Ph.D., Psychology and Cognitive Science with additional Certificate in Modeling in Cognitive Science, March 2009.
Specialized Coursework: cognitive neuroscience, computational neuroscience, neuropsychology, philosophical foundations of cognitive science, dynamical systems, mathematical psychology, partial differential equations
M.S., Computer Science, June 1995.
Specialized Coursework: artificial intelligence, neurocomputation, pattern recognition, speech recognition, intelligent systems
B.S., Computer Engineering, May 1993.
Charter Class, June 1989.
computational cognitive neuroscience: executive / volitional processing, affective processing, learning, motor control, attention, embodied cognition, spatiotemporal pattern recognition, language processing; artificial intelligence / robotics; brain-machine interfaces
Advisor: Dr. William Lytton
Worked on DARPA collaborative effort involving development of brain-machine interface (BMI) technology for neuroprosthetic devices. The focus of the Lytton lab on this grant was development of realistic "in-silico brain" models to be integrated with BMI systems. Developed a NEURON-based model of reinforcement learning in primary motor cortex (M1) for controlling a virtual arm. Developed a NEURON-based multilayer spiking model of M1 based on mouse M1 connectivity data. Began development of socket interface between NEURON simulation model and Barrett Technologies Whole Arm Manipulator (WAM) robotic arm. Began development of a Python framework for building network models in NEURON. (May 2010-Sept. 2013).
Advisor: Dr. Olaf Sporns
In doctoral dissertation, A Neurocomputational Model of the Functional Role of Dopamine in Stimulus-Response Task Learning and Performance, developed an integrative theory and corresponding model of neural substrate and dopaminergic mechanisms for reinforcement learning of simple stimulus-response tasks.
Developed a neurocomputational model (using MATLAB) to investigate tonic dopaminergic mechanisms of task-oriented behavior selection and working memory in prefrontal cortex. Coauthored publication with Dr. Sporns for Journal of Cognitive Neuroscience. (May 2002-Feburary 2006)
Designed and developed hidden Markov model-based speech recognition / natural language understanding software and created Java GUI for demo prototype for a voice-controlled jukebox system. (1999)
Research and development of algorithms for phoneme segmentation, signal detection and classification, target tracking, and threat evaluation for defense and commercial applications. Methodologies: neural networks, evolutionary programming, fuzzy logic, hidden Markov models, Kalman filtering. Coauthored 2 SBIRs and 4 conference papers. (1994-1999)
Conducted research and coauthored and presented paper on audiovisual lip-reading digit-recognition using hidden Markov modeling and linear predictive coding. (Paper coauthored with Dr. Movellan.) (1994)
SUNY Downstate Medical Center School of Graduate Studies Annual Research Partial Travel Fellowship (2012), Indiana University Cognitive Science Program Summer Research Fellowships (5/2005-9/2005, 5/2006-9/2006), National Institute of Health training grant fellowship in Modeling in Cognition (9/2002-8/2003, 9/2004-8/2005), Toastmasters International CTM, Edmund James Scholar (1989/1990, 1990/1991), Dean's List (1989/1990, Fall 1990, Spring 1993).
Chadderdon, G. L., & Sporns, O. (2006). A large-scale neurocomputational model of task-oriented behavior selection and working memory in prefrontal cortex. Journal of Cognitive Neuroscience, 18(2), 242-257. (PDF online here)
Chadderdon, G. L. (2008). Assessing machine volition: an ordinal scale for rating artificial and natural systems. Adaptive Behavior, 16(4), 246-263. (preprint version PDF online here, supplementary materials PDF)
Kerr, C. C., Neymotin, S. A., Chadderdon, G. L., Fietkiewicz, C. T., Francis, J. T., & Lytton, W. W. (2012). Electrostimulation as a prosthesis for repair of information flow in a computer model of neocortex. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 20(2), 153-160 (PDF online here).
Chadderdon, G. L., Neymotin, S. A., Kerr, C. C., & Lytton, W. W. (2012). Reinforcement learning of targeted movement in a spiking neuronal model of motor cortex. PLoS ONE, 7(10): e47251.
Kerr, C. C., Van Albada, S.J., Neymotin, S. A., Chadderdon, G. L., Robinson, P. A., & Lytton, W. W. (2013). Cortical information flow in Parkinson's disease: a composite network/field model. Frontiers in Computational Neuroscience, 7:39.
Neymotin, S. A., Chadderdon, G. L., Kerr, C. C., Francis, J. T., & Lytton, W. W. (2013). Reinforcement learning of two-joint virtual arm reaching in a computer model of sensorimotor cortex. Neural Computation. (PDF online here)
Dura-Bernal, S., Chadderdon, G. L., Neymotin, S. A., Francis, J. T., & Lytton, W. W. (2013). Towards a real-time interface between a biomimetic model of sensorimotor cortex and a robotic arm. Pattern Recognition Letters: Special Issue on Multimodal Interfaces. (PDF online here)
Chadderdon, G., & Movellan, J. R. (1995). Testing for channel independence in bimodal speech recognition. In Proceedings of the 2nd Joint Symposium on Neural Computation, University of California, San Diego and California Institute of Technology (pp. 84-90). San Diego, CA: University of California, San Diego.
