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» Bayesian inference in spiking neurons
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ICA
2010
Springer
13 years 6 months ago
Recovering Spikes from Noisy Neuronal Calcium Signals via Structured Sparse Approximation
Two-photon calcium imaging is an emerging experimental technique that enables the study of information processing within neural circuits in vivo. While the spatial resolution of th...
Eva L. Dyer, Marco F. Duarte, Don H. Johnson, Rich...
NECO
2000
133views more  NECO 2000»
13 years 5 months ago
Neural Coding: Higher-Order Temporal Patterns in the Neurostatistics of Cell Assemblies
Recent advances in the technology of multi-unit recordings make it possible to test Hebb's hypothesis that neurons do not function in isolation but are organized in assemblie...
Laura Martignon, Gustavo Deco, Kathryn B. Laskey, ...
BC
2007
107views more  BC 2007»
13 years 5 months ago
Decoding spike train ensembles: tracking a moving stimulus
We consider the issue of how to read out the information from nonstationary spike train ensembles. Based on the theory of censored data in statistics, we propose a ‘censored’ m...
Enrico Rossoni, Jianfeng Feng
NIPS
2004
13 years 6 months ago
Spike Sorting: Bayesian Clustering of Non-Stationary Data
Spike sorting involves clustering spike trains recorded by a microelectrode according to the source neuron. It is a complicated problem, which requires a lot of human labor, partl...
Aharon Bar-Hillel, Adam Spiro, Eran Stark
NIPS
2003
13 years 6 months ago
Decoding V1 Neuronal Activity using Particle Filtering with Volterra Kernels
Decoding is a strategy that allows us to assess the amount of information neurons can provide about certain aspects of the visual scene. In this study, we develop a method based o...
Ryan Kelly, Tai Sing Lee