Standard sequences @ 3T

Multiband BOLD fMRI

Overview sequences

All with 10% gap, Sens 1.5, moderate PNS, maximum gradient mode, regular dynamic stabilization, 175Hz fat suppression SPIR offset

   3.0mm, TR=0550ms, MB4 S1.5, FOV 240x240x118mm, WFS 14.2pix (42.6mm), Max dyns 1820
   2.7mm, TR=0700ms, MB4 S1.5, FOV 240x240x130mm, WFS 14.4pix (38.9mm), Max dyns 1489
   2.0mm, TR=1600ms, MB4 S1.5, FOV=224x224x125mm, WFS 23.7pix (47.4mm), Max dyns 1170 

Considerations:

set shimbox to contain as little non-brain tissue and air as possbile
Create second GE-EPI with opposite fatshift direction, set preparation to auto for this sequence (so it won't perform a second B0 shim) and group the sequences
Perhaps not include dummies and use one of the pre-saturation scans for registration as it has better grey/white matter contrast (see Multiband data registration)

GABA edited spectroscopy

We use a patch from Richard Edden (John's Hopkins University), which contains a MEGA-PRESS sequence for 3T. For more information on the development of this patch, see: www.gabamrs.com.

Please visit this website first for an explanation of the method used, before you start your experiment.

If you have any remaining questions after reading this Wiki page, please contact Anouk Schrantee.

The patch

The patch needs to be loaded with Select Patch and is currently called R5_4 MEGA. Please make sure you read the instructions on the do's and don't's of using patches here.

<to be inserted: photo how to select the correct patch>

How to acquire GABA data

There are currently two implementations to scan GABA working on the 3T.

- GABA_68_PAR: without macromolecule suppression

- GABA_80_PAR: with macromolecule suppression

The HERMES implementation is not yet working.

The analysis software

The developers of the patch also provide an analysis toolbox to analyze your spectroscopy data. For more information on this, and examples, please see: www.gabamrs.com. It exists of a series of Matlab scripts, but it can easily be called from the command line in Matlab - no need to change the scripts for the standard implementation. The manual of how to analyze your data is also in the folder mentioned below.

Important: You can download Gannet on their website, but we have optimized the analysis toolbox for the data that we acquire at the Spinoza, so please use the version you can find here: Gannet 2.0