A Novel Strategy for Combating Obesity: Reprogramming Neural Circuits

描述（由申请人提供）：肥胖和2型糖尿病在美国儿童和成人中已飙升至流行病的比例。为了预防肥胖症的发作，启动逆转，避免复发，我们必须首先确定不健康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预测强迫性糖过度消费的神经代码，并开发新的方法，算法和技术来实时检测渴望的神经信号，以前所未有的精度避免适应不良行为。具体而言，项目大纲将开始确定 调节强迫性蔗糖寻求的神经回路接下来，我们将使用GCaMP 5表达细胞的体内电生理学和荧光显微内窥镜记录神经活动，以在线索诱导的恢复和强迫行为测定期间收集具有高信噪比的精确的一阶原始特征，其时间锁定的神经相关性允许识别渴望状态。然后，我们将使用机器学习算法，如神经活动的支持向量机分类，允许贝叶斯隐马尔可夫模型用于渴望-强迫-消费行为链中状态之间的转换图。在识别神经活动信号“渴望”状态（操作上定义为紧接在强迫性奖赏寻求之前的行为状态）之后，实时状态检测将用于触发强迫性蔗糖寻求的精确光遗传学抑制。这项研究的成功结果将为肥胖症的治疗建立一个新的范式，专注于重新编程导致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，包括成瘾，焦虑，抑郁症，双相情感障碍和强迫症（OCD）。 这项提案非常适合新创新者奖，原因如下：首先，这项研究的最终目标是为将神经回路重编程转化为人类患者奠定基础。其次，该提案侧重于技术开发，提供新技术，使非状态识别和动态触发用于神经回路重编程，并作为其他领域的跳板。第三，这个建议充分利用了我在蔗糖自我管理，复发，光遗传学，电生理学和成像方面的独特背景，但在技术和概念上与我实验室的其他影响焦虑，抑郁和成瘾的急性扰动研究不同。作为麻省理工学院的一名新教师，我在科学，工程，计算和技术的联系中保持平衡，并具备精确的技能和专业知识来执行这个高风险，但潜在的 革命性的项目。

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.