Papers

Wirzberger, M., Borst, J. P., Krems, J. F., & Rey, G. D. (2020). Memory-related cognitive load effects in an interrupted learning task: A model-based explanation. Trends in Neuroscience and Education, 20, 100139. https://doi.org/10.1016/j.tine.2020.100139
Borst, J.P. & Anderson, J.R. (2017). A Step-By-Step Tutorial on using the Cognitive Architecture ACT-R in combination with fMRI Data. Journal of Mathematical Psychology 76, pp. 94-103.
Pyke, A. A., Fincham, J. M., & Anderson, J. R. (2017). When math operations have visuospatial meanings versus purely symbolic definitions: Which solving stages and brain regions are affected?. NeuroImage.
Koerner, F. S., Anderson, J. R., Fincham, J. M., & Kass, R. E. (2017). Change-point detection of cognitive states across multiple trials in functional neuroimaging. Statistics in Medicine, 36(4), 618-642.
Anderson, J. R., Pyke, A., & Fincham, J. M. (2016). Hidden Stages of Cognition Revealed in Patterns of Brain Activation. Psychological Science, 27(9), 1215-1226.
Anderson, J.R., Bothell, D., Fincham, J.M., & Moon, J. (2016). The Sequential Structure of Brain Activation Predicts Skill. Neuropsychologia, 81, 94-106.
Tenison, C., Fincham, J.M., & Anderson, J.R. (2016). Phases of Learning: How Skill Acquisition Impacts Cognitive Processing. Cognitive Psychology, 87, 1-28.
Borst, J.P. & Anderson, J.R. (2015). Using the ACT-R Cognitive Architecture in combination with fMRI data. In B.U. Forstmann, & E.-J. Wagenmakers (Eds.), An Introduction to Model-Based Cognitive Neuroscience. Springer: New York.
Tenison, C., & Anderson, J. R. (2015, November 9). Modeling the Distinct Phases of Skill Acquisition. Journal of Experimental Psychology: Learning, Memory, and Cognition. Advance online publication. http://dx.doi.org/10.1037/xlm0000204
Borst, J.P., Nijboer, M., Taatgen, N.A., Van Rijn, H., & Anderson, J.R. (2015). Using Data-Driven Model-Brain Mappings to Constrain Formal Models of Cognition. PLoS ONE 10(3): e0119673.
Lee, H. S., Fincham, J. M., & Anderson, J. R. (2015). Learning from examples versus verbal directions in mathematical problem solving. Mind, Brain, and Education, 9(4), 232-245.
Tenison, C., Fincham, J. M., & Anderson, J. R. (2014). Detecting math problem solving strategies: An investigation into the use of retrospective self-reports, latency and fMRI data. Neuropsychologia, 54, 41-52.
Anderson, J. R. & Fincham, J. M. (2014). Extending Problem-Solving Procedures. Cognitive Psychology, Nov;74:1-31.
Anderson, J. R., Lee, H. S., & Fincham, J. M. (2014). Discovering the structure of mathematical problem solving. NeuroImage, 97, 163-177.
Lee, H. S., Fincham, J. M., Betts, S. & Anderson, J. R. (2014). An fMRI investigation of instructional guidance in mathematical problem solving. Trends in Neuroscience and Education, 3(2), 50–62.
Anderson, J. R. & Fincham, J. M. (2013). Discovering the sequential structure of thought. Cognitive Science, 37(6), 1-31.
Anderson, J. R., Betts, S. A., Ferris, J. L., & Fincham, J. M. (2013). Can neural imaging be used to investigate learning in an educational task? In J. Stazewski (Ed.) Expertise and skill acquisition: The impact of William G. Chase (pp. 299-324). Taylor and Francis: New York.
Borst, J. P., & Anderson, J. R. (2013). Using model-based functional MRI to locate working memory updates and declarative memory retrievals in the fronto-parietal network. Proceedings of the National Academy of Sciences U.S.A., 110(5), 1628-1633.
