Stephen M. Gordon

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OF TALK Engineers have long used control systems utilizing models and feedback loops to control real-world systems. Limitations of modelbased control led to a generation of intelligent control techniques such as adaptive and fuzzy control. Human brain, on the other hand, is known to process a variety of inputs in parallel, ignore distractions to focus on(More)
Objective: Brain-Computer Interface (BCI) technologies enable direct communication between humans and computers by analyzing brain measurements, such as electroencephalography (EEG). BCI processing typically consists of heuristically extracting features for specific tasks, limiting the generalizability of the BCI across tasks. Here, we asked whether we can(More)
Detecting significant periods of phase synchronization in EEG recordings is a non-trivial task that is made especially difficult when considering the effects of volume conduction and common sources. In addition, EEG signals are often confounded by non-neural signals, such as artifacts arising from muscle activity or external electrical devices. A variety of(More)
This paper introduces a new approach to develop robots that can learn general affordance relations from their experiences. Our approach is a part of larger efforts to develop a cognitive robot and has two components: (a) the robot models affordances as statistical relations among actions, object properties and the effects of actions on objects, in the(More)
As robotic systems encompass larger numbers of individual robotic agents, interface design must provide better visual representations that account for factors affecting the human operator’s situational awareness. This work investigates three robotic team visualizations via an evaluation with sixteen participants who either had used robots or had no(More)
Decades of heavy investment in laboratory-based brain imaging and neuroscience have led to foundational insights into how humans sense, perceive, and interact with the external world. However, it is argued that fundamental differences between laboratory-based and naturalistic human behavior may exist. Thus, it remains unclear how well the current knowledge(More)
BACKGROUND Blind source separation techniques have become the de facto standard for decomposing electroencephalographic (EEG) data. These methods are poorly suited for incorporating prior information into the decomposition process. While alternative techniques to this problem, such as the use of constrained optimization techniques, have been proposed, these(More)
Future technologies such as Brain-Computer Interaction Technologies (BCIT) or affective Brain Computer Interfaces (aBCI) will need to function in an environment with higher noise and complexity than seen in traditional laboratory settings, and while individuals perform concurrent tasks. In this paper, we describe preliminary results from an experiment in a(More)