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Edited by Terrence J. Sejnowski, Salk Institute for Biological Studies, La Jolla, CA, and approved November 14, 2016 (received for review March 30, 2016)
Article Figures & SI
Figures
- Fig. 1.
Neurophysiological analysis. (A) Grand average ERP at Fz (n = 19) time-locked to cursor movement, divided into eight groups depending on angular deviance. (B) Peak amplitudes around 180 ms for the ERP in A, and mean classifier output for cursor movements sorted by angular deviance with selected significant differences indicated (***P < 0.001, **P < 0.01, *P < 0.05). (C) Grand average ERP (n = 19) projected through the sources focused on in the third time window (150–200 ms; indicated in gray). (D) Scalp map of difference-between-classes activity that contributed to classification in the third time window. (E) Source localization for the third time window.
- Fig. 2.
Cursor behavior and user model generation. (A) Sample online cursor movements. Also indicated: selected movement directions, their relative angular deviance, and class membership (calibration phase). Movements with an angular deviance >0°, <135° (e.g., gray arrows) were not in the training set. (B) User model evolution during the movements in A based on movement classifications. Ground truth is taken from button presses. (C) The mean final user model representing the directional probabilities/preferences upon reaching the target, grouped by absolute target position.
- Fig. 3.
Performance measure distributions for nonsupported, online, and perfectly reinforced cursor movements on the two online grid sizes. (A) Performance on the 4 × 4 grids. (B) Performance on the 6 × 6 grids. All differences between the three conditions are significant (P < 0.025). Whiskers cover ±2.7σ.
Related Data
Data supplements
Supporting Information
- Download Supporting Information (PDF)
- Download Appendix (PDF)
- Download Movie_S01 (MP4) - Event-related potential at electrode Fz, and class-correlated scalp activity derived from the LDA filter weights of sequential 50-ms time windows, spanning the 400 ms used for classification.
- Download Movie_S02 (MP4) - Dipole densities weighted by relevance for classification in sequential 50-ms time windows, spanning the 400 ms used for classification.
- Download Movie_S03 (MP4) - Online experimental stimuli accompanied by classification output, illustrating the online process and outcome.
- Download Movie_S04 (MP4) - Offline experimental stimuli.
Related Data
Toward neuroadaptive technology
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- Physical Sciences
- Computer Sciences
- Biological Sciences
- Neuroscience
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