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Examplecode Documentation Release 0.1 examplecode Documentation Release 0.1 Tim Apr 23, 2021 CONTENTS: 1 About 1 2 Arterial Spin Labeling (ASL)3 3 Directions 7 4 DIY fMRI 9 5 DTI 17 6 Fieldmaps 19 7 JPEG Format Variations 25 8 Legacy Web Pages 29 9 Optimizing FSL and SPM 31 10 Sensation and Perception (PSYC450) 37 11 Image to Inference (PSYC589/888) 49 12 Perfusion-weighted imaging (PWI) 55 13 spmScripts 61 14 Slice Time Correction (STC) 63 15 Publications 67 16 Indices and tables 69 i ii CHAPTER ONE ABOUT 1.1 Topics • Attention and perception. Our senses flood the brain with an overwhelming amount of information – how do we select the relevant information? Clinical syndromes such as spatial neglect (where individuals ignore information on their left side) provide insight into how the brain achieves this. • Speech and language. Communication is invaluable for sharing information, planning and coordinating actions in a group. Human language is quantitatively and qualitatively a quantum leap from that seen in other species. Cognitive neuroscience is able to employ new techniques to understand language. This work will help reveal who we are, and may help people who have suffered profound communication difficulties following brain injury. 1.2 Tools • Behavioral Tasks. Each of our studies requires us to develop sensitive behavioral tasks: for example in an fMRI study of time perception we will want to compare tasks where the person makes temporal judgments (e.g. which item appeared first) to perceptually identical tasks where the participant judges a different domain (for example the shape of the items). We have extensive skill in designing and implementing these tasks. • MRI scans use radio signals to take pictures of the brain. fMRI is a type of MRI scan that is is sensitive to oxygenation concentration, allowing us to infer brain function. Typically, we have people perform simple tasks in the scanner while we collect fMRI scans. We have used this technique to identify the brain areas involved with speech and perception. In addition, we have used fMRI to examine recovery from brain injury. • Lesion behavior mapping associates the location of brain injury with the resulting symptoms. For example, we use this technique to identify the brain injuries that result in speech impairment. We can also use this technique to identify the best targets for neurosurgery. 1 examplecode Documentation, Release 0.1 • Transcranial Direct Current Stimulation. tDCS applies weak electrical currents to the scalp. It appears that tDCS can induce subtle changes in brain activity, with regions near the positive electrode showing slightly increased firing rates, whereas regions under the negative electrode show small decreases in firing rate. Curiously, these changes seem to persist for many minutes after the stimulation ends. Because this technique is very safe and inexpensive, this technique offers potential for the helping people recover from brain injury as well as revealing the function of the healthy brain. We have devised methods for double-blind testing of tDCS (where neither the participant nor the experimenter knows the type of stimulation used) to investigate this mysterious but promising technique. • TMS uses a brief magnetic pulse to stimulate parts of the brain near the TMS coil. The region of stimulation is relatively focused. By introducing TMS pulses while participants are conducting a task we can 2 Chapter 1. About CHAPTER TWO ARTERIAL SPIN LABELING (ASL) Arterial Spin Labeling (ASL) is a Magnetic Resonance Imaging (MRI) technique for measuring blood flow. Whereas conventional Perfusion Weighted Imaging (PWI) uses an external agent like Gadolinium (Gd) to tag blood, ASL directly tags the blood entering the brain. Conventional PWI has high signal to noise, but we tend to only track the perfusion of a single bolus (e.g. Gd is injected once into the arm, and we measure the latency and amount of this agent reaching different parts of the brain). In contrast, with ASL we have low signal to noise, but can easily acquire and compare hundreds of images. The rest of this page focuses on ASL, for more details on conventional PWI, please visit my PWI page.. ASL can be used to measure make quantitative measures of perfusion, such as the relative cerebral blood flow (rCBF). In addition, ASL scans can be used to infer brain function, similar to T2*-weighted fMRI. In general, ASL fMRI has slower acquisition, reduced field of view, and worse spatial distortions relative to T2* fMRI. However, it does provide a more direct measure of blood flow that may be helpful in cases where the canonical hemodynamic response has been disrupted. In any case, FSL makes it pretty easy to analyses ASL fMRI in a manner that is very similar to T2* fMRI. The FSL web page provides more details. Therefore, the