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Institute of Neuroinformatics

Wireless brain imaging

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Unlike rodents and non-human primates, who are limited to innate vocalizations, songbirds share with humans the ability to modify and learn vocalizations by imitating conspecifics. This vocal imitation ability relies on self-reinforced, auditory-guided motor learning. Many parallels between speech acquisition in humans and birdsong learning are present at the behavioral, neural, and genetic levels.

To study this model system, we are working on the development of new state-of-the-art wireless devices for simultaneously recording animal communication signals and brain activity.

Our group has been developing sensors for recording vocal communication in songbirds (Anisimov at al., 2014) and wireless devices suitable for both recording and manipulation of behavior (Magno et al 2019). We now want to further develop wireless sensor devices to enable applications in neuroscience research by simultaneously recording animal communication signals and brain activity.

In collaboration with Michele Magno from the Center for Project-Based Learning, we develop hardware and software solutions for remote sensing applications, design and fabricate wireless Bluetooth low-energy devices for in vivo fluorescence recording of neuronal activity.  

Student Project

We are looking for MSc students interested in the development of state-of-the-art wireless devices. The ideal candidate for this position has a solid background in engineering and/or neuroscience. A strong commitment to teamwork is a top asset and crucial for succeeding in this project. If you are interested, contact Richard Hahnloser and Michele Magno

Keywords: embedded devices, Bluetooth Low Energy, Arm Cortex, data compression, neural networks, fiber photometry, optogenetics.

 

References

V. N. Anisimov, J.A. Herbst, A.N. Abramchuk, A.V. Latanov, R.H.R. Hahnloser, A.L. Vyssotski. Reconstruction of vocal interactions in a group of small songbirds. Nature Methods 11, 1135–1137  doi:10.1038/nmeth.3114 (2014).

M. Magno, F. Vultier, B. Szebedy, H. Yamahachi, R.H.R. Hahnloser, L. Benini. A Bluetooth-Low-Energy Sensor Node for Acoustic Monitoring of Small Birds. IEEE Sensors Journal (2019).