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    DETECTION OF ASSEMBLY ACTIVITY IN MASSIVELY PARALLEL SPIKE DATA: WORKFLOW AND STATISTICS
    Date:
    07/18/2014
    Speaker:
    Prof. Sonja Grün
    Inst. of Neuroscience & Medicine (INM-6) & Inst. for Advanced Simulation (IAS-6), Jülich Research Centre and JARA, Jülich, Germany; Theoretical Systems Neurobiology, RWTH Aachen Univ., Aachen, Germany
    Title:
    DETECTION OF ASSEMBLY ACTIVITY IN MASSIVELY PARALLEL SPIKE DATA:
    WORKFLOW AND STATISTICS
    Abstract:
    We aim at getting an understanding into cortical network processing during natural behavior. This requires a) performing recordings from a large number of neurons during complex behavior [e.g., 1], b) development of statistical methods for the analysis of neuronal interaction in a trial-by-trial and time resolved manner [2], c) analysis of data in relation to behavior [3], d) reproducible workflows and related necessary software to realize collaborations within and across labs [4]. In this talk I will present our work
    related to these aspects and present preliminary results of our analysis of massively parallel data.

    [1] Riehle et al (2013) Front Neural Circuits 7: 48
    [2] e.g. Grün et al (2010) In: Analysis of parallel spike trains. eds. Grün & Rotter. Springer, New York; Staude et al (2010) J Comput Neurosci, 29 (1-2): 327-350; Torre et al (2013) Front Comput Neurosci 7:132
    [3] e.g. Kilavik et al (2009) J Neurosci, 29(40), 12653-12663; Ito et al (2011) Cereb. Cortex 21 (11): 2482-2497
    [4] Zehl et al (2014) and Denker et al (2014), both INCF conference 2014
    Place:
    University of Heidelberg, INF 328, SR 25, 15:00-16:00