10 research outputs found

    EEG-based biomarkers for optimizing deep brain stimulation contact configuration in Parkinson’s disease

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    ObjectiveSubthalamic deep brain stimulation (STN-DBS) is a neurosurgical therapy to treat Parkinson’s disease (PD). Optimal therapeutic outcomes are not achieved in all patients due to increased DBS technological complexity; programming time constraints; and delayed clinical response of some symptoms. To streamline the programming process, biomarkers could be used to accurately predict the most effective stimulation configuration. Therefore, we investigated if DBS-evoked potentials (EPs) combined with imaging to perform prediction analyses could predict the best contact configuration.MethodsIn 10 patients, EPs were recorded in response to stimulation at 10 Hz for 50 s on each DBS-contact. In two patients, we recorded from both hemispheres, resulting in recordings from a total of 12 hemispheres. A monopolar review was performed by stimulating on each contact and measuring the therapeutic window. CT and MRI data were collected. Prediction models were created to assess how well the EPs and imaging could predict the best contact configuration.ResultsEPs at 3 ms and at 10 ms were recorded. The prediction models showed that EPs can be combined with imaging data to predict the best contact configuration and hence, significantly outperformed random contact selection during a monopolar review.ConclusionEPs can predict the best contact configuration. Ultimately, these prediction tools could be implemented into daily practice to ease the DBS programming of PD patients

    Ageing changes effective connectivity of motor networks during bimanual finger coordination

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    Bimanual finger coordination declines with age. However, relatively little is known about the neurophysiological alterations in the motor-system causing this decline. In the present study, we used 128-channel electroencephalography (EEG) to evaluate causal interactions of cortical, motor-related brain areas. Right-handed young and elderly subjects performed complex temporally and spatially coupled as well as temporally coupled and spatially uncoupled finger tappings. Employing dynamic causal modelling (DCM) for induced responses, we inferred task-induced effective connectivity within a core motor network comprising bilateral primary motor cortex (M1), lateral premotor cortex (lPM), supplementary motor area (SMA), and prefrontal cortex (PFC).Behavioural analysis showed significantly increased error rates and performance times for elderly subjects, confirming that motor functions decrease with ageing. Additionally, DCM analysis revealed that this age-related decline can be associated with specific alterations of interhemispheric and prefrontal to premotor connectivity. Young and elderly subjects exhibited inhibitory left to right M1-M1 coupling during performance of temporally and spatially coupled movements. Effects of ageing on interhemispheric connectivity particularly emerged when movements became spatially uncoupled. Here, elderly participants still expressed inhibitory left to right M1-M1 coupling, whereas no such connection was present in the young. Furthermore, ageing affected prefrontal to premotor connectivity. In all conditions, elderly subjects showed significant couplings from left PFC to left lPM. In contrast, young participants exhibited left PFC to SMA connections.These results demonstrate that (i) in spatially uncoupled movements interhemispheric M1-connectivity increases with age and (ii) support the idea that ageing is associated with enhanced lateral prefrontal to premotor coupling (PFC to lPM) and hypoactivation of a medial pathway (PFC to SMA) within the dominant hemisphere
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