CNI Wiki - User contributions [en]

Main Page

2023-09-21T21:06:04Z

Wandell:

= Welcome to the CNI Wiki = __NOTOC__

This site provides technical information for users of the Stanford Center for Cognitive and Neurobiological Imaging (CNI) facilities. All CNI users are invited to contribute their knowledge by editing content here. It is important that you verify the accuracy of any information that you post.

Follow [[Getting Started | this Getting Started link]] if you are new to the CNI and would like to learn about the basic facilities and how to get access and help in using the CNI facilities.

* General information is on the [http://cni.su.domains/ CNI administrative site (wordpress)]
* To schedule time on the facilities, see the [https://cni.stanford.edu/scheduler CNI resource scheduler].

'''If you are experiencing problems with the scanner or the peripherals, please consult the [[Troubleshooting|Troubleshooting]] section.'''

= Mission Statement =

Discoveries about the brain have implications for fields ranging from Business, Law, Psychology, and Education. The Stanford Center for Cognitive and Neurobiological Imaging (CNI) supports scientific investigations into the brain that make rigorous connections between neuroscience and society. Our Mission is to:

<ol>
<li> Support neuroscience discovery for enhancing society
<li> Develop and disseminate cognitive and neurobiological imaging methods
<li> Create a structured, safe, and innovative teaching environment for human neuroscience research
</ol>

= People =
Daily operations of the MRI facility are managed by Adam Kerr (akerr@stanford.edu), the Research Director, and by Laima Baltusis (laimab@stanford.edu), the Facility Manager. The MR Physics work at the CNI is led by Hua Wu (huawu@stanford.edu). Michael Perry oversees the information technology (e.g., NIMS).

The CNI operations are guided by a faculty [http://cni.stanford.edu/content/cni-team#Internal_Advisory_Board Advisory Board] that includes representatives from the School of Humanities and Sciences, School of Education, the Department of Neurology, the Department of Psychiatry, and the School of Engineering. The Board receives input from colleagues in the Law School and CCRMA.

Stanford University oversight is through the office of the [http://dor.stanford.edu/ Vice-Provost and Dean of Research].

= Facilities =

The first CNI project was construction of the MR facility in the basement of Building 420. The MR scanner was delivered on November 13th, 2010 and began running within a year.

In addition to the MRI scanner, there is a mock scanner for training, experimental testing rooms, and integrated experimental equipment (displays and EEG). (See [[Facilities and Resources]] for more details and text useful when preparing sections of NIH or other grants.)

= Data Management =

The scanner is heavily used. We train about 100 new users each year

The [[ Flywheel | Data Management ]] page contains information about how we use Flywheel to store the data collected at the CNI, and to run certain data analyses.

We have some summary statistics for the last few years gleaned from the Flywheel site that has been up since 2017.

* We have collected approximately 1700 data sets (one hour sessions at the scanner) each year
* We have run about 75,000 jobs (Flywheel Gears) per year
* We are storing 540,000 files, including
** 50,000 T1 anatomical files
** 30,000 DWI diffusion files
** 250,000 functional MR files

= Computational Resources =

At startup time (2011), the CNI received funding from [http://biox.stanford.edu/biox/neuro.html BIO-X Neuroventures] for what was then a high-powered compute server which will be used to provide computational resources to CNI users. That system evolved to use Linux containers.

In the early years we implemented a data management systems (NIMS) for storing and distributing all the data collected at the CNI. We also implemented an [[LXC | LXC Page]] system to support user computations. NIMS was retired in 2017 and the LXC system was retired in 2021.

In 2017 we installed Flywheel, which is a commercialized version of NIMS. That system continues to evolve and holds a great deal of data. It supports cloud-based computations (docker containers, which Flywheel calls Gears).

In 2023 the CNI received funding from [https://csharp.stanford.edu/ C-ShARP] to upgrade our computational facilities with advanced GPUs. These are being installed and will be heavily used for advanced reconstruction methods, particularly for quantitative methods developed by Kawin Setsompop's group.

MediaWiki notes.

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MR Scanner

2023-08-24T22:35:52Z

Wandell: /* MR Scanner (GE 750) */

When the GE OS is upgraded there are certain procedures that must be followed to get certain peripherals working normally. Those procedures are described on the [[Scanner Upgrade Procedure]] page.

