Biomedical Engineering Reference
In-Depth Information
•
What is the most efficient decoding strategy (i.e., the one that has the minimum decoding
error)?
What are the relationships between resolution and synchronization in the neural represen-
tation? We have shown a variety of techniques that can alter the interpretation of the neural
representation and depend upon time resolution incorporated in the neural recordings and
the synchronization techniques with behavioral or neural events.
What is the biological plausibility of the encoding or decoding strategy that is assumed?
The constraints used in biological systems are very different than those used in computa-
tional environments. One must identify and discuss these limitations within the constructs
of the BMI computational goals.
•
•
In this chapter, we have observed that the neuronal and ensemble responses are highly non-
stationary (i.e., local correlations over time) and sparse (spike trains). Moreover, firing rate analysis
and its correlation with behavior highly depend on the appropriate choice of the rate window. The
important message of this analysis is that standard optimal signal processing techniques (linear filters,
neural networks, etc.) were not designed for data that is nonstationary and discrete valued. Ideally,
we would like our optimal signal processing techniques to capture the changes observed in Figure
2.13
. However, the reader should be aware that in the environment of BMI datasets, applying any of
the “out-of-the-box” signal processing techniques means that the neural to motor mapping may not
be optimal. More importantly, any performance evaluations and model interpretations drawn by the
experimenter can be directly linked and biased by the mismatch between data and model type.
REFERENCES
Crammond, D.J.,
Motor imagery: never in your wildest dream.
Trends in Neurosciences, 1997.
20
(2): pp. 54-57.
doi:10.1016/S0166-2236(96)30019-2
Kupfermann,
Localization of Higher Cognitive and Affective Functions: The Association Cortices
, in
Principles of Neural Science, E.R. Kandel, J.H. Schwartz, and T.M. Jessel, eds. 1991, Norwalk,
CT: Appleton & Lange. pp. 823-838.
Andersen, R.A., et al.,
Multimodal representation of space in the posterior parietal cortex and its use
in planning movements.
Annual Review of Neurosciences 1997.
20
: pp. 303-330.
doi:10.1146/
Chen, R., L.G. Cohen, and M. Hallett,
Role of the ipsilateral motor cortex in voluntary movement.
Can. J. Neurol. Sci., 1997.
24
: pp. 284-291.
Cisek, P., D.J. Crammond, and J.F. Kalaska,
Neural activity in primary motor and dorsal premotor
cortex In reaching tasks with the contralateral versus ipsilateral arm.
Journal of Neurophysiology,
2003.
9
(2): pp. 922-942.
doi:10.1152/jn.00607.2002
1.
2.
3.
4.
5.
