CRCNS: Real-time neural decoding for calcium imaging

CRCNS：钙成像实时神经解码

基本信息

批准号：
9769912
负责人：
SHUVRA S BHATTACHARYYA
金额：
$ 22.83万
依托单位：
UNIVERSITY OF MARYLAND BALTIMORE
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2021-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9769912
关键词：
Address Algorithms Animals Attention BRAIN initiative Behavior Biological Models Brain Brain Diseases Calcium Cells Cognition Collection Complex Computer software Data Data Analyses Detection Devices Disease Electrodes Emotions Encapsulated Epilepsy Esthesia Etiology Event Feedback Fiber Frequencies Generations Image Knowledge Laboratories Language Learning Link Location Magnetic Resonance Imaging Masks Measures Memory Methods Modeling Monitor Motion Movement Network-based Neurocognitive Neurons Neurosciences Pain Patients Perception Performance Photometry Principal Investigator Process Records Research Resolution Science Scientist Sleep Speed Stream System Techniques Time Training Vision Wakefulness Work base cellular imaging cost efficient data acquisition deep neural network design experimental study high dimensionality improved in vivo innovation multidimensional data nervous system disorder network architecture neural circuit neural stimulation neuromechanism neuroregulation neurotransmission novel optical imaging optogenetics predictive modeling programs prototype real-time images relating to nervous system signal processing spatiotemporal temporal measurement tool

项目摘要

Program Director/Principal Investigator (Last, First, Middle): Chen, Rong PROJECT DESCRIPTION A. BACKGROUND AND SIGNIFICANCE Real-time neural decoding centers on predicting behavior variables based on neural activity data, where the prediction is performed at a pace that reliably keeps up with the speed of the activity that is being monitored. Neuromodulation devices are becoming one of the most powerful tools for the treatment of brain disorders, enhancing neurocognitive performance, and demonstrating causality (Bergmann et al., 2016; Knotkova and Rasche, 2015). A precise neuromodulation system (Figure 1) integrates neural activity monitoring, real-time neural decoding, and neuromodulation. In precise neuromodulation, a decoding device predicts a behavior variable based on neural data streams in real-time. Based on the decoding results, neuromodulation parameters such as timing, frequency, duration, and amplitude are changed. Precise neuromodulation systems with closed-loop real-time feedback are superior to the fixed (open- loop) neuromodulation paradigm (Brocker et al., 2017; deBettencourt et al., 2015; Ezzyat et al., 2017). A recent direct brain stimulation study (Ezzyat et al., 2017) demonstrated significant advantages of precise neuromodulation over open-loop neuromodulation. Ezzyat et al. applied direct brain stimulation with decoding capability to patients with epilepsy to improve their memory. They found that stimulation increased memory function only if delivered when the decoding device indicated low encoding efficiency while stimulation decreased memory function if delivered when the decoding device indicated high encoding efficiency. An open-loop neuromodulation system with a fixed stimulation paradigm may not always facilitate memory function. Miniature cellular imaging (Ghosh et al., 2011; Kerr and Nimmerjahn, 2012; Scott et al., 2013) is one of the most powerful ways to study neural circuits. It enables us to investigate neural circuits during behaviors for an understanding of network architecture of behavior, cognition, and emotion. Miniature cellular imaging records neuronal activity at cellular and sub-second levels of spatial and temporal resolution in freely moving animals. Miniature cellular imaging has many advantages. First, compared with in vivo multi-electrode recording, miniature calcium imaging can probe all cells in the field of view, and visualize the spatial location of monitored cells (Kerr et al., 2005). Second, compared with magnetic resonance imaging, which measures brain activity at the macroscopic scale and with low temporal resolution, miniature cellular imaging provides high spatial and temporal resolution. Third, fiber photometry (Cui et al., 2014) lacks cellular-level resolution, while miniature cellular imaging allows concurrent tracking of neural calcium activities at cellular spatial resolution. Simultaneous neural activity monitoring and intetvention Stimulation Calcium imaging Real-time decoding system Figure 1 A precise neuromodulation system. Our project centers on developing RNDC-Lab. PHS 398 (Rev. 01 /18 Approved Through 03/31/2020) Page 26 Miniature cellular imaging with real- time decoding capability captures the central vision of brain science, (The brain initiative, 2014). Combined with optogenetics, it is a tremendous asset to studying neural mechanisms underlying normal and disease states, and leads to precise neuromodulation. However, developing such systems is a challenging task. A major obstacle is the analysis of the large imaging streams that are generated. The massive high-dimensional data streams that are generated include 0MB No. 0925-0001

计划总监/首席调查员（最后，第一，中间）：陈，Rong 项目描述 A.背景和意义实时神经解码集中于基于神经活动数据预测行为变量的中心，以可靠地跟上活动速度的速度执行预测的地方正在监视。神经调节设备已成为最强大的工具之一用于治疗脑部疾病，增强神经认知表现并证明因果关系（Bergmann等，2016； Knotkova和Rasche，2015）。精确的神经调节系统（图1）整合神经活动监测，实时神经解码和神经调节。在精确的神经调节中，解码设备预测了行为变量基于实时的神经数据流。基于解码结果，神经调节更改时间，频率，持续时间和振幅等参数。精确的具有闭环实时反馈的神经调节系统优于固定（开放式）循环）神经调节范式（Brocker等，2017； Debettencourt等，2015； Ezzyat等， 2017）。最近的一项直接大脑刺激研究（Ezzyat等，2017）表现出显着的精确的神经调节优于开环神经调节的优点。 Ezzyat等。应用直接脑刺激，并为癫痫患者的解码能力提高记忆力。他们发现，只有在解码设备时传递时，刺激增加了记忆的功能指示的低编码效率低，而刺激降低记忆功能，如果交付解码设备表示高编码效率。开环神经调节系统使用固定的刺激范式可能并不总是促进内存功能。微型细胞成像（Ghosh等，2011; Kerr和Nimmerjahn，2012; Scott等，2013）是研究神经回路的最有力方法之一。它使我们能够调查神经回路在行为中，了解行为，认知和情感的网络结构。微型细胞成像记录了在空间的细胞和亚秒级别的神经元活性和自由移动动物的时间分辨率。微型蜂窝成像具有许多优势。首先，与体内多电极记录相比，微型钙成像可以探测视野中的所有细胞，并可视化受监测细胞的空间位置（Kerr等， 2005）。其次，与磁共振成像相比，该成像测量了大脑在宏观尺度且时间分辨率低，微型蜂窝成像可提供高度空间和时间分辨率。第三，纤维光度法（Cui et al。，2014）缺乏细胞级分辨率，而微型细胞成像允许同时跟踪神经钙活动在细胞空间分辨率下。同时进行神经活动监视和进行详尽刺激钙成像即时的解码系统图1精确的神经调节系统。我们的项目开发RNDC-LAB的中心。 PHS 398（Rev. 01/18通过03/31/2020批准）第26页微型细胞成像，时间解码功能捕获了脑科学的中央视觉，（大脑倡议，2014年）。与光遗传学，这是一项巨大的资产研究神经机制基本正常状态和疾病状态，并导致精确的神经调节。但是，开发这样的系统是一项具有挑战性的任务。一个主要障碍是大型成像的分析生成的流。这大量的高维数据生成的流包括 0MB编号0925-0001