SIU Vision Lab

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About the SIUC Vision Lab

The SIUC Vision lab investigates cognitive development and adaptive behavior in both humans and autonomous artificial agents. There are three major ongoing research projects:

Visual attention and spatial working memory. Several current research studies are investigating how infants, children, and adults use both memory and visual skill to guide their attention across space and time. We also study how people divide their attention while working on two or more simultaneous tasks. As noted below, this work is complemented by a number of computer models that simulate eye-movement activity in real time.

Neural network models of vision and oculomotor control. In collaboration with Dima Amso (Brown University) and Scott Johnson (UCLA), we also design and test computer models of early visual processing and oculomotor control. These models have three important features:

  1. Biological inspiration: the architectures and learning algorithms used in these models are inspired by the anatomy and physiology of the mammalian visual system
  2. Embodied knowledge: these models are designed with simple physical bodies, which enable them to interact with and learn from their environment--a critical element of robotics and machine learning models that must deal with noisy or uncertain environments
  3. Realtime performance: although current modeling work is computer-simulated, the goal of each model is to reproduce behavior (e.g., eye movements, hand and arm movements) as it unfolds in real time

Developmental cognitive neuroscience. A third project uses neural-imaging methods (e.g., fMRI) to investigate the neural substrates of working memory and spatial-directed attention. This work not only informs the computer models that are being developed, but it is also shaped and influenced by the results of the modeling work.