A Novel Strategy for Combating Obesity: Reprogramming Neural Circuits

对抗肥胖的新策略：重新编程神经回路

• 批准号: 9284928
• 负责人: Kay Maxine Tye
• 金额: $ 0.26万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-30 至 2018-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9284928
• 关键词: Acute; Adult; Affect; Algorithms; American; Anxiety; Award; Behavior; Behavioral; Behavioral Assay; Bipolar Disorder; Cells; Child; Classification; Code; Consumption; Cues; Detection; Eating; Electrophysiology (science); Engineering; Epidemic; Faculty; Fluorescence; Foundations; Gap Junctions; Goals; Habits; Human; Image; Machine Learning; Mediating; Mental Depression; Noise; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Obsessive-Compulsive Disorder; Outcomes Research; Patients; Relapse; Research; Rewards; Science; Self Administration; Signal Transduction; Sucrose; Technology; Time; Translating; addiction; combat; compulsion; craving; high risk; in vivo; innovation; markov model; member; neural circuit; neural correlate; neuropsychiatric disorder; neurotransmission; new technology; novel strategies; obesity treatment; optogenetics; prevent; relating to nervous system; skills; sugar; technology development

DESCRIPTION (provided by applicant): Obesity and Type 2 diabetes have skyrocketed to epidemic proportions in American children and adults. To prevent the onset, initiate the reversal, and avoid the relapse of obesity, we must first identify the neural underpinnings of unhealthy eating choices and habits. The immediate goals of this innovative proposal are to decipher the neural code predicting compulsive overconsumption of sugar and to develop new approaches, algorithms, and technologies to detect neural signals of craving in real-time to avert maladaptive behaviors with unprecedented precision. Specifically, the project outline will begin by identifying neural circuits mediating compulsive sucrose seeking. Next, we will record neural activity using in vivo electrophysiology and fluorescence microendoscopy of GCaMP5-expressing cells to collect precise, first-order, raw features with high signal-to-noise ratio during cue-induced reinstatement and compulsion behavioral assays with their time-locked neural correlates allows for the identification of craving states. Then, we will use machine learning algorithms such as support vector machine classification of neural activity allows for a Bayesian hidden Markov model for a transition diagram between states in craving-compulsion-consumption behavioral chains. Following identification of neural activity signaling "craving" states (operationally defind as the behavioral state immediately preceding compulsive reward-seeking), real-time state detection will be used to trigger precise optogenetic inhibition of compulsive sucrose-seeking. A successful outcome of this research would establish a new paradigm for the treatment for obesity, focusing on reprogramming the neural circuit perturbations that cause obesity, as opposed to treating the physical consequences of a neural circuit imbalance - an approach that could also be applied to other neuropsychiatric disorders including addiction, anxiety, depression, bipolar disorder and obsessive compulsive disorder (OCD). This proposal is ideally suited for the New Innovator Award for the following reasons: First, the ultimate goal of this research is to lay the foundation for translating Neural Circuit Reprogramming to human patients. Second, the proposal is focused on technology development, delivering new technologies that will enable not state-identification and dynamic triggering used for Neural Circuit Reprogramming, and serve as springboards for other fields. Third, this proposal heavily leverages my unique background in sucrose-self administration, relapse, optogenetics, electrophysiology and imaging, but is technically and conceptually distinct from my lab's other studies on acute perturbations that affect anxiety, depression and addiction. As a new faculty member at MIT, I am poised at the nexus of science, engineering, computation and technology and am equipped with the precise skill set and expertise to execute this high-risk, yet potentially revolutionary project.

描述（由申请人提供）：肥胖和2型糖尿病已经在美国儿童和成人的流行病上飙升。为了防止发作，开始逆转并避免肥胖复发，我们必须首先确定不健康的饮食选择和习惯的神经基础。这项创新提案的直接目标是破译神经法规，预测糖的强迫性过度消耗，并开发新方法，算法和技术，以实时检测渴望的神经信号，以避免以前所未有的精确确定的适应性行为。具体而言，项目大纲将首先确定 神经回路介导强迫性蔗糖寻求。接下来，我们将使用体内电生理学和表达GCAMP5表达细胞的荧光微型内镜记录神经活动，以收集具有高信噪比的精确的，一阶的原始特征，在提示诱导的恢复和强迫性行为分析过程中具有高信噪比，并具有时间锁定的神经相关性，可以识别可识别的识别可识别的可爱状态。然后，我们将使用机器学习算法，例如支持向量机的神经活动分类，可以使贝叶斯隐藏的马尔可夫模型在渴望迫切消耗行为链中的状态之间进行过渡图。在鉴定神经活动信号传导“渴望”状态（在操作上作为在强迫奖励寻求奖励之前的行为状态）之后，将使用实时状态检测来触发对强迫性蔗糖寻求的精确的光遗传学抑制。这项研究的成功结果将为肥胖治疗的新范式建立新的范式，重点是重新编程引起肥胖的神经回路扰动，而不是治疗神经回路失衡的身体后果 - 这种方法也可以应用于其他神经精神疾病，包括其他神经心理疾病，包括成瘾，抑郁，抑郁，抑郁，bip骨，bip骨，bip骨，biply症和对比不当（Ocd）。 由于以下原因，该提案非常适合新的创新奖：首先，这项研究的最终目标是为将神经回路重新编程转换为人类患者奠定基础。其次，该提案的重点是技术开发，提供了新技术，这些技术将使无法进行神经电路重编程的状态识别和动态触发，并充当其他领域的跳板。第三，该提案在很大程度上利用了我在蔗糖自我给药，复发，光遗传学，电生理学和成像方面的独特背景，但从技术和概念上讲，我与实验室的其他有关影响焦虑，抑郁和成瘾的急性扰动的研究不同。作为麻省理工学院的新教师，我已经准备好科学，工程，计算和技术的联系，并配备了精确的技能和专业知识，以执行这种高风险，但潜在的可能 革命项目。