Levodopa Responsive Parkinsonism in Patients with Hemochromatosis: Case Presentation and Literature Review

Hemochromatosis is an autosomal recessive disorder which leads to abnormal iron deposition in the parenchyma of multiple organs causing tissue damage. Accumulation of iron in the brain has been postulated to be associated with several neurodegenerative diseases including Parkinson\u27s disease. The excess iron promotes Parkin and α-synuclein aggregation in the neurons. Excess iron has also been noted in substantia nigra on MRI especially using susceptibility weighted imaging in patients with Parkinson\u27s disease. We present a case of a young male with alleles for both C282Y and H63D who presented with signs of Parkinsonism and demonstrated significant improvement with levodopa treatment

EDEN: A high-performance, general-purpose, NeuroML-based neural simulator

Modern neuroscience employs in silico experimentation on ever-increasing and more detailed neural networks. The high modelling detail goes hand in hand with the need for high model reproducibility, reusability and transparency. Besides, the size of the models and the long timescales under study mandate the use of a simulation system with high computational performance, so as to provide an acceptable time to result. In this work, we present EDEN (Extensible Dynamics Engine for Networks), a new general-purpose, NeuroML-based neural simulator that achieves both high model flexibility and high computational performance, through an innovative model-analysis and code-generation technique. The simulator runs NeuroML v2 models directly, eliminating the need for users to learn yet another simulator-specific, model-specification language. EDEN's functional correctness and computational performance were assessed through NeuroML models available on the NeuroML-DB and Open Source Brain model repositories. In qualitative experiments, the results produced by EDEN were verified against the established NEURON simulator, for a wide range of models. At the same time, computational-performance benchmarks reveal that EDEN runs up to 2 orders-of-magnitude faster than NEURON on a typical desktop computer, and does so without additional effort from the user. Finally, and without added user effort, EDEN has been built from scratch to scale seamlessly over multiple CPUs and across computer clusters, when available.Comment: 29 pages, 9 figure

BrainFrame: A node-level heterogeneous accelerator platform for neuron simulations

Objective: The advent of High-Performance Computing (HPC) in recent years has led to its increasing use in brain study through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though modern HPC platforms can often deal with such challenges, the vast diversity of the modeling field does not permit for a single acceleration (or homogeneous) platform to effectively address the complete array of modeling requirements. Approach: In this paper we propose and build BrainFrame, a heterogeneous acceleration platform, incorporating three distinct acceleration technologies, a Dataflow Engine, a Xeon Phi and a GP-GPU. The PyNN framework is also integrated into the platform. As a challenging proof of concept, we analyze the performance of BrainFrame on different instances of a state-of-the-art neuron model, modeling the Inferior- Olivary Nucleus using a biophysically-meaningful, extended Hodgkin-Huxley representation. The model instances take into account not only the neuronal- network dimensions but also different network-connectivity circumstances that can drastically change application workload characteristics. Main results: The synthetic approach of three HPC technologies demonstrated that BrainFrame is better able to cope with the modeling diversity encountered. Our performance analysis shows clearly that the model directly affect performance and all three technologies are required to cope with all the model use cases.Comment: 16 pages, 18 figures, 5 table

Fast Nearest Neighbor Search in Medical Image Databases

We examine the problem of finding similar tumor shapes. Starting from a natural similarity function (the so-called `max morpholog- ical distance'), we showed how to lower-bound it and how to search for nearest neighbors in large collections of tumor-like shapes. Specifically, we used state-of-the-art concepts from morphology, namely the `pattern spectrum' of a shape, to map each shape to a point in $n$-dimensional space. Following \cite{Faloutsos94Fast,Jagadish91Retrieval}, we organized the $n$-d points in an R-tree. We showed that the $L_infty$ (= max) norm in the $n$-d space lower-bounds the actual distance. This guarantees no false dismissals for range queries. In addition, we developed a nearest-neighbor algorithm that also guarantees no false dismissals. Finally, we implemented the method, and we tested it against a testbed of realistic tumor shapes, using an established tumor- growth model of Murray Eden \cite{Eden:61}. The experiments showed that our method is up to 27 times faster than straightfor- ward sequential scanning. (Also cross-referenced as UMIACS-TR-96-17

Sensorimotor Integration and GABA-ergic Activity in Embouchure Dystonia: An Assessment with Magnetoencephalography

Background: Embouchure dystonia (ED) is a task-specific dystonia affecting musicians thought to be related to alteration in sensorimotor processing and loss of cortical inhibition. Case Report: Magnetoencephalography-coherence source imaging (MEG-CSI) was used to map connectivity between brain regions by imaging neuronal oscillations that are coherent across the brain in patient with ED at rest and while using the index finger to evoke dystonia normally triggered by playing the flute. Discussion: During rest, there was increased coherence in the bilateral frontal and parietal regions that became more focal during dystonia. Diffuse hyperexcitability and increased coherence persisted in bilateral parietal regions as well as the bilateral frontal regions

