Dear Bruce,
I did set the DIAG and ran it again with no luck. Below is the output and attached please find the result.

Best

ray@athens-b8-e8-56-47-e6-54:~\> tcsh
[athens-b8-e8-56-47-e6-54:~] ray% 
[athens-b8-e8-56-47-e6-54:~] ray% setenv DIAG 0x04040
[athens-b8-e8-56-47-e6-54:~] ray% 
[athens-b8-e8-56-47-e6-54:~/Data/P00001613/FreeSurferClean] ray% cd surf/
[athens-b8-e8-56-47-e6-54:P00001613/FreeSurferClean/surf] ray% 
[athens-b8-e8-56-47-e6-54:P00001613/FreeSurferClean/surf] ray% mris_register -1 -parea 0 -curv -dist .25 lh.sphere ../../../P00001639/FreeSurferClean/surf/lh.sphere lh.sphere_dis25_parea0.reg
treating target as a single subject's surface...
using l_parea = 0.000
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=athen, nav=1024, nbrs=1, l_extern=10000.000, 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=athen, nav=1024, nbrs=1, l_extern=10000.000, 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
reading precomputed curvature from lh.sulc

blurring surfaces with sigma=4.00...
done.
curvature mean = 0.044, std = 0.847
curvature mean = 0.022, std = 0.852
finding optimal rigid alignment
Starting MRISrigidBodyAlignGlobal()
000: dt: 0.000, sse: 135379.3 (0.279, 21.6, 0.412, 0.853), neg: 0 (%0.00:%0.00), avgs: 1024
scanning 64.00 degree nbhd, min sse = 95165.92
(+64.00, +64.00, -64.00), min @ (0.00, 0.00, 0.00) = 95165.9   
scanning 32.00 degree nbhd, min sse = 95165.92
(+32.00, +32.00, -32.00), min @ (8.00, 0.00, 0.00) = 90765.7   
  d=32.00 min @ (8.00, 0.00, 0.00) sse = 90765.7, tmin=1.1635
min sse = 90765.70 at (8.00, 0.00, 0.00)
001: dt: 0.000, sse: 130979.1 (0.279, 21.6, 0.412, 0.833), neg: 0 (%0.00:%0.00), avgs: 1024
scanning 16.00 degree nbhd, min sse = 90765.70
(+16.00, +16.00, -16.00), min @ (-4.00, -4.00, 0.00) = 87371.6   
  d=16.00 min @ (-4.00, -4.00, 0.00) sse = 87371.6, tmin=1.7380
min sse = 87371.58 at (-4.00, -4.00, 0.00)
002: dt: 0.000, sse: 127584.9 (0.279, 21.6, 0.412, 0.817), neg: 0 (%0.00:%0.00), avgs: 1024
scanning 8.00 degree nbhd, min sse = 87371.58
(+8.00, +8.00, -8.00), min @ (-2.00, 0.00, 0.00) = 86754.0   
  d=8.00 min @ (-2.00, 0.00, 0.00) sse = 86754.0, tmin=2.3264
min sse = 86754.03 at (-2.00, 0.00, 0.00)
003: dt: 0.000, sse: 126967.4 (0.279, 21.6, 0.412, 0.814), neg: 0 (%0.00:%0.00), avgs: 1024
scanning 4.00 degree nbhd, min sse = 86754.03
(+4.00, +4.00, -4.00), min @ (1.00, 1.00, 0.00) = 86449.9   
  d=4.00 min @ (1.00, 1.00, 0.00) sse = 86449.9, tmin=2.9298
min sse = 86449.91 at (1.00, 1.00, 0.00)
004: dt: 0.000, sse: 126663.3 (0.279, 21.6, 0.412, 0.813), neg: 0 (%0.00:%0.00), avgs: 1024
scanning 2.00 degree nbhd, min sse = 86449.91
(+2.00, +2.00, -2.00), min @ (0.00, -0.50, 0.50) = 86436.5   
  d=2.00 min @ (0.00, -0.50, 0.50) sse = 86436.5, tmin=3.5333
min sse = 86436.46 at (0.00, -0.50, 0.50)
005: dt: 0.000, sse: 126649.8 (0.279, 21.6, 0.412, 0.813), neg: 0 (%0.00:%0.00), avgs: 1024
