[bioundgrd] Special topics course in Brain and Cognitive Sciences - spring 2014

[Janice Chang]

Begin forwarded message:

From: Susan S Lanza <sdl at mit.edu<mailto:sdl at mit.edu>>
Date: January 15, 2014 3:53:10 PM EST
Subject: special topics course SP 14

Hi Janice,

Could you please send this announcement out to your students, it is a special topics course, 9.S912 that is being offered this SP on Mondays from 1-4 pm in 46-5056

Thanks
S

Title:                           Computation and Visual Attention
Instructor:                  J.K. Tsotsos (
www.cse.yorku.ca/~tsotsos<http://www.cse.yorku.ca/~tsotsos>
)
Term:                          Spring
Years:                         2014 only
Level:                         Graduate
Units:                          3 - 0 - 6
Prerequisites:             at least one introductory course in computer vision,
                                   visual perception, and/or visual neuroscience

Description

Interest in the phenomenon known as attention has a long history, and recently there seems to have been a small explosion of research effort, experimental, theoretical and empirical, whose goal is to develop a deeper and more complete understanding of attention, particularly visual, in humans, non-human primates and machines. The problem with all this work is that it seems to generate more confusion rather than a deeper understanding. This course will explore many of the different approaches and perspectives in the current literature with the intent of developing a 'big picture' view of what this thing called visual attention might entail and how can we best further deepen our understanding.

Each class will have a duration of 3 hours. The opening classes will be lectures by the instructor introducing the topic, providing basic background in the psychology and neurobiology of attention, detailing  the computational foundations for attentive processing, wandering through a brief tour of highlights in attention during the history of Artificial Intelligence, Cognitive Science and Computational Neuroscience, and finally covering one theory, the Selective Tuning theory, in its full detail. Then, the following classes will be a combination of student led themed discussion and guest lecturers. The point of these is to explore different viewpoints and theories, as contrasts to Selective Tuning,  so that the class can develop an appreciation of both strengths and weaknesses not only of the research but also the methodologies. The last class will be led by the instructor but intended to be class discussion and debate on what has been covered with the goal of prescribing a !
pathway fo
r future research on the topic. Depending on interest and progress, this last class could conclude with writing a brief technical report, authored by the whole class, detailing the routes the class feels would be most fruitful.

Recommended Reading:
J.K. Tsotsos, A Computational Perspective on Visual Attention, MIT Press, 2011

http://mitpress.mit.edu/books/computational-perspective-visual-attention


A tentative schedule is:

Week 1: Introduction to attention
Week 2: Computational foundations of visual attention
Week 3: Selective Tuning Part I
Week 4: Selective Tuning Part II
Week 5: The Feature Integration Theory and Guided Search families
Week 6: Neurobiology of Attention
Week 7: Saliency Map Models
Week 8: Biased Competition and its enhancements
Week 9: Dynamical Systems Models
Week 10: The Roles of Gist, Task and Prior Knowledge
Week 11: Bayesian Methods in Attention
Week 12: Final Integrative Discussion

The relative ordering of the class topics for weeks 5 through 11  will depend on the availability and scheduling constraints of invited guest lecturers.

Guest lecturers who will be contacted include:
Week 5: Feature Integration Theory and Guided Search Theory families
           Jeremy Wolfe (Harvard)
Week 6: Neurobiology of Attention
           Robert Desimone (MIT) ; John Maunsell (Harvard)
Week 7: Saliency Map Models
           Neil Bruce (U of Manitoba)
Week 8: Biased Competition and its enhancements
           Robert Desimone (MIT)
Week 9: Dynamical Systems Models and the role of oscillations
           Salva Ardid (York U)
Week 10: The Roles of Gist, Task and Prior Knowledge
           Antonio Torralba (MIT)
Week 11: Bayesian Methods in Attention
           Tomaso Poggio (MIT)

********************************************************
Susan D. Lanza
Undergraduate Administrator
MIT Department of Brain & Cognitive Sciences
46-2005, 77 Massachusetts Avenue
Cambridge, MA  02139
Tel: 617-253-0482
Fax: 617-253-9767

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