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Automatic Analysis (aa) system for neuroimaging

aa release 1.0

Manual version 2.0– 12/1/2006

Rhodri Cusack, MRC CBU, Cambridge rhodri.cusack@mrc-cbu.cam.ac.uk__

Acknowledgements: Thank you to Matthew Brett, who wrote scripts that formed the basis of some of the modules. Thanks to Jessica Grahn for the descriptions of the modules in section Error! Reference source not found..

CONTENTS

Table Of Contents

[#s Summary]

[#s Main Features]

[#s System overview]

[#s User script]

4.

[#s4. Overview]

4.

[#s4. Choosing the recipe]

4.

[#s4. Modify parameter set selection]

4.

[#s4. Setting your acquisition parameters]

4.

[#s4. Set specific parameters that you wish to differ from the defaults]

[#s Everyday tasks]

5.

[#s5. Getting ready to use AA]

5.

[#s5. Running an analysis]

5.

[#s5. Restarting an analysis]

5.

[#s5. How do I force an analysis to start all over again?]

5.

[#s5. How do I force an analysis to start from a particular stage?]

[#s Pitfalls - beware!]

6.

[#s6. Check your data]

6.

[#s6. Changing the aa_user script]

[#s Reference]

7.

[#s7. Available recipes]

7.

[#s7. Available parameter sets]

7.2.

[#s7.2. directory_conventions]

7.2.

[#s7.2. options]

7.2.

[#s7.2. tasklist]

7.2.

[#s7.2. spmanalysis]

7.2.

[#s7.2. acq_details]

7.

[#s7. Individual parameters]

7.3.

[#s7.3. acq_details]

7.3.

[#s7.3. directory_conventions]

7.3.

[#s7.3. options]

7.3.

[#s7.3. spmanalysis]

7.3.

[#s7.3. tasklist]

7.

[#s7. Initialisation modules]

7.4.

[#s7.4. aamod_checkparameters.m]

7.4.

[#s7.4. aamod_make_subjects_short]

7.4.

[#s7.4. aamod_autoidentifyseries.m]

7.

[#s7. Modules]

7.5.

[#s7.5. aamod_newsubj_init.m]

7.5.

[#s7.5. aamod_copyfieldmaps.m]

7.5.

[#s7.5. aamod_pvconv.m]

7.5.

[#s7.5. aamod_copystructural.m]

7.5.

[#s7.5. aamod_ana4dto3d.m]

7.5.

[#s7.5. aamod_slicetiming.m]

7.5.

[#s7.5. aamod_realign.m]

7.5.

[#s7.5. aamod_undist.m]

7.5.

[#s7.5. aamod_coreg.m]

7.5.1

[#s7.5.1 aamod_norm.m]

7.5.1

[#s7.5.1 aamod_undist_reslice.m]

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Summary

The system automates the analysis of neuroimaging data. This version has been configured to work on data from the Wolfson Brain Imaging Centre, reading Bruker data and analysing it with SPM. It is written in Matlab.

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Main Features

  • Automatic. Almost completely automatic analysis, currently up to the end of normalisation.

  • Flexible control. Users that are new to neuroimaging don’t get bombarded with options, but are directed to what is essential, while all other settings take sensible defaults. More experienced users can easily change a range of settings, and advanced users can add or replace modules to the system to change any behaviour

  • Restartable. If the users stops the script, or if it crashes (e.g., because of a machine fault, or because the right data aren’t there) then when restarted it will begin at the stage where it left off.

  • Modular. The system is modular at two levels, to make it easy to switch in or out relevant parts.

  • Automatic good citizen behaviour. Field maps and structurals are automatically detected. Structurals are copied to /imaging/local/structurals/cbu automatically by default.

  • Easy to maintain. The code components are stored in a central repository (/cbu/imagers/spm/aa ?) which means that new components can be made available, or existing ones changed in new releases

  • Record keeping. Unlike SPM used from the GUI, the system records exactly which parameters were used, and allows easy recreation of a dataset from the raw data at a later date.

  • Simple interface for new modules. It is easy for Matlab programmers to write new modules and incorporate them into the processing stream.