scanning 1.00 degree nbhd, min sse = 86436.45
(+1.00, +1.00, -1.00), min @ (0.00, 0.25, -0.25) = 86423.4   
  d=1.00 min @ (0.00, 0.25, -0.25) sse = 86423.4, tmin=4.1242
min sse = 86423.41 at (0.00, 0.25, -0.25)
006: dt: 0.000, sse: 126636.8 (0.279, 21.6, 0.412, 0.813), neg: 0 (%0.00:%0.00), avgs: 1024
scanning 0.50 degree nbhd, min sse = 86423.41
(+0.50, +0.50, -0.50), min @ (0.00, 0.00, 0.00) = 86423.4   
MRISrigidBodyAlignGlobal() done   4.71 min
tol=5.0e-01, sigma=4.0, host=athen, nav=1024, nbrs=1, l_extern=10000.000, l_nlarea=1.000, l_corr=1.000, l_dist=0.250
using quadratic fit line minimization
nlarea/corr = 1.000
integrating with navgs=1024 and tol=5.002e-01
007: dt: 241.975, sse: 109215.9 (0.308, 23.5, 0.429, 0.709), neg: 48 (%0.00:%0.01), avgs: 1024
008: dt: 117.533, sse: 99575.6 (0.298, 23.7, 0.432, 0.651), neg: 50 (%0.00:%0.01), avgs: 1024
009: dt: 136.508, sse: 95352.8 (0.305, 24.1, 0.436, 0.620), neg: 101 (%0.00:%0.02), avgs: 1024
010: dt: 105.985, sse: 92867.4 (0.303, 24.8, 0.442, 0.597), neg: 176 (%0.01:%0.03), avgs: 1024
011: dt: 149.343, sse: 90631.3 (0.311, 25.4, 0.448, 0.573), neg: 334 (%0.01:%0.06), avgs: 1024
012: dt: 85.796, sse: 89225.0 (0.312, 25.9, 0.453, 0.557), neg: 439 (%0.02:%0.08), avgs: 1024
013: dt: 177.745, sse: 87895.2 (0.321, 26.7, 0.460, 0.536), neg: 690 (%0.04:%0.13), avgs: 1024
014: dt: 66.370, sse: 87281.5 (0.322, 27.0, 0.463, 0.527), neg: 782 (%0.05:%0.14), avgs: 1024
015: dt: 236.440, sse: 86602.8 (0.331, 27.8, 0.472, 0.508), neg: 1155 (%0.08:%0.22), avgs: 1024
016: dt: 69.671, sse: 86419.9 (0.332, 28.0, 0.474, 0.502), neg: 1213 (%0.09:%0.23), avgs: 1024
integrating with navgs=256 and tol=2.505e-01
017: dt: 122.246, sse: 82435.7 (0.347, 29.5, 0.492, 0.436), neg: 2026 (%0.16:%0.43), avgs: 256
018: dt: 69.015, sse: 81795.8 (0.350, 29.8, 0.499, 0.417), neg: 1971 (%0.12:%0.42), avgs: 256
019: dt: 36.896, sse: 81619.9 (0.353, 30.1, 0.502, 0.407), neg: 2059 (%0.12:%0.44), avgs: 256
integrating with navgs=64 and tol=1.260e-01
020: dt: 33.532, sse: 80387.5 (0.362, 30.7, 0.513, 0.370), neg: 2300 (%0.10:%0.49), avgs: 64
021: dt: 9.860, sse: 80325.9 (0.364, 30.9, 0.516, 0.362), neg: 2391 (%0.10:%0.51), avgs: 64
integrating with navgs=16 and tol=6.442e-02
022: dt: 6.761, sse: 80080.1 (0.368, 30.9, 0.520, 0.348), neg: 1935 (%0.07:%0.41), avgs: 16
023: dt: 0.929, sse: 80074.6 (0.368, 31.0, 0.521, 0.347), neg: 1928 (%0.06:%0.40), avgs: 16
integrating with navgs=4 and tol=3.494e-02
024: dt: 1.444, sse: 80034.9 (0.370, 31.0, 0.522, 0.343), neg: 1734 (%0.06:%0.35), avgs: 4
025: dt: 0.556, sse: 80028.6 (0.370, 31.0, 0.523, 0.341), neg: 1762 (%0.05:%0.36), avgs: 4
integrating with navgs=1 and tol=2.210e-02
026: dt: 0.066, sse: 80027.9 (0.370, 31.0, 0.523, 0.341), neg: 1753 (%0.05:%0.36), avgs: 1
integrating with navgs=0 and tol=1.562e-02
027: dt: 0.050, sse: 80016.6 (0.370, 31.0, 0.523, 0.341), neg: 1716 (%0.05:%0.33), avgs: 0

