臺灣博碩士論文加值系統

大多數知覺專家相關研究，所聚焦討論的腦區多集中於下枕顳葉的物體類別選擇區(尤其是臉孔選擇區，FFA)，對初級視覺皮層(Early Visual Cortex, 或EVC)的探討是較少的。而且，文獻中對知覺專家看專家物體，如車專家看車，在EVC 的反應，也有不一致的結論。經由文獻回顧，我們假設刺激呈現是否符合視網膜拓譜特性，為一影響知覺專家效應是否出現在EVC 的重要因素。因此本研究第一部分針對自然界的專家— 賞鳥專家，藉由操弄刺激呈現方式(中央呈現與周邊跳動呈現)，發現唯有刺激呈現於視野中央，即符合視網膜拓譜特性時，EVC 的反應才會與行為專家指標呈顯著正相關。本研究第二部分探討人造物體古力寶(Greeble)的專家訓練過程中，EVC 是否也會出現專家效應。結果發現，古力寶訓練會改變EVC 神經反應模式。且在作業屬性更需要專家的自動化處理情形下，EVC 的BOLD 反應會在訓練後顯著提高。
本研究的結論為：專家的知覺處裡效應並非侷限於物體選擇區。當刺激呈現符合視網膜拓譜特性以及作業需要專家的自動化處理時，EVC 的顯著相關(研究一)或顯著差異(研究二)就可被觀察到。綜合上述兩個研究結果，本研究對知覺專家處理的動態歷程，以及與大腦視覺皮層處理階段的相關性，提供更深一層的省思。

Most of the neuroimaging studies on perceptual expertise exclusively put their focus on the category-selective areas of inferior occipitotemperal cortex, especially Fusiform Face Area, or FFA. Few studies addressed the engagement of Early Visual Cortex (EVC) in expertise processing. In addition, whether real-world experts (such as car experts viewing cars) could induce neural changes of EVC remains controversial. By reviewing the extant literature, we hypothesized that the retinotopic properties of EVC as a crucial factor to determine engagement of EVC. Therefore, in the first part of this study, we focused on a real-world expertise – bird, and altered stimulus location presented on the visual field to modulate the retinotopic properties.
The result showed that expertise-related neural changes were observed only when stimuli were always presented on the center of the visual field (that is, follow the rule of the retinotopic property) but not at the context when stimuli appeared randomly on the four quadrats. In the second part, we focused on a different expertise category called Greeble, to ask whether the expertise effect of EVC could generalize into artificial objects. The result can be inferred that, training could induce changes of neural pattern for Greeble. In addition, with task demand which enhance experts’ automaticity involvement into expertise objects, BOLD response of EVC would significantly increase after training.
The conclusion of this study is that the expertise effect is not limited to the category-selective areas. A significant correlation (Study 1) or a significant difference (Study 2) of EVC can be observed when the stimulus presentation meets the retinotopic properties and when task demand enhances experts’ automaticity involvement. Combining the results of the above two studies, this study provides a deeper reflection on the dynamic processing of expertise as well as on the necessity of existence of visual hierarchy.

Introduction ............... 1
Expertise-related activity in higher visual cortex ....... 1
Category selectivity in early visual areas .......... 2
Evidence of expertise engagement in early visual areas....... 3
Experiment 1 .............. 6
Bird expertise: passive-viewing task .......... 6
Method ................ 6
Results............... 13
Experiment 2 .............. 19
Bird expertise: one – back identity task .......... 19
Method ................ 19
Results............... 21
Experiment 3 .............. 28
Greeble expertise: passive-viewing task .......... 28
Method ................ 28
Results............... 33
Experiment 4 .............. 42
Greeble expertise: verification task ........... 42
Method ................ 42
Results............... 44
Discussion ............... 47
Stimulus position affects engagement of early visual areas ..... 47
Influences of top-down engagement ......... 48
Conclusion .............. 49
Reference ................ 50

1. Bilalic, M., Langner, R., Ulrich, R., Grodd, W., 2011. Many faces of expertise:
fusiform face area in chess experts and novices. J. Neurosci. 31, 10206–10214.
2. Brants, M., Wagemans, J., Op de Beeck, H.P., 2011. Activation of fusiform face
area by greebles is related to face similarity but not expertise. J. Cogn. Neurosci.
23, 3949–3958.
3. Coutanche, M. N., Thompson-Schill, S. L., ＆ Schultz, R. T. (2011). Multi-voxel
pattern analysis of fMRI data predicts clinical symptom
severity. NeuroImage,57(1), 113-123. doi:10.1016/j.neuroimage.2011.04.016
4. Dehaene, S., Pegado, F., Brago, L. W., Ventura, P., Filho, G. N., Jobert, A., et al.
(2010). How learning to read changes the cortical networks for vision and
language. Science, 330, 1359.