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System overview

An overview of the different types of components is shown in this table:

Component

Description

Location of file

Expertise needed to write new ones

User script

In overall control. Selects a recipe, adds study specific information, and changes any defaults

User's directory

Beginner

Recipes

Specifies which parameter sets to use

Centrally

Beginner/ Intermediate

Parameter sets

Set default parameters. There are five different basic types of parameter set

Centrally

Intermediate

Modules

Run individual stages of processing

Centrally

Advanced

Engine

Main automatic analysis engine, which contols module execution

Centrally

Advanced

= =The most important of these by far from the user’s point of view is the “User script”. The next section describes this. Anchor(s)

User script

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4. Overview

This is the master script, which controls the analysis. Most studies can be analysed with this alone.

There are 6 sections to the user script:

  • Section

    Probability you need to change it and when

1

Choosing a recipe

(0.2) If you use a non-standard acquisition sequence or wish to do a quite different type of analysis

2

Changing any of the parameter sets in the recipe

(0.1) If you wish to change a single parameter set controlling part of the automatic processing from what is specified in a recipe

3

Initialising using the parameter sets

(0.01) Usually never

4

Setting study specific details

(1.0) Always

5

Set any other parameters that need to differ from the defaults

(0.6) If you wish to change single parameters

6

Calling aa_doprocessing to do the processingBR

(0.01) Usually never

An example, which will process 3 subjects each with 4 sessions up to and including normalisation is below:

An example, which will process 3 subjects each with 4 sessions up to and including normalisation is below:

% Automatic analysis

% User master script

% Rhodri Cusack MRC CBU Cambridge 2005

% (1) RESET ALL PARAMETERS

aap=[];

% (2) ANALYSIS RECIPE

% General auto TR recipe; slice order Siemens product sequence default

aap=aarecipe_general(aap);

% (3) MODIFY STANDARD RECIPE MODULE SELECTION HERE IF YOU'D LIKE

  • % do this here

% (4) GET ALL THE PARAMETERS FOR THIS RECIPE

aap=aa_init(aap);

% (5) DEFINE STUDY SPECIFIC PARAMETERS

aap.options.aa_minver=1.0; % will only work on aa version 1.0 or above

  • % The study directory

aap.acq_details.root = '/home/rhodri/pvs/cbu';

  • % Add subjects and session numbers for EPI data

aap=aas_addsubject(aap,'*CBU050011/*',[5 11]);

aap=aas_addsubject(aap,'*CBU050012/*',[4 10]);

  • % Condition names for each session, must be same for all subjects

aap.acq_details.sessions={'mystery1','mystery2'};

  • % Number of dummy scans at the start of each session

aap.acq_details.numdummies=18;

% (6) SET ANY OTHER PARAMETERS YOU WOULD LIKE TO BE DIFFERENT FROM THE DEFAULTS

% (7) SET ANY SPM DEFAULTS IF NEEDED

aap.spm.defaults.normalise.write.vox=[3 3 3];

% (8) DO PROCESSING

aa_doprocessing(aap);

The four sections you are mostly likely to need to change (1, 2, 4 and 5) are now discussed in turn.

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4. Choosing the recipe

These are chosen with the line

aap=[recipename](aap);

e.g., aap=aarecipe_general(aap);

An example recipe is shown below. Descriptions of the parameter sets are in the next section. A full list of recipes is in the “Reference” section.

Name:

aarecipe_general

Description:

Standard automatic TR recipe

Parameter set choice:

Type

Parameter set

directory_conventions

aap_directory_conventions_ver00

options

aap_options_ver00

tasklist

aap_tasklist_cbudefault_ver00

spmanalysis

aap_spmanalysis_tr1p1_ver00

acq_details

aap_acq_details_ver00

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4. Modify parameter set selection

A recipe comprises a description of the parameter sets that should be included. Once you’ve chosen a recipe you may override some of the different parameter sets. You would do this in stage 2 of the user script (see Error! Reference source not found.) with a line like

aap.recipe.directory_conventions=’aap_directory_conventions_mynewstyle’

(NB: no ‘.m’ on end)

There are 5 different types of parameter sets. A full list of the available parameter sets is given in the “Reference” section.

