Detecting time-dependent coherence between non-stationary electrophysiological signals—A combined statistical and time–frequency approach

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Detecting time-dependent coherence between non-stationary electrophysiological signals--a combined statistical and time-frequency approach.

Various time-frequency methods have been used to study time-varying properties of non-stationary neurophysiological signals. In the present study, a time-frequency coherence estimate using continuous wavelet transform (CWT) together with its confidence intervals are proposed to evaluate the correlation between two non-stationary processes. The approach is based on averaging over repeat trials. ...

متن کامل

Detecting Correlations between Non-stationary Brain Signals

A new approach is proposed to detect instantaneous correlations between neural activity in different parts of the brain measured with extracellular multi-site recordings. With this method one can also study how the coupling between different areas changes while the animal is performing certain tasks. We illustrate this method by investigating the coupling between the two mushroom bodies of the ...

متن کامل

Using Wavelets and Splines to Forecast Non-Stationary Time Series

 This paper deals with a short term forecasting non-stationary time series using wavelets and splines. Wavelets can decompose the series as the sum of two low and high frequency components. Aminghafari and Poggi (2007) proposed to predict high frequency component by wavelets and extrapolate low frequency component by local polynomial fitting. We propose to forecast non-stationary process u...

متن کامل

Detecting dynamic spatial correlation patterns with generalized wavelet coherence and non-stationary surrogate data

Time series measured from real spatially extended systems are generally noisy, complex and display statistical properties that evolve continuously over time. Here, we present a method that combines wavelet analysis and non-stationary surrogates to detect spatial coherent patterns in nonstationary multivariate time-series. In contrast with classical methods, the surrogate data used here are real...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of Neuroscience Methods

سال: 2006

ISSN: 0165-0270

DOI: 10.1016/j.jneumeth.2006.02.013