Every waking moment, we make decisions, from where to move our eyes to what to eat for dinner. The ease and speed with which we do this belie the complexity of the underlying neuronal processing. In the visual system, every scene is processed via a complicated network of neurons that extends from the retina through multiple areas in the visual cortex. Each decision requires rapid coordination of signals from the relevant neurons. Deficits in this integration are likely causes of debilitating learning disorders, yet we know little about the processes involved. Previous studies of the macaque visual cortex indicate that as monkeys learn a new task the parts of the brain involved in decision making select which neurons they “listen to”: the most informative neurons become more strongly associated with the animal’s decisions as it learns. However, this process has only been studied over the course of several months as monkeys gradually learn a complex task. We set out to probe the dynamics of this relationship on a shorter timescale. We studied the middle temporal area (MT) of the visual cortex, where neurons are selective for binocular disparity (a depth cue) and motion direction; they have also been shown to contribute to perceptual decisions during motion- and depth-based tasks. After training monkeys on motion and depth detection tasks, we degraded the sensitivity of MT neurons for depth more than motion by reversibly inactivating two major inputs to MT—visual areas V2 and V3—by cooling. We hypothesized that degrading depth information more than motion would lead to bigger changes in the extent to which MT neurons contributed to decisions during the depth task than the motion task. We monitored this contribution to decisions, as measured by detect probability (DP), prior to and during daily inactivation sessions. We found that neuronal DP decreased during the depth task, indicating that neurons became less involved in these decisions. DP did not change during the motion task, suggesting that these changes can be specific to one feature. Our results revealed a level of fast, selective flexibility in the decision circuitry.
| Identifer | oai:union.ndltd.org:harvard.edu/oai:dash.harvard.edu:1/9795731 |
| Date | 06 October 2014 |
| Creators | Smolyanskaya, Alexandra |
| Contributors | Born, Richard Todd |
| Publisher | Harvard University |
| Source Sets | Harvard University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Rights | open |
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