Patient disability following a stroke may depend on the severity, type, or location of the bleed or clot that caused it. But to date, it has been difficult to predict how well any individual might recover from a stroke.
This is especially true for anticipating how well a patient may regain common motor functions, like walking or using a spoon.
New research shows brain wave patterns may be a biomarker for motor skill recovery potential in stroke patients. That’s according to a study published in October 2020 in the Oxford Academic journal Brain Communications.
“While cortical oscillations may be only one of several factors important for motor learning, they may have value as markers of cortical function and plasticity after stroke,” according to the study.
Beta oscillations “may offer novel targets for therapeutic interventions aimed at modifying plasticity, such as pharmacological and non-invasive brain stimulation approaches,” the study suggests.
Previous studies have shown correlations between brain wave properties and impaired movement after strokes. This, however, is the first study to examine whether beta oscillation patterns can predict motor learning capacity after a stroke.
Scientists from the UK, Canada, and the Netherlands used electroencephalography (EEG) to track sensorimotor cortex brain activity of study participants as they learned how to perform a new skill with their wrist.
In this case, patients were taught to flex and extend their wrist to follow a target. Motor skill improvements were measured in 18 well-recovered stroke patients and 20 age-matched controls.
Surprisingly, researchers found no significant difference in brain wave activity between groups at baseline before training started. Previous studies, the authors noted, have suggested there should be a difference between stroke survivors and adults who have not had a stroke.
Once training began, however, researchers did find differences in brain wave patterns as well as the study participant’s ability to learn the movement.
Researchers observed motor learning improvements in both groups, but overall performance was better in the control group. A distinct pattern of beta wave change also occurred in the control group. This did not occur in the stroke survivors.
This pattern comes from the post-movement beta rebound (PMBR) effect, or an increase in power within the beta (15–30 Hz) frequency band that typically follows movement.
“Patients who exhibited lower PMBR after training performed better on the repeated sequence 24 hours after training,” the authors write. “We might speculate that this physiological response is necessary for practice-dependent plasticity processes to occur, and if absent or reduced as observed in the stroke patients, corresponds to reduced motor learning ability.”
In other words, even patients who have fully recovered from a stroke have a lowered ability to learn motor skills. This is associated with brain activity that supports this kind of learning. This study shows well-recovered stroke survivors may be able to regain previous motor function. How well they can could depend on biomarkers like beta wave patterns.
The authors acknowledge the small sample size of their study. Future studies need to include acute stroke patients for a more complete assessment of the findings.