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The neuronal dynamics underlying cognitive flexibility in set shifting tasks

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Abstract

The ability to switch attention from one aspect of an object to another or in other words to switch the “attentional set” as investigated in tasks like the “Wisconsin Card Sorting Test” is commonly referred to as cognitive flexibility. In this work we present a biophysically detailed neurodynamical model which illustrates the neuronal base of the processes related to this cognitive flexibility. For this purpose we conducted behavioral experiments which allow the combined evaluation of different aspects of set shifting tasks: uninstructed set shifts as investigated in Wisconsin-like tasks, effects of stimulus congruency as investigated in Stroop-like tasks and the contribution of working memory as investigated in “Delayed-Match-to-Sample” tasks. The work describes how general experimental findings are usable to design the architecture of a biophysical detailed though minimalistic model with a high orientation on neurobiological findings and how, in turn, the simulations support experimental investigations. The resulting model is able to account for experimental and individual response times and error rates and enables the switch of attention as a system inherent model feature: The switching process suggested by the model is based on the memorization of the visual stimuli and does not require any synaptic learning. The operation of the model thus demonstrates with at least a high probability the neuronal dynamics underlying a key component of human behavior: the ability to adapt behavior according to context requirements—cognitive flexibility.

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References

  • Abeles, A. (1991). Corticonics. New York: Cambridge University Press.

    Google Scholar 

  • Almeida, R., Deco, G., & Stetter, M. (2004). Modular biased-competition and cooperation: A candidate mechanism for selective working memory. European Journal of Neuroscience, 20, 2789–2803.

    Article  PubMed  Google Scholar 

  • Amos, A. (2000). A computational model of information and processing in the frontal cortex and basal ganglia. Journal of Cognitive Neuroscience, 12, 505–519.

    Article  CAS  PubMed  Google Scholar 

  • Barceló, F., & Knight, R. T. (2002). Both random and perseverative errors underlie wcst deficits in prefrontal patients. Neuropsychologia, 40, 349–356.

    Article  PubMed  Google Scholar 

  • Berdia, S., & Metz, J. (1998). An artificial neural network stimulating performance of normal subjects and schizophrenics on the Wisconsin card sorting test . Artificial Intelligence in Medicine, 13, 123–138.

    Article  CAS  PubMed  Google Scholar 

  • Brunel, N., & Wang, X.-J. (2001). Effects of neuromodulation in a cortical network model of object working memory dominated by recurrent inhibition. Journal of Computational Neuroscience, 11(1), 63–85.

    Article  CAS  PubMed  Google Scholar 

  • Chen, N.-H., White, I. M., & Wise, S. P. (2001). Neuronal activity in dorsomedial frontal cortex and prefrontal cortex reflecting irrelevant stimulus dimensions. Experimental Brain Research, 139, 116–119.

    Article  CAS  Google Scholar 

  • Corchs, S., & Deco, G. (2002). Large-scale neural model for visual attention: Integration of experimental single-cell and fMRI data. Cerebral Cortex, 12(4), 339–348.

    Article  PubMed  Google Scholar 

  • Deco, G., & Rolls, E. T. (2003). Attention and working memory: A dynamical model of neural activity in the prefrontal cortex. European Journal of Neuroscience, 18, 2374–2390.

    Article  PubMed  Google Scholar 

  • Deco, G., & Rolls, E. T. (2005). Synaptic and spiking dynamics underlying reward reversal in the orbitofrontal cortex. Cerebral Cortex, 15(1), 15–30.

    Article  PubMed  Google Scholar 

  • Deco, G., Rolls, E. T., & Horwitz, B. (2004). What and where in visual working memory: A computational neurodynamical perspective for integrating fMRI and single-neuron data. Journal of Cognitive Neuroscience, 16, 683–701.

    Article  PubMed  Google Scholar 

  • Dehaene, S., & Changeux, J. (1991). The Wisconsin Card Sorting Test: Theoretical analysis and modeling in a neuronal network. Cerebral Cortex, 1(1), 62–79.

    Article  CAS  PubMed  Google Scholar 

  • Durstewitz, D., & Seamans, J. K. (2002). The computational role of dopamine d1 receptors in working memory. Neural Networks, 15, 561–572.

    Article  PubMed  Google Scholar 

  • Egner, T., & Hirsch, J. (2005). Cognitive control mechanisms resolve conflict through cortical amplification of task-relevant information. Nature Neuroscience, 12, 1784–1790.

    Article  Google Scholar 

  • Everett, J., Lavoie, K., Gagnon, J.-F., & Gosselin, N. (2001). Performance of patients with schizophrenia on the Wisconsin Card Sorting Test (WCST). Journal of Psychiatry & Neuroscience 26(2), 123–130.

    CAS  Google Scholar 

  • Gilbert, S. J., & Shallice, T. (2002). Task switching: A PDP model. Cognitive Psychology, 44, 297–337.

    Article  PubMed  Google Scholar 

  • Goldstein, G., Beers, S. R., & Shemansky, W. J. (1996). Neuropsychological differences between schizophrenic patients with heterogenous Wisconsin Card Sorting Test Performance. Schizophrenia Research, 21, 13–18.

