Dear Bruce,
Thank again for your kind help. I知 running version 5.1.0. 
Below is the output of the command.
I also ran it with parea=0 but almost no change in the result (see the attachment-1)
I also plot the sluci map for comparison (see the attachment-2) but still not satisfactory. 

Best

~/Data/P00001613/FreeSurferClean/surf\> mris_register -1 -curv -dist .25 lh.sphere ../../../P00001639/FreeSurferClean/surf/lh.sphere lh.sphere_dis25.reg
treating target as a single subject's surface...
using smoothwm curvature for final alignment
l_dist = 0.250
$Id: mris_register.c,v 1.59 2011/03/02 00:04:33 nicks Exp $
  $Id: mrisurf.c,v 1.693.2.7 2013/05/12 22:28:01 nicks Exp $
reading surface from lh.sphere...
reading spherical surface ../../../P00001639/FreeSurferClean/surf/lh.sphere...
curvature mean = -0.000, std = 1.000
computing parameterization for surface ../../../P00001639/FreeSurferClean/surf/lh.inflated.H...
curvature mean = 0.000, std = 0.566
computing parameterization for surface ../../../P00001639/FreeSurferClean/surf/lh.sulc...
curvature mean = -0.030, std = 0.282
computing parameterization for surface ../../../P00001639/FreeSurferClean/surf/lh.smoothwm...
MRISregister() -------
max_passes = 4 
min_degrees = 0.500000 
max_degrees = 64.000000 
nangles = 8 
tol=5.0e-01, sigma=0.0, host=unkno, nav=1024, nbrs=1, l_extern=10000.000, l_parea=0.100, l_nlarea=1.000, l_corr=1.000, l_dist=0.250
using quadratic fit line minimization
complete_dist_mat 0
rms 0
smooth_averages 0
remove_neg 0
ico_order 0
which_surface 0
target_radius 0.000000
nfields 0
scale 0.000000
desired_rms_height -1.000000
momentum 0.950000
nbhd_size -10
max_nbrs 10
niterations 25
nsurfaces 0
SURFACES 3
flags 16 (10)
use curv 16
no sulc 0
no rigid align 0
mris->nsize 1
mris->hemisphere 0
randomSeed 0

--------------------
tol=5.0e-01, sigma=0.0, host=unkno, nav=1024, nbrs=1, l_extern=10000.000, l_parea=0.100, l_nlarea=1.000, l_corr=1.000, l_dist=0.250
using quadratic fit line minimization
1 Reading lh.sulc
curvature mean = 0.000, std = 0.583
curvature mean = 0.044, std = 0.847
curvature mean = 0.022, std = 0.852
Starting MRISrigidBodyAlignGlobal()
  d=32.00 min @ (8.00, 0.00, 0.00) sse = 90765.7, tmin=0.9987
  d=16.00 min @ (-4.00, -4.00, 0.00) sse = 87371.6, tmin=1.5086
  d=8.00 min @ (-2.00, 0.00, 0.00) sse = 86754.0, tmin=2.0493
  d=4.00 min @ (1.00, 1.00, 0.00) sse = 86449.9, tmin=2.5976
  d=2.00 min @ (0.00, -0.50, 0.50) sse = 86436.5, tmin=3.1563
  d=1.00 min @ (0.00, 0.25, -0.25) sse = 86423.4, tmin=3.6949
MRISrigidBodyAlignGlobal() done   4.24 min

curvature mean = 0.036, std = 0.923
curvature mean = 0.010, std = 0.931
curvature mean = 0.036, std = 0.951
curvature mean = 0.004, std = 0.967
curvature mean = 0.036, std = 0.962
curvature mean = 0.001, std = 0.984
2 Reading smoothwm
curvature mean = -0.027, std = 0.269
tol=1.0e+00, sigma=0.5, host=unkno, nav=1024, nbrs=1, l_extern=10000.000, l_parea=0.100, l_nlarea=1.000, l_corr=0.050, l_spring=0.500, l_dist=0.250
using quadratic fit line minimization
curvature mean = 0.090, std = 0.337
curvature mean = 0.059, std = 0.386
curvature mean = 0.091, std = 0.507
curvature mean = 0.020, std = 0.580
curvature mean = 0.091, std = 0.618
curvature mean = 0.011, std = 0.723
curvature mean = 0.093, std = 0.681
curvature mean = 0.004, std = 0.828
MRISregister() return, current seed 0
expanding nbhd size to 1
writing registered surface to lh.sphere_dis25.reg...

