Protocol to Study Spatial Subgoal Learning Using Escape Behavior in Mice

Abstract

Rodent spatial navigation is a key model system for studying mammalian cognition and its neural mechanisms. Of particular interest is how animals memorize the structure of their environments and compute multi-step routes to a goal. Previous work on multi-step spatial reasoning has generally involved placing rodents at the start of a maze until they learn to navigate to a reward without making wrong turns. It thus remains poorly understood how animals rapidly learn about the structure of naturalistic open environments with goals and obstacles. Here we present an assay in which mice spontaneously memorize two-step routes in an environment with a shelter and an obstacle. We allow the mice to explore this environment for 20 min, and then we remove the obstacle. We then present auditory threat stimuli, causing the mouse to escape to the shelter. Finally, we record each escape route and measure whether it targets the shelter directly (a 'homing-vector' escape) or instead targets the location where the obstacle edge was formerly located (an 'edge-vector' escape). Since the obstacle is no longer there, these obstacle-edge-directed escape routes provide evidence that the mouse has memorized a subgoal location, i.e., a waypoint targeted in order to efficiently get to the shelter in the presence of an obstacle. By taking advantage of instinctive escape responses, this assay probes a multi-step spatial memory that is learned in a single session without pretraining. The subgoal learning phenomenon it generates can be useful not only for researchers working on navigation and instinctive behavior, but also for neuroscientists studying the neural basis of multi-step spatial reasoning.

Keywords: Behavior; Defensive behavior; Escape; Mouse; Navigation; Neuroscience; Spatial memory; Subgoals.

Figure 1.. Shelter + obstacle environment.

A. Schematic of the relative positions of the equipment used to build and record from the shelter + obstacle environment. B. Top view of the behavioral arena. During the obstacle removal experiment, the obstacle panel is replaced with the flat panel, by the experimenter. The suggested threat zone (not visibly marked on the actual platform) is 50 cm long and extends 15 cm from rightmost point of the platform. C. Picture of the platform with the obstacle panel in place and the mouse peeking out of the shelter.

Figure 2.. Classifying escape trajectories.

The initial escape target uses the mouse’s position 10 cm in front of the obstacle (gray and green dots), normalized between 0 (direct path from the escape initiation point to shelter) and 1 (direct path from the escape initiation point to the obstacle edge location). Escape initiation (mouse silhouette on top) is where the mouse’s speed relative to the shelter exceeds 20 cm/s. The dotted line represents the location where the obstacle had been during the 20-min exploration period. A. A homing-vector escape response, with an initial escape target of 0.53. This is less than the threshold value of 0.65 at which point escapes are classified as edge vectors. B. An edge-vector escape response. C. Closeup of the offset distances used to compute the escape target score. Offset_EV (green) is the distance from the mouse to the edge-vector line. Offset_HV (gray) is the distance from the mouse to the homing-vector line. Offset_HV-EV (blue) is the length of the line connecting the edge-vector and homing-vector lines, with the constraint that this line must pass through the average of the two vectors at the point 10 cm in front of the obstacle (i.e., it must pass through the point corresponding to an escape target score of 0.5). Figure adapted from Shamash and Branco (2021).