In SPM, there is also a high-pass filter that is applied to the data. If you look in spm_spm: W will be an identity matrix if you turn off AR(1) xX.K is the high-pass filter. xX.xKXs = spm_sp('Set',spm_filter(xX.K,W*xX.X)); % KWX xX.xKXs.X = full(xX.xKXs.X); xX.pKX = spm_sp('x-',xX.xKXs); KWY = spm_filter(xX.K,W*Y); beta = xX.pKX*KWY; Best Regards, Donald McLaren ================= D.G. McLaren, Ph.D. Postdoctoral Research Fellow, GRECC, Bedford VA Research Fellow, Department of Neurology, Massachusetts General Hospital and Harvard Medical School Office: (773) 406-2464 ===================== This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is intended only for the use of the individual or entity named above. If the reader of the e-mail is not the intended recipient or the employee or agent responsible for delivering it to the intended recipient, you are hereby notified that you are in possession of confidential and privileged information. Any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited and may be unlawful. If you have received this e-mail unintentionally, please immediately notify the sender via telephone at (773) 406-2464 or email. On Sun, Jul 10, 2011 at 2:17 PM, Hongjian He <[log in to unmask]> wrote: > Dear all, > Does anyone have any idea about the beta calculation in SPM? I found > it different with what I got from matlab regression. > I run SPM with a simple first level model with the design matrix > including two task condition, a linear trend term and a dc-term. No > global normalization and AR(1) are specified. After the estimation, I > can find the beta value for a example voxel, such as 0.5288. > > I then take the time series of that voxel (Y), and do the regression > in matlab. The design matrix (or regressors X) has been set to be > exactly the same with SPM.xX.X. To find the beta value, I did the > calculation as (X' * X) \ X' * Y. However, the value I got is > -4.9671. I also considered the percentage unit, and did the > normalization with a factor of 100/dc-term. The result of that is > -0.6954. > > Could anyone help me to understand the procedure I missed to find the > same regression value for the two cases? > > Thanks in advance! > ------------------------------------------------------------------- > Hongjian He > Zhejiang University, Hangzhou, China. > Email: hehongj(AT)gmail.com >