Comparison of human population receptive field estimates between scanners and the effect of temporal filtering [version 2; peer review: 2 approved]
Background: Population receptive field (pRF) analysis with functional magnetic resonance imaging (fMRI) is an increasingly popular method for mapping visual field representations and estimating the spatial selectivity of voxels in human visual cortex. However, the multitude of experimental setups an...
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| Format: | Article |
| Language: | English |
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F1000 Research Ltd
2020-02-01
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| Series: | F1000Research |
| Online Access: | https://f1000research.com/articles/8-1681/v2 |
| _version_ | 1818283718704365568 |
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| author | Catherine Morgan D. Samuel Schwarzkopf |
| author_facet | Catherine Morgan D. Samuel Schwarzkopf |
| author_sort | Catherine Morgan |
| collection | DOAJ |
| description | Background: Population receptive field (pRF) analysis with functional magnetic resonance imaging (fMRI) is an increasingly popular method for mapping visual field representations and estimating the spatial selectivity of voxels in human visual cortex. However, the multitude of experimental setups and processing methods used makes comparisons of results between studies difficult. Methods: Here, we compared pRF maps acquired in the same three individuals using comparable scanning parameters on a 1.5 and a 3 Tesla scanner located in two different countries. We also tested the effect of low-pass filtering of the time series on pRF estimates. Results: As expected, the signal-to-noise ratio for the 3 Tesla data was superior; critically, however, estimates of pRF size and cortical magnification did not reveal any systematic differences between the sites. Unsurprisingly, low-pass filtering enhanced goodness-of-fit, presumably by removing high-frequency noise. However, there was no substantial increase in the number of voxels containing meaningful retinotopic signals after low-pass filtering. Importantly, filtering also increased estimates of pRF size in the early visual areas which could substantially skew interpretations of spatial tuning properties. Conclusion: Our results therefore suggest that pRF estimates are generally comparable between scanners of different field strengths, but temporal filtering should be used with caution. |
| first_indexed | 2024-12-13T00:41:22Z |
| format | Article |
| id | doaj.art-8c5be1731882403293701d51061a5950 |
| institution | Directory Open Access Journal |
| issn | 2046-1402 |
| language | English |
| last_indexed | 2024-12-13T00:41:22Z |
| publishDate | 2020-02-01 |
| publisher | F1000 Research Ltd |
| record_format | Article |
| series | F1000Research |
| spelling | doaj.art-8c5be1731882403293701d51061a59502022-12-22T00:05:07ZengF1000 Research LtdF1000Research2046-14022020-02-01810.12688/f1000research.20496.224307Comparison of human population receptive field estimates between scanners and the effect of temporal filtering [version 2; peer review: 2 approved]Catherine Morgan0D. Samuel Schwarzkopf1School of Psychology and Centre for Brain Research, University of Auckland, Auckland, New ZealandSchool of Optometry & Vision Science, University of Auckland, Auckland, New ZealandBackground: Population receptive field (pRF) analysis with functional magnetic resonance imaging (fMRI) is an increasingly popular method for mapping visual field representations and estimating the spatial selectivity of voxels in human visual cortex. However, the multitude of experimental setups and processing methods used makes comparisons of results between studies difficult. Methods: Here, we compared pRF maps acquired in the same three individuals using comparable scanning parameters on a 1.5 and a 3 Tesla scanner located in two different countries. We also tested the effect of low-pass filtering of the time series on pRF estimates. Results: As expected, the signal-to-noise ratio for the 3 Tesla data was superior; critically, however, estimates of pRF size and cortical magnification did not reveal any systematic differences between the sites. Unsurprisingly, low-pass filtering enhanced goodness-of-fit, presumably by removing high-frequency noise. However, there was no substantial increase in the number of voxels containing meaningful retinotopic signals after low-pass filtering. Importantly, filtering also increased estimates of pRF size in the early visual areas which could substantially skew interpretations of spatial tuning properties. Conclusion: Our results therefore suggest that pRF estimates are generally comparable between scanners of different field strengths, but temporal filtering should be used with caution.https://f1000research.com/articles/8-1681/v2 |
| spellingShingle | Catherine Morgan D. Samuel Schwarzkopf Comparison of human population receptive field estimates between scanners and the effect of temporal filtering [version 2; peer review: 2 approved] F1000Research |
| title | Comparison of human population receptive field estimates between scanners and the effect of temporal filtering [version 2; peer review: 2 approved] |
| title_full | Comparison of human population receptive field estimates between scanners and the effect of temporal filtering [version 2; peer review: 2 approved] |
| title_fullStr | Comparison of human population receptive field estimates between scanners and the effect of temporal filtering [version 2; peer review: 2 approved] |
| title_full_unstemmed | Comparison of human population receptive field estimates between scanners and the effect of temporal filtering [version 2; peer review: 2 approved] |
| title_short | Comparison of human population receptive field estimates between scanners and the effect of temporal filtering [version 2; peer review: 2 approved] |
| title_sort | comparison of human population receptive field estimates between scanners and the effect of temporal filtering version 2 peer review 2 approved |
| url | https://f1000research.com/articles/8-1681/v2 |
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