Thanks. I will try and let you know the result.


> From: Daniel Simmonds <[log in to unmask]>
> Date: Mon, 23 Jul 2007 13:03:09 -0400
> To: <[log in to unmask]>, Jiansong Xu <[log in to unmask]>
> Subject: Re: [SPM] simple regression
> 
> somebody can correct me if i'm wrong, but here's what i would do.
> first, i would just run 2 simple regression models, one for each group.
> then, i'd create a multiple regression model with 4 factors - 2 factors
> identifying the groups (ie for one regressor, you put 1's for patients
> and 0's for controls, and for the other, the opposite) and 2 containing
> the RTs for each group (ie one regressor has the RT values for the
> patients and 0's for the controls, and the other has the opposite).  you
> can then show areas in which one group shows a "more positive"
> correlation or a "more negative" correlation with RT than the other
> group.  for instance, if your design matrix was [patients   controls
> patients_RT   controls_RT], then [0 0 1 -1] shows regions in which
> patients have a greater positive correlation with RT than do controls.
> you can then pull out each subject's betas for any significant ROIs and
> run post-hoc tests to determine the actual nature of the correlation
> differences (ie positive in one group, negative in the other, or maybe
> positive in one group, no correlation in the other).
> dani
> 
> Daniel Simmonds
> Developmental Cognitive Neurology
> Kennedy Krieger Institute
> [log in to unmask]
> 
>>>> Jiansong Xu <[log in to unmask]> 7/23/2007 12:49 PM >>>
> Across both groups. How to use multiple regression?
> 
> Also, you mentioned "it is consistent with lots of models". Could you
> give
> me one or two examples?
> 
> Thanks
> 
> Jiansong
> 
> 
>> From: Daniel Simmonds <[log in to unmask]>
>> Reply-To: Daniel Simmonds <[log in to unmask]>
>> Date: Mon, 23 Jul 2007 12:20:15 -0400
>> To: <[log in to unmask]>
>> Subject: Re: [SPM] simple regression
>> 
>> hi jiansong,
>> 
>>    is the simple regression you are discussing in the patients, in
> the
>> controls, or across both groups?  it may be that there are different
>> correlations with RT for each group (ie positive correlation in
>> controls/negative correlation in patients and vice versa) and this
> could
>> potentially indicate that the two groups are using this region
>> differently (ie in one group, greater activation in this region leads
> to
>> faster RT's, while in the other, it leads to slower RT's).  this type
> of
>> question could be answered using a multiple regression as opposed to
> a
>> simple regression.
>> 
>> dani
>> 
>> Daniel Simmonds
>> Developmental Cognitive Neurology
>> Kennedy Krieger Institute
>> [log in to unmask]
>> 
>>>>> Jiansong Xu <[log in to unmask]> 7/23/2007 12:11 PM >>>
>> Thanks. But, the problem is:
>> 
>> Relative to control subjects, patients showed longer RT and less
>> activation
>> in the lateral prefrontal cortex and less deactivation in the medial
>> prefrontal cortex.  I¹m glad about this finding and I can claim that
>> the
>> less activation and deactivation exhibited by patients correlated
> with
>> their
>> longer RT than controls.  Now, the RT positively correlated with the
>> BOLD in
>> the lateral prefrontal cortex and negatively correlated with signal
> in
>> the
>> medial cortex.  Such correlation is opposite to my above
> interpretation
>> of
>> ³less activation and deactivation contribute to the longer RT².
>> 
>> One possible interpretation for these ³conflicting² finding is that
>> because
>> of the ³less activation and deactivation² in some brain areas of
>> patients or
>> ³slower² performers, the remaining intact brain areas in patients
> need
>> to
>> work longer to compensate for the impaired brain function.
>> 
>> 
>> I have another study of healthy subjects (different population from
>> above
>> study) with different task.  It also showed greater RT positively
>> correlated
>> with greater signal changes in the prefrontal and parietal cortex,
> and
>> subcortical area (thalamus and striatum) and negatively correlated
>> with
>> signal changes in the ³default brain area² (e.g., medial part of the
>> brain).
>> Follow your comments, these data suggest that the worse performers
>> (i.e.,
>> longer RT) showed greater BOLD signal increase in the positive
> network
>> and
>> greater BOLD signal decrease in the negative network, thus showed
> less
>> functional efficiency in their brain.  Is it reasonable?
>> 
>> Best
>> 
>> Jiansong
>> 
>> 
>> 
>> From: "Weissman, Daniel" <[log in to unmask]>
>> Reply-To: "Weissman, Daniel" <[log in to unmask]>
>> Date: Mon, 23 Jul 2007 11:31:14 -0400
>> To: <[log in to unmask]>
>> Subject: Re: [SPM] simple regression
>> 
>> Dear Jiansong,
>>  
>> If I understand correctly, you've found a positive beta coefficient
> in
>> a
>> simple (across-subjects) regression in which BOLD signal is
> regressed
>> against RT.  In that case, the positive beta coefficient would
> indeed
>> mean
>> that subjects who show larger changes in BOLD signal tend to exhibit
>> longer
>> RT.  Although this finding goes against your prediction, it is
>> consistent
>> with lots of models.  For example, longer RT may indicate greater
> time
>> on
>> task, which results in more activity.
>>  
>> Hope this helps,
>> Daniel
>> 
>>  
>> Dear Friend:
>> 
>> I'm using simple regression to assess the correlation between BOLD
>> signal
>> changes and reaction time.  Several clusters in the prefrontal and
>> parietal
>> cortex showed significant positive correlation between signal
> changes
>> and
>> RT. Does this positive correlation indicate greater signal changes
>> correlated with greater RT? If so, it is opposite to my expectation
> of
>> greater activity correlated with shorter RT.  Any comments are
>> appreciated.
>> 
>> Best
>> 
>> Jiansong
>> 
>> 
> 
> 
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