Type

Description

directory_conventions

Specifies directory and file conventions, for example:BR- directory names for each subject (4d_files, proc_fieldmaps etc.)BR- raw data directory (by default /cbu/wbic_data)BR

options

General aa program options, for example:BR- whether to automatically identify the field maps and SPGR in the incoming datasetBR- whether to copy structurals to the central store

tasklist

The list of tasks to be performed (e.g., modules to be executed) for each study

spmanalysis

SPM & imaging analysis parameters, for example:BR- TR & slice acquisition timeBR- smoothing FWHMBR- evolution time of fieldmaps

acq_details

Acquisition details. Several of the defaults are overridden in the user script, for example:BR- study directoryBR- subject list

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4. Setting your acquisition parameters

You always need to do this, to tell the system which files to analyse. The essential lines with explanation and notes are these:

aap.acq_details.root = '/cbu/scratch2/rhodri.cusack/newsimultaneous';BR

Specifies the directory where the processed study data are stored. This directory should exist before you run the script.

aap.acq_details.sessions={'ns1_block1','ns1_block2','ns2_passive','ns2_active'};BR

These are names of the blocks in your experiment. This must be the same for all subjects. Here, there were four blocks. I find it easiest to use intuitive names that describe the behavioural condition.

aap.acq_details.numdummies=18;BR

Number of dummy scans at the start of each session that need to be thrown away.

Too make it easy to see the correspondence between subject and session number, I now recommend subject names are added with the aas_addsubject command:

aap=aas_addsubject(aap, ‘*CBU050011\*’,[5 11]);

The full syntax of this command is in Error! Reference source not found., but the first string specifies the raw data for this subject (you may use wildcards) and the numbers in square brackets the series numbers for the EPI data. There should be as mank of these are there are blocks, as specified in aap.acq_details.sessions and described above.

By default, MPRAGE structural and GRE_FIELDMAPPING fieldmap scans are automatically detected.

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4. Set specific parameters that you wish to differ from the defaults

Once you’ve set up the parameters using a recipe and any different parameter sets you’d like, there may still be one or two parameters that you need to change. You do this at this stage. For example, in the sample script, if my data were no longer in /mridata/cbu I would add the line:

aap.directory_conventions.rawdatadir='/imaging/rhodri/newsimultaneous';

A full list of parameters with descriptions is given in section Error! Reference source not found..

Set any SPM defaults

Any SPM defaults can be changed. You do this using lines like the following:

aap.spm.defaults.normalise.write.vox=[3 3 3];

The aap.spm.defaults structure gets copied into the GLOBAL “defaults” variable before running SPM functions.

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Everyday tasks

Anchor(s5.)

5. Getting ready to use AA

Once you’ve started a Matlab/SPM session, type

>> aa

at the Matlab prompt to add the automatic analysis paths

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5. Running an analysis

Once you’ve made your user script, just type its name to run it. When it starts to run, it does some checks, and so you may see some warnings. These give you advanced notice that your script may have problems at some stage

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5. Restarting an analysis

To restart an analysis, just type the script name again. It will start from where it left off.

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5. How do I force an analysis to start all over again?

Change to the study directory and delete the “done_aamod_studyinit” flag

Example

Type at UNIX prompt. When you run an analysis again it will redo the realignment stage and all stages after it for this subject.

cd /cbu/scratch2/rhodri.cusack/mystudydir

rm done_aamod_studyinit

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5. How do I force an analysis to start from a particular stage?

To track how far through the analysis it has got, the system writes small files that start with “done_...” and end with the module name. Where a module has to be executed once per study, the done_ file will be in the study directory. Where it has to be executed once per subject, it will be in the subject directory. Where it has to be done for every session, it will be in the individual session directories. If you delete one of these flags, then this stage and all others after it will be re-run. Note it isn’t always completely obvious whether a module is once-per-subject (e.g., realignment) or once-per-session (e.g., slice timing). See the Reference section 0 to check.

Example

Type at UNIX prompt. When you run an analysis again it will redo the realignment stage and all stages after it for this subject.

cd /cbu/scratch2/rhodri.cusack/mystudydir

cd W030511.ls1

rm done_aamod_realign

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Pitfalls - beware!

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6. Check your data

Although the processing is automated, this doesn’t mean that things will never go wrong. Your data may have a problem – scanning glitches or excessive subject movement, for example – or there maybe something wrong with the analysis. Just as you would when doing it by hand, you should check your data at various stages.

Diagnostic JPEGs

One way of checking your data is to check through the images dumped in the analysed study, subject and block directories. These files begin with “diagnostic_aamod” end have a “.jpg” suffix. These are described in the table below.

