Neural computations of decision utility

doi:10.1016/j.tics.2004.10.006

Trends in Cognitive Sciences

Volume 8, Issue 12, December 2004, Pages 519-521

https://doi.org/10.1016/j.tics.2004.10.006 Get rights and content

How are decision alternatives represented in the primate brain? A recent study by Sugrue et al. sought to answer this question by integrating behavioral, computational and physiological methods in examining the choice patterns of monkeys placed in a dynamic foraging environment. They observed specific encoding of the relative value of alternatives by neurons in the parietal cortex, providing an important starting point for researchers interested in how value and probability are combined in the brain to arrive at decision outcomes.

Section snippets

Traditional models of decision-making

We think of a decision ‘occurring’ when a person (or any organism) has an unfulfilled need and takes an action to achieve the goal of satisfying that need. A good decision is one that chooses the best available course of action in the face of uncertainty about what consequences will occur after the action is taken. For many years, psychologists and economists (and before them philosophers and mathematicians) have attempted to model decision-making processes theoretically. The focus of

Representation of utility in the brain

The recent study by Sugrue et al. [1] makes a substantial contribution to this burgeoning field. Their method placed two rhesus monkeys in an experimental setting akin to a natural environment, requiring the animals to ‘forage’ through this environment to seek out rewards (drops of juice). The monkeys were presented with two possible colored targets, red or green; on each trial, they were free to choose either of these targets. The choice was made via an eye saccade to the favored target. The

Deciding where to go now

Other researchers are also now seeking to examine this type of choice behavior in animals [12], and there has in recent years been a vast increase in the number of functional neuroimaging studies concerned with understanding the brain basis of decision-making in humans, examining people in a wide variety of decision-making contexts – as they make decisions about which gambles to choose [13], as they play economic games 14, 15, 16, and even as they choose which member of the opposite sex they

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Decision making
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A chance to learn: On matching probabilities to optimize utilities
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All choices under uncertainty can be modeled as attempts to maximize expected utility. Yet many studies show that human choices do not maximize expected economic utility. Here we investigate one such behavior, known as “probability matching”, and demonstrate that it maximizes an ecologic utility that goes beyond economic utility. To start we present data from a psychological experiment on a game of chance discovery called “Iowa Gambling”. We then derive a mathematical model of game-playing behavior that optimizes ecologic utility, which includes informatic utility in learning and ergonomic utility in effort – as well as economic utility in earning. The model offers a good fit to the data, which supports our claim that human choices are made to optimize a combination of utilities that go beyond just economic utility. To close, we explore applications of probability matching to real-world situations of chance discovery such as web surfing and war fighting.
Impaired error monitoring contributes to face recognition deficit in schizophrenia patients
2006, Schizophrenia Research
It has been proposed that social and cognitive deficits in schizophrenia may result from impaired error monitoring.
We tested the hypothesis that among schizophrenia patients, impaired error monitoring contributes to poor face recognition, an important social skill.
79 schizophrenia patients and 57 healthy individuals were administered a computerized face recognition test which allowed collection of accuracy and latency performance parameters. Error monitoring was assessed by analyzing reaction times for correct (RTC) and incorrect (RTI) responses. Tests of working memory (WM) and processing speed were also administered.
RTI was longer than RTC in patients and controls and did not differ between the groups. RTC was significantly longer in patients than controls. Error monitoring effort, calculated by dividing the difference between RTI and RTC by the sum of RTC and RTI, was significantly smaller in patients than controls. A regression model with face recognition performance as dependent variable showed independent contributions of error monitoring effort, spatial working memory and group (patient/healthy) to test performance and explained 26.1% of the variance.
Error monitoring function influences face recognition accuracy and is impaired in schizophrenia. Impairments in error monitoring, and spatial WM contribute to face recognition deficits in schizophrenia.
Switching costs in stochastic environments drive the emergence of matching behaviour in animal decision-making through the promotion of reward learning strategies
2021, Scientific Reports
Competency ‘Agent’ in Decision Making
2018, SSRN
Competency ‘Agent’ in Decision Making
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Neuroeconomics: Foundational Issues and Consumer Relevance
2018, Handbook of Consumer Psychology

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Trends in Cognitive Sciences

Research FocusNeural computations of decision utility

Section snippets

Traditional models of decision-making

Representation of utility in the brain

Deciding where to go now

Trends Cogn. Sci.

Neuron

Neuroimage

Neuron

Neuron

Organ. Behav. Hum. Dec. Proc.

Cogn. Psychol.

Matching behavior and the representation of value in the parietal cortex

Science

Decision making

Risk-sensitive foraging: decision making in variable environments

Decisions, Uncertainty, and the Brain: The Science of Neuroeconomics

Neural basis of deciding, choosing and acting

Nat. Rev. Neurosci.

Research Focus
Neural computations of decision utility