Individualized cognitive neuroscience needs 7T: Comparing numerosity maps at 3T and 7T MRI
The field of cognitive neuroscience is weighing evidence about whether to move from the current standard field strength of 3 Tesla (3T) to ultra-high field (UHF) of 7T and above. The present study contributes to the evidence by comparing a computational cognitive neuroscience paradigm at 3T and 7T....
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| Format: | Article |
| Language: | English |
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Elsevier
2021-08-01
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| Series: | NeuroImage |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811921004614 |
| _version_ | 1818355527234617344 |
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| author | Yuxuan Cai Shir Hofstetter Wietske van der Zwaag Wietske Zuiderbaan Serge O. Dumoulin |
| author_facet | Yuxuan Cai Shir Hofstetter Wietske van der Zwaag Wietske Zuiderbaan Serge O. Dumoulin |
| author_sort | Yuxuan Cai |
| collection | DOAJ |
| description | The field of cognitive neuroscience is weighing evidence about whether to move from the current standard field strength of 3 Tesla (3T) to ultra-high field (UHF) of 7T and above. The present study contributes to the evidence by comparing a computational cognitive neuroscience paradigm at 3T and 7T. The goal was to evaluate the practical effects, i.e. model predictive power, of field strength on a numerosity task using accessible pre-processing and analysis tools. Previously, using 7T functional magnetic resonance imaging and biologically-inspired analyses, i.e. population receptive field modelling, we discovered topographical organization of numerosity-selective neural populations in human parietal cortex. Here we show that these topographic maps are also detectable at 3T. However, averaging of many more functional runs was required at 3T to reliably reconstruct numerosity maps. On average, one 7T run had about four times the model predictive power of one 3T run. We believe that this amount of scanning would have made the initial discovery of the numerosity maps on 3T highly infeasible in practice. Therefore, we suggest that the higher signal-to-noise ratio and signal sensitivity of UHF MRI is necessary to build mechanistic models of the organization and function of our cognitive abilities in individual participants. |
| first_indexed | 2024-12-13T19:42:44Z |
| format | Article |
| id | doaj.art-34efd59cb1b1449a8abd7f430e84652f |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-12-13T19:42:44Z |
| publishDate | 2021-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-34efd59cb1b1449a8abd7f430e84652f2022-12-21T23:33:39ZengElsevierNeuroImage1095-95722021-08-01237118184Individualized cognitive neuroscience needs 7T: Comparing numerosity maps at 3T and 7T MRIYuxuan Cai0Shir Hofstetter1Wietske van der Zwaag2Wietske Zuiderbaan3Serge O. Dumoulin4Spinoza Centre for Neuroimaging, Amsterdam, Netherlands; Experimental and Applied Psychology, VU University Amsterdam, Amsterdam, Netherlands; Corresponding authors at: Spinoza Centre for Neuroimaging, Meibergdreef 75, 1105 BK, Amsterdam, The Netherlands.Spinoza Centre for Neuroimaging, Amsterdam, NetherlandsSpinoza Centre for Neuroimaging, Amsterdam, NetherlandsSpinoza Centre for Neuroimaging, Amsterdam, NetherlandsSpinoza Centre for Neuroimaging, Amsterdam, Netherlands; Experimental and Applied Psychology, VU University Amsterdam, Amsterdam, Netherlands; Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, Netherlands; Corresponding authors at: Spinoza Centre for Neuroimaging, Meibergdreef 75, 1105 BK, Amsterdam, The Netherlands.The field of cognitive neuroscience is weighing evidence about whether to move from the current standard field strength of 3 Tesla (3T) to ultra-high field (UHF) of 7T and above. The present study contributes to the evidence by comparing a computational cognitive neuroscience paradigm at 3T and 7T. The goal was to evaluate the practical effects, i.e. model predictive power, of field strength on a numerosity task using accessible pre-processing and analysis tools. Previously, using 7T functional magnetic resonance imaging and biologically-inspired analyses, i.e. population receptive field modelling, we discovered topographical organization of numerosity-selective neural populations in human parietal cortex. Here we show that these topographic maps are also detectable at 3T. However, averaging of many more functional runs was required at 3T to reliably reconstruct numerosity maps. On average, one 7T run had about four times the model predictive power of one 3T run. We believe that this amount of scanning would have made the initial discovery of the numerosity maps on 3T highly infeasible in practice. Therefore, we suggest that the higher signal-to-noise ratio and signal sensitivity of UHF MRI is necessary to build mechanistic models of the organization and function of our cognitive abilities in individual participants.http://www.sciencedirect.com/science/article/pii/S1053811921004614Ultra-high fieldBOLDNumerosity mapComputational modelCognitive neuroscience |
| spellingShingle | Yuxuan Cai Shir Hofstetter Wietske van der Zwaag Wietske Zuiderbaan Serge O. Dumoulin Individualized cognitive neuroscience needs 7T: Comparing numerosity maps at 3T and 7T MRI NeuroImage Ultra-high field BOLD Numerosity map Computational model Cognitive neuroscience |
| title | Individualized cognitive neuroscience needs 7T: Comparing numerosity maps at 3T and 7T MRI |
| title_full | Individualized cognitive neuroscience needs 7T: Comparing numerosity maps at 3T and 7T MRI |
| title_fullStr | Individualized cognitive neuroscience needs 7T: Comparing numerosity maps at 3T and 7T MRI |
| title_full_unstemmed | Individualized cognitive neuroscience needs 7T: Comparing numerosity maps at 3T and 7T MRI |
| title_short | Individualized cognitive neuroscience needs 7T: Comparing numerosity maps at 3T and 7T MRI |
| title_sort | individualized cognitive neuroscience needs 7t comparing numerosity maps at 3t and 7t mri |
| topic | Ultra-high field BOLD Numerosity map Computational model Cognitive neuroscience |
| url | http://www.sciencedirect.com/science/article/pii/S1053811921004614 |
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