Control of the time course of dopamine release through optimized electrical brain stimulation.

通过优化脑电刺激来控制多巴胺释放的时间过程。

• 批准号: 10285860
• 负责人: Stephen Leigh Cowen
• 金额: $ 111.76万
• 依托单位: UNIVERSITY OF ARIZONA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-15 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10285860
• 关键词: Affect; Behavior; Behavioral; Brain; Brain region; Cell model; Cognitive; Data; Decision Making; Deep Brain Stimulation; Disease; Dopamine; Drug Addiction; Electric Stimulation; Electrical Stimulation of the Brain; Epilepsy; Food; Frequencies; Goals; Human; Investigation; Investigational Therapies; Knowledge; Learning; Link; Measurement; Measures; Medial; Mental Depression; Methods; Mission; Modeling; Modernization; Motivation; Neuromodulator; Neuronal Plasticity; Neurons; Nucleus Accumbens; Outcome; Parkinson Disease; Patients; Pattern; Periodicity; Phase; Physiologic pulse; Physiological; Pilot Projects; Play; Prefrontal Cortex; Process; Psychological reinforcement; Public Health; Rattus; Research; Reversal Learning; Rewards; Role; Scanning; Schizophrenia; Scientist; Shapes; Signal Transduction; Structure; Synapses; System; Technology; Testing; Therapeutic; Time; Translational Research; Tremor; United States National Institutes of Health; Ventral Tegmental Area; addiction; clinical effect; disability; expectation; flexibility; human data; improved; innovative technologies; insight; mathematical model; median forebrain bundle; motor control; multi-scale modeling; nervous system disorder; neural stimulation; novel strategies; optogenetics; relating to nervous system; response; theories; tool

Project Summary Electrical stimulation of deep brain structures is an essential tool for the causal investigation of neural systems that regulate learning and decision making. Deep brain electrical stimulation is also a valuable tool for treating neurological disorders such as Parkinson's disease and tremor, and recent data suggests that electrical brain stimulation may effectively treat epilepsy and severe depression. Despite its scientific and translational applications, little is known about how electrical stimulation affects the ongoing activities of neurons or the release of neuromodulators such as dopamine. Understanding how electrical stimulation affects dopamine release is particularly important given dopamine's involvement in learning, motor control, decision making, and neuroplasticity. There is considerable evidence that dopamine's function is determined by the time course of release. For example, fast, “phasic” release (~1-2 seconds) is involved in neuroplasticity and reward-guided learning while slow, “tonic” release (tens of seconds) is involved in motor control and motivation. Little is known about how the brain selectively regulates tonic and phasic release, and few methods exist for controlling the time course of dopamine release. Developing such methods could result in 1) new experimental approaches for the causal investigation of the roles phasic and tonic release play in motivation and motor control, and 2) translational tools to correct disrupted patterns of dopamine release in disorders such as Parkinson's disease, schizophrenia, addiction, and depression. Towards these goals, evidence from our group suggests that the frequency and duration of electrical brain stimulation allows selective control of the time course of dopamine release. Our general objective is to characterize how parameters of brain stimulation such as stimulation frequency, variability, and the brain region targeted impacts the time-course of dopamine release and dopamine's role in reward-guided learning. Our experimental objectives are to determine (1) how the frequency and variability of the sequence of pulses delivered during brain stimulation affects phasic and tonic dopamine release, (2) how brain stimulation and tonic and phasic signaling interact to affect reward-driven learning, and (3) and how tonic and phasic signaling affect interactions between neurons and shape neuroplasticity. Our experimental approaches involve voltammetry for dopamine measurement, neural ensemble recordings for measurement of neural coordination, optogenetics, and on-line optimization of dopamine release in anesthetized and behaving rats. Our computational objective is to use data collected to develop multi-scale systems and cellular models that describe how stimulation frequency and variance affect the time course of dopamine release. We predict that multi-scale models will outperform current synaptic models and improve the capacity of scientists and clinicians to control dopamine release in experimental and therapeutic settings. These models may also explain clinical effects such as recent data from human patients suggesting that electrical stimulation of deep brain regions reduces depression.