Borst, J.P., Taatgen, N.A., & Van Rijn, H. (2013). Validating Models of Complex, Real-Life Tasks Using fMRI. In A. Johnson & R.W. Proctor (Eds.), Neuroergonomics: A Cognitive Neuroscience Approach to Human Factors and Ergonomics. Palgrave MacMillan.
Borst, J.P., Nijboer, M., Taatgen, N.A., & Anderson, J.R. (2013). A Data-Driven Mapping of Five ACT-R Modules on the Brain. In R. West & T. Stewart (Eds.), Proceedings of the 12th International Conference on Cognitive Modeling. Ottawa: Carleton University.
Nijboer, M., Borst, J.P., van Rijn, H., & Taatgen, N.A. (2013). Predicting Interference in Concurrent Multitasking. In R. West & T. Stewart (Eds.), Proceedings of the 12th International Conference on Cognitive Modeling. Ottawa: Carleton University.
Wintermute, S., Betts, S. A., Ferris, J. L., Fincham, J. M., & Anderson, J. R. (2012). Brain Networks Supporting Execution of Mathematical Skills versus Acquisition of New Mathematical Competence. Public Library of Science (PLOS) ONE.
Gunzelmann, G., & Moore, L. R. (2012). Evaluating the relationship between neuropsychological function and cognitive performance. In N. Miyake, R. Cooper, and D. Peebles (Eds.). Proceedings of the Thirty-Fourth Annual Meeting of the Cognitive Science Society (pp. 414-419). Austin, TX: Cognitive Science Society.
Stocco, A., Lebiere, C., O’Reilly, R. C., & Anderson, J. R. (2012). Distinct contributions of the caudate nucleus, rostral prefrontal cortex, and parietal cortex to the execution of instructed tasks. Cognitive, Affective, & Behavioral Neuroscience, 12, 611-628.
Borst, J. & Anderson, J., R, (2012). Towards pinpointing the neural correlates of ACT-R: A conjunction of two model-based fMRI analyses. In N. Rußwinkel, U. Drewitz & H. van Rijn (eds.), Proceedings of the 11th International Conference on Cognitive Modeling, Berlin: Universitaetsverlag der TU Berlin.
Anderson, J. R., Fincham, J. M., Schneider, D. W., & Yang, J. (2012). Using brain imaging to track problem-solving in a complex state space. NeuroImage, 60, 633-643.
Anderson, J. R., Betts, S. A., Ferris, J. L., & Fincham, J. M. (2012). Tracking children’s mental states while solving algebra equations. Human Brain Mapping . 33(11), 2650-65.
Anderson, J. R., Betts, S. A., Ferris, J. L., Fincham, & J. M., Yang, J. (2012). Using Brain Imaging to Track Student Problem solving.IEEE Intelligent Systems, 60, 633-643.
Anderson, J. R. (2012). Tracking problem solving by multivariate pattern analysis and hidden markov model algorithms. Neuropsychologia, 50, 487-498.
Borst, J.P., Taatgen, N.A., & Van Rijn, H. (2011). Using a Symbolic Process Model as input for Model-Based fMRI Analysis: Locating the Neural Correlates of Problem State Replacements. NeuroImage, 58(1), 137-147.
Anderson, J. R., Bothell, D., Fincham, J. M., Anderson, A. R., Poole, B. & Qin, Y. (2011). Brain Regions Engaged by Part- and Whole-task Performance in a Video Game: A Model-based Test of the Decomposition Hypothesis. Journal of Cognitive Neuroscience, 23, 3983-3997.
Möbus, C., Lenk, J. C., Özyurt, J., Thiel, C. M., & Claassen, A. (2011). Checking the ACT-R/Brain Mapping Hypothesis with a complex task: Using fMRI and Bayesian identification in a multi-dimensional strategy space. Cognitive Systems Research, In Press, Date accepted 24 Nov. 2010, Corrected Proof, available online 6 Jan 2011.
Lenk, J. C., Möbus, C., Özyurt, J. Margarete, C., & Claassen, A. (2011). From fMRI Data To Cognitive Models: Testing the ACT-R Brain Mapping Hypothesis with an Ex-Post Model. In The Third International Conference on Advanced Cognitive Technologies and Applications (pp. 13-18). Rome, Italy.
