Literature DB >> 22289807

Linear systems analysis of the fMRI signal.

Geoffrey M Boynton1, Stephen A Engel, David J Heeger.   

Abstract

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.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22289807      PMCID: PMC3359416          DOI: 10.1016/j.neuroimage.2012.01.082

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  28 in total

1.  Color signals in human motion-selective cortex.

Authors:  B A Wandell; A B Poirson; W T Newsome; H A Baseler; G M Boynton; A Huk; S Gandhi; L T Sharpe
Journal:  Neuron       Date:  1999-12       Impact factor: 17.173

2.  Spatial heterogeneity of the nonlinear dynamics in the FMRI BOLD response.

Authors:  R M Birn; Z S Saad; P A Bandettini
Journal:  Neuroimage       Date:  2001-10       Impact factor: 6.556

3.  The time course of adaptation to spatial contrast.

Authors:  M W Greenlee; M A Georgeson; S Magnussen; J P Harris
Journal:  Vision Res       Date:  1991       Impact factor: 1.886

4.  Temporal dynamics of contrast gain in single cells of the cat striate cortex.

Authors:  A B Bonds
Journal:  Vis Neurosci       Date:  1991-03       Impact factor: 3.241

5.  Motion selectivity and the contrast-response function of simple cells in the visual cortex.

Authors:  D G Albrecht; W S Geisler
Journal:  Vis Neurosci       Date:  1991-12       Impact factor: 3.241

6.  Factors governing the adaptation of cells in area-17 of the cat visual cortex.

Authors:  T Maddess; M E McCourt; B Blakeslee; R B Cunningham
Journal:  Biol Cybern       Date:  1988       Impact factor: 2.086

7.  Contrast masking in human vision.

Authors:  G E Legge; J M Foley
Journal:  J Opt Soc Am       Date:  1980-12

8.  Striate cortex of monkey and cat: contrast response function.

Authors:  D G Albrecht; D B Hamilton
Journal:  J Neurophysiol       Date:  1982-07       Impact factor: 2.714

9.  Spatial contrast adaptation characteristics of neurones recorded in the cat's visual cortex.

Authors:  D G Albrecht; S B Farrar; D B Hamilton
Journal:  J Physiol       Date:  1984-02       Impact factor: 5.182

10.  Characterization of the functional MRI response temporal linearity via optical control of neocortical pyramidal neurons.

Authors:  Itamar Kahn; Mitul Desai; Ulf Knoblich; Jacob Bernstein; Michael Henninger; Ann M Graybiel; Edward S Boyden; Randy L Buckner; Christopher I Moore
Journal:  J Neurosci       Date:  2011-10-19       Impact factor: 6.167

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  25 in total

1.  Optimizing the general linear model for functional near-infrared spectroscopy: an adaptive hemodynamic response function approach.

Authors:  Minako Uga; Ippeita Dan; Toshifumi Sano; Haruka Dan; Eiju Watanabe
Journal:  Neurophotonics       Date:  2014-08-05       Impact factor: 3.593

2.  Inverted Encoding Models of Human Population Response Conflate Noise and Neural Tuning Width.

Authors:  Taosheng Liu; Dylan Cable; Justin L Gardner
Journal:  J Neurosci       Date:  2017-11-22       Impact factor: 6.167

3.  Unraveling the spatiotemporal brain dynamics during a simulated reach-to-eat task.

Authors:  Ching-Fu Chen; Kenneth Kreutz-Delgado; Martin I Sereno; Ruey-Song Huang
Journal:  Neuroimage       Date:  2018-10-10       Impact factor: 6.556

4.  An investigation of positive and inverted hemodynamic response functions across multiple visual areas.

Authors:  Alexander M Puckett; Jedidiah R Mathis; Edgar A DeYoe
Journal:  Hum Brain Mapp       Date:  2014-07-04       Impact factor: 5.038

Review 5.  Vascular and neural basis of the BOLD signal.

Authors:  Patrick J Drew
Journal:  Curr Opin Neurobiol       Date:  2019-07-21       Impact factor: 6.627

6.  BOLD neurovascular coupling does not change significantly with normal aging.

Authors:  Jack Grinband; Jason Steffener; Qolamreza R Razlighi; Yaakov Stern
Journal:  Hum Brain Mapp       Date:  2017-04-17       Impact factor: 5.038

Review 7.  Statistical power or more precise insights into neuro-temporal dynamics? Assessing the benefits of rapid temporal sampling in fMRI.

Authors:  Logan T Dowdle; Geoffrey Ghose; Clark C C Chen; Kamil Ugurbil; Essa Yacoub; Luca Vizioli
Journal:  Prog Neurobiol       Date:  2021-09-04       Impact factor: 11.685

8.  Compressive Temporal Summation in Human Visual Cortex.

Authors:  Jingyang Zhou; Noah C Benson; Kendrick N Kay; Jonathan Winawer
Journal:  J Neurosci       Date:  2017-11-30       Impact factor: 6.167

9.  Origins of 1/f-like tissue oxygenation fluctuations in the murine cortex.

Authors:  Qingguang Zhang; Kyle W Gheres; Patrick J Drew
Journal:  PLoS Biol       Date:  2021-07-15       Impact factor: 8.029

10.  A mixed L2 norm regularized HRF estimation method for rapid event-related fMRI experiments.

Authors:  Yu Lei; Li Tong; Bin Yan
Journal:  Comput Math Methods Med       Date:  2013-05-12       Impact factor: 2.238

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