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Identification of nonlinear features in cortical and subcortical signals of Parkinson's Disease patients via a novel efficient measure

Tolga Esat Özkurt, Harith Akram, Ludvic Zrinzo, Patricia Limousin, Tom Foltynie, Ashwini Oswal, Vladimir Litvak
2020 NeuroImage  
This study offers a novel and efficient measure based on a higher order version of autocorrelative signal memory that can identify nonlinearities in a single time series.  ...  Conversely, for the cortical signals nonlinearity was present for the ON medication state with a peak in the alpha band and correlated with contralateral akinesia and rigidity (r=0.46, p=0.02).  ...  TEÖ was supported by a grant from Scientific and Technological Research ouncil of Turkey (T B T B EB -2219).  ... 
doi:10.1016/j.neuroimage.2020.117356 pmid:32916287 pmcid:PMC8417768 fatcat:aps4rub5unbobizdgup2ut4loa

Creating the Feedback Loop

Adam O. Hebb, Jun Jason Zhang, Mohammad H. Mahoor, Christos Tsiokos, Charles Matlack, Howard Jay Chizeck, Nader Pouratian
2014 Neurosurgery clinics of North America  
Current DBS therapy delivers a train of electrical pulses at set stimulation parameters.  ...  This review addresses advances to date, not of the technology per se, but of the strategies to apply neuronal signals to trigger or modulate stimulation systems.  ...  Investigations of LFP measured via electrocorticographic arrays in patients with Parkinson's disease have noted increased beta band activity and synchronization within the motor cortex in patients with  ... 
doi:10.1016/j.nec.2013.08.006 pmid:24262909 pmcid:PMC4058859 fatcat:cvxhliuwpzhlxoh3buyll62izu

Evaluating the Different Stages of Parkinson's Disease Using Electroencephalography With Holo-Hilbert Spectral Analysis

Kuo-Hsuan Chang, Isobel Timothea French, Wei-Kuang Liang, Yen-Shi Lo, Yi-Ru Wang, Mei-Ling Cheng, Norden E. Huang, Hsiu-Chuan Wu, Siew-Na Lim, Chiung-Mei Chen, Chi-Hung Juan
2022 Frontiers in Aging Neuroscience  
Electroencephalography (EEG) can reveal the abnormalities of dopaminergic subcortico-cortical circuits in patients with Parkinson's disease (PD).  ...  A novel Holo-Hilbert Spectral Analysis (HHSA) was applied to reveal non-linear features of resting state EEG in 99 PD patients and 59 healthy controls (HCs).  ...  Although our study consolidates the role of HHSA in identification of EEG features in patients with PD, there are some limitations. The numbers of LPD and PDD patients are relatively small.  ... 
doi:10.3389/fnagi.2022.832637 fatcat:4ufnw5v4kjhnnj5zbhuguovdcm

Consensus Paper: Towards a Systems-Level View of Cerebellar Function: the Interplay Between Cerebellum, Basal Ganglia, and Cortex

Daniele Caligiore, Giovanni Pezzulo, Gianluca Baldassarre, Andreea C. Bostan, Peter L. Strick, Kenji Doya, Rick C. Helmich, Michiel Dirkx, James Houk, Henrik Jörntell, Angel Lago-Rodriguez, Joseph M. Galea (+6 others)
2016 Cerebellum  
This consensus paper gathers diverse recent views on a variety of important roles played by the cerebellum within the cerebello-basal ganglia-thalamocortical system across a range of motor and cognitive  ...  Despite increasing evidence suggesting the cerebellum works in concert with the cortex and basal ganglia, the nature of the reciprocal interactions between these three brain regions remains unclear.  ...  , and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1007/s12311-016-0763-3 pmid:26873754 pmcid:PMC5243918 fatcat:3crvl2fd3fdrlejqg3nrqakq6e

Diagnosis of Parkinson's Disease by Electrophysiological Methods [chapter]

Elena Lukhanina, Irina Karaban, Natalia Berezetskay
2011 Diagnostics and Rehabilitation of Parkinson's Disease  
The study patients, who regularly underwent treatment at the Parkinson's Disease Centre of Institute of Gerontology, gave their written informed consent to participate in this investigation.  ...  The amplified analogue signals were fed to a computer, which digitized them at a sampling rate of 1000 Hz and then stored the data for further measurements. The time of each recording was 10 sec.  ...  Fractal dynamics of EMGs in patients with Parkinson's disease Fractal analysis is a new method for biomedical signal processing.  ... 
doi:10.5772/17761 fatcat:7tccedbu7ncy7nn5lpfbytv4ou

