论文标题
用于神经振荡检测和特定相位刺激的可扩展实时体系结构
A Scalable Real-Time Architecture for Neural Oscillation Detection and Phase-Specific Stimulation
论文作者
论文摘要
大脑本地场电位（LFP）中的振荡是神经信息处理的关键特征。在特定阶段将这些振荡驱动以改变神经信息处理是一个积极研究的领域。现有的针对特异性大脑刺激的系统通常不提供实时定时保证（基于台式计算机的系统），或者需要广泛的供应商特定设备编程。这项工作提出了一种实时检测系统体系结构，该体系结构是平台 - 敏捷的，并扩展到数千个记录渠道，并使用基于概念的微控制器实现验证。
Oscillations in the local field potential (LFP) of the brain are key signatures of neural information processing. Perturbing these oscillations at specific phases in order to alter neural information processing is an area of active research. Existing systems for phase-specific brain stimulation typically either do not offer real-time timing guarantees (desktop computer based systems) or require extensive programming of vendor-specific equipment. This work presents a real-time detection system architecture that is platform-agnostic and that scales to thousands of recording channels, validated using a proof-of-concept microcontroller-based implementation.
