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Reliability and Interpretability of High-Density EEG-Based Source Imaging-Enabling Tools for a Cognitive Neuroscience of the Individual
Dr. Akaysha Tang
Tuesday, October 08, 2013, 01:00pm - 02:00pm
University of New Mexico, Departments of Psychology and Neurosciences
A great deal can be learned from patterns of brain activity if one can obtain measures of such activity reliably across time and across individual and if the measures are interpretable in relation to the behavioral and mental states and in terms of known neural mechanisms. In this talk, I will present empirical evidence to demonstrate novel capabilities attainable by applying Second Order Blind Identification (SOBI, Belouchrani & Cardoso, 1993, 1997) to individual (as opposed to group) high density EEG data. I will show that (1) SOBI can provide description of brain activity in terms of signals from specific functional brain regions, instead of mixtures of signals measured at the electrodes locations on the scalp (reduced ambiguity in signal interpretation and increased S/N and reliability); (2) SOBI can arrive at such a description simultaneously for multiple brain regions as well as noisy sources, such as ocular artifacts (no need to throw away large quantity of data); (3) SOBI can achieve such a description without requiring the participant to maintain fixation and eliminate eye movement (source separation under the condition of free eye movement); (4) SOBI can achieve such a description without requiring the participant to engage in a task (source separation from EEG obtained during sleep or coma); (5) SOBI eliminate the need for several major subjective decisions in conventional source localization (increase reproducibility in data analysis); (6) SOBI is deterministic and efficient (increase feasibility in usage); (7) SOBI does not require the use of group data (single-subject and single-trial analysis). Together, these new capabilities may open the door to a new kind of cognitive neuroscience, where it is possible to measure brain activity patterns of an individual and predict behavioral outcomes of an individual.
Akaysha C. Tang, Matthew T. Sutherland, and Christopher J. McKinney (2005). Validation of SOBI components from high-density EEG. NeuroImage, 25(2): 539-553.
Akaysha C. Tang, Matthew T. Sutherland, and Yan Wang (2006). Contrasting Single-Trial ERPs between Experimental Manipulations: Improving Differentiability by Blind Source Separation. NeuroImage, 29(1): 335-346.
Akaysha C. Tang, Jing-Yu Liu, and Matthew T. Sutherland (2005). Recovery of Correlated Neuronal Sources from EEG: The Good and Bad Ways of using SOBI. NeuroImage, 28(2): 507-519.
Matthew T. Sutherland and Akaysha C. Tang (2006). Reliable detection of bilateral activation in human primary somatosensory cortex by unilteral median nerve stimulation. NeuroImage, 33(4): 1042-1054.
Akaysha C. Tang, Matthew T. Sutherland, Christopher J. McKinney, Jing-Yu Liu, Yan Wang, Lucas C. Parra, Adam D. Gerson, and Paul Sajda (2006). Classifying single-trial ERPs from visual and frontal cortex during free viewing. In: IEEE Proceedings of the 2006 International Joint Conference on Neural Networks (IJCNN 2006), July 16-21, 2006; Vancouver, BC, Canada; pp. 1376-1383.
Matthew T. Sutherland and Akaysha C. Tang. (2006). Blind Source Separation can Recover Systematically Distributed Neuronal Sources from "Resting" EEG. In: EURASIP Proceedings of the Second International Symposium on Communications, Control, and Signal Processing (ISCCP 2006). March 13-15, Marrakech, Morocco; http://www.eurasip.org/content/Eusipco/isccsp06/defevent/papers/cr1307.pdf.
Akaysha C. Tang, Matthew T. Sutherland, Peng Sun, Yang Zhen, Masato Nakazawa, Amy M. Korzekwa, ZhangYan, and Mingzhou Ding (2007). Top-down versus bottom-up processing in the human brain: Distinct directional influences revealed by integrating SOBI and Granger causality. Proceedings of the 7th International Conference on Independent Component Analysis and Signal Separation (ICA 2007), London, UK.
Akaysha C. Tang, Matthew T. Sutherland, and Zhen Yang (2010). Capturing “Trial-to-Trial” Variations in Human Brain Activity: from Laboratory to Real World. In Functional Significance of Neuronal Variability, Ed. Ming-Zhou Ding and Dennis Glanzman. Oxford University Press.
Akaysha C. Tang, Barak A. Pearlmutter, Natalie A. Malaszenko, and Dan B. Phung (2002). Independent Components of Magnetoencephalography: Single-trial Response Onset Time Estimation. NeuroImage, 17(4): 1773-1789.
Akaysha C. Tang, Barak A. Pearlmutter, Natalie A. Malaszenko, Dan B. Phung and Bethany C. Reeb (2002). Independent Components of Magnetoencephalography: Localization. Neural Computation, 14(8): 1827-1858.