Relating EEG/fMRI to behavior using multivariate pattern classifiers, statistical decision theory and ideal observer analysis
Both electro-encephalography (EEG) and functional magnetic resonance imaging (fMRI) techniques are used in the laboratory with computional tools (single trial techniques,computational approaches to analyis- statistical decision theory and ideal observer analysis) to attempt to integrate neural measures with behavioral data and modeling. Much of the approach is inspired by animal electrophysiology relating single trial neural activity to perceptual choices. The topics investigated range from: 1. Basic science questions in perceptual decision making, visual search, attention and learning; 2. Methods questions involving comparison of MVPA methods/fMRI designs and use of ideal observers for task normalization of pattern classifier performance. 3. Applications such as EEG person identification, detection of attentional failures and multi-brain computing. Research is conducted as part of the Neuro-Group at the UC Santa Barbara/MIT/Caltech Institute for Collaborative Biotechnologies housed on campus.
Kasper, R. W., Grafton, S. T., Eckstein, M. P., & Giesbrecht, B., Multimodal neuroimaging evidence linking memory and attention systems during visual search cued by context. Annals of the New York Academy of Sciences (2015)
Cecotti, H., Eckstein, M. P., & Giesbrecht, B. (2014). Single-trial classification of event-related potentials in rapid serial visual presentation tasks using supervised spatial filtering. Neural Networks and Learning Systems, IEEE Transactions on, 25(11), 2030-2042.
Cecotti, H., Eckstein, M. P., & Giesbrecht, B. Single-trial classification of neural responses evoked in rapid serial visual presentation: Effects of stimulus onset asynchrony and stimulus repetition. In Engineering in Medicine and Biology Society (EMBC), (pp. 1282-1285) (2014)
Kasper, R. W., Cecotti, H., Touryan, J., Eckstein, M. P., & Giesbrecht, B. Isolating the Neural Mechanisms of Interference during Continuous Multisensory Dual-task Performance, Journal of Cognitive Neuroscience, 26(3), 476-489 (2013)
Preston, T. J., Guo, F., Das, K., Giesbrecht, B., & Eckstein, M. P. Neural Representations of Contextual Guidance in Visual Search of Real-World Scenes, The Journal of Neuroscience, 33(18), 7846-7855 (2013)
Guo F., Preston T.J., Das K., Giesbrecht B., Eckstein M.P., Feature-independent neural coding of target detection during search of natural scenes, Journal of Neuroscience, 32, 9499-510, (2012)
Eckstein M.P., Das, K., Pham, B.T., Peterson, M.F., Abbey, C.K., Sy, J.L., Giesbrecht, B., Neural decoding of collective wisdom with multi-brain computing, Neuroimage, 59, 1, (2012)
Cecotti, H., Kasper, R.W., Elliott, J.C., Eckstein, M.P., Giesbrecht, B., Multimodal target detection using single trial evoked EEG responses in single and dual-tasks, IEEE Engineering in Medicine and Biology Society, 6311-4, (2011)
Cecotti, H., Sato-Reinhold, J., Sy, J.L., Elliott, J.C., Eckstein, M.P., Giesbrecht, B., Impact of target probability on single-trial EEG target detection in a difficult rapid serial visual presentation task, IEEE Engineering in Medicine and Biology Society, 6381-4, (2011)
Peterson M.F., Das K., Sy J.L., Li S., Giesbrecht B., Kourtzi Z., Eckstein M.P., Ideal observer analysis for task normalization of pattern classifier performance applied to EEG and fMRI data, Journal of the Optical Society of America A, 27, 2670-83, (2010)
Das K., Giesbrecht B., Eckstein M.P., Predicting variations of perceptual performance across individuals from neural activity using pattern classifiers, Neuroimage, 51(4):1425-37 (2010)
Kasper, R., Das, K., Eckstein, M. P., Giesbrecht, B. (2010). Decoding information processing when attention fails: An electrophysiological approach. In T. Marek, W. Karwowski, & V. Rice (Eds), Advances in Understanding Human Performance: Neuroergonomics, Human Factors, and Special Populations. CRC Press/Taylor & Francis.
Das, K., Li, S., Giesbrecht, B., Kourtzi, Z., Eckstein, M. P. (2010). Predicting perceptual performance from neural activity. In T. Marek, W. Karwowski, & V. Rice (Eds), Advances in Understanding Human Performance: Neuroergonomics, Human Factors, and Special Populations. CRC Press/Taylor & Francis.
Das K., Zhang, S. B. Giesbrecht, M. P. Eckstein, Using Rapid Visually Evoked EEG Activity for Person Identification, in Proc. of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2490-3, (2009)