期刊论文详细信息
Frontiers in Computational Neuroscience
Modeling population spike trains with specified time-varying spike rates, trial-to-trial variability, and pairwise signal and noise correlations
Dmitry R Lyamzin3  Nicholas A Lesica3  Jakob H Macke4 
[1] Ludwig-Maximilians-University Munich;Max Planck Institute for Biological Cybernetics;University College London;University of Tübingen;
关键词: Population;    simulation;    Correlation;    Model;    noise correlation;   
DOI  :  10.3389/fncom.2010.00144
来源: DOAJ
【 摘 要 】

As multi-electrode and imaging technology begin to provide us with simultaneous recordings of large neuronal populations, new methods for modeling such data must also be developed. Here, we present a model for the type of data commonly recorded in early sensory pathways: responses to repeated trials of a sensory stimulus in which each neuron has it own time-varying spike rate (as described by its PSTH) and the dependencies between cells are characterized by both signal and noise correlations. This model is an extension of previous attempts to model population spike trains designed to control only the total correlation between cells. In our model, the response of each cell is represented as a binary vector given by the dichotomized sum of a deterministic ‘signal’ that is repeated on each trial and a Gaussian random ‘noise’ that is different on each trial. This model allows the simulation of population spike trains with PSTHs, trial-to-trial variability, and pairwise correlations that match those measured experimentally. Furthermore, the model also allows the noise correlations in the spike trains to be manipulated independently of the signal correlations and single cell properties. To demonstrate the utility of the model, we use it to simulate and manipulate experimental responses from the mammalian auditory and visual systems. We also present a general form of the model in which both the signal and noise are Gaussian random processes, allowing the mean spike rate, trial-to-trial variability, and pairwise signal and noise correlations to be specified independently. Together, these methods for modeling spike trains comprise a potentially powerful set of tools for both theorists and experimentalists studying population responses in sensory systems.

【 授权许可】

Unknown   

  文献评价指标  
  下载次数:0次 浏览次数:0次