A neural mechanism for learning from delayed postingestive feedback

被引:0
|
作者
Zimmerman, Christopher A. [1 ]
Bolkan, Scott S. [1 ]
Pan-Vazquez, Alejandro [1 ]
Wu, Bichan [1 ]
Keppler, Emma F. [1 ]
Meares-Garcia, Jordan B. [1 ]
Guthman, Eartha Mae [1 ]
Fetcho, Robert N. [1 ]
McMannon, Brenna [1 ]
Lee, Junuk [1 ]
Hoag, Austin T. [1 ]
Lynch, Laura A. [1 ]
Janarthanan, Sanjeev R. [1 ]
Luna, Juan F. Lopez [1 ]
Bondy, Adrian G. [1 ]
Falkner, Annegret L. [1 ]
Wang, Samuel S. -H. [1 ]
Witten, Ilana B. [1 ,2 ]
机构
[1] Princeton Univ, Princeton Neurosci Inst, Princeton, NJ 08544 USA
[2] Princeton Univ, Howard Hughes Med Inst, Princeton, NJ 08544 USA
基金
美国国家卫生研究院;
关键词
CONDITIONED TASTE-AVERSION; FLAVOR-ILLNESS AVERSIONS; SHORT-TERM; CORTICAL-NEURONS; LONG-TERM; AMYGDALA; MEMORY; PROTEIN; PLASTICITY; DYNAMICS;
D O I
10.1038/s41586-025-08828-z
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Animals learn the value of foods on the basis of their postingestive effects and thereby develop aversions to foods that are toxic(1, 2, 3, 4, 5, 6, 7, 8, 9-10) and preferences to those that are nutritious(11, 12-13). However, it remains unclear how the brain is able to assign credit to flavours experienced during a meal with postingestive feedback signals that can arise after a substantial delay. Here we reveal an unexpected role for the postingestive reactivation of neural flavour representations in this temporal credit-assignment process. To begin, we leverage the fact that mice learn to associate novel(14,15), but not familiar, flavours with delayed gastrointestinal malaise signals to investigate how the brain represents flavours that support aversive postingestive learning. Analyses of brain-wide activation patterns reveal that a network of amygdala regions is unique in being preferentially activated by novel flavours across every stage of learning (consumption, delayed malaise and memory retrieval). By combining high-density recordings in the amygdala with optogenetic stimulation of malaise-coding hindbrain neurons, we show that delayed malaise signals selectively reactivate flavour representations in the amygdala from a recent meal. The degree of malaise-driven reactivation of individual neurons predicts the strengthening of flavour responses upon memory retrieval, which in turn leads to stabilization of the population-level representation of the recently consumed flavour. By contrast, flavour representations in the amygdala degrade in the absence of unexpected postingestive consequences. Thus, we demonstrate that postingestive reactivation and plasticity of neural flavour representations may support learning from delayed feedback.
引用
收藏
页数:38
相关论文
共 50 条
  • [1] Learning from delayed feedback: neural responses in temporal credit assignment
    Walsh, Matthew M.
    Anderson, John R.
    COGNITIVE AFFECTIVE & BEHAVIORAL NEUROSCIENCE, 2011, 11 (02) : 131 - 143
  • [2] Learning from delayed feedback: neural responses in temporal credit assignment
    Matthew M. Walsh
    John R. Anderson
    Cognitive, Affective, & Behavioral Neuroscience, 2011, 11 : 131 - 143
  • [3] LEARNING FROM DELAYED FEEDBACK IN ADOLESCENCE
    Davidow, Juliet Y.
    Foerde, Karin
    Galvan, Adriana
    Shohamy, Daphna
    JOURNAL OF COGNITIVE NEUROSCIENCE, 2013, : 167 - 167
  • [4] Learning with Delayed Feedback
    Pranavan, Theivendiram
    Sim, Terence
    2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), 2021, : 4895 - 4902
  • [5] EFFECTS OF DELAYED INFORMATION FEEDBACK AND FEEDBACK CUES IN LEARNING ON DELAYED RETENTION
    SASSENRA.JM
    YONGE, GD
    JOURNAL OF EDUCATIONAL PSYCHOLOGY, 1969, 60 (03) : 174 - &
  • [6] DELAYED FEEDBACK AS A POSSIBLE MECHANISM IN PARKINSONISM
    DINNERSTEIN, AJ
    FRIGYESI, T
    LOWENTHAL, M
    PERCEPTUAL AND MOTOR SKILLS, 1962, 15 (03) : 667 - 680
  • [7] Learning a Neural Semantic Parser from User Feedback
    Iyer, Srinivasan
    Konstas, Ioannis
    Cheung, Alvin
    Krishnamurthy, Jayant
    Zettlemoyer, Luke
    PROCEEDINGS OF THE 55TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2017), VOL 1, 2017, : 963 - 973
  • [8] Planning and learning in environments with delayed feedback
    Walsh, Thomas J.
    Nouri, Ali
    Li, Lihong
    Littman, Michael L.
    MACHINE LEARNING: ECML 2007, PROCEEDINGS, 2007, 4701 : 442 - +
  • [9] Learning and planning in environments with delayed feedback
    Thomas J. Walsh
    Ali Nouri
    Lihong Li
    Michael L. Littman
    Autonomous Agents and Multi-Agent Systems, 2009, 18 : 83 - 105
  • [10] Learning and planning in environments with delayed feedback
    Walsh, Thomas J.
    Nouri, Ali
    Li, Lihong
    Littman, Michael L.
    AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 2009, 18 (01) : 83 - 105