Journal article
Estimating neural response functions from fMRI
Frontiers in neuroinformatics, Vol.8(MAY), pp.48-48
05/08/2014
DOI: 10.3389/fninf.2014.00048
PMCID: PMC4021120
PMID: 24847246
Abstract
This paper proposes a methodology for estimating Neural Response Functions (NRFs) from fMRI data. These NRFs describe non-linear relationships between experimental stimuli and neuronal population responses. The method is based on a two-stage model comprising an NRF and a Hemodynamic Response Function (HRF) that are simultaneously fitted to fMRI data using a Bayesian optimization algorithm. This algorithm also produces a model evidence score, providing a formal model comparison method for evaluating alternative NRFs. The HRF is characterized using previously established "Balloon" and BOLD signal models. We illustrate the method with two example applications based on fMRI studies of the auditory system. In the first, we estimate the time constants of repetition suppression and facilitation, and in the second we estimate the parameters of population receptive fields in a tonotopic mapping study.
Details
- Title: Subtitle
- Estimating neural response functions from fMRI
- Creators
- Sukhbinder Kumar - Newcastle UniversityWilliam Penny - University College London
- Resource Type
- Journal article
- Publication Details
- Frontiers in neuroinformatics, Vol.8(MAY), pp.48-48
- DOI
- 10.3389/fninf.2014.00048
- PMID
- 24847246
- PMCID
- PMC4021120
- NLM abbreviation
- Front Neuroinform
- ISSN
- 1662-5196
- eISSN
- 1662-5196
- Publisher
- Frontiers Media Sa
- Number of pages
- 13
- Grant note
- 091593/Z/10/Z / Wellcome Trust; European Commission
- Language
- English
- Date published
- 05/08/2014
- Academic Unit
- Neurosurgery
- Record Identifier
- 9984303902902771
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