Oregon Decision Neuroscience Symposium

We are delighted to announce the inaugural Oregon Decision Neuroscience Symposium!

Accommodations:

There is no official hotel accommodations for our out-of-town attendees.

Hotels near UO campus:

University Inn & Suites Eugene

Best Western Greentree Inn

Days Inn by Wyndham, Eugene Downtown

Travelers Inn Motel

Red Lion Inn & Suites, Eugene 

 

Airbnb Eugene is also a great option for accommodation

 

Speakers include:

Brian Knutson (Stanford)

Neuroforecasting aggregate choice

Advances in brain-imaging design and analysis have allowed investigators to use neural activity to predict individual choice, while emerging Internet markets have opened up new opportunities for forecasting aggregate choice. I will review emerging research that bridges these levels of analysis by attempting to use group neural activity to forecast aggregate choice. A survey of some initial findings suggests that components of group neural activity might forecast aggregate choice, in some cases even beyond traditional behavioral measures. In addition to demonstrating the plausibility of neuroforecasting, these findings raise the possibility that not all neural processes that predict individual choice forecast aggregate choice to the same degree. We propose that although integrative choice components may confer more consistency within individuals, affective choice components may generalize more broadly across individuals to forecast aggregate choice.

Cendri Hutcherson (Toronto)

Neural and computational dynamics of self-regulation during decision making

Recent work on the computational bases of decision making behaviour suggests that choices emerge out of a dynamic process of value sampling and evidence accumulation. Here, I consider the implications of this architecture for understanding how people self-regulate their choices, and when and why they might fail. Aspects of this work imply important caveats to current discussions about the role of automaticity and control in self-regulation, while other aspects of this work support important ideas in “dual process” models of self-control. I will showcase recent research from my lab highlighting both the challenges inherent to studying these kinds of problems, as well as potential behavioral, neural, and computational approaches to solving them.

Ming Hsu (Berkeley)

Winning hearts and minds: cognitive neuroscience of consumer behavior

The past decade has seen substantial progress in our understanding of the neural basis of economic decision-making. Major gaps remain, however, in applying current neuroeconomic frameworks to understand decision-making in the real world.  In particular, while everyday decision-making in the real world seldom happens without input from semantic memory, which provides the decision-maker (DM) with access to the world knowledge she has acquired, laboratory studies of decision-making to date have largely focused on valuation and have (often explicitly) limited contributions by semantic memory.  We fill this gap by developing a computational approach that conceptualizes MB-C as the product of the interaction between processes involving memory (e.g., retrieval of eligible items from memory) and preference (e.g. valuation of the successfully retrieved items). Our findings reveal an important cognitive mechanism through which semantic memory influences and constrains value-based decision-making.

Amitai Shenhav (Brown)

The costs and benefits of engaging in cost-benefit decisions

Research on value-based decision-making has uncovered a consistent set of behavioral and neural signatures of those decisions and their putative inputs. These findings implicate regions of prefrontal cortex and striatum in the evaluation of choice options and comparison thereof, and demonstrate how choice dynamics can be accounted for by prominent accumulation-to-bound models. However, this research often overlooks key cognitive and affective properties of these decisions that bear on the interpretation of previous findings. I will describe a series of studies that examine questions about these underexplored properties, including (a) the extent to which reward-based decisions are centered on reward-centered versus goal-centered subjective values; (b) the extent to which neural correlates of choice value reflect decision-related processes versus more basic affective appraisal of one’s choice set; and (c) what mechanisms determine our perceptions of the costs of decision-making. Collectively, the findings of these studies force a reinterpretation of common assumptions regarding value-based decision-making and its neural underpinnings.

John Clithero (Oregon)

Applications of Multi-Attribute Sequential Sampling Models in Simple Choice

 A popular model of choice and process from psychology and neuroscience, the Drift-Diffusion Model (DDM), is first introduced in a multi-attribute framework. I will then present results from collaborations applying the multi-attribute DDM to consumer behavior and moral decision making. First, I will present a project containing three laboratory experiments involving everyday consumer purchases. I will show how the multi-attribute DDM can improve forecasts on several canoncial measures of consumer choice behavior. A second paper uses a task that asks participants to inflict electrical shocks to oneself and an anonymous other for money. The latent cognitive parameters of the multi-attribute DDM are leveraged to provide an explanation for how individuals make trade-offs between pain and gains for themselves and for others.

Anita Cservenka (Oregon State)

Heavy marijuana use and risky decision-making in young adult college students

Marijuana (MJ) is the most widely used illicit substance worldwide, and its use is especially prevalent among adolescents and young adults. Previous research suggests frequent MJ use is associated with impairments in cognitive flexibility and inhibition, both of which play important roles in decision-making. However, the effects of MJ use on decision-making performance are mixed and only few studies have examined frequent MJ use and risky decision-making in young adults. Given the protracted development of the prefrontal cortex, the young adult brain may be especially sensitive to the neurotoxic effects of MJ, which could impair decision-making. The current study examined the influence of heavy MJ use on risky decision-making in college students, 18-22 years old. Findings suggest MJ users may be more sensitive to rewards (i.e. pleasure associated with MJ use) and less sensitive to losses (i.e. consequences of heavy MJ use), which perpetuate the maintenance of MJ use.