Forward models demonstrate that repetition suppression is best modelled by local neural scaling
The neural mechanisms underlying the suppression of fMRI responses to repeated stimuli are under debate. Here, the authors compare computational models to show that only a local scaling model can fit univariate and multivariate fMRI repetition effects across two paradigms and multiple brain regions.
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2018
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/9ce89a73cb404da380a5a1660990deec |
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| Sumario: | The neural mechanisms underlying the suppression of fMRI responses to repeated stimuli are under debate. Here, the authors compare computational models to show that only a local scaling model can fit univariate and multivariate fMRI repetition effects across two paradigms and multiple brain regions. |
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