Oscillating central motor networks in pathological tremors and voluntary movements. What makes the difference?

Muthuraman, M.; Heute, Ulrich; Arning, Kathrin; Anwar, Abdul Rauf; Elble, Rodger J.; Deuschl, Günther; Raethjen, Jan

doi:10.1016/j.neuroimage.2012.01.088

Cited by 117 publications

(118 citation statements)

References 51 publications

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“…Local field potential (LFP) recordings of thalamic ventralis intermedius (Vim) nucleus show strong linear correlation with the contralateral EMG during tremor (Marsden et al, 2000). Besides this, there is evidence suggesting the sensorimotor cortex is part of this central tremor related oscillatory network with significant coupling in some cases between the primary motor cortex (M1) and the contralateral tremorogenic EMG (Hellwig et al, 2000, Hellwig et al, 2001, Hellwig et al, 2003, Govindan et al, 2006, Schnitzler et al, 2009, Muthuraman et al, 2012. However, this was not a universal finding and negative results were also reported (Halliday et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

Nonlinear interactions in the thalamocortical loop in essential tremor: A model-based frequency domain analysis

Sarrigiannis

Billings

et al. 2016

Neuroscience

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This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. AbstractThere is increasing evidence to suggest that essential tremor has a central origin. Different structures appear to be part of the central tremorogenic network, including the motor cortex, the thalamus and the cerebellum. Some studies using EEG and MEG show linear association in the tremor frequency between the motor cortex and the contralateral tremor EMG.Additionally, high thalamomuscular coherence is found with the use of thalamic local field potential (LFP) recordings and tremulous EMG in patients undergoing surgery for deep brain stimulation (DBS). Despite a well-established reciprocal anatomical connection between thalamus and cortex, the functional association between the two structures during "tremor- Highlights• We use a nonlinear autoregressive exogenous model to de-codify corticothalamic communication• We reveal nonlinear interactions between motor cortex and thalamus in essential tremor• We define corticothalamic interactions during tremor active and rest states• There are state specific frequencies and time lags in corticothalamic interrelationships

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Section: Introductionmentioning

confidence: 99%

Nonlinear interactions in the thalamocortical loop in essential tremor: A model-based frequency domain analysis

Sarrigiannis

Billings

et al. 2016

Neuroscience

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“…Different computer-aided methods for tremor diagnosis have already been proposed [13][14][15][16][17][18]. Among them, the difference in the energy of the higher tremor harmonics in movement recordings, typically performed with inertial sensors, best discriminates ET and PD patients [17,18].…”

Section: Complexitymentioning

confidence: 99%

“…Among them, the difference in the energy of the higher tremor harmonics in movement recordings, typically performed with inertial sensors, best discriminates ET and PD patients [17,18]. These harmonics are usually computed after using relatively simple frequency filtering techniques which separate the higher tremor frequencies from the relatively low frequencies of voluntary movement [14,15,17,19].…”

Section: Complexitymentioning

confidence: 99%

“…Subcutaneous tissue progressively filters electrical potentials with increasing distance from the muscle fibers, inducing spatial variability of MUAPs across the skin surface [28]. In pathological tremor, the neural drive to muscle has classically been estimated from bipolar surface EMG recordings [14,15,17]. In this procedure, the EMG signals are first rectified and their power spectrum is calculated to estimate the power at the main tremor frequency and its higher harmonics.…”

Section: Neural Drive To Skeletal Muscles and Tremor Demonstration Inmentioning

confidence: 99%

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New Perspectives for Computer-Aided Discrimination of Parkinson’s Disease and Essential Tremor

et al. 2017

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Pathological tremor is a common but highly complex movement disorder, affecting ∼5% of population older than 65 years. Different methodologies have been proposed for its quantification. Nevertheless, the discrimination between Parkinson's disease tremor and essential tremor remains a daunting clinical challenge, greatly impacting patient treatment and basic research. Here, we propose and compare several movement-based and electromyography-based tremor quantification metrics. For the latter, we identified individual motor unit discharge patterns from high-density surface electromyograms and characterized the neural drive to a single muscle and how it relates to other affected muscles in 27 Parkinson's disease and 27 essential tremor patients. We also computed several metrics from the literature. The most discriminative metrics were the symmetry of the neural drive to muscles, motor unit synchronization, and the mean log power of the tremor harmonics in movement recordings. Noteworthily, the first two most discriminative metrics were proposed in this study. We then used decision tree modelling to find the most discriminative combinations of individual metrics, which increased the accuracy of tremor type discrimination to 94%. In summary, the proposed neural drive-based metrics were the most accurate at discriminating and characterizing the two most common pathological tremor types.

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“…91 Source analysis of electroencephalography-electromyography coherence has supported a similar circuit. 143 …”

Section: Mechanistic Understandingmentioning

confidence: 99%

Deep brain stimulation: a mechanistic and clinical update

Karas

Mikell

Christian

et al. 2013

FOC

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Deep brain stimulation (DBS), the practice of placing electrodes deep into the brain to stimulate subcortical structures with electrical current, has been increasing as a neurosurgical procedure over the past 15 years. Originally a treatment for essential tremor, DBS is now used and under investigation across a wide spectrum of neurological and psychiatric disorders. In addition to applying electrical stimulation for clinical symptomatic relief, the electrodes implanted can also be used to record local electrical activity in the brain, making DBS a useful research tool. Human single-neuron recordings and local field potentials are now often recorded intraoperatively as electrodes are implanted. Thus, the increasing scope of DBS clinical applications is being matched by an increase in investigational use, leading to a rapidly evolving understanding of cortical and subcortical neurocircuitry. In this review, the authors discuss recent innovations in the clinical use of DBS, both in approved indications as well as in indications under investigation. Deep brain stimulation as an investigational tool is also reviewed, paying special attention to evolving models of basal ganglia and cortical function in health and disease. Finally, the authors look to the future across several indications, highlighting gaps in knowledge and possible future directions of DBS treatment.

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Oscillating central motor networks in pathological tremors and voluntary movements. What makes the difference?

Cited by 117 publications

References 51 publications

Nonlinear interactions in the thalamocortical loop in essential tremor: A model-based frequency domain analysis

Nonlinear interactions in the thalamocortical loop in essential tremor: A model-based frequency domain analysis

New Perspectives for Computer-Aided Discrimination of Parkinson’s Disease and Essential Tremor

Deep brain stimulation: a mechanistic and clinical update

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