Neuro-Electronic Research Flanders (NERF), Leuven, Belgium. Brain & Cognition Research Unit, KU Leuven, Belgium. VIB, Leuven, Belgium.
J Neural Eng. 2017 Aug;14(4):045004. doi: 10.1088/1741-2552/aa7526.
Closed-loop experiments provide unique insights into brain dynamics and function. To facilitate a wide range of closed-loop experiments, we created an open-source software platform that enables high-performance real-time processing of streaming experimental data.
We wrote Falcon, a C++ multi-threaded software in which the user can load and execute an arbitrary processing graph. Each node of a Falcon graph is mapped to a single thread and nodes communicate with each other through thread-safe buffers. The framework allows for easy implementation of new processing nodes and data types. Falcon was tested both on a 32-core and a 4-core workstation. Streaming data was read from either a commercial acquisition system (Neuralynx) or the open-source Open Ephys hardware, while closed-loop TTL pulses were generated with a USB module for digital output. We characterized the round-trip latency of our Falcon-based closed-loop system, as well as the specific latency contribution of the software architecture, by testing processing graphs with up to 32 parallel pipelines and eight serial stages. We finally deployed Falcon in a task of real-time detection of population bursts recorded live from the hippocampus of a freely moving rat.
On Neuralynx hardware, round-trip latency was well below 1 ms and stable for at least 1 h, while on Open Ephys hardware latencies were below 15 ms. The latency contribution of the software was below 0.5 ms. Round-trip and software latencies were similar on both 32- and 4-core workstations. Falcon was used successfully to detect population bursts online with ~40 ms average latency.
Falcon is a novel open-source software for closed-loop neuroscience. It has sub-millisecond intrinsic latency and gives the experimenter direct control of CPU resources. We envisage Falcon to be a useful tool to the neuroscientific community for implementing a wide variety of closed-loop experiments, including those requiring use of complex data structures and real-time execution of computationally intensive algorithms, such as population neural decoding/encoding from large cell assemblies.
闭环实验为大脑动力学和功能提供了独特的见解。为了促进广泛的闭环实验，我们创建了一个开源软件平台，能够对流式实验数据进行高性能实时处理。
我们编写了 Falcon，这是一个 C++多线程软件，用户可以在其中加载和执行任意处理图。Falcon 图的每个节点都映射到一个单独的线程，节点通过线程安全的缓冲区相互通信。该框架允许轻松实现新的处理节点和数据类型。Falcon 在 32 核和 4 核工作站上进行了测试。流式数据从商业采集系统（Neuralynx）或开源 Open Ephys 硬件读取，而闭环 TTL 脉冲由用于数字输出的 USB 模块生成。我们通过测试具有多达 32 个并行流水线和 8 个串行阶段的处理图，来描述基于 Falcon 的闭环系统的往返延迟，以及软件架构的特定延迟贡献。最后，我们将 Falcon 部署在实时检测自由移动大鼠海马体记录的群体爆发的任务中。
在 Neuralynx 硬件上，往返延迟低于 1ms，并且稳定至少 1 小时，而在 Open Ephys 硬件上，延迟低于 15ms。软件的延迟贡献低于 0.5ms。在 32 核和 4 核工作站上，往返和软件延迟相似。Falcon 成功用于在线检测群体爆发，平均延迟约为 40ms。
Falcon 是一种用于闭环神经科学的新型开源软件。它具有亚毫秒级的固有延迟，并使实验者能够直接控制 CPU 资源。我们设想 Falcon 将成为神经科学界的有用工具，用于实现各种闭环实验，包括那些需要使用复杂的数据结构和实时执行计算密集型算法的实验，例如从大型细胞集合进行群体神经解码/编码。