Current output is all graphical, in the form of JPEG files. These may be viewed using a Windows graphics viewer, or with xv on unix. Examples are below

Name

File directory

Description

diagnostic_aamod_ana4dto3d_rawmean

Session

raw mean as generated by ana4dto3d

diagnostic_aamod_ana4dto3d_rawvar

Session

raw variance as generated by ana4dto3d

diagnostic_aamod_tsdiffana

Session

output from tsdiffana

diagnostic_aamod_realign

Subject

realignment display from SPM

diagnostic_aamod_undist

Subject

evaluation of undistortion. Top pair of images are in distorted space and should be similar in shape and coregistered with each other. Left is distorted fieldmap magnitude, right is raw EPI. Bottom two images are in undistorted space and should be similar in shape and coregistered with each other, although not necessarily with the top two images.

diagnostic_aamod_coreg

Subject

SPM output from coregistration of structural and undistorted EPI

diagnostic_aamod_norm

Subject

SPM output from normalisation

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6. Changing the aa_user script

Be careful about changing the aa_user script after you’ve run part of an analysis. The problem with doing this is that if the changes you make would have affected the parts that have already been completed, you won’t be able to use the script to exactly recreate your data in future.

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Reference

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7. Available recipes

Name:

aarecipe_standard_tr1p1_ver00

Description:

Standard TR=1.1s recipe

Parameter set choice:

Type

Parameter set

directory_conventions

aap_directory_conventions_ver00

options

aap_options_ver00

tasklist

aap_tasklist_cbudefault_ver00

spmanalysis

aap_spmanalysis_tr1p1_ver00

acq_details

aap_acq_details_ver00

*** need sparse, ISS ***

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7. Available parameter sets

To see the full list of settings in a parameter set, at the Matlab prompt type:

>> edit [parameter set name]

e.g.,

>> edit aap_directory_conventions_ver00

Anchor(s7.2.)

7.2. directory_conventions

Parameter set

Description

aap_directory_conventions_ver00

Example fields:BRSub-directories called “4d_files”, “proc_fieldmaps”, “raw_fieldmaps”, “structurals”BRRaw data in /cbu/wbic_dataBRCentral store for structurals /cbu/imagers/data/structuralsBRCentral store for skull-stripped structuralsBR/cbu/imagers/data/structurals/skull_strippedBRTemplate for normalisation /cbu/imagers/spm/spm99/templates/sbrain_avgBR152T1.imBR

Anchor(s7.2.)

7.2. options

Parameter set

Description

aap_options_ver00

Example fields:BRProvide fairly verbose output while running script.BRAutomatically identify field maps and structurals in datasets.BRCopy structurals to central directory.

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7.2. tasklist

Parameter set

Description

aap_tasklist_cbudefault_ver00

Task list: BRaamod_newsubj_initBRaamod_autoidentifyseriesBRaamod_copyfieldmapsBRaamod_pvconvBRaamod_copystructuralBRaamod_ana4dto3dBRaamod_slicetimingBRaamod_realignBRaamod_undistBRaamod_coreg'BRaamod_normBRaamod_undist_reslice

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7.2. spmanalysis

Parameter set

Description

aap_spmanalysis_tr1p1_ver00

Example settings:BRTR=1.1; slicetime=0.0762; smoothing FWHM=10mmBR

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7.2. acq_details

Parameter set

Description

aap_spmanalysis_tr1p1_ver00

Settings mostly overridden by aap_userBR

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7. Individual parameters

Here is a list of the individual parameters. They are divided into sections, by their type (shown in bold). To fill a field, in section 5 of your user script, put:

aap.[type].field=[value];

For example,

aap.directory_conventions.rawdatadir=’/cbu/scratch2/rhodri.cusack/my_raw_data’;

BRAnchor(s7.3.)BR=== 7.3. acq_details ===

see section 4.4 for notes on filling these fields

Field

Typical value

Description

root

'/cbu/scratch2/rhodri.cusack/newsimultaneous'

Path to directory where processed study will be stored. This directory should exist. Must be assigned by user.

subjects

{'W030510.ls1' 'W030511.ls1' 'W030512.ls1'}

List of subjects. Must be assinged by user.

sessions

{'ns1_block1','ns1_block2','ns2_passive','ns2_active'};

List of sessions. Must be assigned by user

brukersessionnums

{[4 5 8 7] [4 5 7 8] [4 5 8 7]}

List of session numbers. Must be assigned by user. [usually done with aas_addsubject command, see]

fieldmaps

[9 11;9 11; 9 12]

