Directories for:

Faculty

Staff

Graduate Students

Ronaldo Vigo

Research Area:
Concepts, Perception, Psychophysics, Similarity, Inference.

Specializations:
Quantitative (Mathematical & Computational Modeling); Cognitive.

Contact Information:

Office: 200 Porter Hall

Phone: (740) 593-1707

E-mail: vigo@ohio.edu

Laboratory:

SCOPE LAB WEBSITE

Research Interests:

Although I am interested in many areas of cognitive research, the core of my work is on the development of mathematical and computational models of concept learning and categorization behavior. For example, I have investigated the degree of difficulty that humans experience when learning different types of concepts. Two key questions emerge from this research. First, why are some types of concepts more difficult to learn than others? Secondly, can the subjective degree of learning difficulty of these concepts be reliably predicted? In my work, I argue that the key to answering these questions lies on the structural properties of the categorical stimulus from which a concept is learned and on certain mental operations that facilitate their detection.
 
Toward this end, I have developed several mathematical frameworks for characterizing and measuring the structural invariance and structural complexity inherent to Boolean categories (i.e., categories defined by Boolean rules). I have been able to show that these structural models, algebraic, analytic, and deterministic in nature (and hence, much like the models encountered in classical physics), are more robust and cognitively plausible predictors of the degree of concept learning difficulty experienced by humans than the well-known alternatives. Remarkably, all of this is accomplished without the need for free parameters. This research has been articulated in several papers and in a forthcoming book entitled Mathematical Principles of Human Concept Learning (Vigo, 2006a, 2006b, 2007, 2008).
 
The SCOPE LAB (Structure, Concepts, and Perception Laboratory) at Ohio University seeks to extend the above research empirically and theoretically. In the SCOPE Lab we conduct empirical and theoretical research on human concept learning and categorical decision-making behavior using eye tracking technology and fMRI. More specifically, we use eye tracking techniques to explore correlations between saccades and the concept learning behavior predicted by a variety of models, including my concept invariance model (Vigo, 2006b); similarly, in collaboration with researchers at Indiana University at Bloomington, we use fMRI to explore possible neural correlates to the Boolean categorization behavior predicted by the same models. The ultimate goal is to develop multilayered-robust mathematical models of categorical learning behavior and concept formation: that is, models that predict not only the behavior, but the associated saccades and the BOLD signal activation levels in regions of interest.
 
Other research activities in the SCOPE Lab include empirical and theoretical research on decision making behavior as a function of similarity assessment, dissimilarity assessment, and categorization. Also, we are interested in researching how humans judge similarity and dissimilarity between structural or configural stimuli such as human faces. In related work, I introduced a mathematical model of similarity that predicts the empirical similarity ordering of a key class of configural stimuli associated with deductive inference (Vigo, 2007). Last, but not least, the SCOPE Lab conducts empirical and theoretical research on problem solving behavior in mathematical domains such as geometry, algebra, and physics, and on the nature of aesthetic judgments. For more information on our research, visit the SCOPE Lab website here.

Recent Publications:

	Vigo, R. (2006a). A Note on the Complexity of Boolean Concepts. Journal of Mathematical Psychology, Vol. 50, 501-510.
	Vigo, R. (2006b). Categorical Invariance and Structural Complexity in Human Concept Learning. Journal of Mathematical Psychology, (2nd round of review).
	Vigo, R. (2007). Modal Similarity. Journal of Experimental and Theoretical Artificial Intelligence, (in press).
	Vigo, R., Newman, S., Allen, C. (2007). Neural Correlates of Boolean Concept Learning. (in preparation).
	Vigo, R. (2007). Two Ways of Measuring the Complexity of Boolean Sets. Complexity Journal, (under review).
	Vigo, R., Allen, C., (2007). Inference and Categorization. Cognitive Processing, (under review).
	Vigo, R. (2008). Mathematical Principles of Human Concept Learning [Principia Mathematica Informatium Hominis]. MIT Press. (Forthcoming Book).
	Vigo, R. (2008). A Taxonomy of Cognitive Models. (in preparation).

Recent Presentations:

Invited Talks:
 

Vigo, R. (2006, April). Towards a Law of Invariance in Human Concept Learning. Mind and Computation Talks, Indiana University.

Vigo, R. (2006, June). Deduction and Categorization in Non-human Animals (with Colin Allen). 32nd Annual Meeting of the Society for Philosophy and Psychology.

Vigo, R. (2007, September). The Good, the Bad, and the Ugly of the Minimization-Complexity Hypothesis of Boolean Concept Learning. Logic Seminar Talks, Indiana University at Bloomington.

Vigo, R. (2008, Spring). Cognitive Complexity in Human Concept Learning. Biocomplexity Institute Colloquium.

Graduate Students:

• Sunil Carspecken
• Jason Harman