CRCNS: Collaborative Research: State-Dependent Control for Brain Modulation

CRCNS：合作研究：大脑调节的状态相关控制

• 批准号: 10222669
• 负责人: BRUCE J GLUCKMAN
• 金额: $ 33.91万
• 依托单位: PENNSYLVANIA STATE UNIV HERSHEY MED CTR
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-15 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10222669
• 关键词: Action Potentials; Algorithms; Auras; Back; Biophysics; Brain; Computer Models; Data; Electric Stimulation; Epilepsy; Feedback; Goals; Health; Intensive Care; Membrane; Methods; Migraine; Modeling; National Institute of Mental Health; Neurons; Normal Range; Oxygen; Pathologic; Physiological; Potassium; Prevention; Property; Recording of previous events; Research; Seizures; Spike Potential; Stroke; Subarachnoid Hemorrhage; System; Tissues; Traumatic Brain Injury; base; biophysical model; experimental study; extracellular; improved; in vivo; in vivo Model; mind control; neuronal circuitry; novel strategies; optical sensor; prevent; spatiotemporal; spreading depression

Abstract There is a several decade history demonstrating that electrical polarization of neurons can modulate neuronal firing, and that such polarization can suppress (or excite) spiking activity and seizures. We have demonstrated seizure control using both open- and closed-loop stimulation strategies (J Neurophysiol, 76:4202-4205,1996; J Neurosci, 21:590-600, 2001). With past NIMH and CRCNS support (R01MH50006, 1R01EB014641) – we discovered a unification in the computational biophysics of spikes, seizures, and spreading depression (J Neurosci, 34:11733-11743, 2014). These findings demonstrate that the repertoire of the dynamics of the neuronal membrane encompasses a broad range of dynamics ranging from normal to pathological, and that seizures and spreading depression are manifestations of the inherent properties of those membranes. Recently we achieved a major experimental verification of key predictions from the unification predictions in in vivo epilepsy. Most recently, we achieved the experimental goal of the most recent CRCNS project, “Model-Based Control of Spreading Depression”, by demonstrating that neuronal polarization can suppress (or enhance), block, or prevent spreading depression, the physiological underpinning of migraine auras. Remarkably, this suppression requires the opposite polarity as that required to suppress spikes and seizures, and is fully consistent with the computational biophysical models of spreading depression. Further surprising findings from these experiments was that suppression of spreading depression does not appear to generate seizures, and vice versa, that when the brain is in seizure activity suppression does not generate spreading depression. The implications of the above is that in controlling brain dynamics from different states of the brain, that there can be state dependent control which is qualitatively very different from that required in other states. Furthermore, the control algorithms required to maintain a given steady state (e.g. normal spiking) may differ from that required to guide a system from a pathological state back into a steady state. We propose the hypothesis that there is an entirely new framework for feedback control of neuronal circuitry – State Dependent Control. This is a model-based framework, wherein neuronal systems are sensed through electrical or optical sensors, and the data assimilated into a biophysical computational model of the possible states. Feedback control is then applied based upon the state, and the trajectory of the system through state space is continually observed. Working out state dependent control for brain activity has health implications for not only epilepsy and migraine, but more broadly in intensive care settings because of the harmful effects of spreading depression waves in traumatic brain injury, stroke, and subarachnoid hemorrhage.

抽象的 有几个十年的历史表明神经元的电化可以调节 神经元发射，这种极化可以抑制（或激发）尖峰活动和癫痫发作。我们有 使用开环刺激策略（J Neurophysiol， 76：4202-4205，1996; J Neurosci，21：590-600，2001）。在过去的NIMH和CRCN支持的情况下（R01MH50006， 1R01EB014641） - 我们在峰值，癫痫发作和癫痫发作的计算生物物理学中发现了一个统一 扩散抑郁（J Neurosci，34：11733-11743，2014）。这些发现表明曲目 神经元膜的动力学包括广泛的动力学范围从正常 病理学，癫痫发作和扩散抑郁是继承特性的表现 这些机制。最近，我们从 体内癫痫中的统一预测。最近，我们实现了最大的实验目标 最近的CRCN项目“基于模型的扩散抑郁症的控制”，证明神经元 极化可以抑制（或增强），阻塞或防止抑郁症，生理 偏头痛的基础。值得注意的是，这种抑制需要相反的极性 抑制尖峰和癫痫发作所需，并且与计算生物物理模型完全一致 扩散抑郁症。这些实验的进一步令人惊讶的发现是抑制 散布抑郁似乎并没有产生癫痫发作，反之亦然，当大脑进入时 癫痫活性抑制不会产生扩散的抑郁症。以上的含义是 在控制大脑不同状态的大脑动力学时，可以存在依赖状态的控制 与其他州所需的质量截然不同。此外，控制算法 保持给定稳态（例如正常峰值）所需的要求与指导A所需的不同之处 从病理状态恢复到稳定状态的系统。我们提出了一个假设，有一个 助理神经元电路反馈控制的新框架 - 状态依赖控制。这是一个 基于模型的框架，其中神经元系统通过电气或光学传感器感测 数据被吸收到可能状态的生物物理计算模型中。反馈控制是 基于状态应用，并连续观察到通过状态空间的系统轨迹。 锻炼国家依赖对大脑活动的控制不仅对癫痫和 偏头痛，但在重症监护环境中更广泛，因为抑郁症的有害影响 创伤性脑损伤，中风和蛛网膜下腔出血中的波。

项目成果

Role of multiple-scale modeling of epilepsy in seizure forecasting.

• DOI: 10.1097/wnp.0000000000000149
• 发表时间: 2015-06
• 期刊: Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society
• 作者: Kuhlmann L;Grayden DB;Wendling F;Schiff SJ
• 通讯作者: Schiff SJ

Towards dynamical network biomarkers in neuromodulation of episodic migraine.

• DOI: 10.2478/s13380-013-0127-0
• 发表时间: 2013-09
• 期刊: Translational neuroscience
• 影响因子: 2.1
• 作者: Dahlem MA;Rode S;May A;Fujiwara N;Hirata Y;Aihara K;Kurths J
• 通讯作者: Kurths J

The Role of Cell Volume in the Dynamics of Seizure, Spreading Depression, and Anoxic Depolarization.

• DOI: 10.1371/journal.pcbi.1004414
• 发表时间: 2015-08
• 期刊: PLoS computational biology
• 影响因子: 4.3
• 作者: Ullah G;Wei Y;Dahlem MA;Wechselberger M;Schiff SJ
• 通讯作者: Schiff SJ

Oxygen and seizure dynamics: II. Computational modeling.

• DOI: 10.1152/jn.00541.2013
• 发表时间: 2014-07
• 期刊: Journal of neurophysiology
• 影响因子: 2.5
• 作者: Yina Wei;G. Ullah;J. Ingram;S. Schiff

Observability of Neuronal Network Motifs.

• DOI: 10.1109/ciss.2012.6310923
• 发表时间: 2012-03
• 期刊: Proceedings of the ... Conference on Information Sciences and Systems. Conference on Information Sciences and Systems
• 作者: Whalen AJ;Brennan SN;Sauer TD;Schiff SJ
• 通讯作者: Schiff SJ