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Linear systems analysis of the fMRI signal

In 1995 when we began our investigations of the human visual system using fMRI, little was known about the temporal properties of the fMRI signal. Before we felt comfortable making quantitative estimates of neuronal responses with this new technique, we decided to first conduct a basic study of how... Full description

Journal Title: NeuroImage 15 August 2012, Vol.62(2), pp.975-84
Main Author: Boynton, Geoffrey M
Other Authors: Engel, Stephen A , Heeger, David J
Format: Electronic Article Electronic Article
Language: English
Subjects:
ID: E-ISSN: 1095-9572 ; PMID: 22289807 Version:1 ; DOI: 10.1016/j.neuroimage.2012.01.082
Link: http://pubmed.gov/22289807
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recordid: medline22289807
title: Linear systems analysis of the fMRI signal
format: Article
creator:
  • Boynton, Geoffrey M
  • Engel, Stephen A
  • Heeger, David J
subjects:
  • Linear Models
  • Brain Mapping -- History
  • Image Processing, Computer-Assisted -- History
  • Magnetic Resonance Imaging -- History
  • Visual Cortex -- Physiology
ispartof: NeuroImage, 15 August 2012, Vol.62(2), pp.975-84
description: In 1995 when we began our investigations of the human visual system using fMRI, little was known about the temporal properties of the fMRI signal. Before we felt comfortable making quantitative estimates of neuronal responses with this new technique, we decided to first conduct a basic study of how the time-course of the fMRI response varied with stimulus timing and strength. The results ended up showing strong evidence that to a first approximation the hemodynamic transformation was linear in time. This was both important and remarkable: important because nearly all fMRI data analysis techniques assume or require linearity, and remarkable because the physiological basis of the hemodynamic transformation is so complex that we still have a far from complete understanding of it. In this paper, we provide highlights of the results of our original paper supporting the linear transform hypothesis. A reanalysis of the original data provides some interesting new insights into the published results. We also provide a detailed appendix describing of the properties and predictions of a linear system in time in the context of the transformation between neuronal responses and the BOLD signal.
language: eng
source:
identifier: E-ISSN: 1095-9572 ; PMID: 22289807 Version:1 ; DOI: 10.1016/j.neuroimage.2012.01.082
fulltext: fulltext
issn:
  • 10959572
  • 1095-9572
url: Link


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descriptionIn 1995 when we began our investigations of the human visual system using fMRI, little was known about the temporal properties of the fMRI signal. Before we felt comfortable making quantitative estimates of neuronal responses with this new technique, we decided to first conduct a basic study of how the time-course of the fMRI response varied with stimulus timing and strength. The results ended up showing strong evidence that to a first approximation the hemodynamic transformation was linear in time. This was both important and remarkable: important because nearly all fMRI data analysis techniques assume or require linearity, and remarkable because the physiological basis of the hemodynamic transformation is so complex that we still have a far from complete understanding of it. In this paper, we provide highlights of the results of our original paper supporting the linear transform hypothesis. A reanalysis of the original data provides some interesting new insights into the published results. We also provide a detailed appendix describing of the properties and predictions of a linear system in time in the context of the transformation between neuronal responses and the BOLD signal.
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abstractIn 1995 when we began our investigations of the human visual system using fMRI, little was known about the temporal properties of the fMRI signal. Before we felt comfortable making quantitative estimates of neuronal responses with this new technique, we decided to first conduct a basic study of how the time-course of the fMRI response varied with stimulus timing and strength. The results ended up showing strong evidence that to a first approximation the hemodynamic transformation was linear in time. This was both important and remarkable: important because nearly all fMRI data analysis techniques assume or require linearity, and remarkable because the physiological basis of the hemodynamic transformation is so complex that we still have a far from complete understanding of it. In this paper, we provide highlights of the results of our original paper supporting the linear transform hypothesis. A reanalysis of the original data provides some interesting new insights into the published results. We also provide a detailed appendix describing of the properties and predictions of a linear system in time in the context of the transformation between neuronal responses and the BOLD signal.
doi10.1016/j.neuroimage.2012.01.082
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date2012-08-15