An auditory brain–computer interface (BCI)

Abstract

Brain-computer interfaces (BCIs) translate brain activity into signals controlling external devices. BCIs based on visual stimuli can maintain communication in severely paralyzed patients, but only if intact vision is available. Debilitating neurological disorders however, may lead to loss of intact vision. The current study explores the feasibility of an auditory BCI. Sixteen healthy volunteers participated in three training sessions consisting of 30 2-3 min runs in which they learned to increase or decrease the amplitude of sensorimotor rhythms (SMR) of the EEG. Half of the participants were presented with visual and half with auditory feedback. Mood and motivation were assessed prior to each session. Although BCI performance in the visual feedback group was superior to the auditory feedback group there was no difference in performance at the end of the third session. Participants in the auditory feedback group learned slower, but four out of eight reached an accuracy of over 70% correct in the last session comparable to the visual feedback group. Decreasing performance of some participants in the visual feedback group is related to mood and motivation. We conclude that with sufficient training time an auditory BCI may be as efficient as a visual BCI. Mood and motivation play a role in learning to use a BCI.

Brain–computer interfacing in disorders of consciousness

“…Nijboer et al [31,32] showed that five out of six patients affected by Motor Neuron Disease or Amyotrophic Lateral Sclerosis (ALS) could use the P3-based BCI for communication after one training session. Thereafter, four of them continued using it for functional communication in a second phase of the study, and all were able to spell messages of considerable length when more features were extracted from the EEG [32].…”

Accessing and Processing MEG Signals in Real-Time: Emerging Applications and Enabling Technologies

“…By providing feedback of cortical activity, neuroplasticity can be induced which could potentially impart therapeutic benefits on sensorimotor function. BMI training paradigms have been used to induce motor-related neuroplasticity by providing direct neural feedback of individual's brain activity (Gage et al 2005;Nijboer et al 2008;Hochberg et al 2006;Helms Tillery et al 2003;Buch et al 2008;Mellinger et al 2007). Some work has been done directly with individuals with paralysis as a proof-of-concept for using MEG as rehabilitation therapy.…”

Reaching and grasping a glass of water by locked-in ALS patients through a BCI-controlled humanoid robot

“…Therefore, the P300 can be used in a BCI that automatically detects which stimuli elicited a P300, and thus which stimuli (such as letters) the user wants to communicate. The P300 was first used in a BCI almost 30 years ago (Farwell and Donchin, 1988), and has been validated in ALS patients (Kübler et al, 2001;Sellers and Donchin, 2006;Nijboer et al, 2008a;Fazel-Rezai et al, 2012;Marchetti and Priftis, 2014). Surveys of ALS patients who used the system, and related work, found that some patients were happy with the functionality provided by the BCI, but many had concerns that included robustness and flexibility (Kathner et al, 2015;Pasqualotto et al, 2015).…”