Franklin & Marshall College Franklin & Marshall College

Cognitive Psychology Lab

  • Robot 1

 The Cognitive Psychology lab is a 5-room suite on the first floor of the LSP building.  There are currently four main areas of faculty research, and a great variety of student research projects being pursued there.

 

 

 

 

Understanding the functional structure of the brain. [link to http://www.fandm.edu/bfb/student-and-faculty-research/a-co-activation-network-for-the-brain  ]   The lab develops techniques for mining large amounts of brain-imaging data to answer questions about how the brain is organized to support cognition.  What does what, and how do the various parts of the brain cooperate to give rise to the mind?  F&M is home to a database containing over 2,600 fMRI experiments, and much of the work has used this resource. 

Selected publications

Anderson, M.L. (2010). Neural reuse: A fundamental organizational principle of the brain. (Target article) Behavioral and Brain Sciences, 33(4).

Anderson, M.L. (2010). Cortex in context: Reply to commentaries. Behavioral and Brain Sciences, 33(4).

Anderson, M.L., Brumbaugh, J. & Şuben, A. (2010).  Investigating functional cooperation in the human brain using simple graph-theoretic methods.  In: A. Chaovalitwongse, P.M. Pardalos, V. and P. Xanthopoulos, (eds.). Computational Neuroscience. Springer.

Anderson, M.L. (2007). Evolution of cognitive function via redeployment of brain areas. The Neuroscientist, 13(1): 13-21.

 

The fundamentals of embodied cognition.  Embodied cognition is an approach to understanding the mind that treats cognition as a coordinated set of tools evolved by organisms for coping with their environments. This approach foregrounds agency and environmental interaction over internal symbol manipulation (although it need not deny the importance of the latter).  In the lab we have lightweight, wearable accelerometers and high-definition cameras for motion studies. 

Selected publications

Anderson, M.L. (2009). What mindedness is. Europe’s Journal of Psychology, 4: 1-12.

Anderson, M.L. & Chemero, T. (2009). Affordances and intentionality: Reply to Roberts. Journal of Mind and Behavior, 30(4): 301-12.

Anderson, M.L. & Rosenberg, G. (2008). Content and action: The guidance theory of representation. Journal of Mind and Behavior, 29(1-2): 55-86.

Anderson, M.L. (2006). Cognitive science and epistemic openness. Phenomenology and the Cognitive Sciences 5(2): 125-54.

Anderson, M.L. (2003). Embodied cognition: A field guide. Artificial Intelligence 149(1): 91-130. 

The basis of numerical cognition. 

Improving the perturbation tolerance of artificial intelligence systems. An investigation of the thesis that metacognitive monitoring and control (in a form we call the metacognitive loop, or MCL) can play an important role in improving the perturbation tolerance of real-world agents, that is, their ability to detect and recover from errors or unexpected changes. We have shown that adding an MCL component can improve the performance of a diverse range of systems from natural-language human-computer interfaces to simple Q-learners. A more specialized project along these same lines is an investigation into the use of metalanguage in conversation, and its role in helping maintain the fluidity, flexibility and error-tolerance of human-human dialog. 

Currently the main work of the lab involves using F&Ms two corobots [link to http://robotics.coroware.com/corobot ] to simulate Mars Rovers [link to http://thediplomat.fandm.edu/article/68 ] and search-and-rescue vehicles, to see if our technology can make such systems smarter and more reliable.

Selected publications

Schmill, M.D., Anderson, M.L., Fults, S., Josyula, D., Oates, T., Perlis, D., Shahri, H., Wilson, S. & Wright, D. (2010). The Metacognitive Loop and reasoning about anomalies. In: M. Cox and A. Raja, (eds.). Metareasoning: Thinking about thinking. MIT Press.

Anderson, M.L., Fults, S., Josyula, D.P., Oates, T., Perlis, D., Schmill, M.D., and Wilson, S. (2008). A self-help guide for autonomous systems.  AI Magazine, 29(2): 67-76.

Anderson, M.L., Oates, T., Chong, Y. & Perils, D. (2006). The metacognitive loop I: Enhancing reinforcement learning with metacognitive monitoring and control for improved perturbation tolerance.  Journal of Experimental and Theoretical Artificial Intelligence, 18(3): 387-411.

Anderson, M.L. & Perlis, D.R. (2005). Logic, self-awareness and self-improvement: The metacognitive loop and the problem of brittleness. Journal of Logic and Computation 15(1): 21-40.

In addition to faculty research, students have pursued a number of projects using our various software and other resources (including ePrime [link to http://www.pstnet.com/eprime.cfm ], SuperLab [link to http://www.superlab.com/ ], and several Dell and Apple computers).  For instance, Elizabeth Parzych (’08) investigated Triesman’s feature detection theory as it pertained to color perception; Aysu Suben (’09) used a picture-priming paradigm to investigate some of the cognitive and perceptual processes that help extract meanings from ambiguous images; and Treysi Terziyan (’10) did some cross-cultural studies of perception and language using Turkish-English and Spanish-English bilinguals.

Selected publications

Weast, R. & Neiman, N. (2010). The effect of cognitive load and meaning on selective attention. Proceedings of the 32nd Annual Conference of the Cognitive Science Society.

Terziyan, T. &  Gilkey, J. (2010). Cross-cultural study of change blindness in Turkish and American students. Proceedings of the 32nd Annual Conference of the Cognitive Science Society.

Şuben, A., Anderson, M.L. & Chemero, T. (2008). The Duck/Rabbit Illusion: Re-examination of information encapsulation. Proceedings of the 30th Annual Meeting of the Cognitive Science Society.

Parzych, E. (2008). Color mixing and Triesman’s theory of feature perception.” Proceedings of the Society for Neuroscience.