Predictors of successful self control during brain-computer communication

Abstract

Objectives: Direct brain-computer communication uses self regulation of brain potentials to select letters, words, or symbols from a computer menu to re-establish communication in severely paralysed patients. However, not all healthy subjects, or all paralysed patients acquire the skill to self regulate their brain potentials, and predictors of successful learning have not been found yet. Predictors are particularly important, because only successful self regulation will in the end lead to efficient brain-computer communication. This study investigates the question whether initial performance in the self regulation of slow cortical potentials of the brain (SCPs) may be positively correlated to later performance and could thus be used as a predictor.

Methods: Five severely paralysed patients diagnosed with amyotrophic lateral sclerosis were trained to produce SCP amplitudes of negative and positive polarity by means of visual feedback and operant conditioning strategies. Performance was measured as percentage of correct SCP amplitude shifts. To determine the relation between initial and later performance in SCP self regulation, Spearman's rank correlations were calculated between maximum and mean performance at the beginning of training (runs 1-30) and mean performance at two later time points (runs 64-93 and 162-191).

Results: Spearman's rank correlations revealed a significant relation between maximum and mean performance in runs 1-30 and mean performance in runs 64-93 (r= 0.9 and 1.0) and maximum and mean performance in runs 1-30 and mean performance in runs 162-191 (r=1.0 and 1.0).

Conclusions: Initial performance in the self regulation of SCP is positively correlated with later performance in severely paralysed patients, and thus represents a useful predictor for efficient brain-computer communication.