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研究生:李欣恬
研究生(外文):Hsin-Tien Lee
論文名稱:景觀影像空間頻率對注意力恢復力與腦區反應之影響
論文名稱(外文):Neural Correlates of Natural Scenes: Effects of Scene Category and Spatial Frequency on Brain Activation Responses
指導教授:張俊彥何立智何立智引用關係
指導教授(外文):Chun-Yen ChangLi-Chih Ho
口試委員:黃從仁歐聖榮侯錦雄
口試委員(外文):Tsung-Ren HuangSheng-Jung OuJing-Shoung Hou
口試日期:2016-11-05
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:園藝暨景觀學系
學門:農業科學學門
學類:園藝學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:中文
論文頁數:115
中文關鍵詞:景觀類型空間頻率低階視覺特徵恢復性環境功能性磁振造影
外文關鍵詞:scene categoryspatial frequencylow-level visual propertyrestorative environmentfMRI
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根據前人研究指出,自然景觀相較於都市景觀,能夠受到觀賞者的偏好,且提供較佳的注意力恢復力與心理效益(Bratman et al., 2015; Tennessen & Cimprich, 1995; Ulrich et al., 1991; Van den Berg et al., 2014; Velarde et al., 2007),然而恢復性環境會具有何種環境特徵,是否會受到影像視覺特徵之影響?
本研究目的為以影像低階視覺特徵的觀點,探討不同景觀類型與空間頻率構成的環境影像之偏好與注意力恢復力,並深入討論景觀影像刺激對人體大腦反應之影響。研究方法為將環境影像分為海岸、森林、都市三種景觀類型,再利用空間頻率分布為分類依據,區分高空間頻率與低空間頻率類別,共六種景觀類型,結合持續注意力測驗(Sustained Attention to Response Test; SART)、偏好問卷(preference question scales)與功能性磁振造影(functional magnetic resonance imaging; fMRI)儀器進行實驗。研究結果顯示景觀類型對偏好具有顯著差異(F=19.42, p<0.001),以海岸類型偏好平均數(3.39)為最高;而景觀類型與空間頻率對SART之正確率(Accurate Correct Rate; ACC)與反應時間(Response Time; RT)則無顯著差異。在景觀影像刺激對大腦反應之結果,主要具有顯著活化的腦區為枕葉中之舌回(lingual gyrus)與楔葉(cuneus);而觀看都市類型影像相較於海岸類型,海馬旁回(parahippocampal gyrus)會具有顯著活化的現象。藉由本研究結果能夠提供景觀影像低階視覺特徵對人們感知之影響的研究觀點,並瞭解人們與自然環境間互動的關係。
Previous researches have shown that human have a preference for images of natural scenes over built environments, and being in or viewing natural scenes can improve attention and psychological benefits (Ulrich et al., 1991; Tennessen & Cimprich, 1995; Lohr & Pearson-Mims, 2006; Velarde et al., 2007; Van den Berg et al., 2014). However, what are the features in the landscapes that produce these benefits? On the another hand, these benefits whether affect by the visual property of landscape images?
With the development of functional magnetic resonance imaging (fMRI), it provides different perspectives for landscape studies, and we can get understanding of environmental stimuli and the human brain activation. Therefore, the purpose of this study is to explore the responses of brain activation and psychology to natural scenes. We focused on the relationship between individuals’ perceptions and the environmental features. According to prior studies, the landscape type of natural and urban were mainly be discussed, besides the preference and positive inference of water scenes have been proved (Ulrich et al., 1991; White et al., 2010). In addition, the studies showed that the spatial frequency of landscape images may be the factors influencing viewer preference and attention (Berman et al., 2014; Graham et al., 2016; Ho et al., 2014; Kardan et al., 2015; Kihara & Takeda,2012; Valtchanov & Ellard, 2015). The results of this study are based on three types of landscape: natural forest, urban and water landscape, while analysis the spatial frequency of landscape images to separate low and high frequency categories.
