کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4946595 1439408 2017 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Entropy factor for randomness quantification in neuronal data
ترجمه فارسی عنوان
عامل آنتروپی برای اندازه گیری تصادفی در داده های عصبی
کلمات کلیدی
اندازه گیری متغیر، آنتروپی شانون، روند تجدید، عامل فانوس،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

A novel measure of neural spike train randomness, an entropy factor, is proposed. It is based on the Shannon entropy of the number of spikes in a time window and can be seen as an analogy to the Fano factor. Theoretical properties of the new measure are studied for equilibrium renewal processes and further illustrated on gamma and inverse Gaussian probability distributions of interspike intervals. Finally, the entropy factor is evaluated from the experimental records of spontaneous activity in macaque primary visual cortex and compared to its theoretical behavior deduced for the renewal process models. Both theoretical and experimental results show substantial differences between the Fano and entropy factors. Rather paradoxically, an increase in the variability of spike count is often accompanied by an increase of its predictability, as evidenced by the entropy factor.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neural Networks - Volume 95, November 2017, Pages 57-65
نویسندگان
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