Spatiotemporal properties of microsaccades: Model predictions and experimental tests

• Published in: Scientific reports 2016-10, Vol.6 (1), p.35255-35255, Article 35255
• Main Authors: Zhou, Jian-Fang, Yuan, Wu-Jie, Zhou, Zhao
• Format: Article
• Language: English
• Subjects: 639/705/1042; 639/766/530/2801; 639/766/530/2803; Adaptation; Attention - physiology; Behavior; Cerebral cortex; Eye; Fixation, Ocular - physiology; Humanities and Social Sciences; Humans; Models, Neurological; Models, Theoretical; multidisciplinary; Nervous system; Neural networks; Neurons - physiology; Retina; Saccades - physiology; Science; Short-term depression; Statistical analysis; Synapses; Synaptic depression; Thalamus; Visual Perception - physiology
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/srep35255

Microsaccades are involuntary and very small eye movements during fixation. Recently, the microsaccade-related neural dynamics have been extensively investigated both in experiments and by constructing neural network models. Experimentally, microsaccades also exhibit many behavioral properties. It’s well known that the behavior properties imply the underlying neural dynamical mechanisms, and so are determined by neural dynamics. The behavioral properties resulted from neural responses to microsaccades, however, are not yet understood and are rarely studied theoretically. Linking neural dynamics to behavior is one of the central goals of neuroscience. In this paper, we provide behavior predictions on spatiotemporal properties of microsaccades according to microsaccade-induced neural dynamics in a cascading network model, which includes both retinal adaptation and short-term depression (STD) at thalamocortical synapses. We also successfully give experimental tests in the statistical sense. Our results provide the first behavior description of microsaccades based on neural dynamics induced by behaving activity, and so firstly link neural dynamics to behavior of microsaccades. These results indicate strongly that the cascading adaptations play an important role in the study of microsaccades. Our work may be useful for further investigations of the microsaccadic behavioral properties and of the underlying neural dynamical mechanisms responsible for the behavioral properties.