rest of this web page describes the analysis of quantitative ASL data. There are many different types of ASL sequences. Your sequences will be limited by the type of scanner you have, as well as the sequence licenses you have available. Several major variations are CASL (continuous ASL), PASL (pulsed ASL) and pCASL (pseudo-Continuous ASL). At the MCBI we have the official Siemens PASL sequence (PICORE Q2T) and the pCASL from JJ Wang and his team. The Siemens sequence is elegant, as it automatically creates a rCBF map. However, we tend to prefer the pCASL sequence for our studies. A crucial step when acquiring ASL data is to set the correct post-label delay time. This is the time between when the blood is tagged in the neck and when the image of the brain is acquired. If the delay is too short, the blood will not have time to transit into the image, and if it is too long it will already have washed out of the image. This is especially important, as we will acquire pairs of images: one labelled and one unlabelled. One could imaging that with a very brief post-label delay and a short time between volumes (TR), the tagged blood might not get to the head in time for 3 examplecode Documentation, Release 0.1 the ‘labelled’ image, but be clearly present during the ‘unlabelled’ image acquisition. I strongly suggest consulting the people who developed your sequence to get their suggestions for post-label delay times. For the pCASL sequence we have, Ze Wang has suggested a delay time in the range of 700-1000ms for healthy children and young adults, while for older individuals (65 or older) he suggests 1200-1500ms, finally for stroke patients or patients with vascular diseases he notes that 1800ms might be required. In any case, this selection should be standardized for a single study. For example, a shorter delay may be required for a study of stroke that hopes to examine both the intact and injured hemisphere. However, if you plan to acquire images from special populations (e.g. people with strokes) you may want to consult your physicist. As you adjust the delay time, the minimum TR is also influenced. Ze Wang suggests that your actual TR should always be at least 100ms longer than the minimum TR since the labeling pulses induce Magnetization Transfer (MT) effects to the brain regions to be imaged, so before the spins go back to the steady state, they are suppressed to some extent by the labeling pulses. Longer TRs provide more signal (more time for spins to relax), though at the cost of fewer acquisitions (and more difficulty temporally interpolating data for fMRI-like task based paradigms). In general, a TR of 3500ms seems appropriate (unless your population requires a very long delay time). Another thing you should bear in mind with the CfN pCASL sequence is the bandwidth (indeed, bandwidth is an important decision for echo-planar imaging [EPI] protocols). With regards to the CfN pCASL sequence, Ze Wang notes that high bandwidths can lead to severe eddy currents leading to phase accumulation and a N/2 ghost artifact. Performance varies between scanners, but he suggests that 2232 to 2694 Hz/pixel should be appropriate for most Siemens Trios (you should also check that images from your scanner do not show aliasing artifacts, if you see artifacts then you should collect images without iPAT [as this can also cause artifacts] and iteratively take images while decreasing the bandwidth until the artifacts go away). You will also want to specify your labeling time, for example if your protocol PDF reports 80 blocks, the Labeltime = 80*0.0185, since the CFN pCASL RF block duration is ALWAYS 0.0185s (20 RF pulses with gaps). For our protocol, we use 80 RF blocks, a bandwidth of 2442 Hz/px, and acquire 17 slices. With these settings the minimum TR is 2090ms plus the delay time (so since slicetime=[minTR- labelingtime-delaytime]/#slices, we can compute that our Slicetime is 36.35294118ms). For example, with a 1200ms post label delay the minimum TR is 3290ms, and we typically acquire with a TR of 3500ms. 2.1 pCASL Analysis Simplified This page is old. While the scripts below work, new users may want to consider using FSL’s BASIL. We have set up a simple script for processing our pCASL data. This script requires that you have the following installed: • Matlab (no toolboxes required) • SPM12 • ASLtbx – Since this script uses 4D NIfTI format files, you need a recent version of ASLtbx (the asl_perf_subtract.m text file should report being version May 2 2012 or later). • One NIfTI format T1-weighted anatomical scan per participant • One NIfTI format 4D ASL file per session (each participant may have multiple sessions). • My asl_process_subj.m matlab script (this needs to be in your Matlab path, you might as well put it into your ASLtbx folder,download includes script and sample images).
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