DOI QR코드

DOI QR Code

도형 과제 수행 때 나타나는 청소년의 지능별 대뇌 및 소뇌의 활성도 차이 분석

Activation Differences of Superior Parietal Lobule and Cerebellum Areas While Inferring Geometrical Figures per Intellectual Category in Adolescents

  • 투고 : 2013.09.25
  • 심사 : 2013.10.22
  • 발행 : 2013.10.31

초록

대뇌 피질과 지능과의 관련성은 다양한 방법으로 연구되어 왔으며, 지능 발현에 관여하는 뇌 영역이 속속 밝혀지고 있다. 이와 함께 소뇌도 대뇌처럼 언어와 기억, 정보 처리 등 다양한 인지 기능 수행에 밀접한 관련이 있다는 사실도 연구 결과 나타났다. 그러나 특정 과제 수행 때 지능별 대뇌와 소뇌 영역들의 활성도 차이를 밝힌 연구 결과는 찾기 어렵다. 본 연구는 공간유추 과제를 수행할 때 나타난 대뇌와 소뇌의 활성 영역을 탐색하고, 그 차이를 분석하였다. 건강한 81명(평균 16세 3개월)의 남자 청소년을 대상으로 WAIS 지능 검사를 하여 5개 지능 범주로 나누고, 도형 유추 과제를 수행하게 하면서 기능성자기공명영상기술(fMRI)로 뇌 영상을 촬영하였다. 그 결과 12개 뇌 영역에서 활성이 나타났는데, 대뇌 피질에서는 시각영역인 양측 하후두회 외에 양측 상두정회와 우측하전두회, 양측 미상회, 그리고 소뇌의 5개 세부 영역들이다. 특히 지능(IQ)이 높을수록 이들 영역의 활성이 강하게 나타났으며, 영재 중에서도 지능이 아주 높은 140~147 범주의 피험자들은 다른 지능그룹에 비해 월등히 높은 활성을 보였다. 이런 결과는 아주 높은 지능의 영재들의 뇌 활용 특징일 수 있기 때문에 '슈퍼 영재'들의 판별에 활용할 수 있을 것으로 기대된다.

The relationship between the cerebral cortex and human intelligence has been studied using various methods, and related brain areas involved in intellectual manifestation have been discovered individually. Such studies have also shown the cerebellum is closely involved in various cognitive functions such as language, memory, and information processing. However, studies showing an activity difference between the cerebral cortex and cerebellum when performing specific tasks are hard to find. This study searched and analyzed the active regions of the cerebral cortex and cerebellum seen while performing the inference of geometrical figures. A WAIS intelligence test was conducted using 81 healthy boys (16.3 years of age on average), and five categories were classified. While performing the inference of shapes, their brain images were taken using functional magnetic resonance imaging (fMRI). As a result, the activity in 12 brain regions was observed, including in the cerebral cortex, the bilateral inferior parietal, the visual cortex, bilateral superior parietal, frontal-Inf-Tri-R, and bilateral caudate, while activities in 5 discrete areas were seen in the cerebellum. In particular, the higher the intelligence (IQ) of the subject, the stronger their activity. Among those with the most superior intelligence, subjects with an IQ of 140-147 showed significantly higher activity compared to the other groups. Such results seem to represent a very high utilization of intelligence in a highly gifted group, and we can expect to use this to determine the super gifted.

