CAREER: The control of learning rate through multi-timescale cholinergic neuromodulation

职业：通过多时间尺度胆碱能神经调节控制学习率

基本信息

批准号：
2145247
负责人：
Kishore Kuchibhotla
金额：
$ 90万
依托单位：
Johns Hopkins University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-02-15 至 2027-01-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2145247&HistoricalAwards=false
关键词：
CAREER control learning rate through

项目摘要

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Determining how well environmental cues predict reward or punishment is critical for adaptive behavior. Past experience is more likely to be useful in stable environments. In humans and other animals, behavioral evidence suggests that learning rates depend on environmental uncertainty. In constantly changing environments, when uncertainty is high, it would be helpful to learn quickly. In stable environments, learning can be de-prioritized and instead humans and other animals can exploit their learned knowledge. This rate of learning can be formalized as a ‘learning rate’ and the computational theory of reinforcement learning (RL) aims to explain such learning processes. The proposal will test the role cholinergic neuromodulation, a deep-brain region implicated in a wide array of neurological disorders including Alzheimer’s disease (AD), in setting the learning rate during behavioral tasks. The research within this proposal is complemented with an integrated set of educational goals. A methods workshop on the optical tools that are revolutionizing neuroscience will be developed to augment an ongoing introductory neuroscience course. This workshop, for twenty students in the research track, will introduce students to optical and molecular tools. In addition, this proposal will build on the Psychological and Brain Sciences department’s goal to promote historically excluded identities through its Early Career Colloquium (ECC). A ‘Neuromodulation of Brain Circuits’ ECC segment will be launched with diverse speakers (4-6 trainees from outside JHU, 2-3 trainees within JHU and 1 keynote faculty talk) and networking events, to build a community of diverse scholars in neuromodulation. The proposed research will use quantitative behavior in mouse models and theoretical modeling to predict metalearning and then combine two-color, two-photon imaging, chemogenetics, and projection-specific optogenetics to isolate the roles of cholinergic and noradrenergic neuromodulation in setting biological learning rates. The proposal argues that the neural controller of a dynamic learning rate would benefit from three attributes: (1) encode environmental cues, (2) dynamically reflect uncertainty in the environment (i.e., high when uncertain, low when stable), and (3) modulate circuits involved in stimulus-action learning. Preliminary data show that neuromodulation of auditory cortex meets all three criteria. Cholinergic basal forebrain (CBF) axons in auditory cortex exhibit phasic, stimulus-evoked responses to auditory cues (1) that depend on preceding CBF axon activity, such that early in learning—when uncertainty is high—CBF axons ramp up their ability to discriminate the two auditory cues, and later in learning—when uncertainty is low—this discriminative signal fades (2). This CBF signal precedes cortical plasticity in a region critical for audiomotor learning (3). These data support a core hypothesis: tonic and phasic CBF signaling dynamically set the rate of cortical plasticity critical for sensorimotor learning. To test this idea, the proposal will isolate phasic, auditory input to the CBF to gain control of this signal (Goal 1), use model-based predictions to test whether CBF axon activity tracks a learning rate parameter in discrimination and reversal learning (Goal 2), and causally manipulate CBF signaling during discrimination and reversal learning and examine learning rate (Goal 3).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项的全部或部分资金来源于《2021 年美国救援计划法案》（公法 117-2）。确定环境线索预测奖励或惩罚的程度对于适应行为至关重要，过去的经验在稳定的情况下更可能有用。在人类和其他动物中，行为证据表明，学习率取决于环境的不确定性，当不确定性很高时，在稳定的环境中，学习可以被优先考虑，而不是人类。和其他动物可以利用它们学到的知识。这种学习速率可以形式化为“学习速率”，而强化学习（RL）的计算理论旨在解释这种学习过程。该提案将测试胆碱能神经调节的作用。与包括阿尔茨海默氏病（AD）在内的多种神经系统疾病有关的大脑区域，在设定行为任务期间的学习率方面，该提案中的研究得到了一套关于光学工具的综合教育目标的补充。神经科学将发生革命性的变化该研讨会是为了补充正在进行的神经科学入门课程而开发的，该研讨会将向学生介绍光学和分子工具，此外，该提案还将建立在心理和脑科学系的目标之上，即通过促进历史上被排斥的身份。其早期职业研讨会 (ECC) 将推出“脑回路神经调节”ECC 部分，由不同的演讲者（来自 JHU 外部的 4-6 名学员、JHU 内部的 2-3 名学员和 1 名主旨教师演讲）和网络事件，以建立一个由神经调节领域的不同学者组成的社区，拟议的研究将利用小鼠模型的行为和理论模型来预测元学习，然后结合双色、双光子成像、化学遗传学和投影特异性光遗传学来分离。该提案认为，动态学习率的神经控制器将受益于三个属性：（1）编码环境线索，（2）动态反映环境的不确定性。环境（即不确定时高，稳定时低），以及（3）参与刺激动作学习的调节电路初步数据表明，听觉皮层的胆碱能基底前脑（CBF）轴突满足所有三个标准。对听觉线索 (1) 的阶段性刺激诱发反应取决于先前的 CBF 轴突活动，因此在学习早期（当不确定性很高时）CBF 轴突会增强其区分两种听觉线索的能力，并且在学习过程中（当不确定性较低时）这种辨别信号会先于对听觉运动学习至关重要的区域的皮质可塑性减弱 (3)。紧张性和阶段性 CBF 信号动态设置对感觉运动学习至关重要的皮质可塑性速率，为了测试这一想法，该提案将隔离 CBF 的阶段性听觉输入，以获得对该信号的控制（目标）。 1），使用基于模型的预测来测试CBF轴突活动是否跟踪辨别和逆转学习中的学习率参数（目标2），并在辨别和逆转学习期间因果操纵CBF信号并检查学习率（目标3）。该奖项通过使用基金会的智力价值和更广泛的影响审查标准进行评估，NSF 的法定使命被认为值得支持。