MDS Abstracts

Abstracts from the International Congress of Parkinson’s and Movement Disorders.

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Articles tagged "Electroencephalogram(EEG)"

  • 2023 International Congress

    Data-driven Clustering of Neurodegenerative diseases based on EEG Spectrum power-law decay: the DaCNES Study.

    G. Mostile, R. Terranova, G. Carlentini, C. Terravecchia, G. Donzuso, G. Sciacca, C. Cicero, A. Luca, A. Nicoletti, M. Zappia (Catania, Italy)

    Objective: To test accuracy of the power law exponent β applied to EEG in differentiating neurodegenerative diseases and to explore differences in neuronal connectivity among…
  • 2023 International Congress

    Tai Chi training of people with Parkinson’s disease (PD) – neuropsychological and electrophysiological analyses

    U. Gschwandtner, K. Toloraia, M. Atanasova, TM. Al Tawil, S. Elsas, P. Fuhr (Basel, Switzerland)

    Objective: To analyze the influence of Tai Chi training on neurological changes, neuropsychology, quality of life (QoL) and EEG in PD patients. Background: Besides pharmacological…
  • 2023 International Congress

    Neuropathic mechanism of paroxysmal kinesigenic dyskinesia based on EEG

    XJ. Huang, HC. Luo, TF. Yuan, L. Cao (Shanghai, China)

    Objective: To disclose the neural mechanism of paroxysmal kinesigenic dyskinesia (PKD) based on the findings from high-density electroencephalogram (hd-EEG) and to explore a neural biomarker for…
  • 2023 International Congress

    Utility of quantitative EEG during sleep as a potential biomarker of Lewy body disease progression

    E. Matar, K. Ehgoetz Martens, R. Grunstein, A. D'Rozario, S. Lewis (Sydney, Australia)

    Objective: Objective: To assess whether progression from isolated REM sleep behaviour disorder (iRBD), established Parkinson’s disease (PD) and Dementia with Lewy bodies (DLB) are accompanied…
  • 2023 International Congress

    Linking volume of tissue activated to neural oscillations in deep brain stimulation

    A. Kutuzova, C. Graef, B. Lonergan, Y. Tai, S. Haar (London, United Kingdom)

    Objective: Exploring the effect of deep brain stimulation (DBS) settings on neural oscillations in Parkinson’s disease (PD) patients with subthalamic nucleus (STN) DBS and their…
  • 2023 International Congress

    Cognitive Interference in Postural Control as a Diagnostic and Prognostic Biomarker in Parkinsonian Disorders.

    R. Lloyd, C. Fearon, R. Reilly (Dublin, Ireland)

    Objective: The purpose of this research is to explore whether Progressive supranuclear palsy (PSP) patients display distinct sway patterns compared to idiopathic Parkinson's disease (PD)…
  • 2023 International Congress

    Mobile Brain / Body Imaging in early Parkinson’s Disease: the Twin Brain project

    M. Ajcevic, A. Buoite Stella, A. Miladinovic, M. Peskar, M. Kalc, T. Lombardo, M. Deodato, M. Catalan, U. Marusic, P. Manganotti (Trieste, Italy)

    Objective: We aimed to setup a novel Mobile Brain / Body Imaging (MoBI) system and to perform a feasibility study for the future investigations of…
  • 2023 International Congress

    Chronic sensorimotor cortex sensing using permanently implanted subgaleal leads in a patient receiving deep brain stimulation for Parkinson’s disease

    S. Sandoval-Pistorius, R. Fernandez-Gajardo, S. Cernera, P. Starr (San Francisco, USA)

    Objective: Assess the feasibility of chronic subgaleal cortical sensing using two distinct recording leads. Background: Pathological oscillatory activity in cortico-basal ganglia (BG) circuits is implicated…
  • 2023 International Congress

    Effects of Subthalamic Nucleus Deep Brain Stimulation on Phase Amplitude Coupling in Parkinson’s disease

    A. Bhattacharya, JF. Nankoo, N. Drummond, K. Udupa, A. Lozano, M. Hodaie, S. Kalia, A. Fasano, R. Munhoz, A. Lang, R. Chen (Toronto, Canada)

    Objective: To investigate the effects of deep brain stimulation (DBS) on neural activity in patients with Parkinson's disease (PD). Specifically, to assess the effects of…
  • 2023 International Congress

    Analysis of functional connectivity using machine learning and deep learning in EEG data from patients with focal dystonia

    C. Alves, A. Paulo, D. de Faria, J. Sato, S. Azevedo Silva, V. Borges, H. Ferraz, F. Rodrigues, C. Thielemann, P. Carvalho Aguiar (Sao Carlos Pinhal, Brazil)

    Objective: To apply a novel machine learning (ML) method to EEG data as a tool for the diagnosis of dystonia, providing a medical interpretation and…
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