Analysis of simultaneous MEG and intracranial LFP recordings during Deep Brain Stimulation: a protocol and experimental validation

Oswal, Ashwini; Jha, Ashwani; Neal, Spencer; Reid, Alphonso; Bradbury, David; Aston, Peter; Limousin, Patricia; Foltynie, Tom; Zrinzo, Ludvic; Brown, Peter; Litvak, Vladimir

doi:10.1016/j.jneumeth.2015.11.029

Cited by 54 publications

(66 citation statements)

References 49 publications

(100 reference statements)

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“…Signals were down sampled and large jump artifacts in signal were removed via Z score threshold followed by linear interpolation between gaps. The validity of HPI localization was verified by examining the pairwise distances between the fiducial coils which should remain constant through each trial (Oswal et al, 2015). All the data were found to be valid for this group of subjects.…”

Section: Methodsmentioning

confidence: 99%

The Parkinsonian Subthalamic Network: Measures of Power, Linear, and Non-linear Synchronization and their Relationship to L-DOPA Treatment and OFF State Motor Severity

West

Farmer

Berthouze

et al. 2016

Front. Hum. Neurosci.

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In this paper we investigated the dopaminergic modulation of neuronal interactions occurring in the subthalamic nucleus (STN) during Parkinson's disease (PD). We utilized linear measures of local and long range synchrony such as power and coherence, as well as Detrended Fluctuation Analysis for Phase Synchrony (DFA-PS)- a recently developed non-linear method that computes the extent of long tailed autocorrelations present in the phase interactions between two coupled signals. Through analysis of local field potentials (LFPs) taken from the STN we seek to determine changes in the neurodynamics that may underpin the pathophysiology of PD in a group of 12 patients who had undergone surgery for deep brain stimulation. We demonstrate up modulation of alpha-theta (5–12 Hz) band power in response to L-DOPA treatment, whilst low beta band power (15–20 Hz) band-power is suppressed. We also find evidence for significant local connectivity within the region surrounding STN although there was evidence for its modulation via administration of L-DOPA. Further to this we present evidence for a positive correlation between the phase ordering of bilateral STN interactions and the severity of bradykinetic and rigidity symptoms in PD. Although, the ability of non-linear measures to predict clinical state did not exceed standard measures such as beta power, these measures may help identify the connections which play a role in pathological dynamics.

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Section: Methodsmentioning

confidence: 99%

The Parkinsonian Subthalamic Network: Measures of Power, Linear, and Non-linear Synchronization and their Relationship to L-DOPA Treatment and OFF State Motor Severity

West

Farmer

Berthouze

et al. 2016

Front. Hum. Neurosci.

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“…However, the therapeutic benefit of DBS may depend on modulation of remote brain regions connected to the stimulation site. 2–4 These remote effects of DBS have been measured with both electrophysiology 5,6 and brain imaging. 3,7–10 Furthermore, they can correlate with clinical response.…”

mentioning

confidence: 99%

Connectivity Predicts deep brain stimulation outcome in Parkinson disease

Horn

Reich

Vorwerk

et al. 2017

Annals of Neurology

532

754

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Objective The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remain unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort. Methods A training dataset of 51 PD patients with STN DBS was combined with publicly available human connectome data (diffusion tractography and resting state functional connectivity) to identify connections reliably associated with clinical improvement (motor score of the Unified Parkinson Disease Rating Scale [UPDRS]). This connectivity profile was then used to predict outcome in an independent cohort of 44 patients from a different center. Results In the training dataset, connectivity between the DBS electrode and a distributed network of brain regions correlated with clinical response including structural connectivity to supplementary motor area and functional anticorrelation to primary motor cortex (p<0.001). This same connectivity profile predicted response in an independent patient cohort (p<0.01). Structural and functional connectivity were independent predictors of clinical improvement (p<0.001) and estimated response in individual patients with an average error of 15% UPDRS improvement. Results were similar using connectome data from normal subjects or a connectome age, sex, and disease matched to our DBS patients. Interpretation Effective STN DBS for PD is associated with a specific connectivity profile that can predict clinical outcome across independent cohorts. This prediction does not require specialized imaging in PD patients themselves.

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“…The characteristics of these DBS-related artefacts were already described in detail previously (Litvak et al, 2010;Ramírez et al, 2011;Oswal et al, 2015). Fig.…”

Section: Resultsmentioning

confidence: 98%

“…Other studies removed the DBS artefact successfully by using spatial filters (Mäkelä et al, 2007;Airaksinen et al, 2011Airaksinen et al, , 2012Airaksinen et al, , 2015Ramírez et al, 2011;Oswal et al, 2015). While all these approaches have helped to minimize the effect of the DBS artefact, there is still a demand for an artefact rejection approach which enables retrieving oscillatory activity in different frequency ranges.…”

Section: Introductionmentioning

confidence: 99%

Rejecting deep brain stimulation artefacts from MEG data using ICA and mutual information

Abbasi

Hirschmann

Schmitz

et al. 2016

Journal of Neuroscience Methods

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Analysis of simultaneous MEG and intracranial LFP recordings during Deep Brain Stimulation: a protocol and experimental validation

Cited by 54 publications

References 49 publications

The Parkinsonian Subthalamic Network: Measures of Power, Linear, and Non-linear Synchronization and their Relationship to L-DOPA Treatment and OFF State Motor Severity

The Parkinsonian Subthalamic Network: Measures of Power, Linear, and Non-linear Synchronization and their Relationship to L-DOPA Treatment and OFF State Motor Severity

Connectivity Predicts deep brain stimulation outcome in Parkinson disease

Rejecting deep brain stimulation artefacts from MEG data using ICA and mutual information

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