ArticleNature communications2025
Syntalos: a software for precise synchronization of simultaneous multi-modal data acquisition and closed-loop interventions.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Non-Invasive Brain-Computer Interfaces: Converging Frontiers in Neural Signal Decoding and Flexible Bioelectronics Integration.Nano-micro letters · 2026Review
- Dissecting neuronal circuit function and dysfunction in Alzheimer's disease mouse models: from conventional calcium imaging analysis to machine learning-based approaches.Frontiers in aging neuroscience · 2026Review
- Variation in the Involvement of Hippocampal Pyramidal Cell Subtypes in Spatial Learning Tasks.eNeuro · 2025Article
- A tactile discrimination task to study neuronal dynamics in freely-moving mice.Nature communications · 2025Article
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Authors and funding
8 authors.
Funding
Abstract
Complex experimental protocols often require multi-modal data acquisition with precisely aligned timing, as well as state- and behavior-dependent interventions. Tailored solutions are mostly restricted to individual experimental setups and lack flexibility and interoperability. We present an open-source, Linux-based integrated software solution, called 'Syntalos', for simultaneous acquisition and synchronization of data from an arbitrary number of sources, including multi-channel electrophysiological recordings and different live imaging devices, as well as closed-loop, real-time interventions with different actuators. Precisely matching timestamps for all inputs are ensured by continuous statistical analysis and correction of individual devices' timestamps. New data sources can be integrated with minimal programming skills. Data is stored in a comprehensively structured format to facilitate pooling or sharing data between different laboratories. Syntalos enables precisely synchronized multi-modal recordings as well as closed-loop interventions for multiple experimental approaches. Preliminary neuroscientific experiments on mice with different research questions show the successful performance and easy-to-learn structure of the software suite.
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Registered trials
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