= MR Scanner (UHP) =

We need Adam or Hua to fill in the general properties of this device. Slew rate, max gradient amplitude, anything else?

= MR Scanner (GE 750) =

We need Adam or Hua to fill in the general properties of this device. Slew rate, max gradient amplitude, anything else?

The CNI scanner is a [https://www.gehealthcare.com/products/goldseal---refurbished-systems/goldseal-magnetic-resonance/discovery-mr750?utm_medium=cpc&utm_source=google&utm_campaign=USC-PS-REG-AlwaysOn&utm_term=&utm_content=12518725892&npclid=Cj0KCQjw_5unBhCMARIsACZyzS22deMIMkJbh6ew8m0rnlAg9oZKQjieLUkTJngTj_7XNIPxSubEMXUaAqUmEALw_wcB&gclid=Cj0KCQjw_5unBhCMARIsACZyzS22deMIMkJbh6ew8m0rnlAg9oZKQjieLUkTJngTj_7XNIPxSubEMXUaAqUmEALw_wcB GE Discovery MR750].

To update: It's currently running ESE version 23.1 v02 (the GE operating system). To compile EPIC psd's for the scanner, we have a dedicated server with the necessary software environment installed. Just contact us for details.

Data were acquired at the Stanford Center for Cognitive and Neurobiological Imaging using a 3T General Electric MR 750 scanner with either a Nova 16- or 32-channel head coil. The Nova 16-channel is similar to the Nova 32-channel coil, but with the front half of the coil removed to allow for an unobstructed field of view. Head motion was minimized by padding around the head.

Typically, anatomical data are acquired with the 32-channel coil using a 3D Fast SPGR scan (166 sagittal slices, resolution 0.9375 × 0.9375 × 1 mm).

See the Pulse Sequence Pages for parameters of different standard CNI sequences.

= Coils =
* Standard GE bird-cage head coil
* InVivo 8-channel head array (similar to [http://www.invivocorp.com/coils/coilinfo.php?id=43 this one])
* [http://www.novamedical.com/ Nova Medical] 32-channel head coil (interior coil dimensions - 18.5 cm width, 21 cm length, 24 cm height to nose bridge, 21 cm height to forehead)
* [http://www.novamedical.com/ Nova Medical] 16-channel visual array. This is similar to the Nova 32-channel coil, but with the front half removed to allow a completely unobstructed field of view for visual studies. (interior coil dimensions - 18.5 cm width, 21 cm length, 10 cm height)

= Extras =
* Tektronix TDS2024B4 channel oscilloscope to debug pulse sequences.
* Custom foam padding for positioning subjects.

= MR Simulator =
The CNI has an [[MR Simulator]] available for pre-scan training.

= Physiological Monitoring =
In addition to the respiration and pulse oximetry integrated with the GE scanner, the CNI also has a [http://www.medrad.com/en-us/info/products/Pages/VerisMRVitalSignsMonitor.aspx MedRad Veris] for additional physiological measures, such as ECG.

MR Scanner

2023-08-24T22:35:25Z

Wandell: /* MR Scanner (GE 750) */

When the GE OS is upgraded there are certain procedures that must be followed to get certain peripherals working normally. Those procedures are described on the [[Scanner Upgrade Procedure]] page.

= MR Scanner (UHP) =

We need Adam or Hua to fill in the general properties of this device. Slew rate, max gradient amplitude, anything else?

= MR Scanner (GE 750) =

We need Adam or Hua to fill in the general properties of this device. Slew rate, max gradient amplitude, anything else?

The CNI scanner is a [https://www.gehealthcare.com/products/goldseal---refurbished-systems/goldseal-magnetic-resonance/discovery-mr750?utm_medium=cpc&utm_source=google&utm_campaign=USC-PS-REG-AlwaysOn&utm_term=&utm_content=12518725892&npclid=Cj0KCQjw_5unBhCMARIsACZyzS22deMIMkJbh6ew8m0rnlAg9oZKQjieLUkTJngTj_7XNIPxSubEMXUaAqUmEALw_wcB&gclid=Cj0KCQjw_5unBhCMARIsACZyzS22deMIMkJbh6ew8m0rnlAg9oZKQjieLUkTJngTj_7XNIPxSubEMXUaAqUmEALw_wcB GE Discovery MR750]. It's currently running ESE version 23.1 v02 (the GE operating system). To compile EPIC psd's for the scanner, we have a dedicated server with the necessary software environment installed. Just contact us for details.

