A method for determining venous contribution to BOLD contrast sensory activation.
While BOLD contrast reflects hemodynamic changes within capillaries serving neural tissue, it also has a venous component. Studies that have determined the relation of large blood vessels to the activation map indicate that veins are the source of the largest response, and the most delayed in time....
| Prif Awduron: | , , , , , |
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| Fformat: | Journal article |
| Iaith: | English |
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2002
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| _version_ | 1826285026149400576 |
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| author | Hall, D Gonçalves, MS Smith, S Jezzard, P Haggard, M Kornak, J |
| author_facet | Hall, D Gonçalves, MS Smith, S Jezzard, P Haggard, M Kornak, J |
| author_sort | Hall, D |
| collection | OXFORD |
| description | While BOLD contrast reflects hemodynamic changes within capillaries serving neural tissue, it also has a venous component. Studies that have determined the relation of large blood vessels to the activation map indicate that veins are the source of the largest response, and the most delayed in time. It would be informative if the location of these large veins could be extracted from the properties of the functional responses, since vessels are not visible in BOLD contrast images. The present study describes a method for investigating whether measures taken from the functional response can reliably predict vein location, or at least be useful in down-weighting the venous contribution to the activation response, and illustrates this method using data from one subject. We combined fMRI at 3 Tesla with high-resolution anatomic imaging and MR venography to test whether the intrinsic properties of activation time courses corresponded to tissue type. Measures were taken from a gamma fit to the functional response. Mean magnitude showed a significant effect of tissue type (p < 0.001) where CSF > veins approximately gray matter > white matter. Mean delays displayed the same ranking across tissue types (p < 0.001), except that veins > gray matter. However, measures for all tissue types were distributed across an overlapping range. A logistic regression model correctly discriminated 72% of the veins from gray matter in the absence of independent information of macroscopic vessels (ROC = 0.72). While tissue classification was not perfect for this subject, weighting the T contrast by the predicted probabilities materially reduced the venous component to the activation map. |
| first_indexed | 2024-03-07T01:22:41Z |
| format | Journal article |
| id | oxford-uuid:90e4a44c-abf7-4108-85b6-8ad1b2a69276 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T01:22:41Z |
| publishDate | 2002 |
| record_format | dspace |
| spelling | oxford-uuid:90e4a44c-abf7-4108-85b6-8ad1b2a692762022-03-26T23:14:49ZA method for determining venous contribution to BOLD contrast sensory activation.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:90e4a44c-abf7-4108-85b6-8ad1b2a69276EnglishSymplectic Elements at Oxford2002Hall, DGonçalves, MSSmith, SJezzard, PHaggard, MKornak, JWhile BOLD contrast reflects hemodynamic changes within capillaries serving neural tissue, it also has a venous component. Studies that have determined the relation of large blood vessels to the activation map indicate that veins are the source of the largest response, and the most delayed in time. It would be informative if the location of these large veins could be extracted from the properties of the functional responses, since vessels are not visible in BOLD contrast images. The present study describes a method for investigating whether measures taken from the functional response can reliably predict vein location, or at least be useful in down-weighting the venous contribution to the activation response, and illustrates this method using data from one subject. We combined fMRI at 3 Tesla with high-resolution anatomic imaging and MR venography to test whether the intrinsic properties of activation time courses corresponded to tissue type. Measures were taken from a gamma fit to the functional response. Mean magnitude showed a significant effect of tissue type (p < 0.001) where CSF > veins approximately gray matter > white matter. Mean delays displayed the same ranking across tissue types (p < 0.001), except that veins > gray matter. However, measures for all tissue types were distributed across an overlapping range. A logistic regression model correctly discriminated 72% of the veins from gray matter in the absence of independent information of macroscopic vessels (ROC = 0.72). While tissue classification was not perfect for this subject, weighting the T contrast by the predicted probabilities materially reduced the venous component to the activation map. |
| spellingShingle | Hall, D Gonçalves, MS Smith, S Jezzard, P Haggard, M Kornak, J A method for determining venous contribution to BOLD contrast sensory activation. |
| title | A method for determining venous contribution to BOLD contrast sensory activation. |
| title_full | A method for determining venous contribution to BOLD contrast sensory activation. |
| title_fullStr | A method for determining venous contribution to BOLD contrast sensory activation. |
| title_full_unstemmed | A method for determining venous contribution to BOLD contrast sensory activation. |
| title_short | A method for determining venous contribution to BOLD contrast sensory activation. |
| title_sort | method for determining venous contribution to bold contrast sensory activation |
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