Session number of fieldmaps. Automatically detected by default

newfieldmap

[8; 7; 4]

Automatically detected by default

numdummies

18

Number of dummy scans at the start of each session. Must be assigned by user.

structurals

{}

Session number of structurals. Automatically detected by default

Anchor(s7.3.)BR=== 7.3. directory_conventions ===

Field

Typical value

Description

four_d_dir

'4d_files'

Name of subdirectory in subject directory for 4d analyze files from pvconv.pl

proc_fieldmaps

'proc_fieldmaps'

Name of subdirectory in subject directory for processed fieldmaps

raw_fieldmaps

'raw_fieldmaps'

Name of subdirectory in subject directory for raw fieldmaps

structdirname

'structurals'

Name of subdirectory in subject directory for structurals

rawdatadir

'/cbu/imagers/wbic_data/'

Where raw data are

centralstore_structurals

'/cbu/imagers/data/structurals'

Where structurals should be put

centralstore_ssstructurals

'/cbu/imagers/data/structurals/skull_stripped'

Where to find and put skull stripped structurals

T1sstemplate

/cbu/imagers/spm/spm99/templates/ sbrain_avg152T1.img

Template file for normalisation

subject_directory_format

0: manually specify in aap.directory_conventions.subject_directory_namesBR 1: truncated subject names (e.g., W020123) {default}BR 2: automatically generated ordinal labels for subject directories (S01, S02, S03...)BRBR

Format for subject output directories

subject_filename_format

0: manually specify in field aap.directory_conventions.subject_filenamesBR 1: truncated subject names (e.g., W020123) {default}BR 2: automatically generated ordinal labels for subject directories (S01, S02, S03...)BR

Format for subject directories

subject_directory_namesBR

{‘myfirstsubjdir’,’blob’}

Manually specified names of directories for subjects

subject_filenames

{‘myfirstsubjfilename’,’blob’}

Manually specified names of EPI filenames for subjects

Anchor(s7.3.)BR=== 7.3. options ===

Field

Typical value

Description

verbose

1

Give user regular updates of status when running tool

copystructuraltocentralstore

1

Copy structurals to central store

deletestructuralaftercopyingtoc

1

Delete local copy of structural (before skull stripping) after copying to central store

autoidentifystructural

1

Automatically find structurals in raw datasets

autoidentifyfieldmaps

1

Automatically find fieldmaps in raw datasets

Anchor(s7.3.)BR=== 7.3. spmanalysis ===

Field

Typical value

Description

TRs

1.1

Repetition time

slicetime

0.0762

Time to acquire a single slice

FWHM

10

Smoothing kernel (mm)

evoltime

9.104

Evolution time of field maps

structuralbetf

0.5

Bet fractional threshold value to be used when skull stripping tb_ files

Anchor(s7.3.)BR=== 7.3. tasklist ===

Field

Typical value

Description

initialisationmodules

{'aamod_checkparameters' 'aamod_make_subjects_short' 'aamod_autoidentifyseries'}BR

List of initialisation modules, which are always run during processing

stages

{'aamod_newsubj_init', 'aamod_autoidentifyseries', 'aamod_copyfieldmaps', 'aamod_pvconv', 'aamod_copystructural', 'aamod_ana4dto3d', 'aamod_slicetiming', 'aamod_realign', 'aamod_undist', 'aamod_coreg', aamod_norm', 'aamod_undist_reslice'}

List of modules to be called to perform processing. These are only run once each (i.e., if there is no file done_xxx)

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7. Initialisation modules

These modules are run every time aa_doprocessing is called, which is different from standard modules (see Error! Reference source not found.) which are only executed if they haven’t already been done (as recorded by a “done_” flag).

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7.4. aamod_checkparameters.m

Check that no new fields have been created in the aap structure by the user to trap mis-typing.

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7.4. aamod_make_subjects_short

EPI filenames are short versions of subject number – either session code (e.g., CBU030207) or ordinal labels (e.g., S03) if specified in directory_conventions. This module makes these shorter filenames.

aamod_evaluatesubjectnames

Evaluates any wildcards in the subject names.

Anchor(s7.4.)