5. Detre, G. J., Polyn, S. M., Moore, C. D.,Natu, V. S., Singer, B. D., Cohen, J.
D.,Haxby, J. V., and Norman, K. A. (2006).“The multi-voxel pattern
analysis(MVPA) toolbox, in Annual Meetingof the Organization of Human
BrainMapping, June 11–15, 2006, Florence,Italy.
6. DiCarlo, J. J., Zoccolan, D., ＆ Rust, N. C. (2012). How does the brain solve
visual object recognition? Neuron, 73, 415–434.
7. Ericsson, K. A., ＆ Lehmann, A. C. (1996). EXPERT AND EXCEPTIONAL
PERFORMANCE: Evidence of Maximal Adaptation to Task Constraints. Annual
Review of Psychology, 47(1), 273-305. doi:10.1146/annurev.psych.47.1.273
8. Gauthier, I., Skudlarski, P., Gore, J. C., ＆ Anderson, A. W. (2000). Expertise for
cars and birds recruits brain areas involved in face recognition. Nature
neuroscience, 3(2), 191.
9. Gauthier, I., ＆ Tarr, M. J. (1997). Becoming a “Greeble Expert: Exploring
Mechanisms for Face Recognition. Vision Research,37(12), 1673-1682.
doi:10.1016/s0042-6989(96)00286-6
10. Gauthier, I., Tarr, M. J., Anderson, A. W., Skudlarski, P., ＆ Gore, J. C. (1999).
Activation of the middle fusiform face area increases with expertise in
recognizing novel objects. Nature Neuroscience, 2(6), 568-573.
doi:10.1038/9224
11. Grill-Spector, K., Knouf, N., Kanwisher, N., 2004. The fusiform face area
subserves face perception, not generic within-category identification. Nat.
Neurosci. 7, 555–562.
12. Grill-Spector, K., Kourtzi, Z., ＆ Kanwisher, N. (2001). The lateral occipital
complex and its role in object recognition. Vision research, 41(10-11), 1409-
1422.
13. Gauthier, I., Williams, P., Tarr, M. J., ＆ Tanaka, J. (1998). Training ‘greeble’
experts: A framework for studying expert object recognition processes. Vision
Research,38(15-16), 2401-2428. doi:10.1016/s0042-6989(97)00442-2
14. Harel, A., Gilaie-Dotan, S., Malach, R., ＆ Bentin, S. (2010). Top-Down
Engagement Modulates the Neural Expressions of Visual Expertise. Cerebral
Cortex,20(10), 2304-2318. doi:10.1093/cercor/bhp316
15. Harel, A., Kravitz, D., ＆ Baker, C. (2013). Beyond perceptual expertise:
Revisiting the neural substrates of expert object recognition. Frontiers in Human
Neuroscience,14(10), 820-820. doi:10.1167/14.10.820
16. Harel, A. (2016). What is special about expertise? Visual expertise reveals the
interactive nature of real-world object recognition. Neuropsychologia,83, 88-99.
doi:10.1016/j.neuropsychologia.2015.06.004
17. Harley, E.M., Pope, W.B., Villablanca, J.P., Mumford, J., Suh, R., Mazziotta,
J.C., Enzmann, D., Engel, S. a, 2009. Engagement of fusiform cortex and
disengagement of lateral occipital cortex in the acquisition of radiological
expertise. Cereb. Cortex 19, 2746–2754.
18. Harrison, S. A., ＆ Tong, F. (2009). Decoding reveals the contents of visual
working memory in early visual areas. Nature,458(7238), 632-635.
doi:10.1038/nature07832
19. Haxby, J. V. (2012). Multivariate pattern analysis of fMRI: The early
beginnings. NeuroImage,62(2), 852-855. doi:10.1016/j.neuroimage.2012.03.016
20. Hershler, O., ＆ Hochstein, S. (2009). The importance of being expert: Top-down
attentional control in visual search with photographs. Attention, Perception, ＆
Psychophysics, 71(7), 1478-1486.
21. James, T. W., ＆ James, K. H. (2013). Expert individuation of objects increases
activation in the fusiform face area of children. NeuroImage, 67, 182-192.
22. Jiang, X., Bradley, E., Rini, R. a., Zeffiro, T., VanMeter, J., Riesenhuber, M.,
2007. Categorization training results in shape- and category-selective human
neural plasticity. Neuron 53, 891–903.
23. Jimura, K., ＆ Poldrack, R. A. (2012). Analyses of regional-average activation
and multivoxel pattern information tell complementary
stories. Neuropsychologia,50(4), 544-552.
doi:10.1016/j.neuropsychologia.2011.11.007
24. Kanwisher, N., McDermott, J., ＆ Chun, M. M. (1997). The fusiform face area: a
module in human extrastriate cortex specialized for face perception. Journal of
neuroscience, 17(11), 4302-4311.
25. Krawczyk, D.C., Boggan, A.L., McClelland, M.M., Bartlett, J.C., 2011. The
neural organization of perception in chess experts. Neurosci. Lett. 499, 64–69.
