CRCNS: Neural Basis of Inductive Bias

CRCNS:归纳偏差的神经基础

基本信息

  • 批准号:
    10619184
  • 负责人:
  • 金额:
    $ 43万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-08-12 至 2023-06-30
  • 项目状态:
    已结题

项目摘要

A hallmark of biological intelligence is the ability to learn from a remarkably small set of experiences to select appropriate behaviors in novel contexts. This ability arises from inductive bias, referring to the assumptions used in generalizing prior observations to novel data. In machine learning, inductive bias is essential for efficient learning from a small number of examples as animals frequently do. In neuroscience, inductive bias has been mostly considered as shaped by evolution to produce an innate inductive bias. Although an agent’s inductive bias should be adaptive to changing task demands, how brains develop inductive bias, use it to guide learning, and adapt it to task statistics, remain poorly understood. The overall goal of this project is to study the neural and computational bases of inductive bias adaptation by training non-human primates on a novel learning task, characterizing choice behavior and neuronal activity, and developing computational models of learning in neural networks. Our theoretical framework of neural kernel learning makes precise predictions for behavior and neural activity that will be experimentally tested in the proposed studies. We will characterize behavior in a newly designed “crosstalk” task, which is designed to characterize inductive bias and to drive a subject’s adaptation through well-defined and variable task statistics (Aim 1). In this task, the subject learns through experience to categorize stimuli composed of multiple features. Within a block of trials, certain features are differentially informative of the category. Next, we will record simultaneous spiking activity from neurons in dorsolateral prefrontal cortex and the dorsal striatum during task performance (Aim 2). In parallel, we will develop and refine algorithmic and artificial neural network models of adaptive learning (Aim 3) to generate testable predictions for behavior and neural activity. Results from these studies will impact paradigms used to study the computational and neural bases of learning and generalization in humans and animals.
生物智能的一个标志是能够从非常少的经验中学习

项目成果

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DAEYEOL LEE其他文献

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{{ truncateString('DAEYEOL LEE', 18)}}的其他基金

CRCNS: Neural Basis of Inductive Bias
CRCNS:归纳偏差的神经基础
  • 批准号:
    10916854
  • 财政年份:
    2022
  • 资助金额:
    $ 43万
  • 项目类别:
CRCNS: Neural Basis of Planning
CRCNS:规划的神经基础
  • 批准号:
    10410402
  • 财政年份:
    2019
  • 资助金额:
    $ 43万
  • 项目类别:
Neural Basis of temporal decision making
时间决策的神经基础
  • 批准号:
    9922454
  • 财政年份:
    2019
  • 资助金额:
    $ 43万
  • 项目类别:
CRCNS: Neural Basis of Planning
CRCNS:规划的神经基础
  • 批准号:
    9762221
  • 财政年份:
    2018
  • 资助金额:
    $ 43万
  • 项目类别:
Neural basis of temporal decision making
时间决策的神经基础
  • 批准号:
    9194428
  • 财政年份:
    2015
  • 资助金额:
    $ 43万
  • 项目类别:
Neural basis of temporal decision making
时间决策的神经基础
  • 批准号:
    9007934
  • 财政年份:
    2015
  • 资助金额:
    $ 43万
  • 项目类别:
Learning and Selection in the Basal Ganglia
基底神经节的学习和选择
  • 批准号:
    8753644
  • 财政年份:
    2014
  • 资助金额:
    $ 43万
  • 项目类别:
Decision Making and Orbitofrontal Cortex
决策和眶额皮质
  • 批准号:
    8261937
  • 财政年份:
    2010
  • 资助金额:
    $ 43万
  • 项目类别:
Decision Making and Orbitofrontal Cortex
决策和眶额皮质
  • 批准号:
    8459507
  • 财政年份:
    2010
  • 资助金额:
    $ 43万
  • 项目类别:
Decision Making and Orbitofrontal Cortex
决策和眶额皮质
  • 批准号:
    8043667
  • 财政年份:
    2010
  • 资助金额:
    $ 43万
  • 项目类别:

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