Reliable and reproducible acquisition of multimodal behavioral and neurophysiological data is essential for modern systems neuroscience, but remains technically challenging. Common obstacles include experimenter variability, error-prone device control, consistent (meta)data management, and lack of precise temporal synchronization across heterogeneous hardware that lacks a hardware-based synchronization method. To address these issues, I developed Syntalos, an open-source, Linux-based, modular software framework for integrated data acquisition and control. Written in C++ with built-in Python extensibility, Syntalos provides a unified interface for diverse data acquisition devices, a standardized layout to store recorded data and metadata for reproducible data management, multiple ways to control hardware for live interactions, and a statistical algorithm for continuous time synchronization across multiple data streams. Validation experiments demonstrated robust long-term time synchronization stability of the statistical algorithm: Electrophysiological recordings, Miniscope calcium imaging, and multi-camera video streams remained synchronized within device sampling tolerances for over 24 h. To extend calcium imaging capabilities, driver and software improvements for the UCLA Miniscope were implemented, including structural imaging support and a 3D acquisition option, simplifying integration into behavioral experiments. Modern neuroscience often relies on closed-loop experiments with live interventions during a data acquisition run. Syntalos' roundtrip latencies were sufficient for most closed-loop behavioral experiments. For lower latency needs in the sub-millisecond range, dedicated hardware modules were developed for deterministic responses. In behavior experiments with awake, freely moving mice, Syntalos successfully coordinated calcium imaging, behavioral tracking, and automated reward delivery, enabling precise alignment of neuronal and behavioral data. Additional use cases by independent groups - including multi-camera/Miniscope setups, thalamocortical tactile discrimination tasks, and respiratory rhythm recordings - demonstrated the utility and performance of the software across laboratories and paradigms. Compared with existing proprietary and open-source solutions, Syntalos is distinguished by its built-in algorithmic synchronization, reproducible storage format, and vendor-independent extensibility. These features establish Syntalos as a robust, scalable platform for complex behavioral neuroscience experiments requiring synchronized multimodal acquisition and closed-loop interventions.
Martin Both (2026) studied this question.