Data were acquired at the Stanford Center for Cognitive and Neurobiological Imaging using a 3T General Electric MR 750 scanner with either a Nova 16- or 32-channel head coil. The Nova 16-channel is similar to the Nova 32-channel coil, but with the front half of the coil removed to allow for an unobstructed field of view. Head motion was minimized by padding around the head.

Typically, anatomical data are acquired with the 32-channel coil using a 3D Fast SPGR scan (166 sagittal slices, resolution 0.9375 × 0.9375 × 1 mm).

See the Pulse Sequence Pages for parameters of different standard CNI sequences.

= Coils =
* Standard GE bird-cage head coil
* InVivo 8-channel head array (similar to [http://www.invivocorp.com/coils/coilinfo.php?id=43 this one])
* [http://www.novamedical.com/ Nova Medical] 32-channel head coil (interior coil dimensions - 18.5 cm width, 21 cm length, 24 cm height to nose bridge, 21 cm height to forehead)
* [http://www.novamedical.com/ Nova Medical] 16-channel visual array. This is similar to the Nova 32-channel coil, but with the front half removed to allow a completely unobstructed field of view for visual studies. (interior coil dimensions - 18.5 cm width, 21 cm length, 10 cm height)

= Extras =
* Tektronix TDS2024B4 channel oscilloscope to debug pulse sequences.
* Custom foam padding for positioning subjects.

= MR Simulator =
The CNI has an [[MR Simulator]] available for pre-scan training.

= Physiological Monitoring =
In addition to the respiration and pulse oximetry integrated with the GE scanner, the CNI also has a [http://www.medrad.com/en-us/info/products/Pages/VerisMRVitalSignsMonitor.aspx MedRad Veris] for additional physiological measures, such as ECG.

MR Scanner

2023-08-24T22:31:43Z

Wandell: /* MR Scanner (UHP) */

When the GE OS is upgraded there are certain procedures that must be followed to get certain peripherals working normally. Those procedures are described on the [[Scanner Upgrade Procedure]] page.

= MR Scanner (UHP) =

We need Adam or Hua to fill in the general properties of this device. Slew rate, max gradient amplitude, anything else?

= MR Scanner (GE 750) =

The CNI scanner is a [https://www2.gehealthcare.com/portal/site/usen/menuitem.e8b305b80b84c1b4d6354a1074c84130/?vgnextoid=9760c555ff930210VgnVCM10000024dd1403RCRD&productid=2760c555ff930210VgnVCM10000024dd1403____ GE Discovery MR750]. It's currently running ESE version 23.1 v02 (the GE operating system). To compile EPIC psd's for the scanner, we have a dedicated server with the necessary software environment installed. Just contact us for details.

Data were acquired at the Stanford Center for Cognitive and Neurobiological Imaging using a 3T General Electric MR 750 scanner with either a Nova 16- or 32-channel head coil. The Nova 16-channel is similar to the Nova 32-channel coil, but with the front half of the coil removed to allow for an unobstructed field of view. Head motion was minimized by padding around the head.

Typically, anatomical data are acquired with the 32-channel coil using a 3D Fast SPGR scan (166 sagittal slices, resolution 0.9375 × 0.9375 × 1 mm).

See the Pulse Sequence Pages for parameters of different standard CNI sequences.

= Coils =
* Standard GE bird-cage head coil
* InVivo 8-channel head array (similar to [http://www.invivocorp.com/coils/coilinfo.php?id=43 this one])
* [http://www.novamedical.com/ Nova Medical] 32-channel head coil (interior coil dimensions - 18.5 cm width, 21 cm length, 24 cm height to nose bridge, 21 cm height to forehead)
* [http://www.novamedical.com/ Nova Medical] 16-channel visual array. This is similar to the Nova 32-channel coil, but with the front half removed to allow a completely unobstructed field of view for visual studies. (interior coil dimensions - 18.5 cm width, 21 cm length, 10 cm height)

= Extras =
* Tektronix TDS2024B4 channel oscilloscope to debug pulse sequences.
* Custom foam padding for positioning subjects.

