Hi,
In addition to the other extremely helpful replies, I would add the following:
Our preferred strategy in FMRIB is not to do seed-based analysis, but use ICA and dual regression instead as that solves a lot of problems.
All the best,
Mark
On 24 Jan 2014, at 18:43, "Harms, Michael" <[log in to unmask]> wrote:
> Hi,
> Other recent articles include:
> Yan (2013) http://www.ncbi.nlm.nih.gov/pubmed/23499792
> Power (2014) http://www.ncbi.nlm.nih.gov/pubmed/23994314
> Satterthwaite (2013): http://www.ncbi.nlm.nih.gov/pubmed/22926292
>
> cheers,
> -MH
>
> --
> Michael Harms, Ph.D.
>
> -----------------------------------------------------------
> Conte Center for the Neuroscience of Mental Disorders
> Washington University School of Medicine
> Department of Psychiatry, Box 8134
> 660 South Euclid Ave. Tel: 314-747-6173
> St. Louis, MO 63110 Email: [log in to unmask]
>
>
>
>
> On 1/24/14 12:10 PM, "Connolly, Colm" <[log in to unmask]> wrote:
>
>> Hi Mauricio,
>>
>> If you've not already found them, these articles may be helpful to you in
>> understanding the issues around global signal regression:
>>
>> Fox MD, Zhang D, Snyder AZ, & Raichle ME (2009). The global signal and
>> observed anticorrelated resting state brain networks., Journal of
>> neurophysiology 101, 32703283.
>>
>> Murphy K, Birn RM, Handwerker DA, Jones TB, & Bandettini PA (2009). The
>> impact of global signal regression on resting state correlations: are
>> anti-correlated networks introduced?, NeuroImage 44, 893905.
>>
>> Weissenbacher A, Kasess C, Gerstl F, Lanzenberger R, Moser E, &
>> Windischberger C (2009). Correlations and anticorrelations in
>> resting-state functional connectivity MRI: a quantitative comparison of
>> preprocessing strategies., NeuroImage 47, 14081416.
>>
>> Anderson JS, Druzgal TJ, Lopez-Larson M, Jeong E-K, Desai K, &
>> Yurgelun-Todd D (2010). Network anticorrelations, global regression, and
>> phase-shifted soft tissue correction, Human brain mapping 32, 919934.
>>
>> Saad ZS, Gotts SJ, Murphy K, Chen G, Jo HJ, Martin A, & Cox RW (2012).
>> Trouble at rest: how correlation patterns and group differences become
>> distorted after global signal regression., Brain Connectivity 2, 2532.
>>
>> The following recent article may be of interest if you are finalizing a
>> RSFC pipeline:
>>
>> Hallquist MN, Hwang K, Luna B. (2013). The nuisance of nuisance
>> regression: spectral misspecification in a common approach to
>> resting-state fMRI preprocessing reintroduces noise and obscures
>> functional connectivity. NeuroImage, 82, 20825. PMCID: PMC3759585
>>
>>
>> On Jan 24, 2014, at 2:40 AM, Mauricio Delgado
>> <[log in to unmask]> wrote:
>>
>>> Dear FSL group,
>>>
>>> As you may know there is considerable debate regarding global signal
>>> regression in resting-state fMRI analysis. Though several methods have
>>> been proposed for removing physiological noise out of the data instead
>>> of global signal regression, there is no standard method for doing so.
>>> Hence, I am wondering what the preferred strategy of the FSL group would
>>> be when conducting a seed-based resting-state fMRI analysis?
>>>
>>> Additionally, is it correct that global signal regression would only
>>> increase the probability of artifactual anticorrelations (negative
>>> functional connectivity), while having no adverse effects on, or even
>>> improve, positive correlations?
>>>
>>> Thanks for your time and effort!
>>>
>>> Best,
>>> Mauricio Delgado
>>
>> Regards,
>> --
>> Colm G. Connolly, Ph. D.
>> Dept of Psychiatry
>> University of California, San Francisco
>> 401 Parnassus Avenue,
>> San Francisco, CA 94143
>
>
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