Computer Science Colloquia: Sun, Mar 18 at 11:00 - Elad Schneidman
Niv Buchbinder
Dear all,
Next week we are happy to have Elad Schneidman from the Department of Neurobiology, Weizmann Institute of Science (See also enclosed file).
You can view the upcoming talks of the seminar at:
See you,
Niv Buchbinder.
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Computer Science Colloquia - Open University of Israel
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Time: Sunday, March 18, at 11:00-12:00
Place: Visitor center 194, Open University.
Speaker: Elad Schneidman, Department of Neurobiology, Weizmann Institute of Science.
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Title: Sparse high-order interaction networks underlie learnable neural population codes.
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Abstract:
Information is carried in the brain by the electrical spiking patterns of large groups of neurons. Understanding the structure and function of population neural codes is challenging, due to the exponential number of possible activity patterns and dependencies between neurons. Studying groups of 100 retinal neurons responding to natural movies, we found that they are strongly correlated and that pairwise maximum entropy models, which are highly accurate for small networks, are no longer sufficient. We show that because of the sparse nature of the neural code, the high-order interactions among cells can be easily learned with surprisingly high accuracy using a novel pseudo-likelihood model. We found that a very sparse interaction network underlies the code of large populations of neurons. Additionally, we show that the interaction network is organized in a hierarchical and modular manner, suggesting scalability of the code. Our results suggest that learnability is a key feature of the neural code.