In this study, we used fMRI to monitor brain activity responses. Participants were asked to perform the Sustained Attention to Response Test (SART), answer the preference question scales, while viewing a mixture of photographs of scene category (coast, forest, and urban) and different spatial frequency (low and high frequency). The result shows that there were different patterns of brain activation associated with different landscapes, activation responses were common found in lingual gyrus and cuneus. In viewing urban minus coast images condition, the parahippocampal gyrus were found activated. The functions of lingual gyrus and cuneus are visual information processing, regulating visual stimulation and semantic processing. The parahippocampal gyrus is involved with environmental scene recognition and visual scene memory coding. The findings of this study provide a viewpoint to the influence of landscape features on human perceptions, and how individuals interact with nature and environment.
國立臺灣大學碩士學位論文口試委員會審定書 I
誌謝 II
摘要 III
Abstract IV
目錄 VI
圖目錄 IX
表目錄 XII
第一章 緒論 1
第一節 研究背景 1
第二節 研究目的 2
第三節 研究流程 3
第二章 文獻回顧 4
第一節 不同景觀類型的偏好與注意力恢復力效益 4
一、 恢復(Restoration)相關理論 4
二、 不同景觀類型的偏好與注意力恢復力 6
三、 偏好與注意力恢復力之關係 8
第二節 景觀影像低階視覺特徵對偏好與注意力恢復力之影響 9
一、 景觀影像低階視覺特徵(Low-level visual property) 9
二、 景觀影像低階視覺特徵對偏好與注意力恢復力之影響 9
第三節 景觀刺激之腦神經相關研究 13
一、 不同景觀類型影像刺激之腦神經研究 13
二、 景觀影像低階視覺特徵之腦神經研究 19
第三章 研究方法 26
第一節 研究架構與假設 26
第二節 實驗設計 28
一、 景觀影像實驗刺激 28
二、 實驗儀器與測量工具 31
三、 研究地點 33
四、 研究對象 35
第三節 實驗流程 36
一、 前測實驗 36
二、 正式實驗 37
第四節 實驗資料統計分析方法 40
一、 行為實驗資料分析 40
二、 腦造影實驗資料分析 40
第四章 研究結果與討論 44
第一節 樣本特性分析 44
第二節 行為實驗 44
一、 行為實驗資料篩選標準 44
二、 景觀影像刺激對偏好與注意力恢復力之影響 44
三、 行為實驗結果討論 50
第三節 腦造影實驗 53
一、 合理性檢測(Sanity check) 53
二、 腦造影實驗資料篩選標準 56
三、 景觀影像刺激之腦造影實驗結果 56
四、 腦造影實驗結果討論 78
第五章 結論與建議 80
第一節 結論 80
第二節 後續研究建議 82
參考文獻 83
附錄 i
附錄一、景觀實驗刺激影像 i
附錄二、行為與社會科學研究倫理審查核可證明 iv
附錄三、研究參與者知情同意書 v
附錄四、實驗受測者說明及同意書 ix
附錄五、參考文獻摘錄簡表 xi
附錄六、參考文獻原文摘錄 xviii
Berman, M. G., Hout, M. C., Kardan, O., Hunter, M. R., Yourganov, G., Henderson, J. M., ... & Jonides, J. (2014). The perception of naturalness correlates with low-level visual features of environmental scenes. PloS one, 9(12), e114572.
Berman, M. G., Jonides, J., & Kaplan, S. (2008). The cognitive benefits of interacting with nature. Psychological science, 19(12), 1207-1212.
Berto, R. (2005). Exposure to restorative environments helps restore attentional capacity. Journal of Environmental Psychology, 25, 249–259.
Blondin, F., & Lepage, M. (2005). Decrease and increase in brain activity during visual perceptual priming: An fMRI study on similar but perceptually different complex visual scenes. Neuropsychologia, 43(13), 1887-1900.
Bratman, G. N., Daily, G. C., Levy, B. J., & Gross, J. J. (2015). The benefits of nature experience: Improved affect and cognition. Landscape and Urban Planning, 138, 41-50.
Bratman, G. N., Hamilton, J. P., Hahn, K. S., Daily, G. C., & Gross, J. J. (2015). Nature experience reduces rumination and subgenual prefrontal cortex activation. Proceedings of the national academy of sciences, 112(28), 8567-8572.
