Prefrontal neurons encode a solution to the credit-assignment problem

Wael F. Asaad, Peter M. Lauro, János A. Perge, Emad N. Eskandar

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

To adapt successfully to our environments, we must use the outcomes of our choices to guide future behavior. Critically, we must be able to correctly assign credit for any particular outcome to the causal features which preceded it. In some cases, the causal features may be immediately evident, whereas in others they may be separated in time or intermingled with irrelevant environmental stimuli, creating a potentially nontrivial credit-assignment problem. We examined the neuronal representation of information relevant for credit assignment in the dorsolateral prefrontal cortex (dlPFC) of two male rhesus macaques performing a task that elicited key aspects of this problem. We found that neurons conveyed the information necessary for credit assignment. Specifically, neuronal activity reflected both the relevant cues and outcomes at the time of feedback and did so in a manner that was stable over time, in contrast to prior reports of representational instability in the dlPFC. Furthermore, these representations were most stable early in learning, when credit assignment was most needed. When the same features were not needed for credit assignment, these neuronal representations were much weaker or absent. These results demonstrate that the activity of dlPFC neurons conforms to the basic requirements of a system that performs credit assignment, and that spiking activity can serve as a stable mechanism that links causes and effects.

Original languageEnglish (US)
Pages (from-to)6995-7007
Number of pages13
JournalJournal of Neuroscience
Volume37
Issue number29
DOIs
StatePublished - Jul 19 2017
Externally publishedYes

Fingerprint

Prefrontal Cortex
Neurons
Macaca mulatta
Cues
Learning

Keywords

  • Credit assignment
  • Learning
  • Monkey
  • Population coding
  • Prefrontal cortex
  • Single neuron

ASJC Scopus subject areas

  • Neuroscience(all)

Cite this

Prefrontal neurons encode a solution to the credit-assignment problem. / Asaad, Wael F.; Lauro, Peter M.; Perge, János A.; Eskandar, Emad N.

In: Journal of Neuroscience, Vol. 37, No. 29, 19.07.2017, p. 6995-7007.

Research output: Contribution to journalArticle

Asaad, Wael F. ; Lauro, Peter M. ; Perge, János A. ; Eskandar, Emad N. / Prefrontal neurons encode a solution to the credit-assignment problem. In: Journal of Neuroscience. 2017 ; Vol. 37, No. 29. pp. 6995-7007.
@article{a19f6f8a6a9c4895bc7567d1bee84c6a,
title = "Prefrontal neurons encode a solution to the credit-assignment problem",
abstract = "To adapt successfully to our environments, we must use the outcomes of our choices to guide future behavior. Critically, we must be able to correctly assign credit for any particular outcome to the causal features which preceded it. In some cases, the causal features may be immediately evident, whereas in others they may be separated in time or intermingled with irrelevant environmental stimuli, creating a potentially nontrivial credit-assignment problem. We examined the neuronal representation of information relevant for credit assignment in the dorsolateral prefrontal cortex (dlPFC) of two male rhesus macaques performing a task that elicited key aspects of this problem. We found that neurons conveyed the information necessary for credit assignment. Specifically, neuronal activity reflected both the relevant cues and outcomes at the time of feedback and did so in a manner that was stable over time, in contrast to prior reports of representational instability in the dlPFC. Furthermore, these representations were most stable early in learning, when credit assignment was most needed. When the same features were not needed for credit assignment, these neuronal representations were much weaker or absent. These results demonstrate that the activity of dlPFC neurons conforms to the basic requirements of a system that performs credit assignment, and that spiking activity can serve as a stable mechanism that links causes and effects.",
keywords = "Credit assignment, Learning, Monkey, Population coding, Prefrontal cortex, Single neuron",
author = "Asaad, {Wael F.} and Lauro, {Peter M.} and Perge, {J{\'a}nos A.} and Eskandar, {Emad N.}",
year = "2017",
month = "7",
day = "19",
doi = "10.1523/JNEUROSCI.3311-16.2017",
language = "English (US)",
volume = "37",
pages = "6995--7007",
journal = "Journal of Neuroscience",
issn = "0270-6474",
publisher = "Society for Neuroscience",
number = "29",

}

TY - JOUR

T1 - Prefrontal neurons encode a solution to the credit-assignment problem

AU - Asaad, Wael F.

AU - Lauro, Peter M.

AU - Perge, János A.

AU - Eskandar, Emad N.

PY - 2017/7/19

Y1 - 2017/7/19

N2 - To adapt successfully to our environments, we must use the outcomes of our choices to guide future behavior. Critically, we must be able to correctly assign credit for any particular outcome to the causal features which preceded it. In some cases, the causal features may be immediately evident, whereas in others they may be separated in time or intermingled with irrelevant environmental stimuli, creating a potentially nontrivial credit-assignment problem. We examined the neuronal representation of information relevant for credit assignment in the dorsolateral prefrontal cortex (dlPFC) of two male rhesus macaques performing a task that elicited key aspects of this problem. We found that neurons conveyed the information necessary for credit assignment. Specifically, neuronal activity reflected both the relevant cues and outcomes at the time of feedback and did so in a manner that was stable over time, in contrast to prior reports of representational instability in the dlPFC. Furthermore, these representations were most stable early in learning, when credit assignment was most needed. When the same features were not needed for credit assignment, these neuronal representations were much weaker or absent. These results demonstrate that the activity of dlPFC neurons conforms to the basic requirements of a system that performs credit assignment, and that spiking activity can serve as a stable mechanism that links causes and effects.

AB - To adapt successfully to our environments, we must use the outcomes of our choices to guide future behavior. Critically, we must be able to correctly assign credit for any particular outcome to the causal features which preceded it. In some cases, the causal features may be immediately evident, whereas in others they may be separated in time or intermingled with irrelevant environmental stimuli, creating a potentially nontrivial credit-assignment problem. We examined the neuronal representation of information relevant for credit assignment in the dorsolateral prefrontal cortex (dlPFC) of two male rhesus macaques performing a task that elicited key aspects of this problem. We found that neurons conveyed the information necessary for credit assignment. Specifically, neuronal activity reflected both the relevant cues and outcomes at the time of feedback and did so in a manner that was stable over time, in contrast to prior reports of representational instability in the dlPFC. Furthermore, these representations were most stable early in learning, when credit assignment was most needed. When the same features were not needed for credit assignment, these neuronal representations were much weaker or absent. These results demonstrate that the activity of dlPFC neurons conforms to the basic requirements of a system that performs credit assignment, and that spiking activity can serve as a stable mechanism that links causes and effects.

KW - Credit assignment

KW - Learning

KW - Monkey

KW - Population coding

KW - Prefrontal cortex

KW - Single neuron

UR - http://www.scopus.com/inward/record.url?scp=85025145304&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85025145304&partnerID=8YFLogxK

U2 - 10.1523/JNEUROSCI.3311-16.2017

DO - 10.1523/JNEUROSCI.3311-16.2017

M3 - Article

C2 - 28634307

AN - SCOPUS:85025145304

VL - 37

SP - 6995

EP - 7007

JO - Journal of Neuroscience

JF - Journal of Neuroscience

SN - 0270-6474

IS - 29

ER -