A New Experimental Paradigm for the Investigation of the Secondary System of Human Visual Motion Perception

Perception ◽  
1973 ◽  
Vol 2 (2) ◽  
pp. 167-180 ◽  
Author(s):  
C Lamontagne
Keyword(s):  
Computational Model ◽  
Motion Perception ◽  
Apparent Motion ◽  
Visual Motion ◽  
Experimental Paradigm ◽  
Secondary System ◽  
Visual Motion Perception ◽  
New Family ◽  
The Subject ◽  
Object Relative

An experimental paradigm is derived from a computational model of visual motion perception. The new family of phenomena that support this paradigm is presented in the context of the model. The basic phenomenon can be considered as being the apparent motion and the sustained eyetracking of a physically still object (relative to the subject) in the absence of any other object moving relative to the subject.

A computational model for human visual motion perception system

1999 ◽  
Vol 32 (2) ◽  
pp. 5117-5122
Author(s):  
Huimin Lu ◽  
Shouzhong Liu ◽  
Meide Shi ◽  
Xiuchun Wang ◽  
Aike Guo
Keyword(s):  
Computational Model ◽  
Motion Perception ◽  
Visual Motion ◽  
Visual Motion Perception ◽  
Perception System

Role of the Vermal Cerebellum in Visually Guided Eye Movements and Visual Motion Perception

2019 ◽  
Vol 5 (1) ◽  
pp. 247-268 ◽  
Author(s):  
Peter Thier ◽  
Akshay Markanday
Keyword(s):  
Eye Movements ◽  
Motion Perception ◽  
Visual Motion ◽  
Cerebellar Nuclei ◽  
Visually Guided ◽  
Past Performance ◽  
Visual Motion Perception ◽  
Oculomotor Vermis ◽  
Retinal Information

The cerebellar cortex is a crystal-like structure consisting of an almost endless repetition of a canonical microcircuit that applies the same computational principle to different inputs. The output of this transformation is broadcasted to extracerebellar structures by way of the deep cerebellar nuclei. Visually guided eye movements are accommodated by different parts of the cerebellum. This review primarily discusses the role of the oculomotor part of the vermal cerebellum [the oculomotor vermis (OMV)] in the control of visually guided saccades and smooth-pursuit eye movements. Both types of eye movements require the mapping of retinal information onto motor vectors, a transformation that is optimized by the OMV, considering information on past performance. Unlike the role of the OMV in the guidance of eye movements, the contribution of the adjoining vermal cortex to visual motion perception is nonmotor and involves a cerebellar influence on information processing in the cerebral cortex.

scholarly journals Human visual motion perception shows hallmarks of Bayesian structural inference

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sichao Yang ◽  
Johannes Bill ◽  
Jan Drugowitsch ◽  
Samuel J. Gershman
Keyword(s):  
Motion Perception ◽  
Visual Motion ◽  
Probabilistic Reasoning ◽  
Choice Model ◽  
Human Motion ◽  
Object Motion ◽  
Ideal Observer ◽  
Structure Identification ◽  
Structural Inference ◽  
Visual Motion Perception

AbstractMotion relations in visual scenes carry an abundance of behaviorally relevant information, but little is known about how humans identify the structure underlying a scene’s motion in the first place. We studied the computations governing human motion structure identification in two psychophysics experiments and found that perception of motion relations showed hallmarks of Bayesian structural inference. At the heart of our research lies a tractable task design that enabled us to reveal the signatures of probabilistic reasoning about latent structure. We found that a choice model based on the task’s Bayesian ideal observer accurately matched many facets of human structural inference, including task performance, perceptual error patterns, single-trial responses, participant-specific differences, and subjective decision confidence—especially, when motion scenes were ambiguous and when object motion was hierarchically nested within other moving reference frames. Our work can guide future neuroscience experiments to reveal the neural mechanisms underlying higher-level visual motion perception.

Sign in / Sign up

Export Citation Format

Share Document