blurring surfaces with sigma=2.00...
done.
curvature mean = 0.035, std = 0.927
curvature mean = 0.011, std = 0.928
tol=5.0e-01, sigma=2.0, host=athen, nav=1024, nbrs=1, l_extern=10000.000, l_nlarea=1.000, l_corr=1.000, l_dist=0.250
using quadratic fit line minimization
nlarea/corr = 1.000
integrating with navgs=1024 and tol=5.002e-01
028: dt: 137.600, sse: 83361.7 (0.371, 31.1, 0.524, 0.373), neg: 1570 (%0.04:%0.30), avgs: 1024
integrating with navgs=256 and tol=2.505e-01
029: dt: 16.658, sse: 83344.4 (0.372, 31.1, 0.526, 0.370), neg: 1484 (%0.03:%0.28), avgs: 256
integrating with navgs=64 and tol=1.260e-01
030: dt: 10.485, sse: 83245.6 (0.375, 31.4, 0.530, 0.359), neg: 1316 (%0.03:%0.23), avgs: 64
integrating with navgs=16 and tol=6.442e-02
031: dt: 4.712, sse: 83112.1 (0.379, 31.6, 0.534, 0.346), neg: 1194 (%0.02:%0.19), avgs: 16
032: dt: 0.845, sse: 83109.5 (0.380, 31.6, 0.535, 0.344), neg: 1176 (%0.02:%0.19), avgs: 16
integrating with navgs=4 and tol=3.494e-02
033: dt: 0.700, sse: 83081.6 (0.381, 31.6, 0.536, 0.340), neg: 1147 (%0.02:%0.18), avgs: 4
integrating with navgs=1 and tol=2.210e-02
034: dt: 0.517, sse: 83064.4 (0.382, 31.7, 0.536, 0.338), neg: 1204 (%0.02:%0.19), avgs: 1
integrating with navgs=0 and tol=1.562e-02
035: dt: 0.041, sse: 83050.5 (0.382, 31.7, 0.537, 0.337), neg: 1173 (%0.02:%0.18), avgs: 0
036: dt: 0.042, sse: 83039.7 (0.382, 31.7, 0.537, 0.337), neg: 1171 (%0.02:%0.18), avgs: 0

