PD patients. All participants were recruited from a single neurological unit and the plasma samples were stored for later research at the Bispebjerg Movement Disorder Biobank. All patients were diagnosed according to current consensus criteria. Using multiple variable linear regression analyses, we observed higher levels of anti-α-syn IgG1 and IgG3 NAbs in MSA vs. PD, higher levels of anti-α-syn IgG2 NAbs in PD compared to controls, whereas anti-α-syn IgG4 NAbs were reduced in PD compared to MSA and controls. Anti-α-syn IgM levels were decreased in both MSA and PD. Further our data supported that MSA patients' immune system was affected with reduced IgG1 and IgM global levels compared to PD and controls, with further reduced global IgG2 levels compared to PD. These results suggest distinct autoimmune patterns in MSA and PD. These findings suggest a specific autoimmune physiological mechanism involving responses toward α-syn, differing in neurodegenerative disease with overlapping α-syn pathology.

Recent Advancement and Clinical Implications of 18FDG-PET in Parkinson's Disease, Atypical Parkinsonisms, and Other Movement Disorders.

The molecular imaging field has been very instrumental in identifying the multiple network interactions that compose the human brain. The cerebral glucose metabolism is associated with neural function. 18F-fluoro-deoxyglucose-PET (FDG-PET) studies reflect brain metabolism in a pattern-specific manner. This article reviews FDG-PET studies in Parkinson's disease (PD), atypical parkinsonism (AP), Huntington's disease (HD), and dystonia. The metabolic pattern of PD, disease progression, non-motor symptoms such as fatigue, depression, apathy, impulse control disorders, and cognitive impairment, and the risk of progression to dementia have been identified with FDG-PET studies. In prodromal PD, the REM sleep behavior disorder-related covariance pattern has been described. In AP, FDG-PET studies have demonstrated to be superior to D2/D3 SPECT in differentiating PD from AP. The metabolic patterns of HD and dystonia have also been described. FDG-PET studies are an excellent tool to identify patterns of brain metabolism.

The Ventral Intermediate Nucleus Differently Modulates Subtype-Related Networks in Parkinson's Disease.

Background: Posture instability gait difficulty-dominant (PIGD) and tremor-dominant (TD) are two subtypes of Parkinson’s disease (PD). The thalamus is involved in the neural circuits of both subtypes. However, which subregion of the thalamus has an influence on the PD subtypes remains unclear.Objective: To explore the core subregion of the thalamus showing a significant influence on the PD subtypes and its directional interaction between the PD subtypes.Methods: A total of 79 PD patients (43 TD and 36 PIGD) and 31 normal controls (NC) were enrolled, and the gray matter volume and perfusion characteristics in the thalamus were compared between the three groups. The subregion of the thalamus with significantly different perfusion and volume among three groups was used as the seed of a Granger causality analysis (GCA) to compare the causal connectivity between different subtypes.Results: Perfusion with an increased gradient among the three groups (TD > PIGD > NC) in the bilateral ventral intermediate nucleus (Vim) was observed, which was positively correlated with the clinical tremor scores. The GCA revealed that TD patients had enhanced causal connectivity from the bilateral Vim to the bilateral paracentral gyrus, M1 and the cerebellum compared with the NC group, while the PIGD subtype revealed an increased causal connectivity from the bilateral Vim to the bilateral premotor cortex (preM) and putamen. Additionally, there were positive correlations between the tremor scores and a causal connectivity from the Vim to the cerebellum. The connectivity from the right Vim to the right preM and the right putamen was positively correlated with the PIGD scores.Conclusion: This multilevel analysis showed that the Vim had a significant influence on the PD subtypes and that it differentially mediated the TD and PIGD-related causal connectivity pattern in PD.

Motor Learning Deficits in Parkinson's Disease (PD) and Their Effect on Training Response in Gait and Balance: A Narrative Review.