= MR Simulator =
The CNI has an [[MR Simulator]] available for pre-scan training.

= Physiological Monitoring =
In addition to the respiration and pulse oximetry integrated with the GE scanner, the CNI also has a [http://www.medrad.com/en-us/info/products/Pages/VerisMRVitalSignsMonitor.aspx MedRad Veris] for additional physiological measures, such as ECG.

MR Scanner

2023-08-24T22:30:19Z

Wandell: /* MR Scanner */

When the GE OS is upgraded there are certain procedures that must be followed to get certain peripherals working normally. Those procedures are described on the [[Scanner Upgrade Procedure]] page.

= MR Scanner (UHP) =

= MR Scanner (GE 750) =

The CNI scanner is a [https://www2.gehealthcare.com/portal/site/usen/menuitem.e8b305b80b84c1b4d6354a1074c84130/?vgnextoid=9760c555ff930210VgnVCM10000024dd1403RCRD&productid=2760c555ff930210VgnVCM10000024dd1403____ GE Discovery MR750]. It's currently running ESE version 23.1 v02 (the GE operating system). To compile EPIC psd's for the scanner, we have a dedicated server with the necessary software environment installed. Just contact us for details.

Data were acquired at the Stanford Center for Cognitive and Neurobiological Imaging using a 3T General Electric MR 750 scanner with either a Nova 16- or 32-channel head coil. The Nova 16-channel is similar to the Nova 32-channel coil, but with the front half of the coil removed to allow for an unobstructed field of view. Head motion was minimized by padding around the head.

Typically, anatomical data are acquired with the 32-channel coil using a 3D Fast SPGR scan (166 sagittal slices, resolution 0.9375 × 0.9375 × 1 mm).

See the Pulse Sequence Pages for parameters of different standard CNI sequences.

= Coils =
* Standard GE bird-cage head coil
* InVivo 8-channel head array (similar to [http://www.invivocorp.com/coils/coilinfo.php?id=43 this one])
* [http://www.novamedical.com/ Nova Medical] 32-channel head coil (interior coil dimensions - 18.5 cm width, 21 cm length, 24 cm height to nose bridge, 21 cm height to forehead)
* [http://www.novamedical.com/ Nova Medical] 16-channel visual array. This is similar to the Nova 32-channel coil, but with the front half removed to allow a completely unobstructed field of view for visual studies. (interior coil dimensions - 18.5 cm width, 21 cm length, 10 cm height)

= Extras =
* Tektronix TDS2024B4 channel oscilloscope to debug pulse sequences.
* Custom foam padding for positioning subjects.

= MR Simulator =
The CNI has an [[MR Simulator]] available for pre-scan training.

= Physiological Monitoring =
In addition to the respiration and pulse oximetry integrated with the GE scanner, the CNI also has a [http://www.medrad.com/en-us/info/products/Pages/VerisMRVitalSignsMonitor.aspx MedRad Veris] for additional physiological measures, such as ECG.

QA

2023-08-23T17:38:58Z

Wandell: /* Finding the QA report */

Quality Assurance (QA) reports are generated for all functional MR data acquired at the CNI. These reports should appear in the "datasets" column in the NIMS browser page within an hour after the scan finishes.

=Finding the QA report=

[[File:NIMS_QA.png|thumb|QA reports appear in the datasets column of NIMS.]]

The QA reports take anywhere from a few minutes to an hour to compute, depending on the scan resolution and duration. To view the report, double-click the QA dataset and a pop-over will open showing the motion and spike plots, as well as some global QA values.

=What's in the QA report=
The QA code is still under active development, so we will likely be adding more metrics to the report in the near future. Right now, the report will give you the QA version number (the version of the QA script that was used to generate the report), as well as the following information:

==Temporal SNR==
This is the median tSNR of all brain voxels (as defined by the [http://nipy.org/dipy/examples_built/brain_extraction_dwi.html median_otsu algorithm]). The tSNR is computed after the data have been motion-corrected (details below) and the slow-drift has been removed using a 3rd-order polynomial. Note that tSNR is very sensitive to voxel size, with bigger voxels generally producing higher tSNR. The acceleration factor will also affect tSNR (both inplane acceleration and slice multiplex acceleration), with more acceleration leading to lower tSNR. It is also somewhat sensitive to the TR (with longer TRs producing slightly higher tSNR). So it's a useful metric for comparison across scans with the same voxel size, TR and acceleration, but not useful for comparing across scans with different parameters.