blurring surfaces with sigma=1.00...
done.
curvature mean = 0.033, std = 0.955
curvature mean = 0.005, std = 0.964
tol=5.0e-01, sigma=1.0, host=athen, nav=1024, nbrs=1, l_extern=10000.000, l_nlarea=1.000, l_corr=1.000, l_dist=0.250
using quadratic fit line minimization
nlarea/corr = 1.000
integrating with navgs=1024 and tol=5.002e-01
037: dt: 115.451, sse: 87076.6 (0.383, 31.7, 0.537, 0.378), neg: 1086 (%0.02:%0.16), avgs: 1024
integrating with navgs=256 and tol=2.505e-01
038: dt: 0.037, sse: 87076.2 (0.383, 31.7, 0.537, 0.378), neg: 1087 (%0.02:%0.16), avgs: 256
integrating with navgs=64 and tol=1.260e-01
039: dt: 6.000, sse: 87067.2 (0.385, 31.9, 0.540, 0.372), neg: 1155 (%0.02:%0.17), avgs: 64
integrating with navgs=16 and tol=6.442e-02
040: dt: 0.771, sse: 87047.6 (0.385, 32.0, 0.540, 0.370), neg: 1166 (%0.02:%0.17), avgs: 16
integrating with navgs=4 and tol=3.494e-02
041: dt: 0.926, sse: 86979.7 (0.387, 32.1, 0.542, 0.365), neg: 1169 (%0.02:%0.17), avgs: 4
042: dt: 0.550, sse: 86964.0 (0.388, 32.2, 0.543, 0.362), neg: 1182 (%0.02:%0.17), avgs: 4
integrating with navgs=1 and tol=2.210e-02
043: dt: 0.255, sse: 86957.1 (0.389, 32.2, 0.544, 0.360), neg: 1203 (%0.02:%0.18), avgs: 1
integrating with navgs=0 and tol=1.562e-02
044: dt: 0.035, sse: 86943.6 (0.389, 32.2, 0.544, 0.359), neg: 1219 (%0.02:%0.17), avgs: 0

blurring surfaces with sigma=0.50...
done.
curvature mean = 0.033, std = 0.965
curvature mean = 0.001, std = 0.983
tol=5.0e-01, sigma=0.5, host=athen, nav=1024, nbrs=1, l_extern=10000.000, l_nlarea=1.000, l_corr=1.000, l_dist=0.250
using quadratic fit line minimization
nlarea/corr = 1.000
integrating with navgs=1024 and tol=5.002e-01
045: dt: 39.869, sse: 89122.8 (0.389, 32.2, 0.544, 0.381), neg: 1239 (%0.02:%0.18), avgs: 1024
integrating with navgs=256 and tol=2.505e-01
046: dt: 0.040, sse: 89122.7 (0.389, 32.2, 0.544, 0.381), neg: 1239 (%0.02:%0.18), avgs: 256
integrating with navgs=64 and tol=1.260e-01
047: dt: 0.015, sse: 89122.7 (0.389, 32.2, 0.544, 0.381), neg: 1239 (%0.02:%0.18), avgs: 64
integrating with navgs=16 and tol=6.442e-02
048: dt: 0.763, sse: 89114.0 (0.390, 32.3, 0.545, 0.379), neg: 1259 (%0.02:%0.18), avgs: 16
integrating with navgs=4 and tol=3.494e-02
049: dt: 0.531, sse: 89093.1 (0.391, 32.4, 0.546, 0.376), neg: 1286 (%0.02:%0.18), avgs: 4
integrating with navgs=1 and tol=2.210e-02
050: dt: 0.280, sse: 89084.5 (0.392, 32.4, 0.547, 0.374), neg: 1315 (%0.02:%0.19), avgs: 1
integrating with navgs=0 and tol=1.562e-02
051: dt: 0.128, sse: 89052.0 (0.393, 32.5, 0.547, 0.372), neg: 1300 (%0.04:%0.18), avgs: 0
052: dt: 0.032, sse: 89024.1 (0.392, 32.5, 0.547, 0.372), neg: 1329 (%0.02:%0.18), avgs: 0
053: dt: 0.033, sse: 89014.9 (0.393, 32.5, 0.547, 0.371), neg: 1377 (%0.02:%0.19), avgs: 0
2 Reading smoothwm
curvature mean = -0.027, std = 0.269
calculating curvature of smoothwm surface
tol=1.0e+00, sigma=0.5, host=athen, nav=1024, nbrs=1, l_extern=10000.000, l_nlarea=1.000, l_corr=0.050, l_spring=0.500, l_dist=0.250
using quadratic fit line minimization

