Topographic Factor Analysis: A Bayesian Model for Inferring Brain Networks from Neural Data
نویسندگان
چکیده
منابع مشابه
Topographic Factor Analysis: A Bayesian Model for Inferring Brain Networks from Neural Data
The neural patterns recorded during a neuroscientific experiment reflect complex interactions between many brain regions, each comprising millions of neurons. However, the measurements themselves are typically abstracted from that underlying structure. For example, functional magnetic resonance imaging (fMRI) datasets comprise a time series of three-dimensional images, where each voxel in an im...
متن کاملrodbar dam slope stability analysis using neural networks
در این تحقیق شبکه عصبی مصنوعی برای پیش بینی مقادیر ضریب اطمینان و فاکتور ایمنی بحرانی سدهای خاکی ناهمگن ضمن در نظر گرفتن تاثیر نیروی اینرسی زلزله ارائه شده است. ورودی های مدل شامل ارتفاع سد و زاویه شیب بالا دست، ضریب زلزله، ارتفاع آب، پارامترهای مقاومتی هسته و پوسته و خروجی های آن شامل ضریب اطمینان می شود. مهمترین پارامتر مورد نظر در تحلیل پایداری شیب، بدست آوردن فاکتور ایمنی است. در این تحقیق ...
Estimation of Products Final Price Using Bayesian Analysis Generalized Poisson Model and Artificial Neural Networks
Estimating the final price of products is of great importance. For manufacturing companies proposing a final price is only possible after the design process over. These companies propose an approximate initial price of the required products to the customers for which some of time and money is required. Here using the existing data of already designed transformers and utilizing the bayesian anal...
متن کاملFactor Topographic Latent Source Analysis: Factor Analysis for Brain Images
Traditional approaches to analyzing experimental functional magnetic resonance imaging (fMRI) data entail fitting per-voxel parameters to explain how the observed images reflect the thoughts and stimuli a participant experienced during the experiment. These methods implicitly assume that voxel responses are independent and that the unit of analysis should be the voxel. However, both of these as...
متن کاملA Recurrent Neural Network Model for solving CCR Model in Data Envelopment Analysis
In this paper, we present a recurrent neural network model for solving CCR Model in Data Envelopment Analysis (DEA). The proposed neural network model is derived from an unconstrained minimization problem. In the theoretical aspect, it is shown that the proposed neural network is stable in the sense of Lyapunov and globally convergent to the optimal solution of CCR model. The proposed model has...
متن کاملذخیره 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: PLoS ONE
سال: 2014
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0094914