Cognitive impairment may present an obstacle for patients with amyotrophic lateral sclerosis (ALS) using brain-computer interface devices, according to a study published in the Journal of Neural Engineering. The findings underscore the importance of considering disease heterogeneity when designing these potentially beneficial devices for clinical use.
The study, “Performance predictors of brain–computer interfaces in patients with amyotrophic lateral sclerosis,” was part of a larger survey on the acceptance of brain-computer interface use among ALS patients and their caregivers, and enrolled 25 ALS patients with varying symptoms (excluding those with severe dementia) and 15 controls. Patients were first subjected to a neuropsychological evaluation to assess cognitive and behavioral function. They then completed four one-hour brain-computer interface sessions, spaced over one to two months. Control participants completed only two sessions. Each session was divided into trials using two different brain-interface applications: the P300 spelling system and a motor-imagery task.
P3oo is a kind of brain wave observed by EEG during the process of decision-making. The P300 spelling task consisted of copy spelling a four-letter word by choosing among 32 letters on a checkerboard-type speller. Letters flash in a random order, and when participants spot the correct letter a P300 signal is produced.
In the motor-imagery task, participants were instructed to perform kinesthetic imagery of their left and right hands, meaning that they controlled the movement of a cursor by imaging the grasping of an object with a given hand. They completed 10 right and 10 left trials, as well as 10 no-go trials in which they were instructed to relax.
The study found that presence of cognitive impairment substantially reduced the quality of the control signals needed to use these brain-computer interface applications, impairing performance — regardless of physical symptom progression. Behavioral dysfunction also negatively affected P300 speller performance, and the team found that older individuals performed better on the P300 than the motor-imagery system, possibly indicating an age preference in interface paradigms.
The authors argue that when redesigning brain-computer interface applications, developers need to take specifics about the patient group they are being designed for into account, such as cognitive level and, possibly, age. Different modifications are especially needed for patients with differing degrees of cognitive impairment, they said, suggesting that cognitively compromised patients might benefit most from user interfaces that build on engagement and reward rather than on cognitive load.