Noise in mental exploration for learning

Summary

Principal Investigator: Joshua Gold, Neuroscience @Penn
Title: The role of noise in mental exploration for learning
BRAIN Category: Individuality and Variation

In our unpredictable world, decision-makers face an inherent trade-off: higher certainty leads to more precise and accurate choices when the world is stable but an inability to adjust to change, whereas less certainty can lead to greater adaptability but also more variable and imprecise decisions. The investigators propose that this trade-off is regulated by interactions between arousal and cortical systems.

Principal Investigator: Joshua Gold, Neuroscience @Penn
Title:  The role of noise in mental exploration for learning
BRAIN Category: Individuality and Variation

In our unpredictable world, decision-makers face an inherent trade-off: higher certainty leads to more precise and accurate choices when the world is stable but an inability to adjust to change, whereas less certainty can lead to greater adaptability but also more variable and imprecise decisions. The investigators propose that this trade-off is regulated by interactions between arousal and cortical systems.

Figure 3 from Law and Gold, 2009, depicting reinforcement-driven changes in weights between sensory and decision neurons.

Figure 3 from Law and Gold, 2009, depicting reinforcement-driven changes in weights between sensory and decision neurons.

Abstract

What makes people behave so differently from one another? Consider how we make decisions. Some people are quick and decisive but overly rigid, unable to adapt effectively to new opportunities or threats. In contrast, others may be more deliberative and less confident, making their decisions less predictable but more adaptable to changing circumstances. With funding from the National Science Foundation, Drs. Joshua Gold and Joseph Kable of the University of Pennsylvania are investigating a new theory that in the real world, there is a fundamental tradeoff between these two extremes. The theory includes a novel proposal that what has previously been dismissed by researchers as random variability in human behavior might instead reflect uncertain, adaptable decision-making linked with norepinephrine, a neurochemical implicated in learning and arousal. Does this characteristic explain other aspects of human personality and behavior? Can norepinephrine levels in the brain be manipulated to affect complex learning and decision-making behaviors? In answering these questions, this work will establish foundational, basic knowledge that, in the long term, will help to guide the development of new tools to diagnose and counteract conditions associated with abnormal learning and decision-making, including attention deficit hyperactivity disorder (ADHD), anxiety, depression, and schizophrenia. This knowledge about individual differences in learning will also inform how to best tailor educational and learning practices, as well as how to design computer programs that learn adaptively from experience. Other benefits of this work are resources that will assist research and education in cognitive and neural systems, including publically available datasets, computer code and machine learning algorithms; increased participation of underrepresented groups in this kind of integrative research, via summer research experiences for high school and undergraduate students; and an increased public awareness of neuroscience via public lectures, Brain Awareness Week activities, and contributions to a website that explains brain research in laymen’s terms.
The work is based on a novel hypothesis about brain mechanisms that are responsible for certain idiosyncratic learning and decision processes. Specifically, in our unpredictable world, decision-makers face an inherent trade-off: higher certainty leads to more precise and accurate choices when the world is stable but an inability to adjust to change, whereas less certainty can lead to greater adaptability but also more variable and imprecise decisions. The investigators propose that this trade-off is regulated by interactions between arousal and cortical systems. To test this hypothesis, they use an interdisciplinary and integrative set of approaches with three primary objectives: 1) develop a theoretical framework describing inherent trade-offs between output stability and learning in hierarchical, probabilistic inference processes in unpredictable environments; 2) identify behavioral, physiological, and neural correlates of variability in how individuals navigate these trade-offs while making choices in unpredictable environments; and 3) identify causal influences of the brainstem nucleus locus coeruleus, a key component of the arousal system, on the variability in adaptive inference. The work forges meaningful connections across theory and experiment, spanning multiple spatial and temporal scales and levels of abstraction, to identify computational and physiological underpinnings of individual differences in learning.

 

 

 

NSF Project Information

NSF webpage:  nsf.gov/awardsearch/showAward?AWD_ID=1533623&HistoricalAwards=false

NSF Org: BCS    Division Of Behavioral and Cognitive Sci

Start Date:  August 15, 2015      End Date: July 31, 2018(Estimated)

Award Number: #1533623

Awarded Amount to Date: $1,019,916.00

Investigator(s): Joshua Gold jigold@mail.med.upenn.edu (Principal Investigator)
Joseph Kable (Co-Principal Investigator)

NSF Program(s): BIOMEDICAL ENGINEERING, IntgStrat Undst Neurl&Cogn Sys

Program Reference Code(s): 8089, 8091, 8551

Sponsor: University of Pennsylvania
Research Services
Philadelphia, PA 19104-6205 (215)898-7293

 

Skip to toolbar