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

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
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-08-15 至 2023-05-31

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中文摘要
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英文摘要
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.
期刊论文(8)
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会议论文
DOI: 10.1097/wnp.0000000000000149
发表时间: 2015-06
期刊: Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society
影响因子: --
作者: [Kuhlmann L, Grayden DB, Wendling F, Schiff SJ]
通讯作者: Schiff SJ
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
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
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
影响因子: --
作者: [Whalen AJ, Brennan SN, Sauer TD, Schiff SJ]
通讯作者: Schiff SJ
Cross-Disciplinary Neural Engineering (CDNE) Training Program
Cross-Disciplinary Neural Engineering (CDNE) Training Program
Cross-Disciplinary Neural Engineering (CDNE) Training Program
7th International Workshop on Seizure Prediction (IWSP7)
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