Brain electrical activity in epilepsy: characterization of the spatio-temporal dynamics with cellular neural networks based on a correlation dimension analysis
نویسندگان
چکیده
In this paper we present a new approach for the analysis of the spatio-temporal dynamics of brain electrical activity in epilepsy with Cellular Neural Networks (CNN). We have shown in recent investigations [1] that the dimension D 2(k;m) of brain electrical activity can be approximated by a function of CNN cell outputs. These results obtained with CNN, having non steady-states, were sensitive to parameter deviations occurring in CNN hardware realizations. In this contribution we present an enhanced approximation method, which is based on a steady state determination showing an increased robustness and higher accuracy.
منابع مشابه
STCS-GAF: Spatio-Temporal Compressive Sensing in Wireless Sensor Networks- A GAF-Based Approach
Routing and data aggregation are two important techniques for reducing communication cost of wireless sensor networks (WSNs). To minimize communication cost, routing methods can be merged with data aggregation techniques. Compressive sensing (CS) is one of the effective techniques for aggregating network data, which can reduce the cost of communication by reducing the amount of routed data to t...
متن کاملمعرفی شبکه های عصبی پیمانه ای عمیق با ساختار فضایی-زمانی دوگانه جهت بهبود بازشناسی گفتار پیوسته فارسی
In this article, growable deep modular neural networks for continuous speech recognition are introduced. These networks can be grown to implement the spatio-temporal information of the frame sequences at their input layer as well as their labels at the output layer at the same time. The trained neural network with such double spatio-temporal association structure can learn the phonetic sequence...
متن کاملAnalysis of Resting-State fMRI Topological Graph Theory Properties in Methamphetamine Drug Users Applying Box-Counting Fractal Dimension
Introduction: Graph theoretical analysis of functional Magnetic Resonance Imaging (fMRI) data has provided new measures of mapping human brain in vivo. Of all methods to measure the functional connectivity between regions, Linear Correlation (LC) calculation of activity time series of the brain regions as a linear measure is considered the most ubiquitous one. The strength of the dependence obl...
متن کاملHand Gesture Recognition from RGB-D Data using 2D and 3D Convolutional Neural Networks: a comparative study
Despite considerable enhances in recognizing hand gestures from still images, there are still many challenges in the classification of hand gestures in videos. The latter comes with more challenges, including higher computational complexity and arduous task of representing temporal features. Hand movement dynamics, represented by temporal features, have to be extracted by analyzing the total fr...
متن کاملEvaluation of Phase Locking and Cross Correlation Methods for Estimating the Time Lag between Brain Sites: A Simulation Approach
Introduction: Direction and latency of electrical connectivity between different sites of brain explains brain neural functionality. We compared efficiency of cross correlation and phase locking methods in time lag estimation which are based on local field potential (LFP) and LFPspike signals, respectively. Methods: Signals recorded from MT area of a macaque’s brain was used in a simulation ...
متن کامل