Titlebook: Electromagnetic Brain Imaging; A Bayesian Perspecti Kensuke Sekihara,Srikantan S. Nagarajan Textbook 2015 Springer International Publishing

聲音會爆炸

書目名稱Electromagnetic Brain Imaging影響因子(影響力)




書目名稱Electromagnetic Brain Imaging影響因子(影響力)學(xué)科排名




書目名稱Electromagnetic Brain Imaging網(wǎng)絡(luò)公開度




書目名稱Electromagnetic Brain Imaging網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Electromagnetic Brain Imaging被引頻次




書目名稱Electromagnetic Brain Imaging被引頻次學(xué)科排名




書目名稱Electromagnetic Brain Imaging年度引用




書目名稱Electromagnetic Brain Imaging年度引用學(xué)科排名




書目名稱Electromagnetic Brain Imaging讀者反饋




書目名稱Electromagnetic Brain Imaging讀者反饋學(xué)科排名

簡潔

Zeolithe mit schwankendem SiO2-GehaltIn this chapter, we provide a detailed description of an algorithm for electromagnetic brain imaging, called the Champagne algorithm [., .].

思想流動

C. Doelter,Emil Baur,M. Dittrich,L. JesserThis chapter describes Bayesian factor analysis (BFA), which is a technique that can decompose multiple sensor time courses into time courses of independent factor activities, where the number of factors is much smaller than the number of sensors.

Inexorable

G. d’Achiardi,R. Amberg,E. ZschimmerMagnetoencephalography (MEG) and related electroencephalography (EEG) use an array of sensors to take electromagnetic field (or voltage) measurements from on or near the scalp surface with excellent temporal resolution.

甜瓜

Lagerung und Belastung der Modelle,There has been tremendous interest in estimating the functional connectivity of neuronal activities across different brain regions using electromagnetic brain imaging.

關(guān)心

,Rechenprogramme für die Netzplantechnik,This chapter reviews the methodology for estimating causal relationships among cortical activities in MEG/EEG source space analysis.

關(guān)心

https://doi.org/10.1007/978-3-642-50784-7Neural oscillations across multiple frequency bands have consistently been observed in EEG and MEG recordings.

Humble

Gourmet

Sparse Bayesian (Champagne) Algorithm,In this chapter, we provide a detailed description of an algorithm for electromagnetic brain imaging, called the Champagne algorithm [., .].

容易做

Bayesian Factor Analysis: A Versatile Framework for Denoising, Interference Suppression, and SourceThis chapter describes Bayesian factor analysis (BFA), which is a technique that can decompose multiple sensor time courses into time courses of independent factor activities, where the number of factors is much smaller than the number of sensors.