JiscMail Logo
Email discussion lists for the UK Education and Research communities

Help for SPM Archives


SPM Archives

SPM Archives


SPM@JISCMAIL.AC.UK


View:

Message:

[

First

|

Previous

|

Next

|

Last

]

By Topic:

[

First

|

Previous

|

Next

|

Last

]

By Author:

[

First

|

Previous

|

Next

|

Last

]

Font:

Monospaced Font

LISTSERV Archives

LISTSERV Archives

SPM Home

SPM Home

SPM  November 2009

SPM November 2009

Options

Subscribe or Unsubscribe

Subscribe or Unsubscribe

Log In

Log In

Get Password

Get Password

Subject:

Re: Latency (temp deriv) in 2nd level (Henson)

From:

Rik Henson <[log in to unmask]>

Reply-To:

Rik Henson <[log in to unmask]>

Date:

Fri, 27 Nov 2009 12:17:07 +0000

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (107 lines)

Markus -

First, you might want to check this archived message:

    
https://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=ind0904&L=SPM&D=0&X=1B29E63F8DCB1C3993&Y=rik.henson%40mrc-cbu.cam.ac.uk&P=196039

where Donald McLaren identified a problem with using the precise
sigmoidal equation in Henson et al (2002) for data analysed in SPM5+,
because the scaling in spm_get_bf.m changed (that paper was based on SPM2).

To answer your specific questions:

> I am refering to the paper of Henson et al 2002 NeuroImage 15, 83-95,
> about the Latency differences.
>
> I would like to use this technique.
>
> I am right when I proceed as follows?
>
> a) integrate temporal derivatives into my first level model
Yes. Note however that you can only separate estimation of latency from
estimation of height of an HRF if you have long or jittered SOAs (eg
null events); with rapid, fixed-SOA event-related designs (eg SOA<~2s,
randomised event-types), the temporal derivative for one event-type will
be correlated with the difference in (ie contrast of) canonical HRFs
across event-types. This is just an example of the more general point
that you need to estimate each regressor (temporal basis function) with
high statistical efficiency - ie the distinction between estimating an
HRF *shape* and simply detecting the *amplitude* of an assumed shape
(e.g, relative efficiencies of a canonical HRF vs an FIR basis set; see
Henson, 2004, HBF book chapter).


> b) calculate the beta for the hrf_<each condition> as a [1 0]
>
> c) calculate the beta for the td_<each condition> as a [0 1]
>
> d) use the image calculator to create the latency_image_<each condition>
> using the formula
>
> 2C/(1+exp(D beta2/beta1)) - C;
>
> where C=1.78, D=3.1 (Henson et al 2002, Neuroimage 15, p86).
Yes to points b-d, except that you might need to restimate the
parameters C and D in you are using SPM5+, as Donald found.

Note that these parameters only matter if you want to estimate the
precise latency (eg in seconds), which is only really valid in the
linear regime where the Taylor approximation holds (ie +/-1s of the
canonical latency). Furthermore, precise latency differences in the BOLD
impulse response may not be easily interpretable, because they do not
necessarily reflect latency differences in the underlying neural
activity (which is what I assume you are really interested in) - given
the time integration (see Discussion in Henson et al, 2002) and that the
neural-BOLD coupling is likely to have appreciable nonlinearities. (This
is perhaps one reason that the various published methods for estimating
BOLD latencies have not been used extensively for neuroscientific
conclusions.)

If you don't care about precise latency, then you can view the sigmoidal
function just as a statistical transform that prevents the
derivative:canonical ratio from exploding beyond the linear regime (or
when the canonical estimate is close to zero - ie for voxels where there
is no basic impulse response in the first place). Then the precise
parameters don't matter: you are just conditioning the data so that it
becomes more Gaussian (the ratio won't be precisely Gaussian, even after
transformation (you could use a log transform for that), though with
enough Gaussian smoothing, the parametric stats should be reasonably
robust). It also helps to only analyse voxels where there is a
significant loading on the canonical HRF as well (ie use an inclusive
mask, as in Henson et al, 2002), where the ratio only really makes sense
(as mentioned above).


> e) enter these latency_images into the second level stats (ANOVA).
Yes


> f) And the last question: Is the above formula correctly entered into
> the ImageCalculator when doing:
>
> f = '(2*1.78./(1+exp(3.1*i2./i1))) - 1.78' ( I mean, I do get some
> imges, but are they correct??)
Should be. I can send you a function that writes latency images offline
if you want. But only if you are sure you want to proceed with latency
analyses.... ;-)

Rik


--

-------------------------------------------------------
                 Dr Richard Henson
         MRC Cognition & Brain Sciences Unit
                 15 Chaucer Road
                   Cambridge
                  CB2 7EF, UK

           Office: +44 (0)1223 355 294 x522
              Mob: +44 (0)794 1377 345
              Fax: +44 (0)1223 359 062

http://www.mrc-cbu.cam.ac.uk/people/rik.henson/personal
-------------------------------------------------------

Top of Message | Previous Page | Permalink

JiscMail Tools


RSS Feeds and Sharing


Advanced Options


Archives

October 2019
September 2019
August 2019
July 2019
June 2019
May 2019
April 2019
March 2019
February 2019
January 2019
December 2018
November 2018
October 2018
September 2018
August 2018
July 2018
June 2018
May 2018
April 2018
March 2018
February 2018
January 2018
December 2017
November 2017
October 2017
September 2017
August 2017
July 2017
June 2017
May 2017
April 2017
March 2017
February 2017
January 2017
December 2016
November 2016
October 2016
September 2016
August 2016
July 2016
June 2016
May 2016
April 2016
March 2016
February 2016
January 2016
December 2015
November 2015
October 2015
September 2015
August 2015
July 2015
June 2015
May 2015
April 2015
March 2015
February 2015
January 2015
December 2014
November 2014
October 2014
September 2014
August 2014
July 2014
June 2014
May 2014
April 2014
March 2014
February 2014
January 2014
December 2013
November 2013
October 2013
September 2013
August 2013
July 2013
June 2013
May 2013
April 2013
March 2013
February 2013
January 2013
December 2012
November 2012
October 2012
September 2012
August 2012
July 2012
June 2012
May 2012
April 2012
March 2012
February 2012
January 2012
December 2011
November 2011
October 2011
September 2011
August 2011
July 2011
June 2011
May 2011
April 2011
March 2011
February 2011
January 2011
December 2010
November 2010
October 2010
September 2010
August 2010
July 2010
June 2010
May 2010
April 2010
March 2010
February 2010
January 2010
December 2009
November 2009
October 2009
September 2009
August 2009
July 2009
June 2009
May 2009
April 2009
March 2009
February 2009
January 2009
December 2008
November 2008
October 2008
September 2008
August 2008
July 2008
June 2008
May 2008
April 2008
March 2008
February 2008
January 2008
December 2007
November 2007
October 2007
September 2007
August 2007
July 2007
June 2007
May 2007
April 2007
March 2007
February 2007
January 2007
2006
2005
2004
2003
2002
2001
2000
1999
1998


JiscMail is a Jisc service.

View our service policies at https://www.jiscmail.ac.uk/policyandsecurity/ and Jisc's privacy policy at https://www.jisc.ac.uk/website/privacy-notice

Secured by F-Secure Anti-Virus CataList Email List Search Powered by the LISTSERV Email List Manager