They show the same correlation, but one has a stronger slope. The
conclusion is that your covariate has a larger effect on your brain
for group A compared to group B.
The response is linear in both cases, correlation is 1 in both cases,
but the gradient is higher in one group.
Correlation -- how well the covariate matched the BOLD signal
Slope -- how steep is the relationship.
In the GLM, you will be comparing the slopes, not the correlations. To
compare the correlations, you need to compare the T-statistics, not
the beta of the models.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Postdoctoral Research Fellow, GRECC, Bedford VA
Website: http://www.martinos.org/~mclaren
Office: (773) 406-2464
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On Mon, Aug 13, 2012 at 4:13 AM, Liam Mason <[log in to unmask]> wrote:
> Dear list,
>
> What can I infer from one group's response to a parametric regressor being larger than the other? My initial interpretation was that their neural activity more closely matches (i.e. is more correlated with) the regressor. However, I wondered what would happen in the following situation:
>
> Regressor parameters = [1 2 3 4 5];
> Group 1 betas = [1 2 3 4 5];
> Group 2 betas = [2 4 6 8 10];
>
> i.e. they show identical linear response (same gradient) to the parametric regressor, but one is of twice the magnitude of the other. Would it show a larger parametric response? With the above interpretation this would lead me to believe that Group 2 more closely encodes my parametric, which would not be correct.
>
> Thanks,
> Liam
>
> ---
> School of Psychological Sciences
> University of Manchester
> 0161 275 2692
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