blurring surfaces with sigma=4.00...
done.
curvature mean = 0.089, std = 0.338
curvature mean = 0.065, std = 0.378
tol=1.0e+00, sigma=4.0, host=athen, nav=1024, nbrs=1, l_extern=10000.000, l_nlarea=1.000, l_corr=0.050, l_spring=0.500, l_dist=0.250
using quadratic fit line minimization
nlarea/corr = 20.000
integrating with navgs=1024 and tol=1.000e+00
054: dt: 3.299, sse: 745272.2 (0.384, 31.8, 0.538, 0.745), neg: 1168 (%0.04:%0.21), avgs: 1024
055: dt: 2.605, sse: 738110.4 (0.379, 31.4, 0.532, 0.748), neg: 740 (%0.01:%0.11), avgs: 1024
integrating with navgs=256 and tol=5.010e-01
056: dt: 2.945, sse: 732954.1 (0.377, 31.2, 0.529, 0.751), neg: 774 (%0.02:%0.13), avgs: 256
057: dt: 2.657, sse: 728543.9 (0.374, 30.9, 0.526, 0.753), neg: 511 (%0.01:%0.08), avgs: 256
058: dt: 2.797, sse: 724908.4 (0.373, 30.8, 0.523, 0.756), neg: 551 (%0.01:%0.09), avgs: 256
059: dt: 2.740, sse: 721596.7 (0.371, 30.6, 0.521, 0.758), neg: 404 (%0.00:%0.06), avgs: 256
integrating with navgs=64 and tol=2.519e-01
060: dt: 0.737, sse: 720241.4 (0.370, 30.4, 0.520, 0.758), neg: 307 (%0.00:%0.05), avgs: 64
integrating with navgs=16 and tol=1.288e-01
061: dt: 6.542, sse: 716147.8 (0.370, 30.3, 0.518, 0.758), neg: 559 (%0.01:%0.07), avgs: 16
062: dt: 1.625, sse: 712606.1 (0.367, 29.9, 0.514, 0.757), neg: 151 (%0.00:%0.02), avgs: 16
063: dt: 11.631, sse: 707697.2 (0.368, 29.9, 0.513, 0.757), neg: 580 (%0.02:%0.06), avgs: 16
064: dt: 1.462, sse: 703515.8 (0.365, 29.3, 0.508, 0.756), neg: 88 (%0.00:%0.01), avgs: 16
065: dt: 29.856, sse: 694749.9 (0.368, 29.3, 0.505, 0.756), neg: 702 (%0.03:%0.07), avgs: 16
066: dt: 1.308, sse: 688816.4 (0.363, 28.4, 0.499, 0.756), neg: 56 (%0.00:%0.01), avgs: 16
067: dt: 25.204, sse: 684304.4 (0.364, 28.4, 0.496, 0.756), neg: 526 (%0.02:%0.06), avgs: 16
068: dt: 1.261, sse: 680584.3 (0.361, 27.8, 0.492, 0.756), neg: 60 (%0.00:%0.01), avgs: 16
069: dt: 10.120, sse: 679053.8 (0.362, 27.8, 0.492, 0.756), neg: 168 (%0.00:%0.01), avgs: 16
070: dt: 1.667, sse: 677616.7 (0.361, 27.6, 0.490, 0.756), neg: 51 (%0.00:%0.00), avgs: 16
071: dt: 6.724, sse: 676628.9 (0.361, 27.6, 0.490, 0.756), neg: 124 (%0.00:%0.01), avgs: 16
072: dt: 1.678, sse: 675656.8 (0.360, 27.5, 0.489, 0.756), neg: 52 (%0.00:%0.01), avgs: 16
073: dt: 8.216, sse: 674570.9 (0.361, 27.5, 0.488, 0.757), neg: 133 (%0.00:%0.01), avgs: 16
074: dt: 1.694, sse: 673512.5 (0.360, 27.3, 0.487, 0.757), neg: 53 (%0.00:%0.01), avgs: 16
075: dt: 1.764, sse: 673109.5 (0.360, 27.3, 0.487, 0.757), neg: 50 (%0.00:%0.00), avgs: 16
integrating with navgs=4 and tol=6.988e-02
076: dt: 22.423, sse: 670854.9 (0.362, 27.2, 0.485, 0.742), neg: 200 (%0.00:%0.02), avgs: 4
077: dt: 1.661, sse: 669613.8 (0.361, 27.0, 0.484, 0.743), neg: 95 (%0.00:%0.01), avgs: 4
078: dt: 4.100, sse: 668786.9 (0.361, 27.0, 0.483, 0.744), neg: 92 (%0.00:%0.01), avgs: 4
079: dt: 3.000, sse: 668304.8 (0.361, 27.0, 0.483, 0.744), neg: 102 (%0.00:%0.01), avgs: 4
080: dt: 1.848, sse: 667791.1 (0.361, 26.9, 0.482, 0.744), neg: 77 (%0.00:%0.01), avgs: 4
081: dt: 5.400, sse: 667120.4 (0.361, 26.9, 0.482, 0.745), neg: 105 (%0.00:%0.01), avgs: 4
082: dt: 1.967, sse: 666614.0 (0.361, 26.8, 0.481, 0.745), neg: 73 (%0.00:%0.01), avgs: 4
083: dt: 4.462, sse: 666103.5 (0.361, 26.8, 0.481, 0.745), neg: 103 (%0.00:%0.01), avgs: 4
084: dt: 2.154, sse: 665621.2 (0.361, 26.8, 0.481, 0.745), neg: 76 (%0.00:%0.01), avgs: 4
085: dt: 2.615, sse: 665218.2 (0.361, 26.7, 0.480, 0.745), neg: 74 (%0.00:%0.01), avgs: 4
integrating with navgs=1 and tol=4.419e-02
086: dt: 2.667, sse: 664951.9 (0.361, 26.7, 0.480, 0.744), neg: 76 (%0.00:%0.01), avgs: 1
integrating with navgs=0 and tol=3.125e-02
087: dt: 0.506, sse: 664875.2 (0.361, 26.7, 0.480, 0.743), neg: 76 (%0.00:%0.01), avgs: 0

