$$\rightleftharpoonup{xx}$$
$$\longleftharp{xx}$$,
$$\longrightharp{xx}$$,
Studying the relation between neurophysiology and behavior is the ultimate goal in systems neuroscience. Historically, there has been a tradeoff between animal model choice and behavioral repertoire1-5. While simple organisms like sea slugs6 or squids7 have been used extensively to study properties of single ion channels, neurons and simple neural circuits, higher order species are needed to study more complex functions such as spatial navigation, decision making8-11 and cognitive control12-14. Despite being a standard animal model for human like behavior, use of nonhuman primates prompts cost and ethical considerations that precludes their use across a wide range of experiments in a single laboratory setting15-18. Simpler animal models such as rodents are generally preferred19, provided they have similar neural substrates underlying the behaviors of interest.
There's ample evidence suggesting that rodents share similar cortical and subcortical structures as those found in primates20-22. Rodents are also known to integrate information across multiple sensory modalities to guide their action23-25, for example, by coordinating whisking and sniffing during exploratory behavior26 or by integrating auditory and visual/olfactory events25,27.
Here we describe a framework for operant conditioning of rodents used to test cognitive tasks28-32. In this framework, subjects are required to fixate inside a nosepoke hole and maintain their snout inside the hole until the presentation of a go cue. The behavioral task is a five-hole nosepoke design that is conventionally used for 5-choice serial reaction time task studies. During the delay period, a range of instruction cues is presented to guide the subject to perform an action. This framework can easily be modified to suit a wide range of experiments in which training the subject to minimize its overt movement over a brief interval is needed. This permits studying the extent to which spiking activity of individual neurons is affected by specific cues during this interval. The protocol can minimize the training time and can reduce across-subject learning variability. A schematic flowchart of the task is shown in Figure 1.