Nature Human BehaviourNeurosciencePeer-reviewed journal article
Electrophysiological signatures of veridical head direction in humans
Benjamin James GriffithsiD, Thomas SchreineriD, Julia K. SchaeferiD, Christian VollmariD, Elisabeth KaufmanniD, Stefanie QuachiD, Jan RémiiD, Soheyl NoachtariD, Tobias StaudigliD
Abstract
Information about heading direction is critical for navigation as it provides the means to orient ourselves in space. However, given that veridical head direction signals require physical rotation of the head and most human neuroimaging experiments depend upon fixing the head in position, little is known about how the human brain is tuned to such heading signals. To address this, we asked fifty-two healthy participants undergoing simultaneous EEG and motion tracking recordings (split into two experiments) and ten patients undergoing simultaneous intracranial EEG and motion tracking recordings to complete a series of orientation tasks in which they made physical head rotations to target positions. We then used a series of forward encoding models and linear mixed-effects models to isolate electrophysiological activity that was specifically tuned to heading direction. We identified a robust posterior central signature that predicts changes in veridical head orientation after regressing out confounds including sensory input and muscular activity. Both source localisation and intracranial analysis implicated the medial temporal lobe as the origin of this effect. Subsequent analyses disentangled head direction signatures from signals relating to head rotation and those reflecting location-specific effects. Lastly, when directly comparing head direction and eye gaze-related tuning, we found that the brain maintains both codes while actively navigating, with stronger tuning to head direction in the medial temporal lobe. Together, these results reveal a taxonomy of population-level head direction signals within the human brain that is reminiscent of those reported in the single units of rodents.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 12
- FWCI
- 2.67
- Field percentile
- top 10%
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