项目摘要 脑深部结构的电刺激是神经系统病因研究的重要工具 来规范学习和决策。脑深部电刺激也是治疗 帕金森氏症和震颤等神经疾病，以及最近的数据表明，脑电 刺激可以有效地治疗癫痫和严重的抑郁症。尽管它具有科学性和翻译性 应用方面，电刺激如何影响神经元的持续活动或 释放神经调节剂，如多巴胺。了解电刺激如何影响多巴胺 考虑到多巴胺参与学习、运动控制、决策和 神经可塑性。有相当多的证据表明，多巴胺的功能是由 放手。例如，快速的“阶段性”释放(~1-2秒)与神经可塑性和奖赏引导有关 学习虽然缓慢，但“强效”释放(几十秒)涉及到运动控制和动机。鲜为人知 关于大脑如何选择性地调节紧张和时相的释放，目前还没有什么方法来控制 多巴胺释放的时间进程。开发这样的方法可能会导致1)新的实验方法 研究时相释放和紧张性释放在动机和运动控制中所起作用的因果关系，以及2) 用于纠正帕金森氏症等疾病中多巴胺释放紊乱模式的翻译工具， 精神分裂症、毒瘾和抑郁症。为了实现这些目标，我们小组的证据表明， 电刺激大脑的频率和持续时间允许选择性地控制多巴胺的时间进程 放手。我们的总体目标是表征脑刺激参数，如刺激 频率、变异性和目标大脑区域影响多巴胺释放和 多巴胺在奖赏引导学习中的作用。我们的实验目标是确定(1)频率如何 在脑刺激过程中传递的脉冲序列的可变性会影响相性和强直性多巴胺 释放，(2)大脑刺激和强直和时相信号如何相互作用，影响奖励驱动的学习，以及 (3)强直信号和时相信号如何影响神经元之间的相互作用和形成神经可塑性。我们的 实验方法包括用于多巴胺测量的伏安法，用于 神经协调、光遗传学和多巴胺释放的在线优化的测量 麻醉和行为正常的大鼠。我们的计算目标是使用收集的数据来开发多尺度 系统和细胞模型，描述刺激频率和方差如何影响 多巴胺的释放。我们预测，多尺度模型将优于当前的突触模型，并改善 科学家和临床医生在实验和治疗环境中控制多巴胺释放的能力。 这些模型还可以解释临床效应，例如最近来自人类患者的数据表明 对大脑深层区域的电刺激可以减少抑郁。

项目成果

Automated system for training and assessing string-pulling behaviors in rodents.

用于训练和评估啮齿动物拉绳行为的自动化系统。

• DOI: 10.1101/2023.07.02.547431
• 发表时间: 2023
• 期刊: bioRxiv : the preprint server for biology
• 作者: Jordan,GiannaA;Vishwanath,Abhilasha;Holguin,Gabriel;Bartlett,MitchellJ;Tapia,AndrewK;Winter,GabrielM;Sexauer,MorganR;Stopera,CarolynJ;Falk,Torsten;Cowen,StephenL
• 通讯作者: Cowen,StephenL

Automated system for training and assessing reaching and grasping behaviors in rodents.

用于训练和评估啮齿动物的伸手和抓握行为的自动化系统。

• DOI: 10.1016/j.jneumeth.2023.109990
• 发表时间: 2024
• 期刊: Journal of neuroscience methods
• 影响因子: 3
• 作者: Jordan,GiannaA;Vishwanath,Abhilasha;Holguin,Gabriel;Bartlett,MitchellJ;Tapia,AndrewK;Winter,GabrielM;Sexauer,MorganR;Stopera,CarolynJ;Falk,Torsten;Cowen,StephenL
• 通讯作者: Cowen,StephenL