Computational Neuroscience in Vision @ CSHL: Day 1

The first day of the course starts off with a solid breakfast.

The course is taking place at the Banbury conference center. The session began with a general introduction of all organizers, TAs, lecturers and students. One striking thing is how many of us work with animal models (like 60%). Off-course from here on the main focus was on Tony Movshon. We started feeling his presence right away. The mood is always maintained light with a few jokes here and there.

Key components of Tony’s talk

Synopsis : He mainly talked about three things. 1.what features a visual image generally comprises of, 2. how they get encoded in the early visual systems and 3. how these encoded signals are later decoded higher up.

1. components of visual image: the plenoptic function (x,y,t, lambda, Vx, Vy Vz) and the elements of early vision (gotta read Adelson and Bergen 1991; it has 1179 citations!).  Rather than the values of each parameter, their derivatives are more informative. A cool thing he said is that you can think of motion as orientation in space (x) and time, and disparity as orientation in space and eye position.

2. visual information encoding: He talked about the functions of retina,followed by an explanation of the spatial contrast sensitivity (another very good paper to be read: Enroth-Cugell and Robson 1966). He also touched on centre surround receptive fields, ON and OFF cells, issues with assuming linearity.

3. decoding visual information: This was my favorite part (filled with choice probability, MT recordings, pooled activity etc).

Quote of the day was: ” The brain works the way it does because it’s made of meat, and meat is not deterministic” ..

Some cool applications of dimensionality reduction was also shown here (Yu et al. 2009).

Lunch followed …



Outside the Banbury Conference Center


Side effects of FIFA 2014

After lunch we had  a couple of more talks. Jonathan went over stimulus encoding, decoding, a probability primer (conditionalization, likelihood functions etc: I will soon add my own self tutoring Matlab implementation of this section here). And EJ went over retina in details ( emphasizing how crucial retinal functions are and how features like adaptation, center surround organization etc start at the level of the photo-receptors). He emphasized on retina being a non linear system as well.

After the talks ended, we had a 3 person/side soccer match (where i scored a goal) including Jonathan Pillow (as we figured out- he’s pretty fit), followed by dinner and MATLAB tutorials.

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