P111 A model of 3D eye movements reflecting spatial orientation estimation
Yusuke Shinji1,Yutaka Hirata*2,3,4
1. Dept. Computer Science, Chubu Univ. Graduate School of Engineering, Kasugai, Japan
2. Dept. AI and Robotics, Chubu Univ. College of Science and Engineering, Kasugai, Japan
3. Center for mathematical science and artificial intelligence, Chubu Univ., Kasugai, Japan
4. Chubu University Academy of Emerging Sciences, Chubu Univ., Kasugai, Japan
*Email: yutaka@isc.chubu.ac.jp
Introduction
Spatial orientation (SO) refers to the estimated self-motion state, formed by integrating multiple sensory inputs. Accurate SO formation is crucial for animals to navigate safely through their environment. However, errors in SO estimation can occur, leading to spatial disorientation (SDO).A typical example of SDO is the somatogravic illusion, in which a forward linear acceleration is erroneously perceived as an upward tilt. The vestibulo-ocular reflex (VOR) is driven by the estimated head motion, generating counter-rotations of the eyes to stabilize vision. Thus, the VOR is a reflection of SO, particularly of head motion states. Currently, we developed a 3D VOR model to elucidate the neural algorithms underlying SO formation.
Methods
The model was configured within the Kalman filter (KF) framework, which estimates hidden physical states from noisy sensor data. In this framework, active 3D head motion is the input to the sensors while passive head motion and 3D visual motion are treated as process noise. These motions are detected by the otolith, semicircular canals, and retina whose outputs are transmitted to the brain. The KF incorporates corresponding sensor models that generate sensory predictions, which are compared with actual sensory outputs. The resulting sensory prediction errors are used to update the estimated head motion state through the KF algorithm.The VOR eye velocity is then produced in the opposite direction to the 3D head motion estimate.
Results
To evaluate the model, we first simulated the somatogravic illusion in goldfish that we recently discovered [1]. The model successfully reproduced the goldfish 3D VOR reflecting somatogravic illusion.Specifically, in the KF, lateral linear head acceleration was misestimated as head roll tilt, resulting in a vertical VOR in goldfish, while head roll tilt motion was correctly estimated as roll tilt.Next, we simulated two representative human vestibular illusions: Off-vertical axis rotation at a constant angular velocity, and Post-rotatory tilt after earth-vertical axis rotation. In both cases, the model misestimated linear head acceleration, reproducing known perceptual errors in humans.
Discussion
These results suggest that our 3D VOR KF model effectively captures the neural computational mechanisms underlying SO formation from noisy sensory signals.Previous studies have demonstrated the cerebellar nodulus and uvula play a critical role in SO formation, specifically in distinguishing head tilt against gravity from head linear translational acceleration [2].As a next step we investigate how the well-characterized cerebellar neuronal circuitry and its synaptic learning rules implement the KF algorithm, utilizing our artificial cerebellum [3]. Understanding this relationship will provide insights into how the brain optimally estimates self-motion and resolves sensory ambiguities.
Acknowledgements
Supported by JST CREST (Grant Number: JPMJCR22P5) and JSPS KAKENHI (Grant Number: 24H02338)
References
1. Tadokoro, S., Shinji, Y., Yamanaka, T., Hirata, Y. (2024). Learning capabilities to resolve tilt-translation ambiguity in goldfish.Front Neurol, 15:1304496. https://10.3389/fneur.2024.1304496
2. Laurens, J. (2022). The otolith vermis: A systems neuroscience theory of the Nodulus and Uvula.Front Neurosci, 16:886284. https://10.3389/fnsys.2022.886284
3. Shinji, Y., Okuno, T., Hirata, Y. (2024). Artificial cerebellum on FPGA: realistic real-time cerebellar spiking neural network model capable of real-world adaptive motor control.Front Neurosci, 18:1220908. https://10.3389/fnins.2024.1220908