Canário, N., Jorge, L., Silva, M. L., Soares, M. A., & Castelo-Branco, M. (2016). Distinct preference for spatial frequency content in ventral stream regions underlying the recognition of scenes, faces, bodies and other objects. Neuropsychologia, 87, 110-119.
Epstein, R. A., & Morgan, L. K. (2012). Neural responses to visual scenes reveals inconsistencies between fMRI adaptation and multivoxel pattern analysis. Neuropsychologia, 50(4), 530-543.
Ganaden, R. E., Mullin, C. R., & Steeves, J. K. (2013). Transcranial magnetic stimulation to the transverse occipital sulcus affects scene but not object processing. Journal of cognitive neuroscience, 25(6), 961-968.
Graham, D., Schwarz, B., Chatterjee, A., & Leder, H. (2016). Preference for luminance histogram regularities in natural scenes. Vision research, 120, 11-21.
Grahn, J. A., & Manly, T. (2012). Common neural recruitment across diverse sustained attention tasks. PloS one, 7(11), e49556.
Hartig, T., & Staats, H. (2006). The need for psychological restoration as a determinant of environmental preferences. Journal of Environmental Psychology, 26(3), 215-226.
Hartig, T., Evans, G. W., Jamner, L. D., Davis, D. S., & Gärling, T. (2003). Tracking restoration in natural and urban field settings. Journal of environmental psychology, 23(2), 109-123.
Head, J., & Helton, W. S. (2012). Natural scene stimuli and lapses of sustained attention. Consciousness and cognition, 21(4), 1617-1625.
Henderson, J. M., Larson, C. L., & Zhu, D. C. (2007). Cortical activation to indoor versus outdoor scenes: an fMRI study. Experimental brain research, 179(1), 75-84.
Ho, L. C., Chen, J. C., & Chang, C. Y. (2014). Changes in the visual preference after stream remediation using an image power spectrum: Stone revetment construction in the Nan-Shi-Ken stream, Taiwan. Ecological Engineering, 71, 426-431.
Johnson, M. R., & Johnson, M. K. (2014). Decoding individual natural scene representations during perception and imagery. Frontiers in human neuroscience, 8, 59. Journal of environmental psychology, 15(1), 77-85.
Kaplan, R., & Kaplan, S. (1989). The experience of nature: A psychological perspective. CUP Archive.
Kaplan, S. (1995). The restorative benefits of nature: Toward an integrative framework. Journal of environmental psychology, 15(3), 169-182.
Kardan, O., Demiralp, E., Hout, M. C., Hunter, M. R., Karimi, H., Hanayik, T., ... & Berman, M. G. (2015). Is the preference of natural versus man-made scenes driven by bottom–up processing of the visual features of nature?. Frontiers in psychology, 6, 471.
Kauffmann, L., Chauvin, A., Pichat, C., & Peyrin, C. (2015a). Effective connectivity in the neural network underlying coarse-to-fine categorization of visual scenes. A dynamic causal modeling study. Brain and cognition, 99, 46-56.
Kauffmann, L., Ramanoël, S., Guyader, N., Chauvin, A., & Peyrin, C. (2015b). Spatial frequency processing in scene-selective cortical regions. NeuroImage, 112, 86-95.
Kihara, K., & Takeda, Y. (2012). Attention-free integration of spatial frequency-based information in natural scenes. Vision research, 65, 38-44.
Kravitz, D. J., Peng, C. S., & Baker, C. I. (2011). Real-world scene representations in high-level visual cortex: it''s the spaces more than the places. The Journal of Neuroscience, 31(20), 7322-7333.
Laumann, K., Gärling, T., & Stormark, K. M. (2003). Selective attention and heart rate responses to natural and urban environments. Journal of environmental psychology, 23(2), 125-134.
Lindquist, M. A. (2008). The statistical analysis of fMRI data. Statistical Science,23(4), 439-464.
Lowe, M. X., Gallivan, J. P., Ferber, S., & Cant, J. S. (2016). Feature diagnosticity and task context shape activity in human scene-selective cortex. NeuroImage, 125, 681-692.
