Neural basis of value based decision making
- Daniel L. Kimmel.
- June 2013.
- Physical description
- online resource (xi, 178 pages) : illustrations (some color)
- Kimmel, Daniel L.
- McClelland, James L. thesis advisor.
- McClure, Samuel M. thesis advisor.
- Moore, Tirin, 1969- thesis advisor.
- Newsome, William T. thesis advisor (primary).
- Stanford University. Neurosciences Program.
- Stanford University. Committee on Graduate Studies. degree grantor.
- Includes bibliographical references (p. 171-178).
- For many decisions, we must explicitly compare the value of two or more goods being offered. However, often decisions are not between multiple goods, but rather between a single offer and the choice to pass on that offer, such as when deciding to buy a new car, marry a significant other, or read this abstract! For these decisions the relevant comparison is between the expected benefit of the offer and its associated cost. We studied cost-benefit decisions in the macaque monkey while recording from single neurons in the orbitofrontal cortex (OFC), which has been implicated previously in decisions between competing goods. We found that the animal was sensitive to the balance of cost and benefit. That is, his willingness to accept an offer increased monotonically as we increased the benefit while keeping the cost constant. We found that the OFC represented task-relevant information--such as benefit, choice, and expected outcome--in a complex manner. These signals were mixed at the level of single neurons, but by examining the population response, we found separable ensembles of neurons that represented each of these task relevant variables. Moreover, different sets of neurons appeared to represent these signals for discrete temporal epochs within and between trials, which may correspond to distinct functional processes revealed by behavior. Taken together, we offer a novel view of how a population of neurons may collectively represent value and choice information and how that population may transform the representation dynamically over time.
- Publication date
- Submitted to the Program in Neurosciences and the Committee on Graduate Studies of Stanford University.
- Thesis (Ph.D.)--Stanford University, 2013.