EEG and MEG primers for tracking DBS network effects

Vladimir Litvak, Esther Florin, Gertrúd Tamás, Sergiu Groppa, Muthuraman Muthuraman
2020 NeuroImage  
It involves implantation of stimulating electrodes in a precisely guided fashion into subcortical structures and, at a later stage, chronic stimulation of these structures with an implantable pulse generator  ...  Here, we review both the technical issues associated with EEG/MEG recordings in DBS patients and the experimental findings to date.  ...  This study was supported by a grant from German Research Council (DFG; CRC-TR-128, CRC 1193).  ... 
doi:10.1016/j.neuroimage.2020.117447 pmid:33059051 fatcat:cyvr77m4nbhhjah4svlsbzivwu

Image guidance in deep brain stimulation surgery to treat Parkinson's disease: a review [article]

Yiming Xiao, Jonathan C. Lau, Dimuthu Hemachandra, Greydon Gilmore, Ali R. Khan, Terry M. Peters
2020 arXiv   pre-print
With rapid development in novel imaging techniques, computational methods, and surgical navigation software, as well as growing insights into the disease and mechanism of action of DBS, modern image guidance  ...  Deep brain stimulation (DBS) is an effective therapy as an alternative to pharmaceutical treatments for Parkinson's disease (PD).  ...  CONCLUSION This review provides the state of the art for medical image guidance in targeting, navigation, and monitoring of the DBS procedure to treat Parkinson's disease.  ... 
arXiv:2003.04822v1 fatcat:s7bthf5r55aafk3iplv4xpvtw4

Evolving Applications, Technological Challenges and Future Opportunities in Neuromodulation: Proceedings of the Fifth Annual Deep Brain Stimulation Think Tank

Adolfo Ramirez-Zamora, James J. Giordano, Aysegul Gunduz, Peter Brown, Justin C. Sanchez, Kelly D. Foote, Leonardo Almeida, Philip A. Starr, Helen M. Bronte-Stewart, Wei Hu, Cameron McIntyre, Wayne Goodman (+25 others)
2018 Frontiers in Neuroscience  
The proceedings of the fifth Think Tank summarize progress in neuromodulation neurotechnology and techniques for the treatment of a range of neuropsychiatric conditions including Parkinson's disease, dystonia  ...  The annual Deep Brain Stimulation (DBS) Think Tank provides a focal opportunity for a multidisciplinary ensemble of experts in the field of neuromodulation to discuss advancements and forthcoming opportunities  ...  These results were in contrast to the novel identification of beta-HFO PAC in the GPi of four un-medicated PD patients at rest.  ... 
doi:10.3389/fnins.2017.00734 pmid:29416498 pmcid:PMC5787550 fatcat:24zvpf5ndbcrhhcy7xdrcinaby

Analysis of Oscillatory Neural Activity in Series Network Models of Parkinson's Disease During Deep Brain Stimulation

Clare M. Davidson, Annraoi M. de Paor, Hayriye Cagnan, Madeleine M. Lowery
2016 IEEE Transactions on Biomedical Engineering  
Describing the system behavior with computationally efficient models could aid in the identification of optimal stimulation parameters for patients in a clinical environment.  ...  However, the selection of stimulation parameters is based on qualitative assessment of the patient, which can result in a lengthy tuning period and a suboptimal choice of parameters.  ...  Sample of LFP data recorded via implanted macroelectrodes from the STN of a patient with Parkinson's disease shown before stimulation was applied and during 130-Hz stimulation at 1.5 V with a pulse duration  ... 
doi:10.1109/tbme.2015.2475166 pmid:26340768 fatcat:7y5qxjtdhvft7ergcitaybzlbe

Neural Synchrony in Brain Disorders: Relevance for Cognitive Dysfunctions and Pathophysiology

Peter J. Uhlhaas, Wolf Singer
2006 Neuron  
stimulus selection, routing of signals across distributed cortical networks, sensorymotor integration, working memory, and perceptual awareness.  ...  Following the discovery of context-dependent synchronization of oscillatory neuronal responses in the visual system, novel methods of time series analysis have been developed for the examination of task-and  ...  tools for the assessment of disease progression and efficiency of therapeutic interventions.  ... 
doi:10.1016/j.neuron.2006.09.020 pmid:17015233 fatcat:av72c6ln3fd4pl5ubz6oaiowby

