Barrouillet, P., Bernardin, S. & Camos, V. (2004). Time constraints and resource sharing in adults’ working memory spans. Journal of Experimental Psychology: General, 133, 83-100.
Barrouillet, P., Bernarding, S., Portrat, S., Vergauwe, E. & Camos, V. (2007). Time and cognitive load in working memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 570-585.
Bennett, M. R. & Hacker, P. M. (2006). Language and cortical function: Conceptual developments. Progress in Neurobiology, 80, 20-52.
Brown, G. D. A. & Lewandowsky, S. (2010). Forgetting in memory models: Arguments againts trace decay and consolidation failure. In S. Della Sala (Ed.), Forgetting (pp. 49-75). Hove: Psychology Press.
Brown, S. D. (2012). Common ground for behavioural and neuroimaging research. Australian Journal of Psychology, 64, 4-10.
Camos, V., Lagner, P. & Barrouillet, P. (2009). Two maintenance mechanisms of verbal information in working memory. Journal of Memory and Language, 61, 457-469.
Colthear, M. (2012). The cognitive level of explanation. Australian Journal of Psychology, 64, 11-18.
Corrado, G. & Doya, K. (2007). Understanding neural coding through the model-based analysis of decision making. Journal of Neuroscience, 27, 8178-8180.
Dolan, R. J. (2008). Neuroimaging of cognition: past, present, and future. Neuro, 60, 496-502.
Farrell, S. & Lewandowsky, S. (2010). Computational models as aids to better reasoning in psychology. Current Directions in Psychological Science, 19, 329-335.
Forstmann, B. U., Wagenmakers, E.-J., Eichele, T., Brown, S. & Serences, J. T. (2011). Reciprocal relations between cognitive neuroscience and formal cognitive models: Opposites attract? Trends in Cognitive Sciences, 15, 272-279.
Gallistel, C. R. (1999). Themes of thought and thinking. In R. J. Sternberg (Ed.), The Nature of Cognition. Science, 285, 842–843.
Kieras, D. E., Meyer, D. E., Mueller, S. & Seymour, T. (1999). Insights into working memory from the perspective of the EPIC architecture for modelling skilled perceptualmotor and cognitive human performance. In A. Miyake and P. Shah (Eds.), Models of working memory: Mechanisms
of active maintenance and control (pp. 183-223). New York, NY: Cambridge University Press.
Kihlstrom, J. F. (2010). Social neuroscience: The footprints of Phineas Gage. Social Cognition, 28, 757–783.
Kim, J-J., Kim, M. S., Lee, J. S., Lee, D. S., Lee, M. C., & Kwon, J. S. (2002). Dissociation of working memory processing associated with native and second languages: PET investigation. NeuroImage,
Lewandowsky, S. (1993). The rewards and hazards of computer simulations. Psychological Science, 4, 236-243.
Lewandowsky, S. & Farrell, S. (2011). Computational Modeling in Cognition: Principles and Practice. Thousand Oaks, CA: Sage.
Lewandowsky, S., Ecker, U. K. H., Farrell, S. & Brown, G. D. A. (2012). Models of cognition and constraints from neuroscience: A case study involving consolidation. Australian Journal of Psychology, 64, 37-45.
Mercier, H. & Sperber, D. (2011). Why do humans reason? Arguments for an argumentative theory. Behavioral and Brain Sciences, 34, 57-111.
Mulder, M. J., Wagenmakers, E.-J., Ratcliff, R., Boekel, W., & Forstmann, B. U. (2012). Bias in the brain: A diffusion model analysis of prior probability and potential payoff. The Journal of Neuroscience, 32, 2335-2343.
Naughtin, C. K., Mattingley, J. B. & Dux, P. E. (2014). Distributed and overlapping neural substrates for object individuation and identification in visual short-term memory. Cerebral Cortex. Advance online
O’Doherty, J. P., Hampton, A. & Kim, H. (2007) Model-based fMRI and its application to reward learing and decision making. Annals of the New York Academy of Sciences, 1104, 35-53.
