| week/date | theme | topic | remarks/extras |
|---|
week 1:
1/22
|
Theme I:
feedforward computation |
Introduction and overview. The role of computation in cognition. Statistical
inference. The Bayesian framework.
|
Click on the icon on the left to see the class notes for
this week.
|
week 2:
1/29
|
Theme I:
feedforward computation |
Bayesian neural coding. Multisensory integration.
|
Click on the icon on the left to see the class notes for
this week. Shimon will discuss the papers by Deneve (2007) and by Knill &
Pouget (2004). As always, the papers themselves are under readings.
|
week 3:
2/5
|
Theme I:
feedforward computation |
Bayesian decision-making and motor control.
|
There is an extra reading (optional) for next Tuesday: *Using Bayes' Rule to Model
Multisensory Enhancement in the Superior Colliculus,
T. J. Anastasio, P. E. Patton, and K. Belkacem-Boussaid, Neural Computation
12:1165-1187 (2000).
|
week 4:
2/12
|
Theme II:
sequences |
Neural synchrony, or not
|
Singer; Shadlen
|
week 5:
2/19
|
Theme II:
sequences |
Synfire; polychronization; spike-timing dependent plasticity (STDP)
|
Ikegaya; Izhikevich; Jun and Jin
|
week 6:
2/26
|
Theme II:
sequences |
Birdsong
Language
|
Farries & Perkel; Yu & Margoliash; Drew & Abbott;
Dominey
Optional extra: *What songbirds teach us about
learning, M. S. Brainard and A. J. Doupe, Nature 417:351-358 (2002).
|
week 7:
3/4
|
Theme III:
information integration |
Roles of hippocampus, cortex, basal ganglia, cerebellum
|
Atallah et al.; Doya
[Remember the take-home question: use the O'Reilly/ Doya basal ganglia
model to produce some serially ordered behavior, one of your favorite
serially ordered behaviors.]
|
week 8:
3/11
|
Theme III:
information integration |
Inverse models; models of high-level cognition
|
An extra paper, Internal models for motor control and trajectory
planning, M. Kawato, Current Opinion in Neurobiology 9:718-727
(1999); also O'Reilly, and the extra extra papers listed on the notes page for this week.
|
| Spring Break |
week 9:
3/25
|
Theme III:
information integration |
Lifetime memory integration
|
Merker
|
week 10:
4/1
|
Theme IV:
highly distributed computation |
The amygdala
|
Martinez-Garcia et al.; A. Pitkanen; also an extra: *Emotion Circuits in
the Brain, J. E. LeDoux, Annual Review of Neuroscience, 23:155-184
(2000).
|
week 11:
4/8
|
Theme IV:
highly distributed computation |
The amygdala (cont.)
|
Young, Goodson, and Zald.
|
week 12:
4/15
|
Theme IV:
highly distributed computation |
Understanding Trying to understand the
wheels-within-wheels loops-within-loops
and other quirks of the brain architecture
|
-
subsumption architecture (read Intelligence without representation, Brooks, R. A.,
Artificial Intelligence 47:139-159, 1991)
-
the CogAff / CoSy architecture:
- read
Sloman & Chrisley from the reading
list, under Theme V
-
read More
things than are dreamt of in your biology:
Information-processing in biologically inspired robots, Aaron
Sloman and Ron Chrisley
-
read Natural and artificial
meta-configured altricial information-processing systems,
Jackie Chappell, Aaron Sloman
|
week 13:
4/22
|
Theme V:
open-ended computation |
novel models of computation
|
Maass [maybe also Fernando, C. and Sojakka, S. (2003). Pattern recognition
in a bucket. In Banzhaf, W., Christaller, T., Dittrich, P., Kim, J.T. and
Ziegler, J., editors, Advances in Artificial Life, Proceedings of the 7th
European Conference on Artificial Life (ECAL 2003), pages
588-597. Springer. See Fernando's publication page]
Barrett
|
week 14:
4/29
|
Theme V:
open-ended computation
|
evolution and emergence
|
Gould, S. J. (1986), Evolution and the Triumph of
Homology, or Why History Matters, American Scientist 74:60-69.
Finlay, B. L. (2007) Endless minds most beautiful, Developmental
Science 10:30-34.
Szathmary & Maynard Smith
Clayton & Kauffman
|