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A single board computer implementation of mouse dual brain mesoscale imaging and radio frequency identification

University of British Columbia

The power of social interaction and touch is undisputed across the animal kingdom. To evaluate neuro-correlates of social behaviour, recent studies have focused both on system level human studies to mechanistic studies within animal models. In animals, mechanistic studies have largely focused on social interactions between rodents and this work indicates a fundamental role of the rodent vibrissal system in transmitting social signals between animals. While considerable work has been done in both human and animal models, correlations between subjects over high sampling rates and relatively large expanses of the cortex have not been done. Here, we employ mouse mesoscale GCaMP imaging to establish how calcium activity is correlated when two mice engage in social touch-like behaviour. The two mice begin at a distance where social touch is not possible, then they are transiently brought close to each other in order to allow them to interact. Afterwards, the mice are moved back to their initial separated state. When the mice are in the together state we observe that the mice engage in bouts of mutual whisking resulting in simultaneous barrel cortex activity. Additionally, we find that brain-wide calcium signals at a frequency band of 0.01-0.1Hz become synchronized when the mice are together. We also developed a cost effective radio-frequency based system for mouse identification. We describe a simple protocol to tag and identify mice using glass-encapsulated tags, which were injected sub-cutaneously after brief anesthesia. Python software provides a flexible, cross-platform solution for interfacing with the tag reader, which is capable of reading the tags at a distance of 30.2 ± 2.4mm. The system facilitates automated behavioural experiments that require animal identification [Murphy et al., 2016, Silasi et al., 2017, Woodard et al., 2017]. The radio frequency identification (RFID) system could be applied to further automate social touch studies.

Text

2018-07-24

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/66568

Neuroscience

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/