-- 
Ray Razlighi, Ph.D.
Assistant Professor
Quantitative Neuroimaging Laboratory
Division of Cognitive Neuroscience
Department of Neurology
Columbia University

Alt: razlighi@gmail.com
Office Phone: 212-342-1352
Office Fax: 212-342-1838
Website: http://www.columbia.edu/cu/qnl/

On Nov 4, 2015, at 7:30 PM, Bruce Fischl <fischl@nmr.mgh.harvard.edu> wrote:

Hi Ray

what version of FS are you using? Can you send me the output of the command? The distance term will prevent the curvatures from deforming too much. You can set it much smaller and see what happens if you want. There may also be an area constraint. Trying using -parea 0 also (or something small)

cheers
Bruce

On Wed, 4 Nov 2015, Razlighi, Qolamreza R. wrote:

Hi Bruce,
Thanks for reply. I thought after registering, the source surface's curvature map should be very similar to the target one. I don't see that here. The registered surface has pretty much the same curvature map only slightly shifted.
Am I missing something here?

Best

On Nov 4, 2015, at 5:56 PM, Bruce Fischl <fischl@nmr.mgh.harvard.edu>
wrote:

Hi Ray

that sounds right. The way I visualize these is using nmovie (which I think we include in our distribution) and flipping back and forth between the different images showing the different surfaces/curv maps.

Which inaccuracy are you referring to?

cheers
Bruce

On Wed, 4 Nov 2015, Razlighi, Qolamreza R. wrote:

Dear Bruce,
I did run it again with option (-dist 0.25); however the result did not
change much (See the attachment). These results do not seem right to me and
I think I知 running the command correctly (see the first email). However,
I知 not sure I知 visualizing the curvature maps correctly. I assume the
lh.sphere.reg has the same vertices and facets as lh.sphere but slightly
displaced in space to match the curvature and sulci map of the source
surface to target surface. Therefore, I visualize the lh.sphere.reg by
pulling the same lh.curv file from the source image. If this is wrong,
please let me know how can I correctly visualize the lh.sphere.reg,
otherwise I have no idea why this surface based registration produce such
inaccurate results. Any comments or suggestion is greatly appreciated.
Best
[IMAGE]
--
Ray Razlighi, Ph.D.
Assistant Professor
Quantitative Neuroimaging Laboratory
Division of Cognitive Neuroscience
Department of Neurology
Columbia University
Alt: razlighi@gmail.com
Office Phone: 212-342-1352
Office Fax: 212-342-1838
Website: http://www.columbia.edu/cu/qnl/
On Nov 3, 2015, at 3:47 PM, Bruce Fischl <fischl@nmr.mgh.harvard.edu> wrote:

    Hi Ray

    the -1 means that the target is a single surface and not an
    atlas, but the registration is still nonlinear. The variances
    will all be 1 so you may have to play with the weights in the
    energy functional. We don't do this very much and it probably
    defaults to quite rigid. Try reducing the weight on the metric
    preservation term (e.g. -dist .25) if you want it to be more
    nonlinear

    cheers
    Bruce

    On Tue, 3 Nov 2015, Razlighi, Qolamreza R. wrote:

          Hi Guys,
          I read in the sidenote here
          (https://surfer.nmr.mgh.harvard.edu/fswiki/SurfaceRegAndTemplates)
          that
          inter-subject surface base registration using
          mris_register and -1 flag
          performs a sort of rigid registration. So I tried it
          between two of my
          subjects with the command below
          mris_register -1 -curv
          P00001639/FreeSurferClean/surf/lh.sphere
          P00001639/FreeSurferClean/surf/lh.sphere
          lh.sphere3.reg
          and got the results (see the attachment). It is
          clear that the registration
          output is just a shifted version of the source.
          Having this confirmed I want
          to know if there is any way to force the
          mris_register to perform a complete
          non-linear surface based registration for
          inter-subjects registration the
          same way it does for template.
          I have to mention that I visualize the
          lh.sphere3.reg using freeview and
          loaded the sane lh.curv on that surface. I hope I知
          not doing anything
          stupid.

          [IMAGE]
          Best
          --
          Ray Razlighi, Ph.D.
          Assistant Professor
          Quantitative Neuroimaging Laboratory
          Division of Cognitive Neuroscience
          Department of Neurology
          Columbia University
          Alt: razlighi@gmail.com
          Office Phone: 212-342-1352
          Office Fax: 212-342-1838
          Website: http://www.columbia.edu/cu/qnl/

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