Danker, J. F., Fincham, J. M., & Anderson, J. R. (2011). The neural correlates of competition during memory retrieval are modulated by attention to the cues. Neuropsychologia, 49, 2427-2438.
Anderson, J. R.,Betts, S. A., Ferris, J. L., & Fincham, J. M. (2011). Cognitive and metacognitive activity in mathematical problem solving: Prefrontal and parietal patterns.Cognitive, Affective, and Behavioral Neuroscience, 11, 52-67.
Lenk, J.C., Möbus, C., Özyurt, J., Thiel, C.M., & Claassen, A. (2011). How to Assess ACT-R Models Predicting BOLD Curves for a Complex Problem, In J. Özyurt, A. Anschütz, S. Bernholt, J. Lenk (eds.), Interdisciplinary Perspectives on Cognition, Education and the Brain, Hanse Studies, Vol. 7, Hanse-Wissenschaftskolleg (HWK), (pp.219-228)Institute for Advanced Study, Oldenburg: BIS-Publisher.
Anderson, J. R., Betts, S. A., Ferris, J. L., & Fincham, J. M. (2010). Neural imaging to track mental states while using an intelligent tutoring system. Proceedings of the National Academy of Science, 107(15), 7018-7023.
Borst, J.P., Taatgen, N.A., Stocco, A., & Van Rijn, H. (2010). The Neural Correlates of Problem States: Testing fMRI Predictions of a Computational Model of Multitasking. PLoS ONE 5(9): e12966. doi:10.1371/journal.pone.0012966.
Ragni, M., Fangmeier, T., & Brüssow, S. (2010). Deductive spatial reasoning: From neurological evidence to a cognitive model. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 193-198). Philadelphia, PA: Drexel University.
Borst, J., Taatgen, N. A., & van Rijn, H. (2010). Locating the Neural Correlates of the Problem State Resource: Analyzing fMRI Data on the Basis of a Computational Model. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 287-288). Philadelphia, PA: Drexel University.
Borst, J., Taatgen, N. A., van Rijn, H., & Stocco, A. (2010). Testing fMRI predictions of a Cognitive Model of the Problem State Multitasking Bottleneck. Poster presented at the 32nd Annual Conference of the Cognitive Science Society. Portland, OR.
Möbus, C., Lenk, J. C., Claassen, A., Özyurt, J., & Thiel, C. (2010). Checking the Brain Mapping Hypothesis: Predicting and Validating BOLD Curves for a Complex Task Using ACT-R. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 163-168). Philadelphia, PA: Drexel University.
Danker, J. F. & Anderson, J. R. (2010). The ghosts of brain states past: Remembering reactivates the brain regions engaged during encoding. Psychological Bulletin, 136, 87-102.
Fincham, J.M., Anderson, J.R., Betts, S.A., & Ferris, J.L. (2010). Using Neural Imaging and Cognitive Modeling to Infer Mental States while Using an Intelligent Tutoring System. In Proceedings of the Third International Conference on Educational Data Mining (EDM2010). Pittsburgh, PA.
Stocco, A., Lebiere, C., O’Reilly, R. C., & Anderson, J. R. (2010). The role of the anterior prefrontal-basal ganglia circuit as a biological instruction interpreter. In A. V. Samsonovich, K. R. Jóhannsdóttir, A. Chella, & B. Goertzel (Eds.) Biologically Inspired Cognitive Architectures 2010. Frontiers in Artificial Intelligence and Applications, (pp. 153-162). Amsterdam, The Netherlands: IOS Press.
Anderson, J. R., Betts, S. A., Ferris, J. L., & Fincham, J. M. (2009). Can neural imaging investigate learning in an educational task? In proceedings of the 36th Annual Carnegie Symposium on Cognition, June 2-3, Carnegie Mellon University.
Anderson, J. R., Anderson, J. F., Ferris, J. L., Fincham, J. M., & Jung, K.-J. (2009). The Lateral Inferior Prefrontal Cortex and Anterior Cingulate Cortex are Engaged at Different Stages in the Solution of Insight Problems. Proceedings of the National Academy Sciences, 106 (26), 10799-10804.