Oberauer, K. & Kliegl, R. (2006). A formal model of capacity limits in working memory. Journal of Memory and Language, 55, 601-626.
Oberauer, K. & Lewandowsky, S. (2011). Modeling working memory: A computational implementation of the Time-Based Resource-Sharing theory. Psychonomic Bulletin & Review, 18, 10-45.
Oberauer, K. Lewandowsky, S., Farrell, S., Jarrod, C. & Greaves, M. (2012). Modeling working memory: An interference model of complex span. Psychonomic Bulletin & Review, 19, 779-819.
Pages, M. P. A. & Norris, D. (1998). The primacy model: A new model of immediate serial recall. Psychological Review, 105, 761-781.
Peigneux P., Schmitz R., & Urbain, C. (2010). Sleep and Forgetting. In S. Della Sala (Ed.), Forgetting (pp. 165- 184). Hove: Psychology Press.
Ratcliff, R. (2002). A diffusion model account of reaction time and accuracy in a two choice brightness discrimination task: Fitting real data and failing to fit fake but plausible data. Psychonomic Bulletin and Review, 9, 278–291.
Ratcliff, R. & McKoon, G. (2007). The diffusion decision model: Theory and data for two-choice decision task. Neural Computation, 20, 873-922.
Sauseng, P., Klimesch, W., Heise, K. F., Gruber, W. R., Holz, E., Karim, A. A.,… Hummel, F. C. (2009). Brain oscillatory substrates of visual short-term memory capacity. Current Biology, 19, 1846-1852.
Sternberg, R. J. & Sternberg, K. (2011). Cognitive Psychology. Cengage Learning: Belmont California. Vogel, E., McCollough, A. W. & Machizawa, M. G. (2005). Neural measures reveal individual diferences in controlling access to working memory. Nature, 438, 500-503.
Voss, A., Nagler, M. & Lerche, V. (2013). Diffusion models in experimental psychology: a practical introducction. Experimental Psychology, 60, 385-402.
Weisberg, D. S., Keil, F. C., Goodstein, J., Rawson, E. & Gray, J. R. (2008). The seductive allure of neuroscience explanations. Journal of Cognitive Neuroscience, 20, 470-477.
Wixted, J. T. (2004). The psychology and neuroscience of forgetting. Annual Review of Psychology, 55, 235-269.
Wixted, J. T. (2010). The role of retroactive interference and consolidation in everyday forgetting. In S. Della Sala (Ed.), Forgetting (pp. 285-312). Hove: Psychology Press.
Yechiam, E., Busemeyer, J. R., Stout, J. C. & Bechara, A. (2005). Using cognitive models to map relations between neuropsychological disorders and human decision-making déficits. Psychological Science, 16, 973-978.
- Abstract viewed - 3404 times
- PDF (Español (España)) downloaded - 1807 times
- carta (Español (España)) downloaded - 0 times
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Odir Rodríguez Villagra
Centro de Investigación en Neurociencias e Instituto de Investigaciones Psicológicas, Universidad de Costa Rica
How to Cite
Formal cognitive models: A tool for the knowledge integration of cognitive psychology and cognitive neuroscience
Vol 28 No 117 (2014): Actualidades en Psicología: Neurociencia y Psicología
Submitted: May 5, 2014
Published: Nov 20, 2014
The aim of this review was to propose some pieces of advice to cognitive psychologists interested in incorporate the study of the nervous system on their researches. First, this work presents the scholars’ resistances to take into account theories and findings from neurosciences or cognitive psychology in their respective research area; then, some risks related to the allure of neurosciences are offered. Second, formal cognitive models are proposed as an important tool to incorporate in the cognitive neuroscience research. Third, some arguments and examples showing how formal cognitive models aid reasoning and research in cognitive neuroscience are given. Finally, some proposals are presented in order to promote a suitable start in the cognitive neuroscience research.