Localization of human cortical areas activated on perception of ordered and chaotic images

被引：22

作者：

Fokin V.A. ^{[1
]}

Shelepin Yu.E. ^{[2
]}

Kharauzov A.K. ^{[2
]}

Trufanov G.E. ^{[1
]}

Sevost'yanov A.V. ^{[1
]}

Pronin S.V. ^{[2
]}

Koskin S.A. ^{[3
]}

机构：

[1] Department of Roentgenology and Radiology, Military Medical Academy, 194044 St. Petersburg

[2] Visual Physiology Laboratory, I. P. Pavlov Institute of Physiology, Russian Academy of Sciences, 199034 St. Petersburg

[3] Department of Ophthalmology, Military Medical Academy, 199044 St. Petersburg

来源：

Neuroscience and Behavioral Physiology | 2008年 / 38卷 / 7期

基金：

俄罗斯基础研究基金会;

关键词：

Chaotic and ordered images; Decision-taking center; Frontal cortex; Functional magnetic resonance imaging;

D O I：

10.1007/s11055-008-9033-2

中图分类号：

学科分类号：

摘要：

The aims of this study were to identify the locations of areas in the human cortex responsible for describing fragmented test images of different degrees of ordering and to identify the areas taking decisions regarding stimuli of this type. The locations of higher visual functions were determined by functional magnetic resonance imaging (fMRI) using a scanner fitted with a superconducting magnet and a field strength of 1.5 T. The blood oxygen level-dependent (BOLD) method was based on measurements of the level of hemoglobin oxygenation in the blood supplied to the brain. This level was taken to be proportional to the extent of neuron activation in the corresponding part of the gray matter. Stimuli were matrixes consisting of Gabor elements of different orientations. The measure of matrix ordering was the ratio of the number of Gabor elements with identical orientations to the total number of elements in the image. Brain neurons were activated by simultaneous changes in the orientations of all the elements, leading to substitution of one matrix by another. Substitution of the orientation was perceived by observers as rotation of the elements in the matrix. Stimulation by matrixes with a high level of ordering was found to activate the occipital areas of the cortex, V1 and V2 (BA17-BA18), while presentation of matrixes with random element orientations also activated the parietal-temporal cortex, V3, V4, V5 (BA19), and the parietal area (BA7). Brain zones responsible for taking decisions regarding the level of order or chaos in the organization of the stimuli are located in different but close areas of the prefrontal and frontal cortex of the brain, including BA6, BA9, and BA10. The results are assessed in terms of concepts of the roles and interactions of different areas of the human brain during recognition of fragmented images of different degrees of complexity. © Springer Science+Business Media, Inc. 2008.

引用

页码：677 / 685

页数：8

共 22 条

[1]

Glezer V.D., Vision and Thought, (1993)

[2]

Krasil'nikov N.N., Shelepin Yu.E., A functional model of vision, Optich. Zh., 64, 2, pp. 72-82, (1997)

[3]

Luriya A.R., Basic Neuropsychology, (1973)

[4]

Trufanov G.E., Fokin V.A., Sevost'yanov A.V., Shelepin Yu.E., Kharauzov A.K., Pronin S.V., Mapping of human brain areas supported higher mental visual and gnostic functions, Polenov Readings, (2006)

[5]

Shelepin Yu.E., Kharauzov A.K., Pronin S.V., Trufanov G.E., Fokin V.A., Sevost'yanov A.V., Vakhrameeva O.A., Recognition of visual objects and questions of the localization of visual functions, Polenov Readings, (2006)

[6]

Shelepin Yu.E., The relationship between measures of evoked potentials in the cat striate cortex and image size, Fiziol. Zh. SSSR, 59, 5, pp. 688-695, (1973)

[7]

Shelepin Yu.E., Localization of areas of the cat visual cortex giving invariant responses on changes in image size, Neirofiziologiya, 5, 2, pp. 115-121, (1973)

[8]

Bechara A., Damasio A.R., The somatic marker hypothesis: A neural theory of economic decision, Games Economic Behavior, 52, pp. 336-372, (2005)

[9]

Damasio A., Category-related recognition defects as a clue to the neural substrates of knowledge, Trends Neurosci., 13, 3, pp. 95-98, (1990)

[10]

Field D., Match filters, wavelets and the statistics of natural scenes, J. Opt. Technol., 66, 9, pp. 788-796, (1999)

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