ArticleBiological cybernetics2017
A spiking neural network model of the midbrain superior colliculus that generates saccadic motor commands.
Article in Biological cybernetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Neural encoding of instantaneous kinematics of eye-head gaze shifts in monkey superior Colliculus.Communications biology · 2023Article
- Dual STDP processes at Purkinje cells contribute to distinct improvements in accuracy and speed of saccadic eye movements.PLoS computational biology · 2022Article
- A spiking neural network model of the Superior Colliculus that is robust to changes in the spatial-temporal input.Scientific reports · 2022Article
- Functional connectome of brainstem nuclei involved in autonomic, limbic, pain and sensory processing in living humans from 7 Tesla resting state fMRI.NeuroImage · 2022Article
- Dynamic control of eye-head gaze shifts by a spiking neural network model of the superior colliculus.Frontiers in computational neuroscience · 2022Article
- Recognition of Volleyball Player's Arm Motion Trajectory and Muscle Injury Mechanism Analysis Based upon Neural Network Model.Journal of healthcare engineering · 2022Article
- Frontal eye field inactivation alters the readout of superior colliculus activity for saccade generation in a task-dependent manner.Journal of computational neuroscience · 2021Article
- Spatiotemporal factors influence sound-source segregation in localization behavior.Journal of neurophysiology · 2021Article
- Noise suppression ability and its mechanism analysis of scale-free spiking neural network under white Gaussian noise.PloS one · 2020Article
- Microstimulation in a spiking neural network model of the midbrain superior colliculus.PLoS computational biology · 2019Article
- Maps and sensorimotor transformations for eye-head gaze shifts: Role of the midbrain superior colliculus.Progress in brain research · 2019Article
- Electrical stimulation in a spiking neural network model of monkey superior colliculus.Progress in brain research · 2019Article
- Neurophysiology of visually guided eye movements: critical review and alternative viewpoint.Journal of neurophysiology · 2018Review
- Instantaneous Midbrain Control of Saccade Velocity.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2018Article
- Dynamic parallelism for synaptic updating in GPU-accelerated spiking neural network simulations.Neurocomputing · 2018Article
- Modeling auditory-visual evoked eye-head gaze shifts in dynamic multisteps.Journal of neurophysiology · 2018Article
- Double Stimulation in a Spiking Neural Network Model of the Midbrain Superior Colliculus.Frontiers in applied mathematics and statistics · 2018Article
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2 authors.
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Abstract
Single-unit recordings suggest that the midbrain superior colliculus (SC) acts as an optimal controller for saccadic gaze shifts. The SC is proposed to be the site within the visuomotor system where the nonlinear spatial-to-temporal transformation is carried out: the population encodes the intended saccade vector by its location in the motor map (spatial), and its trajectory and velocity by the distribution of firing rates (temporal). The neurons' burst profiles vary systematically with their anatomical positions and intended saccade vectors, to account for the nonlinear main-sequence kinematics of saccades. Yet, the underlying collicular mechanisms that could result in these firing patterns are inaccessible to current neurobiological techniques. Here, we propose a simple spiking neural network model that reproduces the spike trains of saccade-related cells in the intermediate and deep SC layers during saccades. The model assumes that SC neurons have distinct biophysical properties for spike generation that depend on their anatomical position in combination with a center-surround lateral connectivity. Both factors are needed to account for the observed firing patterns. Our model offers a basis for neuronal algorithms for spatiotemporal transformations and bio-inspired optimal controllers.
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