A user operating the
brain–computer interface stroke rehabilitation system.
By
monitoring brain connections in their resting state, researchers show that rehabilitation
based on brain–computer interfaces could be superior to robot-assisted programs
Changes in the pattern of connections in the resting
brain predict the extent to which stroke patients will recover following
rehabilitation, according to new research led by Cuntai Guan of the A*STAR
Institute for Infocomm Research, Singapore and Karen Chua of the Tan Tock Sen
Hospital, Singapore, in collaboration with Bálint Várkuti of the University of
Tübingen, Germany1.
Strokes are caused by blockage of, or damage to, blood
vessels in the brain. They are a leading cause of death, often result in speech
deficits and paralysis on one side of the body, and frequently cause brain
damage and disability. Rehabilitation, however, can help to partially restore
the motor deficits.
Guan and his co-workers studied nine individuals who
had recently suffered their first stroke. The team trained the participants for
one month using either a robot-assisted rehabilitation program or a brain–machine
interface (BCI). Via scalp electrodes, the BCI reads brain waves associated
with movement planning, and then translates them into commands that move a
robotic arm (see image).
The researchers used functional magnetic resonance
imaging to examine connections in the participants’ brains. They also used a
standardized clinical scale to assess their upper-limb movements, both before
and after rehabilitation. Specifically, they examined long-range connections
within the so-called default mode network, a set of brain regions that become
active when external stimuli are ignored and the mind is allowed to wander
instead.
Guan and co-workers found that patients rehabilitated
with the BCI recovered better than those who received robot-assisted rehabilitation.
This was associated with increased connectivity between certain components of
the default mode network — especially the anterior cingulate cortex, the
inferior parietal lobule, and the supplementary motor cortex. Furthermore,
these connectivity changes accurately predicted the extent to which the stroke
patients would recover.
A stroke often disrupts long-range connections within
the brain, but neuroscientists now widely believe that the brain can build or
strengthen alternative pathways to compensate for the damage, leading to some
functional recovery. The enhanced connectivity in the brain’s resting state
observed by the team could therefore be an after-effect of these processes, and
may reflect increased cooperation between the regions involved, which
compensates for the damage caused by the stroke.
“Stroke rehab is a complex and effortful process,”
says Guan, “and in terms of saving therapists' time, there is currently a lack
of efficient and productive approaches.” The team’s BCI stroke rehabilitation
system can supplement other approaches. ”We are now working with industry to
further develop [the system] and make it accessible to patients in hospitals,
rehab centers, and eventually the home.”
The A*STAR-affiliated researchers contributing to this
research are from the Institute
for Infocomm Research
References
- Várkuti, B., Guan, C., Pan, Y., Phua, K. S., Ang, K. K. et al.
Resting state changes in functional connectivity
correlate with movement recovery for BCI and robot-assisted
upper-extremity training after stroke.Neurorehabilitation and Neural
Repair 27, 53–62 (2013). | article
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