Neural assemblies: technical issues, analysis, and modeling
نویسندگان
چکیده
Neurons often work together to compute and process information, and neural assemblies arise from synaptic interactions and neural circuits. One way to study neural assemblies is to simultaneously record from several or many neurons and study the statistical relations among their spike trains. From this analysis researchers can try to understand the nature of the assemblies, which can also lead to attempts at modeling the underlying mechanisms. In this review we discuss three important parts of this process: (1) technical issues related to simultaneously recording more than one single unit, (2) ways of analyzing the data and (3) recent models offering hypothetical mechanisms of neural assemblies, especially models which incorporate feedback.
منابع مشابه
Modeling and Control of Gas Turbine Combustor with Dynamic and Adaptive Neural Networks (TECHNICAL NOTE)
متن کامل
DIFFERENT NEURAL NETWORKS AND MODAL TREE METHOD FOR PREDICTING ULTIMATE BEARING CAPACITY OF PILES
The prediction of the ultimate bearing capacity of the pile under axial load is one of the important issues for many researches in the field of geotechnical engineering. In recent years, the use of computational intelligence techniques such as different methods of artificial neural network has been developed in terms of physical and numerical modeling aspects. In this study, a database of 100 p...
متن کاملMachine learning algorithms in air quality modeling
Modern studies in the field of environment science and engineering show that deterministic models struggle to capture the relationship between the concentration of atmospheric pollutants and their emission sources. The recent advances in statistical modeling based on machine learning approaches have emerged as solution to tackle these issues. It is a fact that, input variable type largely affec...
متن کاملA Nonlinear Autoregressive Model with Exogenous Variables Neural Network for Stock Market Timing: The Candlestick Technical Analysis
In this paper, the nonlinear autoregressive model with exogenous variables as a new neural network is used for timing of the stock markets on the basis of the technical analysis of Japanese Candlestick. In this model, the “nonlinear autoregressive model with exogenous variables” is an analyzer. For a more reliable comparison, here (like the literature) two approaches of Raw-based and Signal-ba...
متن کاملPredicting the Coefficients of Antoine Equation Using the Artificial Neural Network (TECHNICAL NOTE)
Neural network is one of the new soft computing methods commonly used for prediction of the thermodynamic properties of pure fluids and mixtures. In this study, we have used this soft computing method to predict the coefficients of the Antoine vapor pressure equation. Three transfer functions of tan-sigmoid (tansig), log-sigmoid (logsig), and linear were used to evaluate the performance of diff...
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:
- Neural networks : the official journal of the International Neural Network Society
دوره 14 6-7 شماره
صفحات -
تاریخ انتشار 2001