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Cognitive Psychology at Ohio University

About the Cognitive Psychology Laboratories

Cognitive psychology at Ohio University consists of several labs studying a wide range of cognitive phenomena, including memory, judgment and decision-making, and concept formation. Specifically, the research questions range from the roles of conscious and unconscious processes in source-monitoring to preference formation and choice, to the extent to which eye movements reflect the complexity of categorization.

Faculty and Research Interests

Francis Bellezza

Multinomial Modeling

His main area of research involves applying general-processing-tree (multinomial) models to explaining the functioning of human memory. These mathematical techniques allow research to analyze complex behavior into basic cognitive mechanisms retrieval of information from memory and decision-making. Remembering is a mix of storing information, retrieving incomplete information from memory, and making decisions and judgments based on typically incomplete information.

  • Bellezza, Francis S. "Evaluation of six multinomial models of conscious and unconscious processes with the recall-recognition paradigm." Journal of Experimental Psychology: Learning, Memory, and Cognition, v. 29 issue 5, 2003, p. 779-796.

Claudia Gonzalez-Vallejo

Her work encompasess several areas of basic and applied research that concern how people make decisions and judgments. Basic research includes understanding of basic trade-off mechanisms in choice guided by predictions from the Stochastic Differece Model (SDM, Gonzalez-Vallejo, 2002) and its proportional difference rule (PD). Current research explores time/money trade-offs and modeling of inter-temporal choices with PD. Extensions of SDM to dynamic decisions with feedback in risky, uncertain, and inter-temporal domains are underway with special emphasis on understanding the role of references. Additionally, dynamics of the evolving preference states as measured by hand trajectories are studied and modeled.

Proportional Difference Model

Many products may be described in terms of their quality and their price. Because typically higher quality also implies higher price, the decision is not easy. How do individuals resolve the conflict inherit in choosing? What affects the consistency of decision-making? How do people perceive changes in attribute values as a function of the context? How does persuasion affect the evaluation of objects to determine a final choice? Some of the basic notions in this research program are also applied to consumer and medical decision-making situations. Current research is also exploring the interaction between people's affective reactions to choice options and their cognitive evaluations of them. Some publications on this topic are:

  • Scheibehenne, B., Rieskamp, J. & González-Vallejo, C. (2009). Cognitive Models of Preferential Choice: Comparing Decision Field Theory with the Stochastic Difference Model. Cognitive Science.
  • Reid, A. & González-Vallejo, C. (2008). Emotion as a tradeable quantity. Journal of Behavioral Decision Making, 21, 1-29.
  • González-Vallejo, C. & Reid, A. A. (2006) Quantifying persuasion effects on choice behavior with the decision threshold of the stochastic choice model. Organizational Behavior and Human Decision Processes, 100, 250-267.
  • Gonzalez-Vallejo, C. (2002). Making trade-offs: A probabilistic and context-sensitive model of choice behavior. Psychological Review, 109(1), 137.

Intertemporal Decisions

Exploring the many facets of discounting the value of future rewards.

  • Cheng, Jiuqing, et al. "Temporal discounting in heroin-dependent patients: No sign effect, weaker magnitude effect, and the relationship with inhibitory control." Experimental and clinical psychopharmacology 20.5 (2012): 400.
  • Cheng, Jiuqing, and Claudia González-Vallejo. "Hyperbolic Discounting: Value and Time Processes of Substance Abusers and Non-Clinical Individuals in Intertemporal Choice." PloS one 9.11 (2014): e111378.

Unconscious Thought / Online Impression Formation

The role of unconscious processes in higher-order judgment and decision making processes is both an exciting and controversial area in the JDM field. This research aims to find parsimonious explanations for psychological phenomena that have been used by other researchers as evidence for the superiority of unconscious to conscious processing in complex judgments and decisions.

  • González-Vallejo, C., Lassiter G.D., Bellezza, F.S., &Lindberg, M. (2008). “Save Angels Perhaps”: A Critical Examination of Unconscious Thought Theory and the Deliberation Without Attention Effect. Review of General Psychology, 12, 282-296.
  • Lassiter, G. Daniel, et al. "The deliberation-without-attention effect evidence for an artifactual interpretation." Psychological Science 20.6 (2009): 671-675.
  • González-Vallejo, Claudia, and Nathaniel Phillips. "Predicting soccer matches: A reassessment of the benefit of unconscious thinking." Judgment and Decision Making 5.3 (2010): 200-206.
  • González Vallejo, Claudia, et al. "Early Positive Information Impacts Final Evaluations: No Deliberation-Without-Attention Effect and a Test of a Dynamic Judgment Model." Journal of Behavioral Decision Making 27.3 (2014): 209-225.

