Abstract
Cognitive sciences try to understand the working of the brain. As the most important recording techniques (Electroencephalogram and functional Magnetic Resonance Imaging) only measure a combination of different active brain sources, Blind Source Separation (BSS) techniques have a wide range of applications in this field. BSS aims at extracting individual brain processes. The current state of the art of BSS in neuroscience will be discussed. This chapter aims at clarifying why different problems are solved in different ways that reflect different assumptions. We will explain some algorithms in detail. We will focus on Canonical Correlation Analysis (CCA), Independent Component Analysis (ICA) and CPA (Canonical/Parallel Factor Analysis). It will be shown how these algorithms can be applied to enhance brain research. We will highlight the potential and limitations of current BSS techniques.
Keywords: decomposition, neuroscience, ICA, CCA, CPA, EEG
Related Books
6G Wireless Communications and Mobile Networking
Recent Advances in Renewable Energy
Recent Advances in Renewable Energy
Recent Advances in Renewable Energy
Recent Advances in Renewable Energy
Recent Advances in Renewable Energy
Solar Thermal Systems: Thermal Analysis and its Application
Recent Developments in Artificial Intelligence and Communication Technologies
40 YEARS OF SHS: A LUCKY STAR OF A SCIENTIFIC DISCOVERY A Presentation with Elements of a Scientific Lecture
A Review: Chill-Block Melt Spin Technique, Theories & Applications