I’m currently (as of 2005) a graduate student in the computational neurobiology program at UCSD, in Charles Stevens's lab. In general, I’m interested in models of neural coding, computation, and learning in systems with of about 3-30,00 neurons.
Most of these questions are so big that I don’t expect them to be answered in my lifetime.
how qualitative mental states can be encoded in quantitative data parameters
fundamental computational elements of local microcircuits, network motifs
the neural coding of semantic knowledge / semantic memory
exploring the differerent classes of neural network models and other models of computation that have been imagined
interoperability in the brain; how is data shared between different "thought modules"? how is data routed through the neural network?
Thalamus, basal ganglia, and neocortex. I’m interested in understanding the "basic plan" of these structures, at the microstructure/local circuit level, across placental mammals; I’m also interested in theoretical models of their operation and function.
Neuronal cell culture as an experimental preparation for studying network activity and local circuit computation. Yes it’s unnatural, but it’s the only prep we’ve got where we have a shadow of a chance of simultaineously monitoring the activity of ALL of the cells involved in a particular computation (at least for the next couple of years). I’m also interested in the experimental techniques necessary for doing these sorts of experiments (for example, all-optical electrophysiology, multi-electrode arrays).
Central pattern generators. Particularly small ones in invertebrates. These serve as a tractable system for cataloging part of the fundamental reportoire of neural computational architectures.
Song memory in the Zebra Finch: In this system, we have a real chance to discover exactly how the song is encoded in memory. And, we can do this by going backwards from the motor outputs, without having to worry about other parts of the system (for instance, audition) (if we were trying to figure out how the song is learned, we’d have to care about this other stuff; but determining the format of the storage of the memory should be easier).
Multi-electrode arrays: seem to be the best way right now to simultaineously record or stimulate a number of neurons
All-optical electrophysiology techniques: over the course of decades, I agree with Eric that optical methods will displace MEAs. </ul>
What is the function of the reciprocal signal from cerebral cortex to thalamus? — an underappreciated open question in the systems neuroscience of the cerebral cortex
short list of ideas for a programming language that works like the brain
Introduction to Reverse Engineering the Brain — (incomplete) list of the subset of topics of systems neuroscience that are most relevant to the topic "What is the algorithm of thought?" (e.g. so that you can focus/prioritize your study of neuroscience if this question is your goal)
/notes-science-neuro (beware: these notes were written for personal use; they are not necessarily readable)