a few thoughts about science
aims of theoretical work
Computational neuroscience cannot exist in a bubble. All good theoretical work should make testable predictions (even if they are crazy ones that cannot be realized right away), which should undergo experimental scrutiny. The good theories may be able to stand up to the rigors of real biological phenomena, and theoretical work can provide real insight into the intricacies of the human brain, in addition to guiding experimental investigations. A wonderful article from the NIH and NINDS outlines some issues in computational neuroscience.
subjectivity, unity, intentionality. emergent property?
The holy grail of human neural science is consciousness, I think. It is the ultimate narcissistic goal. Learning and memory are not far behind, but I would argue that considerably more has been done in these two related arenas than in consciousness, a property so elusive that it evades definition. (See Kandel et al 2000 Ch. 20 for an inspiring discussion on this topic. Also see Christof Koch's excellent book Quest for Consciousness.)
nature always leaves secrets to be discovered
However, though we would all like to be part of the solution to such a grand problem in a fit of egoism, Santiago Ramón y Cajal would argue that there is no such thing as a small discovery. I would agree, especially considering my physics-educated tendency to want to simplify things as much as possible. I am interested in basic science and basic properties, and I can only hope that stumbling upon solutions to small, obscure but interesting problems might one day be integrated into something meaningful and give us a complete, Grand Unified Theory of Cognition. Finally, it is a grander desire to wish that our collective, collaborative work will help in the understanding and treatment of neurodegenerative diseases in the human brain.
