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Paul Sajda
Researcher at Columbia University
Publications - 261
Citations - 9050
Paul Sajda is an academic researcher from Columbia University. The author has contributed to research in topics: Electroencephalography & EEG-fMRI. The author has an hindex of 45, co-authored 243 publications receiving 8015 citations. Previous affiliations of Paul Sajda include United States Army Research Laboratory & Sarnoff Corporation.
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Journal ArticleDOI
Spatiotemporal Properties of Intracellular Calcium Signaling in Osteocytic and Osteoblastic Cell Networks under Fluid Flow
TL;DR: The findings show that the unsupervised ICA-based technique results in more sensitive and quantitative signal extraction than traditional ROI analysis, with the potential to be widely employed in Ca(2+) signaling extraction in the cell networks.
Proceedings ArticleDOI
Electrooculogram based system for computer control using a multiple feature classification model.
Armen R. Kherlopian,Joseph P. Gerrein,Minerva Yue,Kristina E. Kim,Ji Won Kim,Madhav Sukumaran,Paul Sajda +6 more
TL;DR: The Telepathix system was designed to accept eye movement commands denoted by looking to the left, looks to the right, and looking straight ahead to navigate a virtual keyboard, and a typing speed of 6 letters per minute was achieved.
Journal ArticleDOI
Neurally and ocularly informed graph-based models for searching 3D environments
TL;DR: It is shown that neural and ocular signals reflecting subjective assessment of objects in a 3D environment can be used to inform a graph-based learning model of that environment, resulting in an hBCI system that improves navigation and information delivery specific to the user's interests.
Journal ArticleDOI
Prestimulus EEG alpha oscillations modulate task-related fMRI BOLD responses to auditory stimuli
Jennifer M. Walz,Robin I. Goldman,Michael Carapezza,Jordan Muraskin,Truman R. Brown,Paul Sajda +5 more
TL;DR: The phase analysis revealed correlates in the bilateral thalamus, providing support for a thalamo-cortical loop in attentional modulations and suggesting that the cortical alpha rhythm acts as a cyclic modulator of task-related responses very early in the processing stream.
Proceedings ArticleDOI
Unsupervised adaptive transfer learning for Steady-State Visual Evoked Potential brain-computer interfaces
TL;DR: This work's novel Adaptive-C3A method incorporates an unsupervised adaptation algorithm that requires no calibration data and provides robust class separation in feature space leading to increased classification accuracy in SSVEP detection.