Abstract: A flat optogenetic cuff interface (FOCI) is configured for functional optical stimulation of axons in a single fascicle of a peripheral nerve bundle in which the axons have been genetically modified to express light sensitive proteins for excitation or inhibition of the nerves. The FOCI is configured to gradually reshape the single fascicle to a final height between 0.2 mm and 0.5 mm by reorganizing the individual axons within the fascicle without reshaping (and damaging) the individual axons. The FOCI facilitates stimulation of axons over the entire cross-section of the reshaped fascicle within the power limitations for pulsed laser energy. An electrical interface may be included to sense nerve activity of either the stimulated axons to provide closed-loop feedback to control the optical sources or stimulated axons of a different modality to record the response.

Abstract: A flat optogenetic cuff interface (FOCI) is configured for functional optical stimulation of axons in a single fascicle of a peripheral nerve bundle in which the axons have been genetically modified to express light sensitive proteins for excitation or inhibition of the nerves. The FOCI is configured to gradually reshape the single fascicle to a final height between 0.2 mm and 0.5 mm by reorganizing the individual axons within the fascicle without reshaping (and damaging) the individual axons. The FOCI facilitates stimulation of axons over the entire cross-section of the reshaped fascicle within the power limitations for pulsed laser energy. An electrical interface may be included to sense nerve activity of either the stimulated axons to provide closed-loop feedback to control the optical sources or stimulated axons of a different modality to record the response.

Abstract: EEG-based acceleration of second language learning is accomplished by measuring via single-trial EEG a learner's cognitive response to the presentation (visual or auditory) of language learning materials and updating a user model of latent traits related to language-learning skills in accordance with the cognitive response. The user model is suitably updated with each trial, each trial being triggered by learner fixation on a portion of visual materials and/or a next phoneme in auditory materials. Additional discrimination may be achieved through the use of saccades or fixation duration features.

Abstract: EEG-based acceleration of second language learning is accomplished by measuring via single-trial EEG a learner's cognitive response to the presentation (visual or auditory) of language learning materials and updating a user model of latent traits related to language-learning skills in accordance with the cognitive response. The user model is suitably updated with each trial, each trial being triggered by learner fixation on a portion of visual materials and/or a next phoneme in auditory materials. Additional discrimination may be achieved through the use of saccades or fixation duration features.

Abstract: Neurophysiological responses such as EEG signals of brainwave activity, dilation signals of pupillary response, dwell time signals of eye movement and imaging signals of vascular response are monitored as a correlate of the operator's cognitive response. These responses are processed to determine if there is a significant cognitive response to a stimulus (visual or non-visual) to generate a positive cue. The operator's eye movement is monitored to determine when the operator fixates on the stimulus and the position of the stimulus in the operator's field-of view (FOV). The positive cue and position of the stimulus, and typically the time-stamp of the cue are output triggering a system response. The temporal sequence of cues and stimulus position may be processed to reinforce or reject the cue or refine the stimulus position.

Abstract: Bayesian super-resolution techniques fuse multiple low resolution images (possibly from multiple bands) to infer a higher resolution image. The super-resolution and fusion concepts are portable to a wide variety of sensors and environmental models. The procedure is model-based inference of super-resolved information. In this approach, both the point spread function of the sub-sampling process and the multi-frame registration parameters are optimized simultaneously in order to infer an optimal estimate of the super-resolved imagery. The procedure involves a significant number of improvements, among them, more accurate likelihood estimates and a more accurate, efficient, and stable optimization procedure.