Workshop: quantifying structure in large neural datasets

Columbia University, Sept 22-23, 2014

Please register by emailing grossman@stat.columbia.edu. Registration is free, but is necessary so that we can provide adequate coffee and snacks. Seating in the venue is capped, so please register early. (No receipt of email will be provided.) Due to high demand, we can not accept any additional registrations from non-Columbia guests (all registrations received by Sept 15 will be honored). Columbia faculty, students, and postdocs are still encouraged to register, if you haven't done so already.

In systems neuroscience, it is becoming increasingly common to record the activity of hundreds of neurons simultaneously via electrode arrays or optical imaging. Emerging technologies promise further increases in the number of simultaneous recordings. We will thus often be limited not by our measurements but by our ability to interpret those measurements. How should one translate a long list of spike times / activity levels into an understanding of what the neural population is doing? Is a specialized approach always necessary or can we agree on a set of standardized techniques? What quantitative tools are currently available, and what have they taught us so far? What tools do we need that have yet to be developed? The goal of this meeting is to propagate a dialogue that focuses on such questions.

Tentative Schedule:

September 22
8:00     Continental breakfast
8:45     Introductory remarks
9:00     Carlos Brody (Princeton University): Neural substrates of decision-making in the rat
9:40     Mark Churchland (Columbia University): Viewing neural events at the moment of voluntary movement initiation
10:20   Coffee
10:40   Guillaume Hennequin (University of Cambridge): From dynamics to statistics: trial-average trajectories and across-trial variability of cortical responses
11:20   Brent Doiron (University of Pittsburgh): The neural mechanics of attention-mediated suppression of noise correlations
12:00   Lunch
1:20     Nima Mesgarani (Columbia University): Reverse engineering the neural mechanisms involved in robust speech processing
2:00     Genevera Allen (Rice University): Inference for connectomics
2:40     Coffee
3:00     Rebecca Willett (University of Wisconsin-Madison): Tracking dynamic point processes on networks
3:40     Tony Zador (Cold Spring Harbor Laboratory): Sequencing the connectome

September 23
8:00     Continental breakfast
9:00     Adam Cohen (Harvard University): Probing neural circuit dynamics in vitro with all-optical electrophysiology
9:40     Mark Schnitzer (Stanford University): Reading neural codes, ~1000 cells at a time in behaving mice
10:20   Coffee
10:40   Andrew Leifer (Princeton University): Optical neurophysiology in freely moving C. elegans
11:20   Michael Long (New York University): Analyzing the circuit underlying a complex motor skill
12:00   Lunch
1:20     Adam Kepecs (Cold Spring Harbor): Model-free discovery of model-based decision variables in cortical representations
2:00     Nicole Rust (University of Pennsylvania): Population-based approaches reveal how visual and target information are compared during target search
2:40     Coffee
3:00     Tony Movshon (New York University): Neural population representations for perception and action
3:40     Concluding remarks

All talks will be in the Presidential Ballroom, on the third floor of the Faculty House. Note that the address is technically 64 Morningside drive. However, one must enter from a large gate on the north side of 116th Street between Amsterdam and Morningside. A map from the 1 subway train to the Faculty House is here.


« Back to the Grossman Center for the Statistics of Mind main page