We are using rats to investigate the neural mechanisms underlying the flexible, top-down selection of which features of a stimulus are used to drive decisions. For example, if standing on a busy street and you want to flag a taxi, the color of the cars might be the most important feature driving your actions; but if you intend to cross the road, the most important feature might be the motion of the cars. Two broad classes of models are prominent in the literature. In one, top-down signals selectively control, or “gate”, the feedforward pathway from posterior sensory regions to anterior decision-making regions. The gate lets through only information about the selected feature. In the other class of models, no feedforward gating occurs; feature selection is instead instantiated by selectively controlling the nature of recurrent dynamics within frontal regions. Seeking to distinguish between the two types of models, we trained rats to perform a flexible feature-selection task where information is presented in randomly timed pulses. We developed analyses that use neural responses to such pulses to distinguish between the two main models. Instead of evidence clearly favoring one or the other model, we found that different individuals lay along a continuous spectrum between the two models. The behavioral analysis confirmed the neurally suggested position on that spectrum for each individual. Our results underscore the importance of recognizing and identifying individual variability in neural mechanisms. The common practice of reporting only findings that are consistent across animals may discard genuine, informative biological variability. This problem may be particularly acute for cognitive processes, where widely differing internal algorithms may produce indistinguishable behavioral responses. 

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Those who wish to meet the speaker should contact Ken Wengler (Horga Lab). 

The Columbia Neuroscience Seminar series is a collaborative effort of Columbia's Zuckerman Institute, the Department of Neuroscience, the Doctoral Program in Neurobiology and Behavior and the Columbia Translational Neuroscience Initiative, and with support from the Kavli Institute for Brain Science.