Borst, J. P., Taatgen, N. A., van Rijn , D. H., Stocco, A., & Fincham, J. M. (2009). Testing fMRI predictions of a dual-task interference model. In Proceedings of the 9th International Conference of Cognitive Modeling (paper 236), Manchester, United Kingdom.
Rosenberg-Lee, M., Lovett, M., & Anderson, J. R. (2009). Neural correlates of arithmetic calculation strategies. Cognitive, Affective, & Behavioral Neuroscience, 9(3), 270-285.
Anderson, J.R., Byrne, D., Fincham, J., & Gunn, P. (2008). Role of Prefrontal and Parietal Cortices in Associative Learning. Cerebral Cortex, 18(4), 904-914.
Rosenberg-Lee, M., Lovett, M., & Anderson, J. R. (2008). Strategy variation in multi-digit mental multiplication: fMRI, behavioral and modeling perspectives. In Proceedings of the Annual Meeting of the Cognitive Neuroscience Society, San Francisco, CA, p. 72.
Fincham, J. M., Qin, Y., & Anderson, J. R. (2008). An fMRI study of cognitive demand and control during skill acquisition. In Proceedings of the Annual Meeting of the Cognitive Neuroscience Society, San Francisco, CA, p. 244.
Anderson, J.R., Fincham, J. M., Qin, Y., & Stocco, A. (2008). A Central circuit of the mind. Trends in Cognitive Science. 12(4), 136-143.
Stocco, A. & Anderson, J. R. (2008) Endogenous control and task representation: An fMRI study in algebraic problem solving. Journal of Cognitive Neuroscience, 20(7), 1300-1314.
Anderson, J. R., Anderson, J. F., Ferris, J. L., Fincham, J. M., & Jung, K-J. (unpublished, 2008). Word puzzles produce distinct patterns of activation in the ventrolateral prefrontal cortex and anterior cingulate cortex.
Anderson, J. R. & Qin, Y. (2008). Using Brain Imaging to Extract the Structure of Complex Events at the Rational Time Band. Journal of Cognitive Neuroscience, 20 (9) , 1624-1636.
Danker, J. F., Gunn, P. & Anderson, J. R. (2008). A rational account of memory predicts left prefrontal activation during controlled retrieval. Cerebral Cortex, 18, 2674-2685.
Anderson, J. R., Carter, C. S., Fincham, J. M., Qin,. Y., Ravizza, S. M., & Rosenberg-Lee, M. (2008). Using fMRI to Test Models of Complex Cognition. Cognitive Science, 32, 1323-1348.
Qin, Y., Bothell, D., & Anderson, J. R. (2007). ACT-R meets fMRI. In Proceedings of LNAI 4845 (pp.. 205-222). Berlin, Germany: Springer-Verlag.
Shibata, M., Abe, J., Terao, A., & Miyamoto, T. (2007). Neural mechanisms involved in the comprehension of metaphoric and literal sentences: An fMRI study. Brain Research, 1166, 92-102.
Danker, J. M. & Anderson, J. R. (2007). The Roles of Prefrontal and Posterior Parietal Cortex in Algebra Problem Solving: A Case of Using Cognitive Modeling to Inform Neuroimaging Data. NeuroImage. 35, 1365-1377.
Anderson, J. R. (2007). The Algebraic Brain. In Gluck, M. A., Anderson, J. R , & Kosslyn, S. M. (Eds.). Memory and Mind: A Festschrift for Gordon H. Bower. New Jersey: Lawrence Erlbaum Associates.
Anderson, J. R. (2007). Using brain imaging to guide the development of a cognitive architecture. In W. D. Gray (Ed.), Integrated Models of Cognitive Systems (pp. 49-62).New York, NY: Oxford University Press.
Anderson, J. R. (2007). The image of complexity. In The 29th Annual Conference of the Cognitive Science Society. Nashville, Tennessee, USA.
