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O'Reilly, Randall Charles Professor

Positions

Research Areas research areas

Research

research overview

  • Dr. O'Reilly's research focuses on biologically-based computational models of learning mechanisms in different brain areas, including hippocampus, prefrontal cortex & basal ganglia, and posterior visual cortex. His models provide a bridge between neuroscience and cognition, using biological mechanisms to explain cognitive function. These models can perform complex cognitive tasks, and thus are also of considerable practical interest (e.g., in robotics or other application domains of artificial intelligence) in their increasing ability to capture important aspects of human intelligence. Currently, individual brain area models are being integrated into an overall cognitive architecture, which is trained in a virtual robotic environment, providing necessary 'embodiment' to the learning process.

keywords

  • computational cognitive neuroscience, neocortex, hippocampus, prefrontal cortex, basal ganglia, learning, memory, executive function, vision, object recognition

Publications

selected publications

Teaching

courses taught

  • PSYC 1001 - General Psychology
    Primary Instructor - Fall 2018
    Provides a foundation for engaging with scientific research on human behavior, and surveys the basic principles and theories of psychology. Topics include biological and hereditary influences on behavior; human perception, attention, learning, and memory; social influences; personality; psychiatric disorders and treatments.
  • PSYC 4011 - Senior Thesis
    Primary Instructor - Fall 2018 / Fall 2019
    Critically reviews some aspect of psychological literature, scholarly analysis of a major psychological issue, and/or empirical research project. See the psychology honors director for further information.
  • PSYC 4175 - Computational Cognitive Neuroscience
    Primary Instructor - Spring 2018 / Spring 2019
    Introduction to cognitive neuroscience (how the brain gives rise to thought) using computer simulations based on the neural networks of the brain. Covers a full range of cognitive phenomena including perception and attention, learning and memory, language, and higher-level cognition based on both large-scale cortical neuroanatomy and detailed properties of cortical neural networks. One lab per week. Same as PSYC 5175.
  • PSYC 5175 - Computational Cognitive Neuroscience
    Primary Instructor - Spring 2018 / Spring 2019
    Introduction to cognitive neuroscience (how the brain gives rise to thought) using computer simulations based on the neural networks of the brain. Covers a full range of cognitive phenomena including perception and attention, learning and memory, language, and higher-level cognition based on both large-scale cortical neuroanatomy and detailed properties of cortical neural networks. One lab per week. Same as PSYC 4175.

Background

International Activities

Other Profiles

Github

  • rcoreilly