Brainâ€“Computer Interfaces - Index of

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30 J.R. Wolpaw and C.B. Boulay by brain signals (such as electroencephalographic activity (EEG)), instead of being executed through peripheral nerves and muscles. Furthermore, these brain signals do not depend on neuromuscular activity for their generation. Thus, a true, or “independent,” BCI is a communication and control system that does not rely in any way on muscular control. Like other communication and control systems, a BCI establishes a real-time interaction between the user and the outside world. The user encodes his or her intent in brain signals that the BCI detects, analyzes, and translates into a command to be executed. The result of the BCI’s operation is immediately available to the user, so that it can influence subsequent intent and the brain signals that encode that intent. For example, if a person uses a BCI to control the movements of a robotic arm, the arm’s position after each movement affects the person’s intent for the succeeding movement and the brain signals that convey that intent. BCIs are not “mind-reading” or “wire-tapping” devices that listen in on the brain, detect its intent, and then accomplish that intent directly rather than through neuromuscular channels. This misconception ignores a central feature of the brain’s interactions with the external world: that the skills that accomplish a person’s intent, whether it be to walk in a specific direction, speak specific words, or play a particular piece on the piano, are mastered and maintained by initial and continuing adaptive changes in central nervous system (CNS) function. From early development throughout later life, CNS neurons and synapses change continually to acquire new behaviors and to maintain those already mastered [5, 6]. Such CNS plasticity is responsible for basic skills such as walking and talking, and for more specialized skills such as ballet and piano, and it is continually guided by the results of performance. This dependence on initial and continuing adaptation exists whether the person’s intent is carried out normally, that is, by peripheral nerves and muscles, or through an artificial interface, a BCI, that uses brain signals rather than nerves and muscles. BCI operation is based on the interaction of two adaptive controllers: the user, who must generate brain signals that encode intent; and the BCI system, which must translate these signals into commands that accomplish the user’s intent. Thus, BCI operation is a skill that the user and system acquire and maintain. This dependence on the adaptation of user to system and system to user is a fundamental principle of BCI operation. 1.3 The Origin of Brain Signals Used in BCIs In theory, a BCI might use brain signals recorded by a variety of methodologies. These include: recording of electric or magnetic fields; functional magnetic resonance imaging (fMRI); positron emission tomography (PET); and functional nearinfrared (fNIR) imaging [7]. In reality, however, most of these methods are at present not practical for clinical use due to their intricate technical demands, prohibitive expense, limited real-time capabilities, and/or early stage of development. Only
Brain Signals for Brain–Computer Interfaces 31 electric field recording (and possibly fNIR [8]) is likely to be of significant practical value for clinical applications in the near future. Electric field recordings measure changes in membrane potentials of CNS synapses, neurons, and axons as they receive and transmit information. Neurons receive and integrate synaptic inputs and then transmit the results down their axons in the form of action potentials. Synaptic potentials and action potentials reflect changes in the flow of ions across the neuronal membranes. The electric fields produced by this activity can be recorded as voltage changes on the scalp (EEG), on the cortical surface (electrocorticographic activity (ECoG)), or within the brain (local field potentials (LFPs) or neuronal action potentials (spikes)). These three alternative recording methods are shown in Fig. 1. Any voltage change that can be detected with these recording methods might constitute a brain signal feature useful for a BCI. Intracortical electrodes can detect modulations in the spiking frequencies of single neurons; LFP, ECoG, or EEG recording can detect eventrelated voltage potentials (ERPs) or rhythmic voltage oscillations (such as mu or beta rhythms [9]). ERPs are best observed in the averaged signal time-locked to the evoking event or stimulus, and cortical oscillations are best observed by examining the frequency components of the signal. While the number of brain signal features that might be useful for a BCI is large, only a few have actually been tested for this purpose. Fig. 1 Recording sites for electrophysiological signals used by BCI systems. (a):Electroencephalographic activity (EEG) is recorded by electrodes on the scalp. (b): Electrocorticographic activity (ECoG) is recorded by electrodes on the cortical surface. (c): Neuronal action potentials (spikes) or local field potentials (LFPs) are recorded by electrode arrays inserted into the cortex (modified from Wolpaw and Birbaumer[120])
Page 2 and 3: THE FRONTIERS COLLECTION
Page 4 and 5: Bernhard Graimann · Brendan Alliso
Page 6 and 7: Preface It’s an exciting time to
Page 8 and 9: Contents Brain-Computer Interfaces:
Page 10 and 11: Contributors Brendan Allison Instit
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Page 14 and 15: List of Abbreviations ADHD Attentio
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84 G. Pfurtscheller et al. A B C 1
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98 E.W. Sellers et al. Fig. 1 Three
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Detecting Mental States by Machine
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138 Y. Wang et al. which has been e
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140 Y. Wang et al. After many studi
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142 Y. Wang et al. Left Hand Right
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144 Y. Wang et al. 0-degree 60-degr
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146 Y. Wang et al. 3.1.2 Stimulatio
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150 Y. Wang et al. be summarized as
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152 Y. Wang et al. Fig. 10 A player
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154 Y. Wang et al. 22. Y. Wang, R.
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156 N. Birbaumer and P. Sauseng C A
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Non Invasive BCIs for Neuroprosthes
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BCIs Based on Signals from Between
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Toward Ubiquitous BCIs Brendan Z. A
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Toward Ubiquitous BCIs 359 BCI Chal
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Toward Ubiquitous BCIs 361 communic
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Toward Ubiquitous BCIs 365 The best
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Toward Ubiquitous BCIs 371 controll
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Toward Ubiquitous BCIs 377 Table 1
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Toward Ubiquitous BCIs 385 31. F.H.
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Toward Ubiquitous BCIs 387 67. G. S
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390 Index 65, 157, 163, 217, 221-23
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392 Index 208, 236, 243, 245, 260-2
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