Fincham, J. M., & Anderson, J. R. (2007). An fMRI study of the neural correlates of performance and learning in an algebraic isomorph task. In Proceedings of the Annual Meeting of the Cognitive Neuroscience Society. New York, NY, p. 271
Stocco, A., & Anderson, J. R. (2007). Endogenous control in algebraic problem solving: An fMRI study. In Proceedings of the Annual Meeting of the Cognitive Neuroscience Society. New York, NY, p. 271.
Danker, J. F. & Anderson, J. R. (2007). The roles of prefrontal and posterior parietal cortex in algebra problem-solving: A case of using cognitive modeling to inform neuroimaging data. Neuroimage, 35, 1365-1377.
Sohn, M.-H., Albert, M. V.., Stenger, V. A, Jung, K.-J., Carter, C. S., & Anderson, J. R. (2007). Anticipation of conflict monitoring in the anterior cingulate cortex and the prefrontal cortex. Proceedings of National Academy of Science, 104, 10330-10334.
Kao, Y. & Anderson, J. R. (2006). What are they thinking? Decomposing a complex task. In proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 2523) . Vancouver, British Columbia, Canada.
Sohn, M.-H., Goode, A., Stenger, V. A, Jung, K.-J., Carter, C. S., & Anderson, J. R. (2005). An information-processing model of three cortical regions: Evidence in episodic memory retrieval, NeuroImage , 21-33.
Anderson, J. R., Albert, M. V., & Fincham, J.M. (2005) Tracing Problem Solving in Real Time: fMRI Analysis of the Subject-Paced Tower of Hanoi. Journal of Cognitive Neuroscience, 17 1261-1274.
Jung, K.-J., Prasad, p., Qin, Y., & Anderson, J. R. (2005). Extraction of overt verbal response from acoustic noise from the scanner in fMRI by use of segmented active noise cancellation. Magnetic Resonance Imaging, 53, 739-744.
Terao, A., Koedinger, K. R., Sohn, M-H., Qin, Y., Anderson, J. R., & Carter, C. S. (2004). An fMRI study of the interplay of symbolic and visuo-spatial systems in mathematical reasoning.In Proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 1327-1332).
Anderson, J. R., Qin, Y., Stenger, V. A., & Carter, C. S. (2004). The relationship of three cortical regions to an information-processing model. Journal of Cognitive Neuroscience, 16 (4), 637-653.
Sohn, M.-H., Goode, A., Stenger, V. A, Carter, C. S., & Anderson, J. R. (2003). Competition and representation during memory retrieval: Roles of the prefrontal cortex and the posterior parietal cortex, Proceedings of National Academy of Sciences, 100, 7412-7417.
Qin, Y., Carter, C. S., Silk, E., Stenger, V. A., Fissell, K., Goode, A. & Anderson, J.R. (2004). The change of the brain activation patterns as children learn algebra equation solving. Proceedings of National Academy of Sciences,101(15), 5686-5691.
Qin, Y., Sohn, M-H, Anderson, J. R., Stenger, V. A., Fissell, K., Goode, A. Carter, C. S. (2003). Predicting the practice effects on the blood oxygenation level-dependent (BOLD) function of fMRI in a symbolic manipulation task. Proceedings of the National Academy of Sciences of the United States of America. 100(8): 4951-4956.
Anderson, J. R., Qin, Y., Sohn, M-H., Stenger, V. A. & Carter, C. S. (2003) An information-processing model of the BOLD response in symbol manipulation tasks. Psychonomic Bulletin & Review. 10, 241-261.
Fincham, J. M., Carter, C. S., van Veen, V., Stenger, V. A., & Anderson, J. R. (2002). Neural mechanisms of planning: A computational analysis using event-related fMRI. In Proceedings of the National Academy of Sciences. 99 (5), 3346-3351, 2002.
Sohn, M.-H., Ursu, S., Anderson, J. R., Stenger, V. A., & Carter, C. S. (2000). The role of prefrontal cortex and posterior parietal cortex in task-switching. In Proceedings of National Academy of Science, 97 (24), 13448-13453.
Danker, J. & Anderson, J. R. (submitted). Left ventrolateral prefrontal activity during retrieval precisely reflects the difficulty of accessing information in memory. Cerebral Cortex.