blurring surfaces with sigma=2.00...
done.
curvature mean = 0.090, std = 0.502
curvature mean = 0.020, std = 0.575
tol=1.0e+00, sigma=2.0, host=athen, nav=1024, nbrs=1, l_extern=10000.000, l_nlarea=1.000, l_corr=0.050, l_spring=0.500, l_dist=0.250
using quadratic fit line minimization
nlarea/corr = 20.000
integrating with navgs=1024 and tol=1.000e+00
088: dt: 6.568, sse: 665480.4 (0.359, 26.7, 0.479, 0.937), neg: 270 (%0.02:%0.04), avgs: 1024
integrating with navgs=256 and tol=5.010e-01
089: dt: 1.744, sse: 664408.7 (0.359, 26.6, 0.478, 0.938), neg: 58 (%0.00:%0.01), avgs: 256
integrating with navgs=64 and tol=2.519e-01
090: dt: 6.774, sse: 663527.8 (0.360, 26.6, 0.478, 0.941), neg: 186 (%0.01:%0.03), avgs: 64
integrating with navgs=16 and tol=1.288e-01
091: dt: 1.450, sse: 662806.6 (0.359, 26.5, 0.477, 0.939), neg: 45 (%0.00:%0.00), avgs: 16
integrating with navgs=4 and tol=6.988e-02
092: dt: 6.720, sse: 662316.9 (0.359, 26.4, 0.477, 0.920), neg: 63 (%0.00:%0.01), avgs: 4
093: dt: 4.200, sse: 662053.0 (0.360, 26.5, 0.477, 0.913), neg: 85 (%0.00:%0.01), avgs: 4
integrating with navgs=1 and tol=4.419e-02
094: dt: 0.903, sse: 661962.4 (0.360, 26.5, 0.477, 0.910), neg: 79 (%0.00:%0.01), avgs: 1
integrating with navgs=0 and tol=3.125e-02
095: dt: 0.110, sse: 661952.2 (0.360, 26.5, 0.477, 0.909), neg: 73 (%0.00:%0.01), avgs: 0

