Models of MT and MST areas using wake-sleep algorithm. 2004

Katsuki Katayama, and Masataka Ando, and Tsuyoshi Horiguchi
Research Institute of Electrical Communication, Tohoku University, Sendai 980-8577, Japan.

We present two-layered neural network models with Q (> or =2)-states neurons for a system with middle temporal (MT) neurons and medial superior temporal (MST) neurons by using a wake-sleep algorithm proposed by Hinton et al.; we notice that the wake-sleep algorithm consists of local learning rules. We first investigate a model with binary neurons for response properties of the MST neurons to optical flows as for various types of motion. We next extend the model with binary neurons to a model with Q (> or =3)-states neurons and investigate the response properties of the MST neurons for various values of Q (> or =3). We obtain better response properties for the model with Q (> or =3)-states neurons than for the one with binary neurons.

UI MeSH Term Description Entries
D009039 Motion Perception The real or apparent movement of objects through the visual field. Movement Perception,Perception, Motion,Perception, Movement
D009474 Neurons The basic cellular units of nervous tissue. Each neuron consists of a body, an axon, and dendrites. Their purpose is to receive, conduct, and transmit impulses in the NERVOUS SYSTEM. Nerve Cells,Cell, Nerve,Cells, Nerve,Nerve Cell,Neuron
D010775 Photic Stimulation Investigative technique commonly used during ELECTROENCEPHALOGRAPHY in which a series of bright light flashes or visual patterns are used to elicit brain activity. Stimulation, Photic,Visual Stimulation,Photic Stimulations,Stimulation, Visual,Stimulations, Photic,Stimulations, Visual,Visual Stimulations
D003198 Computer Simulation Computer-based representation of physical systems and phenomena such as chemical processes. Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D000465 Algorithms A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task. Algorithm
D000818 Animals Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA. Animal,Metazoa,Animalia
D012890 Sleep A readily reversible suspension of sensorimotor interaction with the environment, usually associated with recumbency and immobility. Sleep Habits,Sleeping Habit,Sleeping Habits,Habit, Sleep,Habit, Sleeping,Habits, Sleep,Habits, Sleeping,Sleep Habit
D014793 Visual Cortex Area of the OCCIPITAL LOBE concerned with the processing of visual information relayed via VISUAL PATHWAYS. Area V2,Area V3,Area V4,Area V5,Associative Visual Cortex,Brodmann Area 18,Brodmann Area 19,Brodmann's Area 18,Brodmann's Area 19,Cortical Area V2,Cortical Area V3,Cortical Area V4,Cortical Area V5,Secondary Visual Cortex,Visual Cortex Secondary,Visual Cortex V2,Visual Cortex V3,Visual Cortex V3, V4, V5,Visual Cortex V4,Visual Cortex V5,Visual Cortex, Associative,Visual Motion Area,Extrastriate Cortex,Area 18, Brodmann,Area 18, Brodmann's,Area 19, Brodmann,Area 19, Brodmann's,Area V2, Cortical,Area V3, Cortical,Area V4, Cortical,Area V5, Cortical,Area, Visual Motion,Associative Visual Cortices,Brodmanns Area 18,Brodmanns Area 19,Cortex Secondary, Visual,Cortex V2, Visual,Cortex V3, Visual,Cortex, Associative Visual,Cortex, Extrastriate,Cortex, Secondary Visual,Cortex, Visual,Cortical Area V3s,Extrastriate Cortices,Secondary Visual Cortices,V3, Cortical Area,V3, Visual Cortex,V4, Area,V4, Cortical Area,V5, Area,V5, Cortical Area,V5, Visual Cortex,Visual Cortex Secondaries,Visual Cortex, Secondary,Visual Motion Areas
D014851 Wakefulness A state in which there is an enhanced potential for sensitivity and an efficient responsiveness to external stimuli. Wakefulnesses
D016571 Neural Networks, Computer A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming. Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron

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