Lecture slides are posted here as the course progresses, along with notes on each lecture. For topics for which the links don't yet work, you can get a copy of last year's notes at the 2008-2009 site. Anything posted about a lecture that has not yet happened is (of course) a projection that may not turn out to be accurate.
Note that some slides are password protected because they contain copyrighted figures. These should be readable from any University of Edinburgh machine. To read them from an external machine such as a home system, the username and password can be found in /group/teaching/cnv/README on a UE Informatics DICE machine.
Handing out introductory slides and giving overview of course, focusing on why vision is an important topic, why computational modeling can be useful, and what makes a particular type of computational model appropriate for a given use.
Note that this class differs from NIP (Neural Information Processing) in being much more qualitative, with very little mathematical work required, and by providing extensive background material on vision. It differs from NC by focusing on large numbers of units organized into topographic maps, rather than on more detailed study of individual neurons or small populations. It differs from CCN by being focused only on results from the neuroscience of vision and on models grounded on specific visual areas and circuits within them.
Required reading for next class:
Chapter 1 of the CMVC textbook, plus sections 2-4 of Report
of the 1st INCF Workshop on Large-scale Modeling of the Nervous
System. Read the
/group/teaching/cnv/README
file mentioned above for information about obtaining the CMVC book.
Completing course overview, focusing on "ideal" models.
Beginning review of biological data about the visual system. Covering image formation and the gross anatomy of the visual system.
Chapter 2 of the textbook is assigned as background reading.
As we work through this background material, you may find that this article is helpful for explaining any topic that I cover too quickly or that you want to follow up on:
Crick, F. and Asanuma, C. (1986) Certain aspects of the anatomy and physiology of the cerebral cortex. In J. L. McClelland and D. E. Rumelhart (eds.), Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. II, chapter 20, pp. 333-371. MIT Press.
The Crick article is a bit old, but it is useful because it
covers most of the basic concepts in neuroscience from a
modelling perspective, and goes into a lot more detail about
molecular, cellular, and anatomical concepts than we will discuss
in this course. The material in this article is not
examinable, but may be helpful for anyone who does not have a
prior background in this area. There are also a lot of other
basic introductions to neuroscience available; I mention this one
only because it is explicitly written from a modelling
perspective.
Continuing review of the visual system, focusing on the structure and function of the retina.
Suggested background reading: the vision chapter(s) of any
neuroscience textbook, e.g. Bear, Connors, and Paradiso, Neuroscience:
Exploring the Brain, or Kandel, Schwartz, and Jessell,
Principles of Neural Science. But this is just for
background and more information; as with the basic neuroanatomy
reading above, none of it is required or examinable.
Continuing review of the visual system, focusing on cell response types in the retina, LGN, and V1.
Required reading:
Hubel, D. H. and Wiesel, T. (1962). Receptive fields, binocular interaction, and functional architecture in the cat's visual cortex, J. Physiol. 160: 106-154.
Note that this is a long article, and you will not be examined
on any of the details of its contents. So feel free to skim it
at whatever level you prefer. Even so, this is the first
important study of the electrophysiological properties of V1
neurons, and it is well worth reading. Other related
papers on monkey cortex from the same authors can be found on the
Background readings page, if you
are interested.
Continuing review of the visual system, focusing on feature maps in V1.
Required reading:
Blasdel, Gary G. (1992). Orientation selectivity, preference, and continuity in monkey striate cortex, J. Neuroscience 12: 3139--3161.
Again, this is a long and very detailed article, and so feel
free to skim it looking for the high points. Even so, it is
an excellent way to understand how optical imaging experiments
are done, the types of analyses that can be done on cortical
maps, etc.
Continuing review of the visual system, focusing on lateral interactions and feedback.
Completing review of the visual system, focusing on development and spontaneous activity. Briefly introducing the Topographica simulator GUI.
Highly suggested reading:
von Melchner, L., Pallas, S.L., and Sur, M. (2000). Visual behaviour mediated by retinal projections directed to the auditory pathway. Nature 404: 871--876.
An earlier review paper might also be good for background:
Sur, M., Pallas, S.L., and Roe, A.W. (1990).
Cross-modal plasticity in cortical development: Differentiation and specification of sensory neocortex.
Trends in Neurosciences 13: 227--233.
Suggested skimming (or reading if interested):
Huberman, A.D., Feller, M.B., and Chapman, B. (2008) Mechanisms Underlying Development of Visual Maps and Receptive Fields. Annual Review of Neuroscience 31:479--509.
Beginning review of modeling approaches for computational
neuroscience of vision, focusing on non-developmental models for
early visual areas.
Choosing pairs for Assignment 1, helping
everyone find a partner.
Watching movies of visual neurophysiology (Hubel and Wiesel), neural growth cones and axon pathfinding, CNS development, and LGN activity decoding.
Chapter 3 of the text is assigned as required background reading.
Continuing review of modeling approaches, focusing on
SOM-based model of learning retinotopy.
Chapter 4 and section 5.3 of the text is assigned as
background reading.
Completing review of modeling approaches, focusing on the SOM-based model of retinotopy.
Introducing the LISSOM model as a more biologically realistic but closely related way to develop maps, first focusing on a simple retinotopy model and then discussing the LISSOM model of orientation maps. Discussing additional types of analyses, plus starting with mechanisms for working with large-scale images: scaling models to larger areas and densities.
Background reading: Chapter 8 starting with
section 8.2.3, and chapter 15 through 15.2.3 (only skimming
necessary).
Discussing project option for the second assignment briefly.
Continuing discussion of LISSOM model of orientation maps, focusing on contrast-gain control via afferent normalization, the function and behavior of the map for real images, results for different training patterns, and pre-natal and post-natal development of orientation maps.
Background reading: chapter 9.
Completed discussion of LISSOM model of orientation maps.
Discussing what visual features would be useful to measure besides orientation, focusing on properties that can be detected reliably through a small circular aperture with a limited resolution. Introducing LISSOM models of ocular dominance and joint models of orientation and ocular dominance.
Background reading: rest of chapter 5.
In this meeting, we'll try to get everyone started on assignment 2, discussing the overall plan, the "favored" LGN feedback option, and how to choose any other topic that you prefer.
Also collecting feedback on the course so far; if you miss today's lecture, then please fill out an online ITO form.
Discussing LISSOM models of joint ocular dominance, orientation, and motion direction, and individual and joint models for all visual features.
Discussing models of adult visual function, focusing on surround modulation and aftereffects.
Background reading: Chapter 7 and Schwabe et al. (2006), The Journal of Neuroscience, 26:9117--9129.
Models of areas beyond V1, and higher-level visual capabilities.
Background reading: Chapters 16, 17, 18.
Continuing higher-level models.
Finishing higher-level models.
Last updated: 2012/09/11 15:49:09
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