Hippocampal brain-machine interface-based navigation reveals CA1 representations of intended actions

Abstract

The hippocampus integrates external cues and self-motion to construct cognitive maps. Activating these maps independently of immediate sensory and motor signals can support navigation by predicting future locations. The neural basis of such internally driven activation remains poorly understood. To address this, we had mice use a brain-machine interface (BMI) to directly control navigation from real-time hippocampal activity. In this condition, CA1 responses encoding running movement were not navigationally relevant, and place codes rapidly reconfigured to form new representations that discarded locomotion-related signals. By comparing neural representations across BMI-controlled navigation, locomotion-controlled navigation, and passive playback of predetermined routes, we found evidence of response patterns that were specific to conditions in which neural activity could causally influence an animals travel. This suggests the existence of CA1 responses that are not tied to external stimuli or self-motion, and that are suppressed when animals are merely passive observers.