Adjuvant medical therapy in cervical dystonia after deep brain stimulation: A retrospective analysis

Background: There is limited information on optimization of symptomatic management of cervical dystonia (CD) after implantation of pallidal deep brain stimulation (DBS). Objectives: To describe the long-term, real-world management of CD patients after DBS implantation and the role of reintroduction of pharmacologic and botulinum toxin (BoNT) therapy. Methods: A retrospective analysis of patients with focal cervical or segmental craniocervical dystonia implanted with DBS was conducted. Results: Nine patients were identified with a mean follow-up of 41.7 ± 15.7 months. All patients continued adjuvant oral medication(s) to optimize symptom control post-operatively. Three stopped BoNT and four reduced BoNT dose by an average of 22%. All patients remained on at least one medication used to treat dystonia post-operatively. Conclusion: Optimal symptom control was achieved with DBS combined with either BoNT and/or medication. We suggest utilization of adjuvant therapies such as BoNT and/or medications if DBS monotherapy does not achieve optimal symptom control

Heterozygous VPS13A and PARK2 Mutations in a Patient with Parkinsonism and Seizures

Neuroacanthocytosis (NA) is a diverse group of disorders in which nervous system abnormalities co-occur with irregularly shaped red blood cells called acanthocytes. Chorea-acanthocytosis is the most common of these syndromes and is an autosomal recessive disease caused by mutations in the vacuolar protein sorting 13A (VPS13A) gene. We report a case of early onset parkinsonism and seizures in a 43-year-old male with a family history of NA. Neurologic examinations showed cognitive impairment and marked parkinsonian signs. MRI showed bilateral basal ganglia gliosis. He was found to have a novel heterozygous mutation in the VPS13A gene, in addition a heterozygous mutation in the PARK2 gene. His clinical picture was atypical for typical chorea-acanthocytosis (ChAc). The compound heterozygous mutations of VPS13A and PARK2 provide the most plausible explanation for this patient’s clinical symptoms. This case adds to the phenotypic diversity of ChAc. More research is needed to fully understand the roles of epistatic interactions on phenotypic expression of neurodegenerative diseases

The Effect of Botulinum Toxin on Network Connectivity in Cervical Dystonia: Lessons from Magnetoencephalography

Background: Pharmacological management of cervical dystonia (CD) is considered to be symptomatic in effect, rather than targeting the underlying pathophysiology of the disease. Magnetoencephalography (MEG), a direct measure of neuronal activity, while accepted as a modality for pre-surgical mapping in epilepsy, has never been used to explore the effect of pharmacotherapy in movement disorders. Methods: Resting state MEG data were collected from patients with CD, pre- and post-botulinum toxin injections. All of these patients exhibited good clinical benefit with botulinum toxin. Resting state MEG data from four age- and gender-matched healthy controls with no neurological disorders were also collected. Results: Our exploratory study reveals a difference in coherence between controls and patients in the following regions: fronto-striatal, occipito-striatal, parieto-striatal, and striato-temporal networks. In these regions there is an increase after botulinum toxin. Specifically, increased coherence in the left putamen and right superior parietal gyrus was noticeable. Both intrahemispheric and interhemispheric networks were affected. Discussion: This is the first attempt to directly assess changes in functional connectivity with pharmacotherapy using MEG. Botulinum toxin might affect sensorimotor integration, leading to clinical benefit. The presence of increased interhemispheric coherence and intrahemispheric coherence points to the importance of global and local networks in the pathophysiology of dystonia

Multimodal Imaging in a Patient with Hemidystonia Responsive to GPi Deep Brain Stimulation

BACKGROUND: Dystonia is a syndrome with varied phenomenology but our understanding of its mechanisms is deficient. With neuroimaging techniques, such as fiber tractography (FT) and magnetoencephalography (MEG), pathway connectivity can be studied to that end. We present a hemidystonia patient treated with deep brain stimulation (DBS). METHODS: After 10 years of left axial hemidystonia, a 45-year-old male underwent unilateral right globus pallidus internus (GPi) DBS. Whole brain MEG before and after anticholinergic medication was performed prior to surgery. 26-direction diffusion tensor imaging (DTI) was obtained in a 3 T MRI machine along with FT. The patient was assessed before and one year after surgery by using the Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS). RESULTS: In the eyes-closed MEG study there was an increase in brain coherence in the gamma band after medication in the middle and inferior frontal region. FT demonstrated over 50% more intense ipsilateral connectivity in the right hemisphere compared to the left. After DBS, BFMDRS motor and disability scores both dropped by 71%. CONCLUSION: Multimodal neuroimaging techniques can offer insights into the pathophysiology of dystonia and can direct choices for developing therapeutics. Unilateral pallidal DBS can provide significant symptom control in axial hemidystonia poorly responsive to medication