7.4. aamod_autoidentifyseries.m

Identifies data series in the raw data that correspond to fieldmaps, MPRAGE structurals and realtime T maps. For speed, stored in .mat file in subject directory the first time, and loaded from this.

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7. Modules

All of the work is done by a set of modules, each of which performs an individual processing stage. These modules are described below. Each will only be executed if they haven’t been done already, as signified by a “done_” flag (see Error! Reference source not found., Error! Reference source not found.)

Anchor(s7.5.)

7.5. aamod_newsubj_init.m

Makes the subject directory if it doesn’t exist already.

Anchor(s7.5.)

7.5. aamod_copyfieldmaps.m

Copies the raw fieldmaps to the specified “rawphase” directory. The data in this directory will be used by undistort to reconstruct the raw data into processed fieldmaps.

=== aamod_pvconv.m

[no longer used] ===

Script to convert the raw Siemens DICOM data files (generally located in /mridata).

aamod_convertseries.m

Converts EPI data from Siemens DICOM to NIFTI format.

aamod_converttmaps.m

Converts realtime t maps into NIFTI format and puts them into folder realtime_tmaps in each subject directory

Anchor(s7.5.)

7.5. aamod_copystructural.m

Copies the structural to the central unit storage place for structurals (currently /cbu/imagers/data/structurals).

aamod_ana4dto3d.m [no longer used]

Converts the 4dfiles (output of pvconv) to many 3d files. Done on EPI sessions (as you are acquiring multiple volumes across time). You will have as many 3d files in your session as there are TRs (or volumes) in the session. Optional output includes the mean image, the mean variance image, and the variance slice. These are helpful diagnostic images. There is also the option to not write out the dummy scans (because they are simply there to let the scanner signal steady, and won't be included in your analysis).

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7.5. aamod_slicetiming.m

Corrects for the staggered order of slice acquisition. This makes the data on each slice correspond to the same point in time. Otherwise the data on one slice could represent a point in time as far removed as 1/2 the TR from an adjacent slice. Generally one uses sinc interpolation.

Anchor(s7.5.)

7.5. aamod_realign.m

Causes all of the volumes in each session to be registered to the first volume in that session, then all volumes are registered to the first volume of the first session. So, for each session, you get a mat file with the parameters to register all the slices in that session to the first slice in that session. You also get an overall .mat file with all the parameters in relation to the first scan/first volume. This overall mat file is in your first session folder.

You will also get a text file of the realignment parameters--this will be used by SPM during model estimation to get rid of signal due to movement.

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7.5. aamod_undist.m

Creates processed fieldmaps (placed in the processed fieldmaps directory), which are then used to correct distortions in the EPIs. This improves normalization and statistical power.

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7.5. aamod_coreg.m

Puts the selected scans (usually the mean EPI image and the structural) in the same space. Usually one coregisters the structural to the mean EPI image (without reslicing), as this requires reorienting only one structural, as opposed to hundreds of EPIs.

Anchor(s7.5.1)

7.5.1 aamod_norm.m

Transforms the scans into standardised space (given by a template image). One can skull-strip and normalize the structurals to a T1 template, then apply the parameters derived by the normalization to the EPIs. Or one can try masked EPI normalization, in which masks are created for areas of signal dropout in the EPI, and then the EPIs are normalized to an EPI template.

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7.5.1 aamod_undist_reslice.m

Helpful script that writes out the realigned-undistorted-normalized-smoothed images (or just up to normalized, with no smoothing). Saves one from having to write out the EPI images for each of the aforementioned stages individually, by combining all these processes in one resampling step.

Helper functions

aas_addsubject

SYNTAX:

aap=aas_addsubject(aap,’subject file name’,[EPI series number 1, EPI series number 2,...]);

EXAMPLE

aap=aas_addsubject(aap,’*CBU050011/*’,[5 11]);

DESCRIPTION

This function adds the details of a subject to be analysed. The file name of the raw data and EPI session numbers are specified.

You may use filename wildcard characters (*) in the subject directory name.

||By default, the raw data is searched for in /mridata/cbu/ (add line like

  • aap.directory_conventions.rawdatadir='/imaging/rhodri/newsimultaneous';

to user script – see 4.3

The EPI series number should be that of the raw data series directories with names similar to

Series_004_CBU_EPI_Std_RealTime_30s

or

Series_002_CBU_EPI_Standard

aa_benchmark

Tells you how long each stage took to run (in seconds).