Abstract

The subcortical saccade-generating system consists of the retina, superior colliculus, cerebellum and brainstem motoneuron areas. The superior colliculus is the site of sensory-motor convergence within this basic visuomotor loop preserved throughout the vertebrates. While the system has been extensively studied, there are still several outstanding questions regarding how and where the saccade eye movement profile is generated and the contribution of respective parts within this system. Here we construct a spiking neuron model of the whole intermediate layer of the superior colliculus based on the latest anatomy and physiology data. The model consists of conductance-based spiking neurons with quasi-visual, burst, buildup, local inhibitory, and deep layer inhibitory neurons. The visual input is given from the superficial superior colliculus and the burst neurons send the output to the brainstem oculomotor nuclei. Gating input from the basal ganglia and an integral feedback from the reticular formation are also included.We implement the model in the NEST simulator and show that the activity profile of bursting neurons can be reproduced by a combination of NMDA-type and cholinergic excitatory synaptic inputs and integrative inhibitory feedback. The model shows that the spreading neural activity observed in vivo can keep track of the collicular output over time and reset the system at the end of a saccade through activation of deep layer inhibitory neurons. We identify the model parameters according to neural recording data and show that the resulting model recreates the saccade size-velocity curves known as the saccadic main sequence in behavioral studies. The present model is consistent with theories that the superior colliculus takes a principal role in generating the temporal profiles of saccadic eye movements, rather than just specifying the end points of eye movements.

Highlights

  • The mammalian visuomotor system is one of the best studied model systems for elucidating the computational principles of movement control and their neural implementation mechanisms

  • It is composed of the superficial superior colliculus (SC), four functional neuron types in the intermediate SC, the central mesencephalic reticular formation (cMRF) integrator, and a generic inhibitory input marked as substantia nigra pars reticulata (SNpr)

  • The first is the activation of burst neurons by NMDA-type input from the QV neurons and the cholinergic input from the buildup neurons and the subsequent recurrent inhibition from the cMRF integrator neurons

Read more

Summary

Introduction

The mammalian visuomotor system is one of the best studied model systems for elucidating the computational principles of movement control and their neural implementation mechanisms. There have been a variety of models of the SC in visuomotor control from abstract linear system models to detailed models incorporating the anatomical and physiological reality [4]. Computational models of the SC to date, mostly consider population firing rates and continuous neural field approximation and do not allow investigating the spike-level computation and neurobiological mechanisms. The aim of this study is to construct a realistic spiking neuron model of the SC that allows us to bring together the behavioral functions of eye movements, the anatomy and physiology of the SC circuit, and the biophysical properties of the SC neurons

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.