Investigation of brain dynamics in Parkinson's disease by methods derived from nonlinear dynamics.

Investigation of brain dynamics in Parkinson's disease by methods derived from nonlinear dynamics. Research Abstract Details 

Research Abstract Table of Contents

Jump to the:

Investigation of brain dynamics in Parkinson's disease by methods derived from nonlinear dynamics. Abstract Text:

V Müller,W Lutzenberger,F Pulvermüller,B Mohr,N Birbaumer,

EEGs were recorded from patients in early stages of Parkinson's disease (17 patients, 9 females) and healthy controls (12 subjects, 8 females) during rest and during execution/imagining of a complex motor task. The prediction that Parkinson's disease patients compared to controls would show more complex brain dynamics during performance of a complex motor task and imagination of the movements was confirmed by methods derived from nonlinear dynamics. In the resting state, analysis of correlation dimension of EEG time series revealed only slight topographical differences between the groups. During performance of a complex motor task, however, data from Parkinson's disease patients showed higher dimensionality than data from controls, indicating more complex EEG time series. The same difference was found when subjects did not perform any motor movements but imagined the complex movements they had just performed. The data are consistent with the hypothesis that the disturbances in Parkinson's disease result in the recruitment of superfluous cortical networks due to failed inhibition of alternative motor programs in the striatum and thus increase the complexity of cortical representation in motor conditions.

Investigation of brain dynamics in Parkinson's disease by methods derived from nonlinear dynamics. Publishing Authors By Initials

V Müller,W Lutzenberger,F Pulvermüller,B Mohr,N Birbaumer,

For similar psychological phenomena and processes: psychomotor performance research abstracts see: psychological phenomena and processes: psychomotor performance research

PUBMED ID PMID:

MEDLINE DATE:

Investigation of brain dynamics in Parkinson's disease by methods derived from nonlinear dynamics. Journal Published:

PUBLICATION TYPE: Research Support, Non-U.S. Gov

Journal: Experimental brain research. Experimentelle Hirnfo

VOLUME: 137

Page Numbers: 103-10

Journal Abbreviation:

ISSN: 0014-4819

DAY: 15

MONTH: Mar

YEAR: 2001

Investigation of brain dynamics in Parkinson's disease by methods derived from nonlinear dynamics. Information

Number of References:

LANGUAGE: eng

NlmUniqueID: 43312

Investigation of brain dynamics in Parkinson's disease by methods derived from nonlinear dynamics. Keywords Mesh Terms:

KEYWORDS: Psychomotor Performance

MESH TERMS: physiology

Chemical & Substance for Abstract: Investigation of brain dynamics in Parkinson's disease by methods derived from nonlinear dynamics. Information

Substance Name:

Registry Number:

Grant and Affiliation Information for Investigation of brain dynamics in Parkinson's disease by methods derived from nonlinear dynamics.

AFFILIATION: Institute of Medical Psychology and Behavioral Neurobiology, Eberhard-Karls University of Tübingen, Gartenstrasse 29, 72074 Tübingen, Germany. viktor.mueller@uni-tuebingen.de

Country: Germany

AGENCY:

GRANT:

ACRONYM:

MEDLINETA: Exp Brain Res

REFSOURCE:

DATABASENAME:

ACCESSION NUMBER:

Number Hits: 0

Investigation of brain dynamics in Parkinson's disease by methods derived from nonlinear dynamics Related Publications

• A brain-computer interface (BCI) for the locked-in: comparison of different EEG classifications for the thought translation device.
• A multimodal brain-based feedback and communication system.
• Beyond habituation: long-term repetition effects on visual event-related potentials in epileptic patients.
• Biofeedback of slow cortical potentials. I.
• Biofeedback of slow cortical potentials. II. Analysis of single event-related slow potentials by time series analysis.
• Brain areas activated in fMRI during self-regulation of slow cortical potentials (SCPs).
• Category-specific semantic impairment in Alzheimer's disease and temporal lobe dysfunction: a comparative study.
• Cross-frequency phase synchronization: A brain mechanism of memory matching and attention.
• EEG and slow brain potentials during anticipation and control of painful stimulation.
• Electrocortical distinction of vocabulary types.
• FMRI brain-computer interface: a tool for neuroscientific research and treatment.
• High-frequency cortical responses reflect lexical processing: an MEG study.
• Information processing in severe disorders of consciousness: vegetative state and minimally conscious state.
• Investigation of brain dynamics in Parkinson's disease by methods derived from nonlinear dynamics.
• Learning and self-regulation of slow cortical potentials in older adults.
• Mapping P300 waves onto inhibition: Go/No-Go discrimination.
• Motor learning: passing a skill from one hand to the other.
• Negative potential shifts and the prediction of the outcome of neurofeedback therapy in epilepsy.
• Nessi: An EEG-Controlled Web Browser for Severely Paralyzed Patients.
• On "A four-week, task-specific neuroprosthesis program..." Dunning K, et al. Phys Ther. 2008;88:397-405.
• P3 and contingent negative variation in Parkinson's disease.
• Positive shifts of event-related potentials: a state of cortical disfacilitation as reflected by the startle reflex probe.
• Processing of a simple aversive conditioned stimulus in a divided visual field paradigm: an fMRI study.
• Removal of ocular artifacts from the EEG--a biophysical approach to the EOG.
• Self-initiation of EEG-based communication in paralyzed patients.
• The EEG of congenitally blind adults.
• The distribution of mislocalizations across fingers demonstrates training-induced neuroplastic changes in somatosensory cortex.
• The thought translation device: a neurophysiological approach to communication in total motor paralysis.
• Think to Move: a Neuromagnetic Brain-Computer Interface (BCI) System for Chronic Stroke.
• Voluntary brain regulation and communication with electrocorticogram signals.