NemoTrainer: Automated Conditioning for Stimulus-Directed Navigation and Decision Making in Free-Swimming Zebrafish.
Animals (Basel) 2022;
13:ani13010116. [PMID:
36611725 PMCID:
PMC9817937 DOI:
10.3390/ani13010116]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 12/20/2022] [Accepted: 12/22/2022] [Indexed: 12/29/2022] Open
Abstract
Current methods for associative conditioning in animals involve human intervention that is labor intensive, stressful to animals, and introduces experimenter bias in the data. Here, we describe a simple apparatus and a flexible, microcontroller-based conditioning paradigm that minimizes human intervention. Our methodology exploits directed movement towards a target that depends on spatial working memory, including processing of sensory inputs, motivational drive, and attentional mechanisms. Within a stimulus-driven conditioning paradigm designed to train zebrafish, we present a localized pulse of light via LEDs and/or sounds via an underwater transducer. A webcam placed below a glass tank records fish-swimming behavior. For classical conditioning, animals simply associate a sound or light with an unconditioned stimulus, such as a small food reward presented at a fixed location, and swim towards that location to obtain a few grains of food dispensed automatically via a sensor-triggered, stepper motor. During operant conditioning, a fish must first approach a proximity sensor at a remote location and then swim to the reward location. For both types of conditioning, a timing-gated interrupt activates stepper motors via custom software embedded within a microcontroller (Arduino). "Ardulink", a Java facility, implements Arduino-computer communication protocols. In this way, a Java-based user interface running on a host computer can provide full experimental control. Alternatively, a similar level of control is achieved via an Arduino script communicating with an event-driven application controller running on the host computer. Either approach can enable precise, multi-day scheduling of training, including timing, location, and intensity of stimulus parameters; and the feeder. Learning can be tracked by monitoring turning, location, response times, and directional swimming of individual fish. This facilitates the comparison of performance within and across a cohort of animals. Our scheduling and control software and apparatus ("NemoTrainer") can be used to study multiple aspects of species-specific behaviors as well as the effects on them of various interventions.
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