Literature DB >> 15901404

Theory of the snowflake plot and its relations to higher-order analysis methods.

Gabriela Czanner1, Sonja Grün, Satish Iyengar.   

Abstract

The snowflake plot is a scatter plot that displays relative timings of three neurons. It has had rather limited use since its introduction by Perkel, Gerstein, Smith, and Tatton (1975), in part because its triangular coordinates are unfamiliar and its theoretical properties are not well studied. In this letter, we study certain quantitative properties of this plot: we use projections to relate the snowflake plot to the cross-correlation histogram and the spike-triggered joint histogram, study the sampling properties of the plot for the null case of independent spike trains, study a simulation of a coincidence detector, and describe the extension of this plot to more than three neurons.

Mesh:

Year:  2005        PMID: 15901404     DOI: 10.1162/0899766053723041

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  9 in total

1.  An L₁-regularized logistic model for detecting short-term neuronal interactions.

Authors:  Mengyuan Zhao; Aaron Batista; John P Cunningham; Cynthia Chestek; Zuley Rivera-Alvidrez; Rachel Kalmar; Stephen Ryu; Krishna Shenoy; Satish Iyengar
Journal:  J Comput Neurosci       Date:  2011-10-22       Impact factor: 1.621

2.  Measuring correlations and interactions among four simultaneously recorded brain regions during learning.

Authors:  Rony Paz; Elizabeth P Bauer; Denis Paré
Journal:  J Neurophysiol       Date:  2009-02-25       Impact factor: 2.714

Review 3.  Data-driven significance estimation for precise spike correlation.

Authors:  Sonja Grün
Journal:  J Neurophysiol       Date:  2009-01-07       Impact factor: 2.714

4.  NeuroXidence: reliable and efficient analysis of an excess or deficiency of joint-spike events.

Authors:  Gordon Pipa; Diek W Wheeler; Wolf Singer; Danko Nikolić
Journal:  J Comput Neurosci       Date:  2008-01-26       Impact factor: 1.621

5.  Exact solutions for rate and synchrony in recurrent networks of coincidence detectors.

Authors:  Shawn Mikula; Ernst Niebur
Journal:  Neural Comput       Date:  2008-11       Impact factor: 2.026

6.  Information-geometric measures estimate neural interactions during oscillatory brain states.

Authors:  Yimin Nie; Jean-Marc Fellous; Masami Tatsuno
Journal:  Front Neural Circuits       Date:  2014-02-24       Impact factor: 3.492

7.  Methods for identification of spike patterns in massively parallel spike trains.

Authors:  Pietro Quaglio; Vahid Rostami; Emiliano Torre; Sonja Grün
Journal:  Biol Cybern       Date:  2018-04-12       Impact factor: 2.086

8.  VIOLA-A Multi-Purpose and Web-Based Visualization Tool for Neuronal-Network Simulation Output.

Authors:  Johanna Senk; Corto Carde; Espen Hagen; Torsten W Kuhlen; Markus Diesmann; Benjamin Weyers
Journal:  Front Neuroinform       Date:  2018-11-08       Impact factor: 4.081

9.  Distinguishing synchronous and time-varying synergies using point process interval statistics: motor primitives in frog and rat.

Authors:  Corey B Hart; Simon F Giszter
Journal:  Front Comput Neurosci       Date:  2013-05-09       Impact factor: 2.380

  9 in total

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