JRM Vol.20 No.5 pp. 726-730
doi: 10.20965/jrm.2008.p0726


Performance Types and Activation of the Prefrontal Cortex

Harumi Kobayashi and Tetsuya Yasuda

Tokyo Denki University, Graduate School of Advanced Science and Technology, Ishizaka, Hatoyama-machi, Hiki-gun, Saitama, 350-0394 Japan

February 18, 2008
July 4, 2008
October 20, 2008
skill acquisition, working memory, prefrontal cortex
We investigated the relationship between performance types in skill acquisition and the use of the prefrontal cortex (PFC). We used a modified mirror drawing task in which participants using a pen tablet repeated the tracing of a star displayed on a screen. Changes in cerebral blood flow were measured using near infrared spectroscopy (NIRS). Participants conducted two tasks, mirror drawing, i.e., tracing a mirror image of a star, and an usual drawing, i.e., tracing a star. Performance was scored based on the number of errors and drawn lengths. Results suggested that two types of participants - those whose number of errors decreased when they repeated the task and those whose number of errors did not decrease. We thus concluded that (1) changes in oxy-hemoglobin concentration (Oxy-Hb) are higher in the mirror drawing task than in the usual drawing task; (2) oxy-Hb decreased in the right PFC when participants whose number of errors decreased repeated the task 4 days later, but did not decrease in the left PFC; (3) oxy-Hb decreased in the left PFC when participants whose number of errors did not decrease repeated the task 4 days later, but did not decrease in the right PFC. Our findings indicate that activation of the PFC can be used to assess skill levels in on-going tasks and may provide information on how to time assistance.
Cite this article as:
H. Kobayashi and T. Yasuda, “Performance Types and Activation of the Prefrontal Cortex,” J. Robot. Mechatron., Vol.20 No.5, pp. 726-730, 2008.
Data files:
  1. [1] F. Cincottia, D. Mattiaa, F. Aloisea, S. Bufalaria, G. Schalkb, G. Orioloc, A. Cherubinic, M. G. Marciania, and F. Babiloni, “Noninvasive brain-computer interface system: Towards its application as assistive technology,” Brain Research Bulletin, 75, pp. 796-803, 2008.
  2. [2] F. Cincottia, D. Mattiaa, F. Aloisea, S. Bufalaria, L. Astolfia, F. De Vico Fallania, A. Toccia, L. Bianchia, M. G. Marciania, S. Gaof, J.Millang, and F. Babiloni, “High-resolution EEG techniques for brain-computer interface applications,” Journal of Neuroscience Methods, 167, pp. 31-42, 2008.
  3. [3] F. Harashima and S. Suzuki, “Future of mechatronics and human machine operation skill and visual perception,” SICE Journal of Control, Measurement, and System Integration, 1(1), pp. 18-25, 2008.
  4. [4] Y. Hoshi, I. Oda, Y.Wada, Y. Ito, Y. Yamashita, M. Oda, K. Ohta, Y. Yamada, and M. Tamura, “Visuospatial imagery is a fruitful strategy for the digit span backward task: a study with near-infrared optical tomography,” Cognitive Brain Research, 9(3), pp. 339-342, 2000.
  5. [5] A. Baddeley and G. Hitch, “Working Memory,” In G. H. Bower (Ed.), The psychology of learning and motivation, Vol.8, New York: Academic Press. pp. 47-89, 1974.
  6. [6] G. Matsuda and K. Hiraki, “Sustained decrease in oxygenated hemoglobin during video games in the dorsal prefrontal cortex: A NIRS study of children,” NeuroImage, 29, pp. 706-711, 2006.
  7. [7] V. D. Calhoun, J. J. Pekar, V. B. McGinty, T. Adali, T. D. Watson, and G. D. Pearlson, “Different activationdynamics in multiple neural systems during simulated driving, Human Brain Mapping,” 16(3), pp. 158-167, 2002.
  8. [8] M. Hatakenaka, I. Miyai, M. Mihara, S. Sakoda, and K. Kubota, “Frontal regions involved in learning of motor skill –A functional NIRS study,” NeuroImage, 34, pp. 109-116, 2007.
  9. [9] H. Kobayashi, T. Yasuda, and S. Suzuki, “The relations between development of humans’ manipulative skills and physiological signals of brain and hand,” Int. Journal of Assistive Robotics and Mechatronics, 7(1), pp. 49-61, 2006.
  10. [10] J. Henderson, “Memory and forgetting,” London:Routledge, 1999.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on May. 19, 2024