Weighted cue integration in the rodent head direction system

Abstract

How the brain combines information from different sensory modalities and of differing reliability is an important and still-unanswered question. Using the head direction (HD) system as a model, we explored the resolution of conflicts between landmarks and background cues. Sensory cue integration models predict averaging of the two cues, whereas attractor models predict capture of the signal by the dominant cue. We found that a visual landmark mostly captured the HD signal at low conflicts: however, there was an increasing propensity for the cells to integrate the cues thereafter. A large conflict presented to naive rats resulted in greater visual cue capture (less integration) than in experienced rats, revealing an effect of experience. We propose that weighted cue integration in HD cells arises from dynamic plasticity of the feed-forward inputs to the network, causing within-trial spatial redistribution of the visual inputs onto the ring. This suggests that an attractor network can implement decision processes about cue reliability using simple architecture and learning rules, thus providing a potential neural substrate for weighted cue integration.

Keywords: attractor dynamics; head direction cells; path integration; sensory cue integration; vestibular system; vision.

Figure 1.

The experimental protocol. (a) Photograph of the apparatus, showing the light cue behind the translucent wall of the arena. (b) A schematic drawing of the experimental protocol for the 60° conflict condition from Experiment 1. The position of the two lights is shown by the thick arrows (white arrows represent when the light is on and black arrows represent when the light is off). Each trial lasted for 4 min and between each trial the rat foraged in darkness for 10 s (thin arrows).

Figure 2.

Five polar plots of one cell recorded from Rat 321 (PoS implant) during 120° light conflict session in Experiment 1. The white (light on) and black (light off) arrows represent the two torches separated by 120°. Note that the HD cell in this example rotates by approximately 110° between trials, in the same direction as the light.

Figure 3.

(a–f) Plots showing the breakdown of mean ensemble shifts for each trial within a session in Experiment 1. Separate plots indicate each of the six rats. Each data point represents the mean ensemble shift from one trial to the next. Thus, there are two points for each light rotation (two light shifts per session). The diagonal y = x line indicates the amount the light shifted for each session. The filled circles show rotations in the standard (clockwise) direction, while open triangles indicate the mean ensemble firing shift during the probe trials, when the landmark was rotated in the anticlockwise direction.

Figure 4.

Plot showing the relationship between the expected shifts in degrees of the HD cells based on the light shift (dashed line) and the actual mean ensemble firing shift (solid line; error bars show s.e.m as a % of light shift) across each session. The dotted line represents the actual mean ensemble firing shift using data from only the last 2 min of each trial.

Figure 5.

Plot comparing the mean (±s.e.m.) ensemble firing shift of HD cells from Experiment 1 and Experiment 2 during a 140° light shift. The dashed line indicates the degree of light rotation (140°).