NeuroLogger

Wireless & Cost-Effective Solution for EEG Recordings in Freely Moving Animals

Table of Contents
Neurologger TSE Systems

Versatile EEG/EMG Data Logging Solution

The NeuroLogger is a versatile tool designed for use in freely moving animals across various behavioral paradigms and in the study of animal models for epilepsy and sleep disorders. With its plug on/off functionality, it serves as a data logger capable of recording 4 channels of EEG/EMG activity. What sets it apart is its straightforward and cost-effective battery replacement process, ensuring uninterrupted recording cycles.

Key Advantages:

  • Enhanced Subject Freedom: Untethered design minimizes behavioral disruption during recordings.
  • Social Recording Capabilities: Enables simultaneous recordings from multiple animals in shared environments.
  • Precise Event Marking: Synchronizes recordings with external triggers for accurate event analysis.
  • Integrated Movement Monitoring: Provides real-time feedback on animal activity levels.
  • Optional External Signal Alignment: Seamlessly integrates timing signals for enriched data context.

Main Features

Wireless data logger

Up to 90 hours uninterrupted recording

Wireless synchronization with trigger signals for precise analysis and event making

Recording during behavioral testing

Infrared communication with external event recorder

Built-in movement sensor registering whether animal rests or moves

Neurologger TSE Systems

Read-Out Station for Data Retrieval

The NeuroLogger system fosters groundbreaking investigations into animal behavior and physiology by offering unprecedented freedom, precise data capture, and efficient data retrieval.

Compact and wireless, the NeuroLogger transmits data to a dedicated Read-Out Station upon experiment completion, facilitating seamless data retrieval and streamlined post-recording workflows.

Publications

Ponserre, M. A., Ionescu, T. M., Franz, A. A., Deiana, S., Schuelert, N., Lamla, T., Williams, R. H., Wotjak, C. T., Hobson, S., & Dine, J. P. (2024). Long-term adaptation of prefrontal circuits in a mouse model of NMDAR hypofunction. bioRxiv, 2024–02.

Gutnick, T., Neef, A., Cherninskyi, A., Ziadi-Künzli, F., Cosmo, A. D., Lipp, H.-P., & Kuba, M. J. (2023). Recording electrical activity from the brain of behaving octopus. Current Biology, 33(6), 1171-1178.e4. https://doi.org/10.1016/j.cub.2023.02.006

Widmann, M., Lieb, A., Mutti, A., & Schwarzer, C. (2023). Dimethyl sulfoxide’s impact on epileptiform activity in a mouse model of chronic temporal lobe epilepsy. Epilepsy Research, 197, 107235. https://doi.org/10.1016/j.eplepsyres.2023.107235.

Ren, L. Y., Cicvaric, A., Zhang, H., Meyer, M. A., Guedea, A. L., Gao, P., Petrovic, Z., Sun, X., Lin, Y., & Radulovic, J. (2022). Stress-induced changes of the cholinergic circuitry promote retrieval-based generalization of aversive memories. Molecular Psychiatry, 27(9), Article 9. https://doi.org/10.1038/s41380-022-01610-x.

Hoekstra, M. M., Jan, M., Katsioudi, G., Emmenegger, Y., & Franken, P. (2021). The sleep-wake distribution contributes to the peripheral rhythms in PERIOD-2. eLife, 10, e69773. https://doi.org/10.7554/eLife.69773.

Center of Knowledge

NeuroLogger blog post

Researchers record brain waves of free-swimming octopuses for the first time using the Neurologger

Octopuses are considered one of the most intelligent invertebrates. With over 300 million neurons, octopuses have the most complex invertebrate brain. Their brain is composed…

Learn more