Closed-Loop Brain–Machine–Body Interfaces for Noninvasive Rehabilitation of Movement Disorders

Frédéric D. Broccard, Tim Mullen, Yu Mike Chi, David Peterson, John R. Iversen, Mike Arnold, Kenneth Kreutz-Delgado, Tzyy-Ping Jung, Scott Makeig, Howard Poizner, Terrence Sejnowski, Gert Cauwenberghs
2014 Annals of Biomedical Engineering  
Traditional approaches for neurological rehabilitation of patients affected with movement disorders, such as Parkinson's disease (PD), dystonia, and essential tremor (ET) consist mainly of oral medication  ...  As a result, a more efficient and effective management of PD cardinal symptoms has emerged.  ...  Abstract-Traditional approaches for neurological rehabilitation of patients affected with movement disorders, such as Parkinson's disease (PD), dystonia, and essential tremor (ET) consist mainly of oral  ... 
doi:10.1007/s10439-014-1032-6 pmid:24833254 pmcid:PMC4099421 fatcat:4jbihnphwbelhhamj7a7svrnmm

Brain and Cognitive Reserve: Translation via Network Control Theory [article]

John D. Medaglia, Fabio Pasqualetti, Roy H. Hamilton, Sharon L. Thompson-Schill, Danielle S. Bassett
2017 arXiv   pre-print
However, mechanisms of function and resilience in large-scale brain networks remain poorly understood.  ...  In this perspective, we describe recent theoretical approaches from network control theory as a framework for investigating network level mechanisms underlying cognitive function and the dynamics of neuroplasticity  ...  Hall for her generous contributions to Figure 5 and Figure 6 .  ... 
arXiv:1604.04683v2 fatcat:toaleizwfra47be3tay4dro3ve

Brain and cognitive reserve: Translation via network control theory

John Dominic Medaglia, Fabio Pasqualetti, Roy H. Hamilton, Sharon L. Thompson-Schill, Danielle S. Bassett
2017 Neuroscience and Biobehavioral Reviews  
However, mechanisms of function and resilience in large-scale brain networks remain poorly understood.  ...  In this perspective, we describe recent theoretical approaches from network control theory as a framework for investigating network level mechanisms underlying cognitive function and the dynamics of neuroplasticity  ...  We consider the potential for dynamic network approaches to introduce a conceptual framework for understanding variance in clinical trajectories and to delineate novel features of disease syndromes and  ... 
doi:10.1016/j.neubiorev.2017.01.016 pmid:28104411 pmcid:PMC5359115 fatcat:tzquifkopbdhnh4ufrm4vknoqm

The ENIGMA Toolbox: Cross-disorder integration and multiscale neural contextualization of multisite neuroimaging datasets [article]

Sara Lariviere, Casey Paquola, Bo-yong Park, Jessica Royer, Yezhou Wang, Oualid Benkarim, Reinder Vos de Wael, Sofie Louise Valk, Sophia I Thomopoulos, Matthias Kirschner, Sanjay Sisodiya, Carrie McDonald (+3 others)
2020 bioRxiv   pre-print
yielded some of the largest studies of the healthy and diseased brain.  ...  Among 'big data' initiatives, the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium - a worldwide alliance of over 2,000 scientists diversified into over 50 Working Groups - has  ...  P.M.T. received partial grant support from Biogen, Inc., and consulting payments from Kairos Venture Capital, Inc., for work unrelated to ENIGMA and this manuscript.  ... 
doi:10.1101/2020.12.21.423838 fatcat:attlmrhftzhtbp4csnq4pthgni

Machine Learning and Deep Learning Approaches for Brain Disease Diagnosis: Principles and Recent Advances

Protima Khan, Md. Fazlul Kader, S. M. Riazul Islam, Aisha B. Rahman, Md. Shahriar Kamal, Masbah Uddin Toha, Kyung-Sup Kwak
2021 IEEE Access  
In this study, we present a review on recent machine learning and deep learning approaches in detecting four brain diseases such as Alzheimer's disease (AD), brain tumor, epilepsy, and Parkinson's disease  ...  Moreover, a brief overview of different feature extraction techniques that are used in diagnosing brain diseases is provided.  ...  The formula of sensitivity implied that it is a measure of the successful diagnosis of diseased patients.  ... 
doi:10.1109/access.2021.3062484 fatcat:lmhp34ad3zdexb5y4bt5ksntia
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