Computational Intelligence and Neuroscience / 2013 / Article / Fig 3

Research Article

A Functional Model of Sensemaking in a Neurocognitive Architecture

Figure 3

Sample output from Task 1. Participants must generate the likelihood that a probe event (denoted by the “?”) was produced by each category and then perform a forced-choice resource allocation to maximize their trial score. Likelihoods are based on the distance from each category’s centroid and the frequency of events. For instance, Aqua has a higher likelihood because its centroid is closer to the probe and it has a higher frequency (i.e., more events) than Bromine.

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