Spectral factorization-based current source density analysis of ongoing neural oscillations.
نویسندگان
چکیده
BACKGROUND Current source density (CSD) analysis is widely used in neurophysiological investigations intended to reveal the patterns of localized neuronal activity in terms of current sources and sinks. CSD is based on the second spatial derivatives of multi-electrode electrophysiological recordings, and can be applied to brain activity related to repeated external stimulations (evoked brain activity) or ongoing (spontaneous) brain activity. In evoked brain activity, event-related time-series averages of ensembles are used to compute CSD patterns. However, for ongoing neural activity, the lack of external events requires a different approach other than ensemble averaging. NEW METHOD Here, we propose a new spectral factorization-based current source density (SF-CSD) analysis method for ongoing neural oscillations. RESULTS We validated this new SF-CSD analysis method using simulated data and demonstrated its effectiveness by applying to experimental intra-cortical local field potentials recorded on multi-contact depth electrodes from monkeys performing selective visual attention tasks. COMPARISON WITH EXISTING METHODS The proposed method gives space-unbiased estimates since it does not rely on a reference for CSD calculation in the frequency-domain. CONCLUSION The proposed SF-CSD method is expected to be a useful tool for systematic analysis of neural sources and oscillations from multi-site electrophysiological recordings.
منابع مشابه
On the role of neuronal oscillations in auditory cortical processing
ON THE ROLE OF NEURONAL OSCILLATIONS IN AUDITORY CORTICAL PROCESSING Monica Noelle O’Connell Adviser: Charles E. Schroeder, Ph.D. Although it has been over 100 years since William James stated that “everyone knows what attention is”, its underlying neural mechanisms are still being debated today. The goal of this research was to describe the physiological mechanisms of auditory attention using ...
متن کاملCite as : Cole SR & Voytek B , Brain oscillations and the importance of waveform shape ,
Oscillations are a prevalent feature of brain recordings. They are believed to play key roles in neural communication and computation. Current analysis methods for studying neural oscillations often implicitly assume the oscillations are sinusoidal. While these approaches have proven fruitful, here we show that there are numerous instances in which neural oscillations are nonsinusoidal. We high...
متن کاملAnalysis of Human Skin Hyper-Spectral Images by Non-negative Matrix Factorization
This article presents the use of Non-negative Matrix Factorization, a blind source separation algorithm, for the decomposition of human skin absorption spectra in its main pigments: melanin and hemoglobin. The evaluated spectra come from a Hyper-Spectral Image, which is the result of the processing of a Multi-Spectral Image by a neural network-based algorithm. The implemented source separation ...
متن کاملArea-Correlated Spectral Unmixing Based on Bayesian Nonnegative Matrix Factorization
To solve the problem of the spatial correlation for adjacent areas in traditional spectral unmixing methods, we propose an area-correlated spectral unmixing method based on Bayesian nonnegative matrix factorization. In the proposed method, the spatial correlation property between two adjacent areas is expressed by a priori probability density function, and the endmembers extracted from one of t...
متن کاملQuantification of melanin and hemoglobin in humain skin from multispectral image acquisition: use of a neuronal network combined to a non-negative matrix factorization
This article presents a multispectral imaging system which, coupled with a neural network-based algorithm, reconstructs reflectance cubes. The reflectance spectra are obtained using artificial neural-netwok reconstruction which generates reflectance cubes from acquired multispectral images. Then, a blind source separation algorithm based on Non-negative Matrix Factorization is used for the deco...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Journal of neuroscience methods
دوره 224 شماره
صفحات -
تاریخ انتشار 2014