Extracting Temporal Firing Patterns of Neurons from Noisy Data

スポンサーリンク

概要

• 論文の詳細を見る

• We propose a novel method for analysis of time-related neuronal activities. This method can be used for the detection of firing patterns in the presence of noise, which is inevitable in physiological experiments. This method is also useful for probability density estimation, because it enables precise information quantification from a small amount of data.

• 社団法人電子情報通信学会の論文
• 2002-04-01

著者

• Iwamoto Toshihiro

  Faculty Of Engineering The University Of Tokyo

• Jimbo Yasuhiko

  Ntt Basic Research Laboratories Ntt Corporation

• Jimbo Yasuhiko

  Ntt Basic Research Laboratories

• AIHARA Kazuyuki

  Faculty of Engineering, The University of Tokyo and CREST, Japan Science and Technology Corporation

• Jimbo Y

  Department Of Human And Engineered Environmental Studies Graduate School Of Frontier Sciences Univer

• Aihara Kazuyuki

  Faculty Of Engineering The University Of Tokyo And Crest Japan Science And Technology Corporation (j

• Aihara Kazuyuki

  Faculty Of Engineering The University Of Tokyo

関連論文

• Extracting Temporal Firing Patterns of Neurons from Noisy Data
• Modeling of Single Neuron Computation (特集 生体系の計測とモデル解析) -- (特集解説)
• Electrochemical Monitoring of Glutamate Release at Multiple Positions in a Rat Hippocampal Slice
• Prediction of Chaotic Time Series with Noise
• An Analysis on Additive Effects of Nonlinear Dynamics for Combinatorial Optimization
• Global Bifurcation Structure of Chaotic Neural Networks and its Application to Traveling Salesman Problems
• A Current-Mode Implementation of a Chaotic Neuron Model Using a SI Integrator
• On Dimension Estimates with Surrogate Data Sets

スポンサーリンク