    Article  CAS  PubMed  Google Scholar 

  • Hodgkin, A., & Huxley, A. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. Journal of Physiology (London), 117, 500–544.

    CAS  Google Scholar 

  • Kolb, B., & Wishaw, I. Q. (1983). Performance of schiziophrenic patients on tests sensitive to left or right frontal, temporal, or parietal function in neurological patients. The Journal of Nervous and Mental Disease, 171(7), 435–443.

    Article  CAS  PubMed  Google Scholar 

  • Konishi, S., Kawazu, M., Uchida, I., Kikyo, H., Asakura, I., & Miyashita, Y. (1999). Contribution of working memory to transient activation in human inferior prefrontal cortex during performance of the Wisconsin Card Sorting Test. Cerebral Cortex, 9(7), 745–753.

    Article  CAS  PubMed  Google Scholar 

  • Landro, N. I., Pape-Ellefsen, E., Hagland, K. O., & Odland, T. (2001). Memory deficits in young schizophrenics with normal intellectual function. Scandinavian Journal of Psychology, 42, 459–466.

    Article  CAS  PubMed  Google Scholar 

  • Meunier, C., & Segev, I. (2002). Playing the Devil’s advocate: Is the Hodgkin Huxley model useful? Trends in Neuroscience, 25, 558–563.

    Article  CAS  Google Scholar 

  • Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24, 167–202.

    Article  CAS  PubMed  Google Scholar 

  • Milner, B. (1963). Effects of different brain lesions on card sorting. Archives of Neurology, 9, 90–100.

    Google Scholar 

  • Monsell, S. (2003). Task switching. Trends in Cognitive Science, 7, 134–140.

    Article  Google Scholar 

  • Nakahara, K., Hayashi, T., Konishi, S., & Miyashita, Y. (2002). Functional MRI of macaque monkeys performing a cognitive set-shifting task. Science, 295(5559), 1532–1536.

    Article  CAS  PubMed  Google Scholar 

  • Owen, A., Roberts, A., Hodges, J., Summers, B., Polkey, C., & Robbins, T. (1993). Contrasting mechanisms of impaired attentional set-shifting in patients with frontal lobe damage or Parkinson’s disease. Brain, 116(5), 1159–1175.

    Article  PubMed  Google Scholar 

  • Rainer, G., & Miller, E. K. (2002). Timecourse of object-related neural activity in the primate prefrontal cortex during a short-term memory task. European Journal of Neuroscience, 15(7), 1244–1244.

    Article  PubMed  Google Scholar 

  • Rougier, N. P., Noelle, D. C., Braver, T. S., Cohen, J. D., & O’Reilly, R. C. (2005). Prefrontal cortex and flexible cognitive control: Rules without symbols. In Proceedings of the National Academy of Sciences of the United States of America, 102, 7338–7343.

    Article  CAS  PubMed  Google Scholar 

  • Rougier, N. P., & O’Reilly, R. C. (2002). Learning representations in a gated prefrontal cortex model of dynamic task switching. Cognitive Science, 26, 503–520.

    Article  Google Scholar 

  • Stemme, A. (2007). Neuronal principles underlying cognitive flexibility—a biophysical model for set shifting tasks. Ph.D. thesis, Technical University Munich. Norderstedt, Germany, BooksOnDemand.

  • Stemme, A., Deco, G., Busch, A., & Schneider, W. X. (2005). Neurons and the synaptic basis of the fMRI signal associated with cognitive flexibility. NeuroImage, 26/2, 454–470.

    Article  Google Scholar 

  • Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18, 643–662.

    Article  Google Scholar 

  • Tuckwell, H. C. (1988). Introduction to theoretical neurobiology I: Linear cable theory and dendritic structure. Cambridge: Cambridge University Press.

    Google Scholar 

  • Wallis, J. D., Anderson, K. C., & Miller, E. K. (2001). Single neurons in prefrontal cortex encode abstract rules. Nature, 411.

  • White, I. M., & Wise, S. P. (1999). Research article: Rule-dependent neuronal activity in the prefrontal cortex. Experimental Brain Research, 126(3), 315–335.

    Article  CAS  Google Scholar 

  • Wilson, F., Scalaidhe, S., & P.S., G.-R. (1994). Functional synergism between putative-aminobutyrate-containing neurons and pyramidal neurons in prefrontal cortex. Proceedings of the National Academy of Sciences of the United States of America, 91, 4009–4013.

    Article  CAS  PubMed  Google Scholar 

  • Wong, K. F., & Wang, X. J. (2006). A recurrent network mechanism of time integration in perceptual decisions. The Journal of Neuroscience, 26(4), 1314–1328.

    Article  CAS  PubMed  Google Scholar 

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Correspondence to Anja Stemme.

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Stemme, A., Deco, G. & Busch, A. The neuronal dynamics underlying cognitive flexibility in set shifting tasks. J Comput Neurosci 23, 313–331 (2007). https://doi.org/10.1007/s10827-007-0034-x

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  • DOI: https://doi.org/10.1007/s10827-007-0034-x

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