Brotherton, T. W., & Chadderdon, G. (1998). Automated rule extraction for engine health monitoring. In V. W. Porto, N. Saravanan, D. Waagen & A. E. Eiben (Eds.), Evolutionary Programming VII: Proceedings of the 7th International Conference, EP98, San Diego, California, March 1998 (pp. 725-734). New York, NY: Springer.
Brotherton, T., Johnson, T., & Chadderdon, G. (1998). Classification and novelty detection using linear models and a class-dependent elliptical basis function neural network. In Proceedings of International Joint Conference on Neural Networks, Anchorage, Alaska, May 1998.
Brotherton, T., Chadderdon, G., & Graybill, P. (1999). Automated rule extraction for engine vibration analysis. In Proceedings of the IEEE Aerospace Conference, Aspen, Colorado, March 1999.
Shea, P., Owen, M., & Chadderdon, G. (1999). Fuzzy control in the deployable autonomous distributed system. In Proceedings of SPIE: Signal Processing, Sensor Fusion, and Target Recognition VIII, Orlando, Florida, 1999.
Sporns, O., Bulwinkle, D., Chadderdon, G., & Alexander, W. H. (2003). Neuro-robotic models of learning and addiction. NIH Symposium (Biomedical Information Science and Technology Initiative) Digital Biology: The Emerging Paradigm, Bethesda, Maryland, November 2003.
Chadderdon, G., & Sporns, O. (2003). A large-scale network model of working memory and neuromodulation. Society for Neuroscience (abstract and poster).
Chadderdon, G., & Sporns, O. (2005). A large-scale neurocomputational model of task-oriented behavior selection and working memory in prefrontal cortex. Society for Neuroscience (abstract and poster).
Kerr, C. C., Fietkiewicz, C. T., Chadderdon, G. L., Neymotin, S. A., & Lytton, W. W. (2010). Development of in silico brain for DARPA REPAIR project. DARPA Neural Engineering, Science, and Technology Meeting (poster).
Neymotin, S. A., Kerr, C. C., Fietkiewicz, C. T., Chadderdon, G. L., & Lytton, W. W. (2011). Spike-timing-dependent plasticity and subcortical waves enhance alpha oscillations in a computer model of neocortex. Neuroinformatics (abstract and poster).
Neymotin, S. A., Kerr, C. C., Chadderdon, G. L., Francis, J. T., & Lytton, W. W. (2011). Restoring physiological oscillations using neuroprosthetic spike-timing-dependent plasticity in computer model of neocortex. Society for Neuroscience (abstract and poster).
Lytton, W. W., Neymotin, S. A., Chadderdon, G. L., Kerr, C. C., & Francis, J. T. (2012). Reinforcement learning of 2-joint virtual arm reaching in detailed cortex simulation. Neural Control of Movement (abstract and poster).
Chadderdon, G. L., Neymotin, S. A., Kerr, C. C., Francis, J. T., & Lytton, W. W. (2012). Dopamine-based reinforcement learning of virtual arm reaching task in a spiking model of motor cortex. International Conference on Cognitive and Neural Systems 16 (abstract and poster).
Neymotin, S. A., Chadderdon, G. L., Kerr, C. C., Francis, J. T., & Lytton, W. W. (2012). Reinforcement learning of 2-joint virtual arm reaching in motor cortex simulation. Computational Neuroscience (abstract and poster).
Chadderdon, G. L., Neymotin, S. A., Kerr, C. C., Francis, J. T., & Lytton, W. W. (2012). Dopamine-based reinforcement learning of virtual arm reaching task in a spiking model of motor cortex. Society for Neuroscience (abstract and poster).
Neymotin, S. A., Chadderdon, G. L., Kerr, C. C., Francis, J. T., & Lytton, W. W. (2012). Reinforcement learning of 2-joint virtual arm reaching in computer model of sensory and motor cortex. Society for Neuroscience (abstract and poster).
Kerr, C. C., van Albada, S. J., Neymotin, S. A., Chadderdon, G. L., Robinson, P. A., & Lytton, W. W. (2012). Effects of basal ganglia on cortical computation: a hybrid network/neural field model. Society for Neuroscience (abstract and poster).
Chadderdon, G. L., Mohan, A., Suter, B. A., Neymotin, S. A., Kerr, C. C., Francis, J. T., Shepherd, G. M. G., & Lytton, W. W. (2013). A dual-circuit neocortical model explored in a spiking model of primary motor cortex. SUNY Downstate Research Day (abstract and poster).
P153 (Introduction to Psychology Laboratory I): Fall semester 2005 at Indiana University: A psychology undergraduate introductory research methods class, taught from my own lesson plan.
Interests include: creative writing, music (guitar and composition), philosophy.