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Liam paninski thesis


liam paninski thesis

focuses on recent advances in methods for analyzing neural time-series data with single-neuronal precision. We describe likelihood-based methods for fitting these encoding the black album hanif kureishi essay on models and then for using the models to perform optimal decoding. Python 5 3, mIT Updated Jul 11, 2018 yass-examples, yASS Examples python computational-neuroscience spike-sorting yass-experimental, personal experimental work, updated Mar 1, 2018. This is last half of a talk given to the Statistics Dept. We find that this GL model with functional coupling between neurons captures both the stimulus dependence and the detailed spatiotemporal correlation structure of multi-neuronal responses; in addition, ongoing network activity in the retina accounts for a significant portion of the trial-to-trial variability in a neuron's. Joint work with.J. Sign up yass, yASS: Yet Another Spike Sorter python computational-neuroscience spike-sorting. It is made available under. The encoding' problem concerns how information is encoded in neural spike trains: can we predict the responses of a neuron (or population of neurons given an arbitrary stimulus or observed motor behavior?

Estimation of Entropy and Mutual Information.
Wulfram Gerstner, Werner.
Kistler, Richard Naud, Liam Paninski.
Liam Paninski, Michael Vidne, Brian DePasquale, Daniel Gil Ferreira.

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This talk describes GLM-based techniques that in some cases provide a unified solution to these two coding problems. Grow your team on GitHub, gitHub is home to over 28 million developers working together. Advances in methods for signal processing, network analysis, dimensionality reduction, and optimal control - developed in lockstep with advances in experimental neurotechnology - promise major breakthroughs in multiple fundamental neuroscience problems. People, you cant perform that action at this time. We assess the significance of correlated spiking by performing optimal Bayesian decoding of the population spike responses; we find that approximately 15 more stimulus-related information is captured when correlations are taken into account. Copyright, the copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. Join them to grow your own development teams, manage permissions, and collaborate on projects. We will discuss an application of these methods to data recorded from a complete mosaic of macaque parasol retinal ganglion cells in a small region of visual space. Abstract: There are two basic problems in the statistical analysis of neural data.

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