A neural population model-based characterization and modulation of neural oscillations underlying cognitive control in healthy and depressed/anxious human subjects

项目摘要 认知控制，一种抑制默认的、优先的反应，支持更适应的选择的能力 通常会受到抑郁症和焦虑症等精神障碍的影响。因此，一种用于 改善认知控制可能会在缺乏有效治疗的疾病中得到广泛应用。 成功地解决冲突是认知控制的一种形式，一个人必须抑制自然反应 遵循一条不那么直观的规则。冲突处理引起扣带回和丘脑的theta(4-8赫兹)振荡 内侧前额叶皮质(PFC)也可以通过有创的颅内脑电(IEEG)进行测量 作为额部中线头皮脑电。高频率的慢性和间歇性短程列车 包膜/纹状体刺激已被证明在改善运动能力的同时增强了theta振荡 执行一项冲突任务。此外，内囊或丘脑底核的脑深部刺激(DBS) 刺激外侧PFC核和经颅电流均能改善认知功能 控制任务。这些发现有力地表明，我们可以调节认知控制及其神经。 通过用外部电刺激瞄准相关的大脑回路来识别信号。这样做的目的是 研究建议是对冲突解决基础上的皮层振荡进行表征和建模 健康和焦虑/抑郁心理状态下的认知控制方面的信息设计 恢复健康精神状态的神经调节干预。我们要三个人 实现这一目标的互补方法。1)应用iEEG记录的癫痫患者接受 对于外科评估的侵入性监测，我们将确定潜在的皮质神经振荡 冲突任务框架下的认知控制。我们还将使用它来区分正常 以及抑郁或焦虑的受试者。2)我们将使用神经种群皮质模型来模拟和 描述PFC和观察到的颞叶皮质振荡背后的可行神经机制 在冲突处理期间。我们将使用数据驱动的方法来估计相关的模型参数。 3)我们将使用针对个体对象校准的模型来设计大脑皮层电刺激 将模拟的振荡调节到所需的健康状态的范例。然后我们将验证 我们的模型通过在人类受试者中测试模型预测，并确定我们是否可以成功 改变神经信号和相关行为。总而言之，这将导致生物物理上的 激励模型用于模拟健康和病态人群中潜在的冲突处理的神经振荡 并使我们能够设计刺激模式来调整它们。这也将提供新的见解 转化为有针对性的神经调节，如出于治疗目的的皮质刺激和知识 Gain可能会向情绪/焦虑症中受损的其他功能区提供信息。

Project Summary Cognitive control, the ability to withhold a default, prepotent response in favor of a more adaptive choice is often compromised across mental disorders such as depression and anxiety. Thus, a method for improving cognitive control could be broadly useful in disorders with few effective treatments. Successfully resolving conflicts is a form of cognitive control where one must suppress a natural response to follow a less intuitive rule. Conflict processing evokes theta (4-8 Hz) oscillations in the cingulate and medial prefrontal cortex (PFC) which can be measured through invasive intracranial EEG (iEEG) as well as frontal midline scalp EEG. Chronic as well as intermittent short trains of high frequency capsular/striatal stimulation have been shown to enhance theta oscillations while improving performance on a conflict task. Furthermore, deep brain stimulation (DBS) of the internal capsule or subthalamic nucleus and transcranial current stimulation of the lateral PFC all improve performance on cognitive control tasks. These findings strongly suggest that we can modulate both cognitive control and its neural signatures by targeting the relevant brain circuits with external electrical stimulation. The goal of this research proposal is to characterize and model cortical oscillations underlying the conflict resolution aspect of cognitive control in the healthy and anxious/depressed mental states to inform design of neuromodulation interventions for restoration towards healthy mental states. We will take three complimentary approaches to achieve this goal. 1) Using iEEG recorded in epilepsy patients undergoing invasive monitoring for surgical evaluation, we will determine cortical neural oscillations underlying cognitive control in the framework of a conflict task. We will also use this to differentiate between normal and depressed or anxious subjects. 2) We will use a neural population cortical model to simulate and characterize feasible neural mechanisms underlying PFC and temporal cortical oscillations observed during conflict processing. We will use a data driven approach for estimating relevant model parameters. 3) We will use the model calibrated to individual subjects to design a cortical electrical stimulation paradigm to modulate the simulated oscillations towards a desired healthy state. We will then validate our model by testing model predictions in our human subjects and determine if we can successfully change both neural signals as well as associated behavior. Together, this will lead to a biophysically motivated model to simulate neural oscillations underlying conflict processing in healthy and pathological states and allow us to design stimulation paradigms to modulate them. This will also provide new insight into targeted neuromodulation, such as cortical stimulation for therapeutic purposes and the knowledge gained will potentially inform other functional domains compromised in mood/anxiety disorders.