Performance of brain-computer communication in Amyotrophic Lateral Sclerosis

Abstract

Amyotrophic Lateral Sclerosis (ALS) is a devastating condition which leads to the degeneration of motor neurons. It is a progressive disorder characterized by loss of mobility and verbal communication (Chaudhary et al., 2015). In 50% of the patients life expectancy estimates are 3-5 years after first symptoms’ onset (Bensimon et al., 1994). However, if patients opt for artificial respiration and feeding life expectancy can be relatively healthy with optimal care. A percentage around 50% of patients present mild to severe cognitive impairment (Ringholz et al., 2005). Since first attempts in the nineties (Birbaumer et al., 1999) brain-computer interface (BCI) systems have been successfully developed to secure communication with social environment in the late stages of the disease. However, BCI-systems in ALS do not reach 100% correct classification accuracy and in some case results are below chance level (McCane et al., 2014). The latter phenomenon is known as “BCI illiteracy” while the former one is generally ascribed to attentive issues, specific functional impairment, motivational factors and/or artefacts of the neurophysiological signals. Our view relies on a more complex picture where many factors account for sub-optimal results, especially in the completely locked-in state (CLIS) when lack of communication is crucial. We will explore the critical factors determining sub-optimal BCI-performance, namely: (i) alteration of cognitive and/or emotional/behavioural states (Martens et al., 2014) such as vigilance/attention (Mak et al., 2012; De Massari et al., 2013), (ii) mild cognitive impairment (Volpato et al., 2016), (iii) the “extinction-of-goal-directed-thought” hypothesis (Kübler & Birbaumer, 2008), (iv) circadian rhythm and sleep disorders (Soekadar et al., 2013) and (v) visual sensory domain alterations (Murguialday et al., 2011). These complementary factors suggest the integration of theoretical background on learning principles (Skinner, 1953), advanced technology (Gallegos-Ayala et al., 2014), multiple neural signals recording (Chaudhary et al., 2017) and vigilance/attention monitoring (De Massari et al., 2013; Silvoni et al., 2016) to reliably solve the communication problem in advanced ALS stages.