Spatial patterns underlying population differences in the background EEG

By Zoltan J. Koles, Michael S. Lazar, Steven Zhiying Zhou. Brain Topography, 2005

372 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/05e979f9cae12531b60c23b7e75a75c2084f552c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. He He
2. Dongrui Wu
3. Ilke Demir
4. Umur Aybars Ciftci
5. Mohammad Rostami
6. Aram Galstyan
7. Serban Stan

Citations in the corpus

• Transfer Learning for Brain–Computer Interfaces: A Euclidean Space Data Alignment Approach (2018, methodology): “In the Euclidean space, after EA, we used CSP [11], [17], [22], [26] for spatial filtering and LDA for classification.”
• FakeCatcher: Detection of Synthetic Portrait Videos using Biological Signals (2019, methodology): “inear discriminant analysis) [100], guiding us towards kernel based SVMs and more feature space exploration. We also applied PCA (principal component analysis) [101] and CSP (common spatial patterns) [102] to reduce the dimensionality of our feature spaces. Figure 12 shows 3D distribution of origina”