Brain–Computer Interfaces - Index of

Brain Signals for Brain–Computer Interfaces 37
2.2 Brain Signal Features Measured from the Cortical Surface
Short-term studies in hospitalized patients temporarily implanted with electrode
arrays on the cortical surface prior to epilepsy surgery have revealed sharply focused
ECoG activity associated with movement or sensation, or with motor imagery [e.g.,
72]. Compared to scalp-recorded EEG, this ECoG activity has higher amplitude,
greater topographical specificity, wider frequency range, and much less susceptibility
to artifacts such as EMG activity. Thus, ECoG might be able to provide
BCI-based communication and control superior to that practical or perhaps even
possible with EEG.
ECoG features in both the time domain and frequency domain are closely related
to movement type and direction [73–76]. The local motor potential is an ECoG signal
feature identified in the time domain that predicts joystick movement [76, 77]. In
the frequency domain, a particularly promising feature of ECoG activity is gamma
activity, which comprises the 35–200 Hz frequency range. Only low-frequency
gamma is evident in EEG, and only at small amplitudes. Unlike lower-frequency
(mu and beta) SMRs, gamma activity increases in amplitude (i.e., displays eventrelated
synchronization (ERS)) with muscle activity. Lower-frequency gamma
(30–70 Hz) increases throughout muscle contraction while higher-frequency gamma
(>75 Hz) increases with contraction onset and offset only [78]. Gamma activity, particularly
at higher frequencies, is somatotopically organized and is more spatially
focused than mu/beta changes [78–82]. While most studies have related gamma to
actual movement or sensory input, others have shown that gamma is modulated by
attention or motor imagery (including speech imagery) [83, 84].
While a gamma-based BCI system has yet to be implemented as a communication
device, recent experiments suggest that gamma activity will be a useful brain
signal for cursor control and possibly even synthesized speech. High-gamma frequencies
up to 180 Hz held substantial information about movement direction in a
center-out task [Fig. 2c; 85], and these signals were used to decode two-dimensional
joystick kinematics [76] or to control a computer cursor with motor imagery [85].
Subjects learned to control cursor movement more rapidly with ECoG features
than with EEG features [76, 86]. More details about ECoG based BCIs are given
in chapters “BCIs Based on Signals from Between the Brain and Skull” and “A
simple, Spectral-Change Based, Electrocorticographic Brain–Computer Interface”
in this book.
2.3 Brain Signal Features Measured Within the Cortex
Intracortical recording (or recording within other brain structures) with microelectrode
arrays provides the highest resolution signals, both temporally and spatially.
Low-pass filtering (1 kHz) reveals individual action
potentials (i.e., spikes) from nearby individual cortical neurons. Both synaptic