Breaking the silence: brain-computer interfaces (BCI) for communication and motor control.

By Niels Birbaumer. Psychophysiology, 2006

770 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/c07206580500cee1afe6a92b8ccd8319e924be91

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In Cellular and Molecular Neuroscience

In Cognitive Neuroscience

Citations in the corpus

The Science of Neural Interface Systems (2009, positive): “They provide insights into human neural processes not available from surface field potentials, which is the other main control signal source being tested for NISs (Birbaumer 2006).”
Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review (2020, background): “This training by operant conditioning is even longer for SCP than for motor rhythms (Birbaumer, 2006).”
Brain–computer interfaces: communication and restoration of movement in paralysis (2007, methodology): “We termed this process ‘extinction of thought’, and it may reduce synaptic plasticity at the molecular level leading to a generalized deficit in learning (Birbaumer & Schmidt, 2005; Birbaumer, 2006a).”
Brain-Computer Interfaces Based on Visual Evoked Potentials (2008, background): “In Birbaumer’s research, only one of 17 ALS patients agreed to use subdural electrodes, despite the fact that implanted electrodes can significantly improve system performance when compared with scalp electrodes [ 20 ].”
An auditory oddball (P300) spelling system for brain-computer interfaces. (2009, methodology): “To elucidate the learning impediment of BCI control in CLIS patients, a longitudinal study with patients in earlier stages of ALS has been proposed (Birbaumer, 2006a, 2006b).”
Clinical Applications of Brain-Computer Interfaces: Current State and Future Prospects (2009, background): “Despite these achievements, SCPs provide only very slow communication (e.g., one minute per letter [17]).”
Bridging the brain to the world: a perspective on neural interface systems. (2008, neutral): “However, there is concern that indirect signals may fail at end stages of the fully locked-in state ( Birbaumer, 2006 ).”
Real-time fMRI neurofeedback: Progress and challenges (2013, background): “It has been shown that BCIs based onoperant learning of electrical or hemodynamic brain responses can be used by paralyzed people to select letters or words with their EEG recorded brain activity and thus restore communication (Birbaumer, 2006; Birbaumer and Cohen, 2007; Birbaumer et al., 2008; Buch”
A review of channel selection algorithms for EEG signal processing (2015, background): “Although invasive technologies have recently shown some promises in different applications for their large accuracy and low noise [2], noninvasive technologies are still used extensively for safety purposes with some additional signal processing tasks to compensate for the noise and resolution limit”
A Brain–Computer Interface Controlled Auditory Event‐Related Potential (P300) Spelling System for Locked‐In Patients (2009, background): “3 , 14 Recently, efforts have been undertaken to use nonvisual stimulation for BCI control.”