Ronaldo Vigo

Research Interests

Although Dr. Vigo is interested in many areas of cognitive research, his core work focuses on the formulation and development of mathematical and computational models of similarity assessment, attention, perception, concept learning, categorization, and choice behavior. For example, he has investigated the degree of difficulty that humans experience when learning different types of concepts. In addition, he has investigated the influence of structural context on the aforementioned capacities. Three key questions drive this research. First, why are some types of concepts more difficult to learn than others? Secondly, can the subjective degree of learning difficulty of different types of concepts be reliably predicted? Thirdly, can context effects in similarity assessment, perception, and choice behavior be accurately accounted for by structure detection? In Dr. Vigo’s work, he argues that the key to answering these questions lies on the ability of organisms to detect invariance structure patterns in categorical stimuli.

Toward this end, Dr. Vigo created several mathematical frameworks and formal models for characterizing the way that observers learn concepts and assess similarities from categorical stimuli. Historical and new empirical evidence suggests that these structural models, algebraic, analytic, and non-probabilistic 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. Notably, all of this is often accomplished without the need for free parameters. This research has been articulated in several papers (Vigo, 2006, 2008, 2009, 2011, 2012, 2013) and in a book entitled "Mathematical Principles of Human Conceptual Behavior: The Structural Nature of Conceptual Representation and Processing" (Vigo, 2014).

The SCOPE LAB (Structure, Concepts, and Perception Laboratory) at Ohio University seeks to extend the above research empirically and theoretically. For example, in the SCOPE Lab we conduct empirical and theoretical research on human concept learning and categorization behavior using eye tracking technology. More specifically, eye tracking techniques are used to explore correlations between saccades and the concept learning behavior predicted by a variety of models, including models from Dr. Vigo’s generalized invariance structure theory (GIST; Vigo, 2013, 2014, 2015) and my representational information theory (RIT; 2011, 2012, 2014).

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, Dr. Vigo is interested in researching how humans judge similarity and dissimilarity between structural or configural stimuli such as human faces. In related work, he introduced a mathematical model of similarity that predicts the empirical similarity ordering of a key class of configural stimuli associated with deductive inference (Vigo, 2009a, 2009b). 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.


Vigo, R., Doan, C. (2015). The Structure of Choice. Cognitive Systems Research, in press.

Vigo, R., Evans, S., Owens, J. (2014). Categorization Behavior in Adults, Adolescents, and ADHD-Adolescents: A Comparative Investigation. Quarterly Journal of Experimental Psychology, Jun;68(6).

Vigo, R. (2014). Mathematical Principles of Human Conceptual Behavior: The Structural Nature of Conceptual Representation and Processing (Oct, 2014), Scientific Psychology Series, Routledge.

Vigo, R. (2013). The GIST (Generalized Invariance Structure Theory) of Concepts, Cognition, 129(1), 138-162.

Vigo, R., Zeigler, D., Halsey, P. (2013). Gaze and Informativeness During Category Learning: Evidence for an Inverse Relation. Visual Cognition, 1-31.

Vigo, R., Basawaraj (2013). Will the most informative object stand? Determining the impact of structural context on informativeness judgments. Journal of Cognitive Psychology, 1-19.

Vigo, R. (2012). Complexity over Uncertainty in Generalized Representational Information Theory (GRIT): A Structure-Sensitive General Theory of Information. Information, 4, 1-30.

Vigo, R. (2011). Representational information: a new general notion and measure of information. Information Sciences, 181, 4847-4859.

Vigo, R. (2011). Towards a Law of Invariance in Human Concept Learning, L. Carlson, C. Hölscher, T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the  Cognitive Science Society, Austin, TX: Cognitive Science Society, 2580-2585.

Vigo, R., (2010). A Dialogue on Concepts. Think, Volume 9, Issue 24, March 2010, pp 109-120.

Vigo, R. (2009). Categorical Invariance and Structural Complexity in Human Concept Learning. Journal of Mathematical Psychology, 53, 203-221.

Vigo, R. (2009). Modal Similarity. Journal of Experimental and Theoretical Artificial Intelligence, 21(3), 181-196.

Vigo, R., Allen, C., (2009). How to reason without words: inference as categorization. Cognitive Processing, 10(1), 51-88.

Vigo, R. (2006). A Note on the Complexity of Boolean Concepts. Journal of Mathematical Psychology,  50, 501-510.