==Spike count==
The number of "spikes" detected. The spikes are detected by a simple threshold of the time series z-score plot (details below). The threshold is currently set to 6. This is somewhat arbitrary (and thus why we show the full plots), but we've found that spikes of this magnitude are generally indicative of a problem, such as excessive subject motion or scan hardware issues.

==Subject Motion==
Subject motion is estimated using [http://nipy.org/nipy/stable/api/generated/nipy.algorithms.registration.groupwise_registration.html FmriRealign4d] (without slice-time correction). A plot of the mean displacement, both absolute and relative, is presented. Absolute displacement is the mean displacement relative to the middle frame. Relative displacement is the mean displacement relative to the previous frame. (Mean displacement is computed using [http://www.fmrib.ox.ac.uk/analysis/techrep/tr99mj1/tr99mj1/index.html Mark Jenkinson's algorithm].)

==Timeseries z-score==
A plot of the mean signal (in z-score units) from each slice of the brain. This last plot is useful for detecting spikes in your data, and for determining if the spikes are caused by your subject (e.g., motion) or by a possible problem with the scanner (e.g., white-pixel noise). When a subject moves, even a little, you will often see spikes that span several or all slices. But a white-pixel noise problem typically only affects one slice at a time. Note that the first few time points are ignored for the spike plot.

For this plot (as well as the motion plot) you can get the exact value of any datapoint by hovering your mouse over one of the curves. Also note that the frame numbers start at zero rather than one. Some examples of QA reports are shown below.

=Artifacts that you may find=
==Subject Motion==
This is by far the dominant cause of spike-like artifacts in most datasets. Even a small relative head displacement can lead to a signal drop and/or increase. Motion usually affects many slices.

==White-pixel noise==
Spike noise is a common and insidious problem with MR, often caused by a loose screw on the scanner or some small stay piece of metal in the scan room that accumulates energy and then discharges randomly, creating broad-band RF noise at some point during the signal read-out. When this happens, one spot in k-space will have an abnormally high intensity and show up as a "white pixel". In the image domain, it will often manifest as an abrupt signal drop in one slice at one time-point (a 'spike' in the time series). The problem is particularly acute for EPI scans because of all the gradient blipping during the read-out.

If you see a lot of spike-noise in your data (either motion-induced or from a white-pixel noise problem), there are various tools available to specifically clean up spike-noise artifacts (like AFNI's 3dDespike). FSL's Melodic can also be used to remove artifacts in general (see [http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/MELODIC#fsl_regfilt_command-line_program fsl_regfit]). You can also try adding the spikes to your GLM as nuisance regressors. If you see a couple of spikes here and there, you might be able to safely ignore them, as they will not have a big effect on most GLM-type analyses. But even one or two spikes can affect certain kinds of correlation analyses, so for that you will have to be more careful.

=Examples of QA reports=
A good subject and well-behaved scanner:
[[Image: qa_good.png| 650px]]

A bad subject and well-behaved scanner:
[[Image: qa_motion.png| 650px]]

A good subject and spikey scanner:
[[Image: qa_spikes.png| 650px]]

=Technical Details=
The QA report generation code is part of the NIMS codebase and is [https://github.com/cni/nims/blob/master/nimsproc/qa_report.py available on Github].

Flywheel

2023-08-23T17:38:15Z

Wandell: /* Default Gear Rules */

The CNI uses [//flywheel.io Flywheel] for data and computational management. Data from the scanner are automatically uploaded to the Flywheel database. The Flywheel system is on the Google Cloud Platform. Users download data either using a web-browser or another of the [//docs.flywheel.io/hc/en-us/articles/360008410994-Getting-Started-Downloading-Data methods provided by Flywheel] (e.g., command-line-interface or software-development-kit).

At the CNI, as data come into the Flywheel they are automatically processed according to rules determined by the CNI staff. For example, upon ingest PHI data are removed, DICOM and raw PFile data are converted to NIfTI format, and metadata about the scan parameters are read and inserted into the database. Some labs may configure initial processing of the data for individual projects differently. For help with customization groups can contact Flywheel directly or ask Michael Perry (see below).

