Oscillatory predictors of training-induced gains after stroke

• Research type

  Research Study

• Full title

  Oscillatory predictors of training-induced gains after stroke

• IRAS ID

  168043

• Contact name

  Nick Ward

• Sponsor organisation

  University College London

• Clinicaltrials.gov Identifier

  Z6364106/2014/11/24, Data Protection

• Duration of Study in the UK

  2 years, 8 months, 30 days

• Research summary

  Stroke is the leading cause of long-term physical disability in the world today. Recovery of skilled movement after stroke is reliant on physical training to engage processes underlying experience dependent neuroplasticity. The balance between cortical inhibition and excitation is a key determinant of the potential for experience dependent plasticity in adults and consequently, an exciting therapeutic target in restorative neurology.

  Electroencephalography (EEG) measures the summation of post-synaptic fields created by neuronal firing which occurs at a variety of different frequencies (termed oscillations). EEG provides direct and non-invasive measures of oscillatory neuronal activity in both time and frequency. Different frequency oscillations are related to different tasks and oscillations in the beta band (15-30 Hz) are known to be important in movement. Animal and human studies have shown that beta oscillations can be altered pharmacologically, thereby linking beta oscillations to inhibitory and excitatory processes. Recent work from our group demonstrated alterations in beta oscillations with aging and after stroke.

  We think that the spectral characteristics of beta oscillations may provide the ideal candidate biomarkers of the potential for cortical plasticity. The aim of the project is to reveal appropriate biomarkers of experience dependent plasticity by examining the relationship between these biomarkers and the effects of motor skill training. We hypothesize that higher levels of cortical excitability and/or lower levels of cortical inhibition increase potential for experience dependent plasticity thereby enhancing training effects. We expect that spectral characteristics of beta oscillations will reflect pre-training levels of cortical inhibition and/or excitation and that variations in cortical oscillations will influence the capacity for experience dependent plasticity. Thus, cortical oscillations may predict gains made during training.
  For this purpose, healthy subjects and stroke patients will perform motor control training of the fingers and/or wrist while their oscillatory brain signals are measured using EEG. Clinical and neurophysiological assessment will be conducted.

• REC name

  London - Chelsea Research Ethics Committee

• REC reference

  15/LO/0346

• Date of REC Opinion

  5 Mar 2015

• REC opinion

  Further Information Favourable Opinion