Park, S., Brady, T. F., Greene, M. R., & Oliva, A. (2011). Disentangling scene content from spatial boundary: complementary roles for the parahippocampal place area and lateral occipital complex in representing real-world scenes. The Journal of Neuroscience, 31(4), 1333-1340.
Peyrin, C., Baciu, M., Segebarth, C., & Marendaz, C. (2004). Cerebral regions and hemispheric specialization for processing spatial frequencies during natural scene recognition. An event-related fMRI study. Neuroimage, 23(2), 698-707.
Peyrin, C., Schwartz, S., Seghier, M., Michel, C., Landis, T., & Vuilleumier, P. (2005). Hemispheric specialization of human inferior temporal cortex during coarse-to-fine and fine-to-coarse analysis of natural visual scenes. Neuroimage, 28(2), 464-473.
Schindler, A., & Bartels, A. (2016). Visual high-level regions respond to high-level stimulus content in the absence of low-level confounds. NeuroImage, 132, 520-525.
Tennessen, C. M., & Cimprich, B. (1995). Views to nature: Effects on attention. Journal of environmental psychology, 15(1), 77-85.
Torralbo, A., Walther, D. B., Chai, B., Caddigan, E., Fei-Fei, L., & Beck, D. M. (2013). Good exemplars of natural scene categories elicit clearer patterns than bad exemplars but not greater BOLD activity. PloS one, 8(3), e58594.
Ulrich, R. S. (1983). Aesthetic and affective response to natural environment. In Behavior and the natural environment (pp. 85-125). Springer US.
Ulrich, R. S., Simons, R. F., Losito, B. D., Fiorito, E., Miles, M. A., & Zelson, M. (1991). Stress recovery during exposure to natural and urban environments.Journal of environmental psychology, 11(3), 201-230.
Valtchanov, D., & Ellard, C. G. (2015). Cognitive and affective responses to natural scenes: Effects of low level visual properties on preference, cognitive load and eye-movements. Journal of Environmental Psychology, 43, 184-195.
Valtchanov, D., Barton, K. R., & Ellard, C. (2010). Restorative effects of virtual nature settings. Cyberpsychology, Behavior, and Social Networking, 13(5), 503-512.
Van den Berg, A. E., Jorgensen, A., & Wilson, E. R. (2014). Evaluating restoration in urban green spaces: Does setting type make a difference?. Landscape and Urban Planning, 127, 173-181.
Van den Berg, A. E., Koole, S. L., & van der Wulp, N. Y. (2003). Environmental preference and restoration:(How) are they related?. Journal of environmental psychology, 23(2), 135-146.
Velarde, M. D., Fry, G., & Tveit, M. (2007). Health effects of viewing landscapes– Landscape types in environmental psychology. Urban Forestry & Urban Greening, 6(4), 199-212.
Walther, D. B., Caddigan, E., Fei-Fei, L., & Beck, D. M. (2009). Natural scene categories revealed in distributed patterns of activity in the human brain. The Journal of Neuroscience, 29(34), 10573-10581.
Watson, D. M., Hartley, T., & Andrews, T. J. (2014). Patterns of response to visual scenes are linked to the low-level properties of the image. NeuroImage, 99, 402-410.
Watson, D. M., Hymers, M., Hartley, T., & Andrews, T. J. (2016). Patterns of neural response in scene-selective regions of the human brain are affected by low-level manipulations of spatial frequency. NeuroImage, 124, 107-117.
White, M., Smith, A., Humphryes, K., Pahl, S., Snelling, D., & Depledge, M. (2010). Blue space: The importance of water for preference, affect, and restorativeness ratings of natural and built scenes. Journal of Environmental Psychology, 30(4), 482-493.
Wilkie, S., & Clouston, L. (2015). Environment preference and environment type congruence: Effects on perceived restoration potential and restoration outcomes. Urban Forestry & Urban Greening, 14(2), 368-376.
Yue, X., Vessel, E. A., & Biederman, I. (2007). The neural basis of scene preferences. Neuroreport, 18(6), 525-529.
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