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Title: Dynamic decoding of ongoing perception
Author(s): Gerven, M.A.J. van ; Kok, P.H.J. ; Lange, F.P. de ; Heskes, T.M.
Publication year: 2011
Source: NeuroImage, vol. 57, iss. 3, (2011), pp. 950-957
ISSN: 1053-8119
DOI: http://dx.doi.org/10.1016/j.neuroimage.2011.05.020
Publication type: Article / Letter to editor

Please use this identifier to cite or link to this item : https://hdl.handle.net/2066/99267   https://hdl.handle.net/2066/99267

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Subject: Cognitive artificial intelligence
DI-BCB_DCC_Theme 4: Brain Networks and Neuronal Communication
Intelligent Systems
160 000 Neuronal Oscillations
180 000 Prediction and Action
Organization: SW OZ DCC KI
SW OZ DCC PL
FSW_Fac. algemeen
Donders Centre for Cognitive Neuroimaging
Intelligent Systems
Former Organization: F.C. Donders Centre for Cognitive Neuroimaging
Journal title:
NeuroImage
Volume: vol. 57
Issue: iss. 3
Page start: p. 950
Page end: p. 957
Abstract:
Decoding of perceptual and mental states using multivariate analysis methods has received much recent attention. It relies on selective responses to experimental conditions in single trials, aggregated across voxels. In this study, we show that decoding is also possible when the state of interest changes continuously over time. It is shown that both orientation and rotation direction of a continuously rotating grating can be decoded with high accuracy using linear dynamical systems and hidden Markov models. These findings extend the decoding results for static gratings and are of importance in the decoding of ongoing changes in mental state.

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