키워드

참고문헌

  1. 김예림 (2013). 청소년의 지능범주별 대뇌피질 변화성 분석 연구. 영재교육연구. 23(3), 421-434. https://doi.org/10.9722/JGTE.2013.23.3.421
  2. 조선희, 김희백, 최유용, 채정호, 이건호 (2005). 뇌기능영상 측정법을 이용한 영재성 평가의 타당성 연구. 영재교육연구. 15(2), 101-125.
  3. Atherton, M., Zhuang, J., Bart, W. M., Hu, X., & He, S. (2003). A functional MRI study of high-level cognition. I. The game of chess. Cognitive Brain Research, 16(1), 26-31. https://doi.org/10.1016/S0926-6410(02)00207-0
  4. Choi, Y. Y., Shamosh, N. A., Cho, S. H., DeYoung, C. G., Lee, M. J., Lee, J. M., Kim, S. I., Cho, Z. H., Kim, K., Gray, J. R., & Lee, K. H. (2008). Multiple Bases of Human Intelligence Revealed by Cortical Thickness and Neural Activation. The Journal of Neuroscience, 28(41), 10323-10329. https://doi.org/10.1523/JNEUROSCI.3259-08.2008
  5. Claeys, K. G., Orban, G. A., Dupont, P., Sunaert, S., Hecke, P. V., & Schutter, E. D. (2003). Involvement of multiple functionally distinct cerebellar regions in visual discrimination: A human functional imaging study. NeuroImage, 20, 840-854. https://doi.org/10.1016/S1053-8119(03)00366-5
  6. Duncan, J., & Owen, A. M. (2000). Common regions of the human frontal lobe recruited by diverse cognitive demands. Trends in Neurosciences 23(10), 475-483. https://doi.org/10.1016/S0166-2236(00)01633-7
  7. Fangmeier, T., Knauff, M., Ruff, C. C., & Sloutsky, V. (2006). fMRI evidence for a three-stage model of deductive reasoning. Journal of Cognitive Neuroscience, 18(3), 320-334. https://doi.org/10.1162/jocn.2006.18.3.320
  8. Ghatan, P. H., Hsieh, J. C., Wirsen-Meurling, A., Wredling, R., Eriksson, L., Stone-Elander, S., Levander, S., & Ingvar, M. (1995). Brain activation induced by the perceptual maze test: A PET study of cognitive Performance. Neuro-Image, 2(2), 112-124.
  9. Goel, V., & Dolan, R. J. (2001). Functional neuroanatomy of three-term relational reasoning. Neuropsychologia, 39(9), 901-909. https://doi.org/10.1016/S0028-3932(01)00024-0
  10. Goel, V., Gold, B., Kapur, S., & Houle, S. (1997). The seats of reason? An imaging study of deductive and inductive reasoning. NeuroReport, 8(5), 1305-1310. https://doi.org/10.1097/00001756-199703240-00049
  11. Goel, V., Gold, B., Kapur, S., & Houle, S. (1998). Neuroanatomical correlates of human reasoning. Journal of Cognitive Neuroscience, 10(3), 293-302. https://doi.org/10.1162/089892998562744
  12. Gray, J. R., Chabris, C. F., & Braver, T. S. (2003). Neural mechanisms of general fluid intelligence. Nature Neuroscience, 6(3), 316-322. https://doi.org/10.1038/nn1014
  13. Haier, R. J. (1993). Cerebral glucose metabolism and intelligence. In P. A. Vernon. (Ed.), Biological approaches to the study of human intelligence (pp. 317-373). Norwood, NJ: Ablex.
  14. Haier, R. J., & Benbow, C. P. (1995). Sex differences and lateralization in temporal lobe glucose metabolism during mathematical reasoning. Developmental Neuropsychology, 11(4), 405-415. https://doi.org/10.1080/87565649509540629
  15. Haier, R. J., White, N. S., & Alkire, M. T. (2003). Individual differences in general intelligence correlate with brain function during non-reasoning tasks. Intelligence, 31(5), 429-441. https://doi.org/10.1016/S0160-2896(03)00025-4
  16. Lee, K. H., Choi, Y. Y., Gray, J. R., Cho, S. H., Chae, J. H., Lee, S., & Kim, K. (2006). Neural correlates of superior intelligence: Stronger recruitment of posterior parietal cortex. NeuroImage, 29(2), 578-586. https://doi.org/10.1016/j.neuroimage.2005.07.036
  17. Lewis, S. M., Jerde, T. A., Tzagarakis, C., Gergopoulos, M. A., Tsekos, N., Amirikian, B., Kim, S. G., Ugurbil, K., & Georgopoulos, A. P. (2003). Cerebellar activation during copying geometrical shapes. Journal of Neurophysiology, 90, 3874-3887. https://doi.org/10.1152/jn.00009.2003
  18. Prabhakaran, V., Smith, J. A., Desmond, J. E., Glover, G. H., & Gabrieli, J. D. (1997). Neural substrates of fluid reasoning: An fMRI study of neocortical activation during performance of the Raven's Progressive Matrices test. Cognitive Psychology, 33(1), 43-63. https://doi.org/10.1006/cogp.1997.0659
  19. O'Boyle, M. W., Cunnington, R., Silk, T. J., Vaughan, D., Jackson, G., Syngeniotis, A., & Egan, G. F. (2005). Mathematically gifted male adolescents activate a unique brain network during mental rotation. Brain Research: Cognitive Brain Research, 25(2), 583-587. https://doi.org/10.1016/j.cogbrainres.2005.08.004
  20. Ogawa, S., Menon, R. S., Tank, D. W., Merkle, H., Kim, S. G., Ellermann, J. M., & Ugurbil, K. (1993). Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model. Biophysical Journal, 64(3), 803-812. https://doi.org/10.1016/S0006-3495(93)81441-3
  21. Jung, R. E., & Haier, R. J. (2007). The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence. Behavioral and Brain Sciences, 30, 135-187. https://doi.org/10.1017/S0140525X07001185
  22. Schmithorst, V. J., & Holland, S. K. (2006). Functional MRI evidence for disparate developmental processes underlying intelligence in boys and girls. NeuroImage, 31(3), 1366-1379. https://doi.org/10.1016/j.neuroimage.2006.01.010
  23. Timothy, C. J., & Richard, B. I. (2001). The Cognitive neuropsychology of the cerebellum, International Review of Psychiatry, 13, 276-282. https://doi.org/10.1080/09540260120082128