Brain–Computer Interfaces - Index of

A Simple, Spectral-Change Based, Electrocorticographic Brain–Computer Interface 253
Interestingly, even with the most robust signal features, once the behavior is
linked to a different task (i.e., the subject is now aiming for a target not just performing
the given movement), the electrocorticographic signal may change. We
have used the concept of “re-screening” (illustrated in Fig. 6) to make use of the
fact that a given signal at a given electrode may be subtly or even dramatically
different when the task condition is changed to include a BCI component.
For applications in patients with certain neurologic impairments that impair
movement, overt motor activity will, of course, not be accessible for a BCI device.
Therefore, attempting to drive BCI with other features is of particular interest. The
methods discussed here employ imagined movement and imagined speech to generate
screening features. The areas of cortex engaged by, for example, imagined hand
movement are remarkably similar to those involved in overt hand movement, though
of much weaker strength (Fig. 7a). Because of the weaker signal, initial control can
be more difficult with an imagined task, however, the presence of cursor feedback
reliably produces an enhancement of the ECoG signal resulting in improved performance.
This remarkable ability to enhance the signal has been reported in different
imagined motor tasks and silent speech [36].
In most circumstances, accuracy increases over time, usually within a few trials
(Fig. 7b,see[8, 10]). BCI2000 allows for a recursive tuning of the weights of a given
feature so that the program learns, based on the signal of correct and incorrect trials,
what the ideal translation between feature and cursor position should be. However,
subjects show a robust learning on their own – the brain is able to learn, as with
any new motor task (riding a bike, etc) to subconsciously modify activity based on
feedback. Taken to an extreme, this concept has allowed BCI to occur even when
the behavior of the cortex underlying the chosen electrode is less well defined [12].
Though originally the cursor control is explicitly linked to the behavior, the subject
is free to explore mental states that achieve better cursor control. Anecdotally,
successful control often is associated with a wide range of experiential strategies.
Some control evolves to being achieved with a throat sensation or, in the most striking
example of behavioral plasticity, the subject simply imagines the cursor to move
in the preferred direction, no longer using the originally prescribed behavior as an
intermediate, as happened with the subject described in the case study at the end of
this chapter.
5Learning
In this particular paradigm, stability of signal is hard to determine given the primary
purpose of the implants is clinical and the implant is removed once the seizure focus
is determined. However, we have had occasion to assess the stability over multiple
days in a 5 day, repeated testing region. Since the recording devices are on the brain,
not fixed to it, one could imagine day-to-day variations in the signal. In fact, the use
of ECoG appears to rely upon a population signal that is not overly sensitive to
daily fluctuations [35] and the same features can be reused with minimal re-training
required to achieve accurate cursor control.