blurring surfaces with sigma=1.00...
done.
curvature mean = 0.091, std = 0.611
curvature mean = 0.012, std = 0.719
tol=1.0e+00, sigma=1.0, host=athen, nav=1024, nbrs=1, l_extern=10000.000, l_nlarea=1.000, l_corr=0.050, l_spring=0.500, l_dist=0.250
using quadratic fit line minimization
nlarea/corr = 20.000
integrating with navgs=1024 and tol=1.000e+00
096: dt: 8.627, sse: 661315.6 (0.359, 26.4, 0.476, 1.011), neg: 227 (%0.02:%0.04), avgs: 1024
integrating with navgs=256 and tol=5.010e-01
097: dt: 1.786, sse: 660256.5 (0.358, 26.3, 0.475, 1.012), neg: 66 (%0.00:%0.01), avgs: 256
integrating with navgs=64 and tol=2.519e-01
098: dt: 5.077, sse: 659704.2 (0.359, 26.3, 0.474, 1.011), neg: 149 (%0.01:%0.02), avgs: 64
integrating with navgs=16 and tol=1.288e-01
099: dt: 1.431, sse: 659144.8 (0.358, 26.2, 0.474, 1.009), neg: 44 (%0.00:%0.00), avgs: 16
integrating with navgs=4 and tol=6.988e-02
100: dt: 2.714, sse: 658944.9 (0.358, 26.2, 0.474, 0.996), neg: 47 (%0.00:%0.00), avgs: 4
integrating with navgs=1 and tol=4.419e-02
101: dt: 0.075, sse: 658940.8 (0.358, 26.2, 0.474, 0.995), neg: 47 (%0.00:%0.00), avgs: 1
integrating with navgs=0 and tol=3.125e-02
102: dt: 0.054, sse: 658935.4 (0.358, 26.2, 0.474, 0.994), neg: 47 (%0.00:%0.00), avgs: 0

blurring surfaces with sigma=0.50...
done.
curvature mean = 0.092, std = 0.682
curvature mean = 0.004, std = 0.828
tol=1.0e+00, sigma=0.5, host=athen, nav=1024, nbrs=1, l_extern=10000.000, l_nlarea=1.000, l_corr=0.050, l_spring=0.500, l_dist=0.250
using quadratic fit line minimization
nlarea/corr = 20.000
integrating with navgs=1024 and tol=1.000e+00
103: dt: 27.636, sse: 656331.2 (0.358, 26.1, 0.472, 1.092), neg: 165 (%0.01:%0.03), avgs: 1024
integrating with navgs=256 and tol=5.010e-01
104: dt: 2.000, sse: 654661.2 (0.357, 25.9, 0.470, 1.083), neg: 82 (%0.00:%0.01), avgs: 256
integrating with navgs=64 and tol=2.519e-01
105: dt: 3.105, sse: 653928.0 (0.357, 25.8, 0.469, 1.076), neg: 67 (%0.00:%0.01), avgs: 64
integrating with navgs=16 and tol=1.288e-01
106: dt: 2.292, sse: 653418.9 (0.357, 25.8, 0.469, 1.066), neg: 53 (%0.00:%0.01), avgs: 16
integrating with navgs=4 and tol=6.988e-02
107: dt: 1.047, sse: 653125.0 (0.357, 25.8, 0.469, 1.057), neg: 35 (%0.00:%0.00), avgs: 4
integrating with navgs=1 and tol=4.419e-02
108: dt: 0.724, sse: 653027.9 (0.357, 25.8, 0.469, 1.047), neg: 36 (%0.00:%0.00), avgs: 1
integrating with navgs=0 and tol=3.125e-02
109: dt: 0.064, sse: 653009.2 (0.357, 25.8, 0.469, 1.044), neg: 34 (%0.00:%0.00), avgs: 0

