John Thomas Wilkinson

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Short- and long-latency somatosensory evoked potentials (SEPs) were elicited by stimulation of the median nerve in 43 patients with neurological disorders. Abnormalities of short-latency peaks, P9, N13, and P14, were seen in patients with lesions of the peripheral nerve, cervical spinal cord, and brain stem, respectively. Subsequent component, N18, was(More)
A blink reflex consists of an early unilateral component, R1, and a late bilateral component, R2. During an acute phase of hemispheric cerebrovascular accident, R1 and R2 were abnormal in 30 and 50 of 66 patients, respectively. Paired stimuli usually corrected R1 but not R2, which was profoundly suppressed. The discrepancy between polysynaptic R2 and(More)
We address the problem of information fusion in uncertain environments. Imagine there are multiple experts building probabilistic models of the same situation and we wish to aggregate the information they provide. There are several problems we may run into by naively merging the information from each. For example, the experts may disagree on the probability(More)
When decisions need to be made in government, the intelligence community (IC) is tasked with analyzing the situation. This analysis is based on a huge amount of information and usually under severe time constraints. As such, it is particularly vulnerable to attacks from insiders with malicious intent. A malicious insider may alter, fabricate, or hide(More)
We are working on the problem of modeling an analyst's intent in order to improve collaboration among intelligence analysts. Our approach is to infer the analyst's goals, commitment, and actions to improve the effectiveness of collaboration. This is a crucial problem to ensure successful collaboration because analyst intent provides a deeper understanding(More)
A user’s cognitive style has been found to affect how they search for information, how they analyze the information, and how they make decisions in an analytical process. In this paper, we propose an approach that uses Hidden Markov Models (HMM) to dynamically capture a user’s cognitive style by automatically exploring the sequence of actions(More)