Centanni, S. W. | Search bioRxiv

bioRxiv2021

PiRATeMC: A highly flexible, scalable, and affordable system for obtaining high quality video recordings for behavioral neuroscience.

With the recent development and rapidly accelerating adoption of machine-learning based rodent behavioral tracking tools such as DeepLabCut, there is an unmet need for a method of acquiring video data that is scalable, flexible, and affordable. Many experimenters use webcams, GoPros, or other commercially available cameras that are not only relatively expensive, but offer very little flexibility over recording parameters. These cameras are not ideal for recording many types of behavioral experiments, and can lead to suboptimal video quality. Furthermore when using relatively affordable commercially available products, it is a challenge, if not impossible, to synchronize multiple cameras with each other, or to interface with third-party equipment (for example, receiving a simple trigger to simultaneously start recording, or acting as a microcontroller for closed-loop experiments). We have developed an affordable ecosystem of behavioral recording equipment, PiRATeMC (Pi-based Remote Acquisition Technology for Motion Capture), that relies on Raspberry Pi Camera Boards that are able to acquire high quality recordings in bright light, low light, or dark conditions under infrared light. PiRATeMC offers users control over nearly every recording parameter, and can be fine-tuned to produce optimal video data in any behavioral arena. This setup can easily be scaled up and synchronously controlled in clusters via a self-contained network to record a large number of simultaneous behavioral sessions without burdening institutional network infrastructure. Furthermore, the Raspberry Pi is an excellent platform for novice and inexperienced programmers interested in using an open-source recording system, with a large online community that is very active in developing novel open-source tools. It easily interfaces with Arduinos and other microcontrollers, allowing simple synchronization and interfacing of video recording with nearly any behavioral equipment using GPIO pins to send or receive 3.3V or 5V (TTL) signals, I2C, or serial communication.

neuroscience↗

bioRxiv2021

Targeting Diacylglycerol Lipase to Reduce AlcoholConsumption

Alcohol use disorder (AUD) is associated with substantial morbidity, mortality, and societal cost, and pharmacological treatment options for AUD are limited. The endogenous cannabinoid (eCB) signaling system is critically involved in reward processing and alcohol intake is positively correlated with release of the eCB ligand 2-Arachidonoylglycerol (2-AG) within reward neurocircuitry. Here we show that genetic and pharmacological inhibition of diacylglycerol lipase (DAGL), the rate limiting enzyme in the synthesis of 2-AG, reduces alcohol consumption in a variety of preclinical models ranging from a voluntary free-access model to aversion resistant-drinking, and dependence-like drinking induced via chronic intermittent ethanol vapor exposure in mice. DAGL inhibition also prevented ethanol-induced suppression of GABAergic transmission onto midbrain dopamine neurons, providing mechanistic insight into how DAGL inhibition could affect alcohol reward. Lastly, DAGL inhibition during either chronic alcohol consumption or protracted withdrawal was devoid of anxiogenic and depressive-like behavioral effects. These data suggest reducing 2-AG signaling via inhibition of DAGL could represent a novel approach to reduce alcohol consumption across the spectrum of AUD severity.

neuroscience↗