Removing remaining folds...
tol=1.0e-01, sigma=0.5, host=athen, nav=64, nbrs=1, l_extern=10000.000, l_nlarea=100.000, l_corr=0.001, l_spring=0.005, l_dist=0.002
using quadratic fit line minimization
nlarea/corr = 199999.984
integrating with navgs=64 and tol=2.519e-02
110: dt: 5.514, sse: 187681.1 (0.355, 25.8, 0.466, 1.062), neg: 85 (%0.00:%0.01), avgs: 64
111: dt: 1.735, sse: 184602.0 (0.355, 25.7, 0.466, 1.064), neg: 16 (%0.00:%0.00), avgs: 64
112: dt: 2.802, sse: 182518.2 (0.354, 25.7, 0.466, 1.068), neg: 16 (%0.00:%0.00), avgs: 64
113: dt: 3.973, sse: 180638.1 (0.355, 25.8, 0.466, 1.072), neg: 16 (%0.00:%0.00), avgs: 64
114: dt: 2.388, sse: 179649.5 (0.355, 25.8, 0.467, 1.075), neg: 20 (%0.00:%0.00), avgs: 64
115: dt: 3.088, sse: 178962.5 (0.355, 25.9, 0.467, 1.079), neg: 28 (%0.00:%0.00), avgs: 64
116: dt: 2.775, sse: 178633.9 (0.356, 26.0, 0.468, 1.082), neg: 36 (%0.00:%0.00), avgs: 64
117: dt: 0.831, sse: 178379.4 (0.356, 26.0, 0.468, 1.083), neg: 37 (%0.00:%0.00), avgs: 64
118: dt: 2.731, sse: 178093.2 (0.356, 26.1, 0.469, 1.087), neg: 52 (%0.00:%0.00), avgs: 64
119: dt: 0.606, sse: 177994.0 (0.356, 26.1, 0.469, 1.088), neg: 46 (%0.00:%0.00), avgs: 64
120: dt: 0.250, sse: 177987.2 (0.356, 26.1, 0.469, 1.088), neg: 48 (%0.00:%0.00), avgs: 64
integrating with navgs=16 and tol=1.288e-02
121: dt: 0.230, sse: 177851.4 (0.357, 26.1, 0.470, 1.089), neg: 46 (%0.00:%0.00), avgs: 16
122: dt: 0.031, sse: 177844.3 (0.357, 26.1, 0.470, 1.089), neg: 45 (%0.00:%0.00), avgs: 16
integrating with navgs=4 and tol=6.988e-03
123: dt: 0.013, sse: 177801.5 (0.357, 26.1, 0.470, 1.089), neg: 38 (%0.00:%0.00), avgs: 4
124: dt: 0.014, sse: 177784.2 (0.357, 26.1, 0.470, 1.089), neg: 32 (%0.00:%0.00), avgs: 4
125: dt: 0.014, sse: 177779.8 (0.357, 26.1, 0.470, 1.089), neg: 31 (%0.00:%0.00), avgs: 4
integrating with navgs=1 and tol=4.419e-03
126: dt: 0.000, sse: 177779.8 (0.357, 26.1, 0.470, 1.089), neg: 31 (%0.00:%0.00), avgs: 1
integrating with navgs=0 and tol=3.125e-03
127: dt: 0.000, sse: 177746.4 (0.357, 26.1, 0.470, 1.089), neg: 30 (%0.00:%0.00), avgs: 0
128: dt: 0.000, sse: 177734.2 (0.357, 26.1, 0.470, 1.089), neg: 28 (%0.00:%0.00), avgs: 0
129: dt: 0.000, sse: 177734.2 (0.357, 26.1, 0.470, 1.089), neg: 28 (%0.00:%0.00), avgs: 0
registration took 0.25 hours
MRISregister() return, current seed 0
expanding nbhd size to 1
writing registered surface to lh.sphere_dis25_parea0.reg...
registration took 0.25 hours
[athens-b8-e8-56-47-e6-54:P00001613/FreeSurferClean/surf] ray% 

 
-- 
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 6, 2015, at 2:16 PM, Bruce Fischl <fischl@nmr.mgh.harvard.edu> wrote:

Hi Ray

try doing:

setenv DIAG 0x04040

then run it again and send me the output

Bruce

On Fri, 6 Nov 2015, Razlighi, Qolamreza R. wrote:

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.[IMAGE][IMAGE] 
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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