Hi Vasudev,

No - your functional and structural data should be in the resolution they were acquired in respectively, and should match the resolution of the images you used in the registration process.  The dimensions you have quoted look like reasonable values for T1/functional EPI data.

To solve your problem, you need to identify the specific point of failure, and focus on fixing that. Refer to the list of steps in my previous email.

In your other email thread, it looked to me like the non-linear registration was not ideal - this could be caused by a poor brain extraction, or an atypical brain. In your most recent screenshot it looks like something more fundamental has gone wrong - I would hazard a guess that one of the files you have used is incorrect.

Paul

On Feb 20 2020, at 9:43 am, Dev vasu <[log in to unmask]> wrote:

Dear Sir,

- that all of the input files have the correct dimensions , is it necessary that dimensions of all functional and structural files should be same ?

The Dimensions of all structural files is

sizeof_hdr     348

data_type      FLOAT32

dim0           3

dim1           160

dim2           256

dim3           256

dim4           1

dim5           1

dim6           1

dim7           1

vox_units      mm

time_units     s

datatype       16

nbyper         4

bitpix         32

pixdim0        0.000000

pixdim1        1.000000

pixdim2        1.000000

pixdim3        1.000000

pixdim4        1.000000

pixdim5        0.000000

pixdim6        0.000000

pixdim7        0.000000

vox_offset     352

Dimensions of all Functional files

sizeof_hdr     348

data_type      INT16

dim0           4

dim1           64

dim2           64

dim3           46

dim4           300

dim5           1

dim6           1

dim7           1

vox_units      mm

time_units     s

datatype       4

nbyper         2

bitpix         16

pixdim0        0.000000

pixdim1        3.000000

pixdim2        3.000000

pixdim3        3.000000

pixdim4        2.500000

pixdim5        1.000000

pixdim6        0.253332

pixdim7        47455.246094

vox_offset     352

cal_max        0.0000

cal_min        0.0000

scl_slope      1.000000

scl_inter      0.000000

phase_dim      0

freq_dim       0

slice_dim      3

slice_name     alternating_increasing_2

slice_code     5

slice_start    0

slice_end      45

slice_duration 0.000000

time_offset    0.000000

intent         Unknown

intent_code    0

intent_name    

intent_p1      0.000000

intent_p2      0.000000

intent_p3      0.000000

qform_name     Scanner Anat

qform_code     1

On Thu, Feb 20, 2020 at 10:26 AM paul mccarthy <[log in to unmask]> wrote:

Hi Vasudev,

As I said in your other thread, this is due to a poor registration. Double check the following:

- that all of the input files have the correct dimensions

- The structural brain extraction is good

- The func-struc registration is good

- The struc-standard registration is good

- The process you used to generate highres2standard_warp_inv  is valid

Paul

On Feb 19 2020, at 8:09 pm, Dev vasu <[log in to unmask]> wrote:

Dear all,

I have done functional preprocessing using FEAT and i would like to perform seed based correlation for visual cortex seed regions, my seed is defined in MNI152 space.

The seed and example_func.nii.gz are completely mismatched ( see picture ) , I have used Visual_thr_mask.nii.gz as seed ( see attachment) and tried to transform by doing

applywarp -i Visual_thr_mask.nii.gz -r reg/example_func.nii.gz -o Visual_func 
--postmat=reg/highres2example_func.mat -w reg/highres2standard_warp_inv

I dont understand what is the problem with my approach-could you please provide

me some input.

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