The blog page Hebbian synapses and spike-time dependent plasticity (STDP) has been updated. The main reading is Our main reading is “Hebbian Learning and Plasticity” by Wulfram Gerstner.
As you start thinking about your Final Project, I recommend you take a look at these good examples.
–Greg
The assignment for Thursday, March 20 is posted. See the blog page The Recent Excitement about Neural Networks.
Upload your work to Bb as Assignment #3. Bring a copy to class and be prepared to share your thoughts.
–Greg
I wish you all a good Spring Break.
If you want to learn more about computational neuroscience over break, here are two ideas (entirely optional).
You could read Genealogy of the “Grandmother Cell” — a short history of neuroscience essay (30 min) that considers philosophical aspects of the concept of feature detectors in visual processing.
As a continuation of our discussion of “sparse coding,” you might watch the seminar “From Natural Scene Statistics to Models of Neural Coding & Representation” by Bruno Olshausen (part 1 only, duration 60 min). This talk was part of a summer school on deep learning and feature detection. The target audience is graduate students studying visual neuroscience and/or computer vision.
Be young. Be safe.
–Greg
The reading for class on Thursday is the classic paper “What the frog’s eye tells the frog’s brain” by Lettvin, J. Y., Maturana, H. R., McCulloch, W. S., & Pitts, W. H. (1959). Proceedings of the IRE, 47(11), 1940-1951.
Focus on the Introduction, Methods, the first paragraph of Findings, General Discussion and Conclusion. That is, read the whole paper but de-emphasize the figures and pp.1944-1951.
Come to class ready for discussion!
–Greg
Our paper for Tuesday is Carr, C.E., 1993. Processing of temporal information in the brain. Annual review of neuroscience, 16(1), pp.223-243. This review discusses studies of neural coding of temporal information in the neuroethological context of weakly electric fish, barn owls, and echolocating bats. The circuits considered achieve their function using delay lines and coincidence detectors.
For background read pp. 363-372 of Baer, Connors, and Paradiso (The Auditory and Vestibular Systems). [PDF]
At the beginning of class, there may be a short “accountability” quiz on the main ideas in these readings and/or recently discussed topics. The questions should be straightforward for students who have done the readings and been paying attention during class discussions.
See you Tuesday!
–Greg
The reading for class on Thursday is a recent review by Mikail Khona and Ila R. Fiete on Attractor and integrator networks in the brain. [PDF]
The entire review is quite good. Please read the text through in its entirety (pp. 744-761). Read closely and be prepared to ask questions. Class Thursday will focus on discussion/clarification.
–Greg
Because William & Mary is closed on Thursday for Winter Storm Kingston, the next class will not be until next week: Tuesday, February 25.
The blog page for Tuesday is Line attractor networks (or how the brain keeps the eyes still). Come to class having carefully read the assigned PNAS article.
Enjoy the snow. Be young and be safe. See you Tuesday!
–Greg
Tuesday will be our second day discussing “neural integrators”. The blog page is Neural Integrators (e.g., the vestibulo-ocular reflex and head direction cells).
The assignment before class on Tuesday is the following two readings.
Have a great weekend!
–Greg
The reading for class on Thursday is Goldman, Compte, and Wang (2009). Neural Integrator Models. Focus on pp. 165-172 and Figures 1-5.
This will be the first of two days discussing “neural integrators”. The blog page for the next two classes is Neural Integrators (e.g., the vestibulo-ocular reflex and head direction cells), but the only assignment before class Tuesday is the above-mentioned reading.
–Greg
The video and readings for class on Tuesday are posted on the course blog page Marr’s Three Levels of Inquiry.
The written part is to be turned in at the beginning of class, so it needs to be printed out (but there is no need to upload it to Blackboard).
–Greg
Computational Neuroscience 
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