Brain decoding: Opportunities and challenges for pattern recognition

Pattern Recognition

Volumn 45, Issue 6, 2012, Pages 2033-2034

  Van De Ville, Dimitri ^a,b   Lee, Seong Whan ^c  

^a UNIVERSITY OF GENEVA   (Switzerland)

^b EPFL   (Switzerland)

^c Korea University   (South Korea)

Author keywords

Brain decoding; Braincomputer interface; Electroencephalography; Functional magnetic resonance imaging; Neuroimaging

Indexed keywords

BIOMEDICAL SIGNAL PROCESSING; BRAIN; BRAIN COMPUTER INTERFACE; DECODING; ELECTROENCEPHALOGRAPHY; ELECTROPHYSIOLOGY; MAGNETIC RESONANCE IMAGING; NEUROIMAGING; PATTERN RECOGNITION;

BRAIN DECODING; BRAIN-COMPUTER INTERFACING; CLINICAL DIAGNOSIS; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HIGH-DIMENSIONAL; SPATIOTEMPORAL CORRELATION; SPECIFIC PROBLEMS; STATISTICAL INFERENCE;

FUNCTIONAL NEUROIMAGING;

EID: 83055168547     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2011.06.001     Document Type: Editorial

References (13)

1. K.J. Friston, A.P. Holmes, K.J. Worsley, J.P. Poline, C.D. Frith, and R.S.J. Frackowiak Statistical parametric maps in functional imaging: a general linear approach Human Brain Mapping 2 1995 189 210 (Pubitemid 124008664)
2. J. Haxby, M.I. Gobbini, M.L. Furey, A. Ishai, J.L. Schouten, and P. Pietrini Distributed and overlapping representations of faces and objects in ventral temporal cortex Science 293 5539 2001 2425 2430 (Pubitemid 32917318)
3. B. Blankertz, G. Curio, and K.-R. Müller Classifying single trial EEG: towards brain computer interfacing T. Diettrich, S. Becker, Z. Ghahramani, Advances in Neural Information Processing Systems (NIPS vol. 14 2002 157 164
4. M. Björnsdotter, J. Wessberg, Clustered sampling improves random subspace brain mapping, Pattern Recognition, this issue, doi: 10.1016/j.patcog.2011.04.005
5. V. Michel, A. Gramforta, G. Varoquaux, E. Eger, C. Keribin, B. Thirion, A supervised clustering approach for fMRI-based inference of brain states, Pattern Recognition, this issue, doi: 10.1016/j.patcog.2011.04.006
6. P.A. Rodriguez, V.D. Calhoun, T. Adali, De-noising, phase ambiguity correction and visualization techniques for complex-valued ICA of group fMRI data, Pattern Recognition, this issue, doi: 10.1016/j.patcog.2011.04.033
7. C. Cabral, M. Silveira, P. Figueiredo, Decoding visual brain states from fMRI using an ensemble of classifiers, Pattern Recognition, this issue, doi: 10.1016/j.patcog.2011.04.015
8. E. Olivetti, S. Veeramachaneni, E. Nowakowska, Bayesian hypothesis testing for pattern discrimination in brain decoding, Pattern Recognition, this issue, doi: 10.1016/j.patcog.2011.04.025
9. P.M. Rasmussen, L.K. Hansen, K.H. Madsen, N.W. Churchill, S.C.Strother, Model sparsity and brain pattern interpretation of classification models in neuroimaging, Pattern Recognition, under review
10. C.O. Plumpton, L.I. Kuncheva, N.N. Oosterhof, S.J. Johnston, Naive random subspace ensemble with linear classifiers for real time classification of fMRI data, Pattern Recognition, this issue, doi: 10.1016/j.patcog.2011.04.023
11. A. Tzovara, M.M. Murray, G. Plomp, M.H. Herzog, C.M. Michel, M. De Lucia, Decoding stimulus-related information from single-trial EEG responses based on voltage topographies, Pattern Recognition, this issue, doi: 10.1016/j.patcog. 2011.04.007
12. I. Daly, S.J. Nasuto, K. Warwick, Brain computer interface control via functional connectivity dynamics, Pattern Recognition, this issue, doi: 10.1016/j.patcog.2011.04.034
13. K.K. Ang, Z.Y. Chin, H. Zhang, C. Guan, Mutual information-based selection of optimal spatial-temporal patterns for single-trial EEG-based BCIs, Pattern Recognition, this issue, doi: 10.1016/j.patcog.2011.04.018