Modeling Orienting Behavior and Its Disorders with “Ecological” Neural Networks

Modeling Orienting Behavior and Its Disorders with "Ecological" Neural Networks

Computational modeling is a useful tool for spelling out hypotheses in cognitive neuroscience and testing their predictions in artificial systems. Here we describe a series of simulations involving neural networks that learned to perform their task by self-organizing their internal connections. The networks controlled artificial agents with an orienting eye and an arm. Agents saw objects with v...

Atypical neural networks for social orienting in autism spectrum disorders

Autism spectrum disorders (ASD) are characterized by significant social impairments, including deficits in orienting attention following social cues. Behavioral studies investigating social orienting in ASD, however, have yielded mixed results, as the use of naturalistic paradigms typically reveals clear deficits whereas computerized laboratory experiments often report normative behavior. The p...

Behavior Modeling by Neural Networks

Modeling of human and animal behavior is of interest for a number of diagnostic purposes. Convolutional neural networks offer a constructive approach allowing learning on a limited number of examples. Chaotic tendencies make that learning is not always successful. The paper looks into a number of applications to find the reason for this anomaly and identifies the need for behavioral references ...

A Laboratory Study on Stress Dependency of Joint Transmissivity and its Modeling with Neural Networks, Fuzzy Method and Regression Analysis

Correct estimation of water inflow into underground excavations can decrease safety risks and associated costs. Researchers have proposed different methods to asses this value. It has been proved that water transmissivity of a rock joint is a function of factors, such as normal stress, joint roughness and its size and water pressure therefore, a laboratory setup was proposed to quantitatively m...

Modeling and Control of Gas Turbine Combustor with Dynamic and Adaptive Neural Networks (TECHNICAL NOTE)