Computational Tools & Models

Physiologically-inspired modeling of visual processing and eye movement decisions (here, for faces). Top: Ideal Observer analysis on small patches for mapping spatial distributions of information (Region Of Interest Ideal Observer, RIO). Bottom: Simulating resolution and sensitivity changes across the visual field for predicting the effects of different eye movement strategies on perceptual performance (Foveated Ideal Observer, FIO). Developed from Peterson & Eckstein, 2012.
Physiologically-inspired modeling of visual processing and eye movement decisions (here, for faces). Top: Ideal Observer analysis on small patches for mapping spatial distributions of information (Region Of Interest Ideal Observer, RIO). Bottom: Simulating resolution and sensitivity changes across the visual field for predicting the effects of different eye movement strategies on perceptual performance (Foveated Ideal Observer, FIO). Developed from Peterson & Eckstein, 2012.

Since its inception, the VIU Lab has focused on the development of formal computational and statistical models for the principled, quantitative testing of hypothesized perceptual and cognitive mechanisms. Bayesian models derived from Signal Detection Theory have always comprised the core class of VIU modeling, with Bayesian Ideal Observer theory offering major contributions to many of our lab's papers. More recently, our lab has incorporated models from the exploding fields of computer science and machine learning, with a special emphasis on cutting-edge deep learning methods (e.g., convolutional and recurrent neural networks). Ultimately, we seek coherent unified explanations for cognitive and perceptual phenomena by using computational modeling to instantiate formal, mechanistic, quantitative model of information processing. The grand goal is the discovery of explicit formal models that reliably predict our perceptual experience and decision making (psychophysics), our active information-seeking mechanisms (eye tracking), and the neural computations and representations that give rise to our experiences, beliefs, and actions (neuroimaging and electrophysiology).

 

 

Affiliated Researchers

Researcher
Psychological & Brain Sciences
Medical Imaging and Physics, Mathematics.
Project Scientist
Psychological & Brain Sciences
Institute for Collaborative Biotechnologies
Cognition, Perception, Cognitive Neuroscience, Electrical & Computer Engineering
Postdoctoral Researcher
Psychological & Brain Sciences
Computational Modeling, Artificial Intelligence, Deep Learning, Medical Imaging
Graduate Student Researcher
Electrical & Computer Engineering
Computer Science, Electrical Engineering, Cognition, Perception
Graduate Student Researcher
Psychological & Brain Sciences
Cognition, Perception, Cognitive Neuroscience, Biomedical Engineering
Graduate Student Researcher
Psychological & Brain Sciences
Cognitive Psychology, Cognition, Perception, Cognitive Neuroscience, Economics
Graduate Student Researcher
Psychological & Brain Sciences
Dynamical Neuroscience, Mathematics, Computer Science, Analytics
Graduate Student Researcher
Psychological & Brain Sciences
Psychology, Cognition, Perception, Cognitive Neuroscience
Graduate Student Researcher
Psychological & Brain Sciences
visual linguistic navigation; artificial intelligence; eye movements; computational modeling
Graduate Student Researcher
Psychological & Brain Sciences
Artificial Intelligence; Common Sense Visual Reasoning; Computational Modeling