26. Kriegeskorte N, Goebel R, Bandettini P. 2006. Information-based functional
brain mapping. Proc Natl Acad Sci USA. 103:3863–3868.
27. Martens, F., Bulthé, J., Vliet, C. V., ＆ Beeck, H. O. (2018). Domain-general and
domain-specific neural changes underlying visual expertise. NeuroImage,169,
80-93. doi:10.1016/j.neuroimage.2017.12.013
28. Matsuzaki, N., Schwarzlose, R.F., Nishida, M., Ofen, N., Asano, E., 2015.
Upright face- preferential high-gamma responses in lower-order visual areas:
evidence from intracranial recordings in children. Neuroimage 109, 249–259.
29. McGugin, R.W., Gatenby, J.C., Gore, J.C., Gauthier, I., 2012a. High-resolution
imaging of expertise reveals reliable object selectivity in the fusiform face area
related to perceptual performance. Proc. Natl. Acad. Sci. 109, 17063–17068.
Available at. http://jov.arvojournals.org/Article.aspx?doi¼10.1167/12.9.1281.
30. Mcgugin, R. W., Gulick, A. E., Tamber-Rosenau, B. J., Ross, D. A., ＆ Gauthier,
I. (2014). Expertise Effects in Face-Selective Areas are Robust to Clutter and
Diverted Attention, but not to Competition. Cerebral Cortex,25(9), 2610-2622.
doi:10.1093/cercor/bhu060
31. Mcgugin, R. W., Newton, A. T., Gore, J. C., ＆ Gauthier, I. (2014). Robust
expertise effects in right FFA. Neuropsychologia,63, 135-144.
doi:10.1016/j.neuropsychologia.2014.08.029
32. Mckone, E., Kanwisher, N., ＆ Duchaine, B. C. (2007). Can generic expertise
explain special processing for faces? Trends in Cognitive Sciences,11(1), 8-15.
doi:10.1016/j.tics.2006.11.002
33. Mongelli, V., Dehaene, S., Vinckier, F., Peretz, I., Bartolomeo, P., Cohen, L.,
2016. Music and words in the visual cortex: the impact of musical expertise.
Cortex 1–15.
34. Moore, C.D., Cohen, M.X., Ranganath, C., 2006. Neural mechanisms of expert
skills in visual working memory. J. Neurosci. 26, 11187–11196.
35. Norman, K. A., Polyn, S. M., Detre, G. J., ＆ Haxby, J. V. (2006). Beyond mindreading:
Multi-voxel pattern analysis of fMRI data. Trends in Cognitive
Sciences,10(9), 424-430. doi:10.1016/j.tics.2006.07.005
36. Pereira, F., Mitchell, T., ＆ Botvinick, M. (2009). Machine learning classifiers
and fMRI: A tutorial overview. NeuroImage,45(1).
doi:10.1016/j.neuroimage.2008.11.007
37. Op de Beeck, H.P., Baker, C.I., DiCarlo, J.J., Kanwisher, N.G., 2006.
Discrimination training alters object representations in human extrastriate cortex.
J. Neurosci. 26, 13025–13036.
38. Quamme, J. R., Weiss, D. J., ＆ Norman, K. A. (2010). Listening for recollection:
a multi-voxel pattern analysis of recognition memory retrieval strategies. Frontiers in Human Neuroscience, 4, 61.
39. Rhodes, G., Byatt, G., Michie, P.T., Puce, A., 2004. Is the fusiform face area
specialized for faces, individuation, or expert individuation? J. Cogn. Neurosci.
16, 189–203.
40. Rivolta, D., Woolgar, A., Palermo, R., Butko, M., Schmalzl, L., ＆ Williams, M.
A. (2014). Multi-voxel pattern analysis (MVPA) reveals abnormal fMRI activity
in both the “core and “extended face network in congenital
prosopagnosia. Frontiers in human neuroscience, 8, 925.
41. Turner, B.O., et al., Spatiotemporal activity estimation for multivoxel pattern
analysis with rapid event-related designs. Neuroimage, 2012. 62(3): p. 1429-38.
42. Uyar, F., Shomstein, S., Greenberg, A. S., ＆ Behrmann, M. (2016). Retinotopic
information interacts with category selectivity in human ventral
cortex. Neuropsychologia, 92, 90-106.
43. Wong, A.C.N., Palmeri, T.J., Rogers, B.P., Gore, J.C., Gauthier, I., 2009. Beyond
shape: how you learn about objects affects how they are represented in visual
cortex. PLoS One 4, 1–7.
44. Wong, Y. K., Peng, C., Fratus, K. N., Woodman, G. F., ＆ Gauthier, I. (2014).
Perceptual expertise and top–down expectation of musical notation engages the
primary visual cortex. Journal of Cognitive Neuroscience, 26(8), 1629-1643.
45. Xu, Y. (2005). Revisiting the role of the fusiform face area in visual expertise.
Cerebral Cortex, 15(8), 1234–1242. https://doi.org/10.1093/cercor/bhi006