Parkinson's disease (PD) is a neurological disorder traditionally associated with degeneration of the dopaminergic neurons within the substantia nigra, which results in bradykinesia, rigidity, tremor, and postural instability and gait disability (PIGD). The disorder has also been implicated in degradation of motor learning. While individuals with PD are able to learn, certain aspects of learning, especially automatic responses to feedback, are faulty, resulting in a reliance on feedforward systems of movement learning and control. Because of this, patients with PD may require more training to achieve and retain motor learning and may require additional sensory information or motor guidance in order to facilitate this learning. Furthermore, they may be unable to maintain these gains in environments and situations in which conscious effort is divided (such as dual-tasking). These shortcomings in motor learning could play a large part in degenerative gait and balance symptoms often seen in the disease, as patients are unable to adapt to gradual sensory and motor degradation. Research has shown that physical and exercise therapy can help patients with PD to adapt new feedforward strategies to partially counteract these symptoms. In particular, balance, treadmill, resistance, and repeated perturbation training therapies have been shown to improve motor patterns in PD. However, much research is still needed to determine which of these therapies best alleviates which symptoms of PIGD, the needed dose and intensity of these therapies, and long-term retention effects. The benefits of such technologies as augmented feedback, motorized perturbations, virtual reality, and weight-bearing assistance are also of interest. This narrative review will evaluate the effect of PD on motor learning and the effect of motor learning deficits on response to physical therapy and training programs, focusing specifically on features related to PIGD. Potential methods to strengthen therapeutic effects will be discussed.

Patient characteristics and drug prescribing pattern in Parkinson disease: A hospital based study in Sri Lanka

Purpose of the study: To describe the demographic factors, pattern of anti-Parkinsonism drugs used and to identify factors influencing treatment in PD patients attending Colombo South Teaching Hospital (CSTH) in Sri Lanka.Methods: A descriptive cross sectional study was conducted at CSTH during March 2012 - September 2012, recruiting patients with PD (according to diagnostic criteria of the United Kingdom Parkinson’s Disease Society Brain Bank) attending neurology and medical clinics.Results: There were 103 PD patients, with a mean age of 64 yrs (SD 9.6, range 43-86) and 58 (56.3%) were males. Duration of illness ranged from 1 month to 15 yrs (median 2 yrs) and average age of onset was 61yrs (SD 9.6, range 41 - 82). 13 patients (12.6%) had onset of PD before 50yrs. Majority (n=57, 55.3%) had at least one co-morbidity. Levodopa alone was the treatment in 100 (97.1%) patients, Ropinirole alone in one, and 10 (9.7%) on Levodopa and Ropinirole combination with 2 (2%) drug-naïve patients. Benzhexol was used in 82 (79.6%) patients. Sex, disease severity, duration of illness, education level or employment status did not differ between treatment groups.Conclusion: PD is a commonly seen neurodegenerative disorder in hospital outpatient clinics and majority had other co-morbidities. Levodopa and Benzhexol are the commonly used drugs in Sri Lanka. Use of dopa agonists are much less common when compared to other countries. Age, the age of onset of PD, cost, and availability are major determinants of treatment.

Abnormal phasic activity in saliency network, motor areas, and basal ganglia in Parkinson's disease during rhythm perception.

Behavioral studies indicate that persons with Parkinson's disease have complexity dependent problems with the discrimination of auditory rhythms. Furthermore, neuroimaging studies show that rhythm processing activates many brain areas that overlap with areas affected by Parkinson's disease (PD). This study sought to investigate the neural correlates of rhythm processing in PD and healthy controls, with a particular focus on rhythmic complexity. We further aimed to investigate differences in brain activation during initial phases of rhythm processing. Functional magnetic resonance imaging was used to scan 15 persons with Parkinson's disease and 15 healthy controls while they listened to musical rhythms with two different levels of complexity. Rhythmic complexity had no significant effect on brain activations, but patients and controls showed differences in areas related to temporal auditory processing, notably bilateral planum temporale and inferior parietal lobule. We found indications of a particular sequential or phasic activation pattern of brain activity, where activity in caudate nucleus in the basal ganglia was time‐displaced by activation in the saliency network—comprised of anterior cingulate cortex and bilateral anterior insula—and cortical and subcortical motor areas, during the initial phases of listening to rhythms. We relate our findings to core PD pathology, and discuss the overall, rhythm processing related hyperactivity in PD as a possible dysfunction in specific basal ganglia mechanisms, and the phasic activation pattern in PD as a reflection of a lack of preparatory activation of task‐relevant brain networks for rhythm processing in PD.