This page describes Flywheel features that are specific to the CNI. You can learn more about Flywheel using the links below:

* A 5 minute video overview of Flywheel is available [//youtu.be/JUoSejTxXUw on YouTube]
* Manual pages and basic material about the system are maintained by Flywheel [//docs.flywheel.io/hc/en-us at this site].
* Links to videos and webinars are on the [//docs.flywheel.io/hc/en-us Flywheel Docs site]

'''Log in to CNI's Flywheel site here: [//cni.flywheel.io cni.flywheel.io]'''

= Authentication =

Authentication to Flywheel at the CNI requires a valid (full-account) SUNetID.

New users should ask the CNI staff to create an account.

= Data upload =
The CNI scanner produces DICOM, P-File, and Physio data. The sequence you are using along with your scan parameters will determine which of those data are generated. Regardless of the type, those data will make their way into Flywheel automatically via one of the Connectors, described next.

== Connectors ==
At the CNI data are uploaded to Flywheel automatically via Connectors (aka Reapers). CNI has multiple Flywheel Connectors running, one for each of the types of data that must make their way into Flywheel.

The connectors running at CNI are:
* DICOM connector - communicates directly with the scanner's DICOM server to "discover" new data, package those data, and upload those data to Flywheel
* P-File connector - packages and transfers raw P-File data from the console to Flywheel.
* Physio connector - packages and transfers physio data from the console to Flywheel. This connector attempts to match the physio data to the correct series/acquisition within Flywheel, however if the scan is ended early, or if the prescribed duration is off from the actual duration, the physio data may not be transferred or it may end up in the wrong series. Please be sure to check your physio data and report any issues to CNI staff right away.

== Getting your data to the right place ==
The Flywheel Connectors determine where to place data in the hierarchy using information entered into the MR console by the user and obtained from the DICOM or PFile data.

We refer to the information provided by the user to help Flywheel understand where the data belong as the "Sort String". It is important to understand how to provide this information correctly so that your data find their way to your project without delay.

If a mistake is made here, worry not, those data will still be uploaded to Flywheel, however they will go to a group and project which only CNI staff have access to. If you believe this has happened to you, please feel free to reach out to CNI staff and we will help get your data where it belongs.

=== Flywheel Sort String (Good) ===

To make sure the data you collect is sent to the correct Flywheel project for your lab, you must enter a "Flywheel sort string" on the console.

Enter this string into the '''Patient ID''' field on the scanner console.

The string format is:

<subject_label>@<group>/<project>

=== Flywheel Sort String (Bad) ===
If you do not enter the sort string correctly, the data will still be sent to Flywheel, but it will not be routed to the correct project. Instead, it will be assigned to the "unknown" group or "Unsorted" project, depending on what Flywheel can determine.

* If the data are sent to the unknown group, you must ask the Site Admins to retrieve your data. (Michael, Laima).
* If the data are sent to the "Unsorted" project (case sensitive), you can find it and move it yourself.

Thus, for a given piece of data coming in through a Connector:

No Group, No Project --> group_id = "unknown", project = "Unsorted"
No Group, Project --> group_id = "unknown", project = <Project>
Group, No Project --> group_id = <Group>, project = "Unsorted"

=== Session Labels and Tags ===
In some cases, users want to set the name of the session rather than have Flywheel use the default name (which is the exam number).

You can control the session name/label by placing information in the ''AdditionalPatientHistory'' section on the console, like so:

To set the '''session label'' using the following format (without the "<>"):

label_<your_desired_session_label>

You may also '''tag a session''' to make it easier to find later. You can '''set a session tag''' by inserting this string in the ''AdditionalPatientHistory'' section.

tag_<tag_name>

= Protected Health Information =

Protected Health Information (PHI) is considered High Risk Data according to the Stanford Data Classification Guidelines. PHI is defined as any information that can be used to identify an individual and may relate to their past, present, or future health. By law, this information must be encrypted by law and must be (a) stored in encrypted form, and (b) transmitted only through secure means.

Anonymized research data for publication can be shared without harm. See [https://med.stanford.edu/irt/security/stanfordinfo/hipaa.html this Stanford site]. Although CNI participants are not medical patients, we treat human subject data with the same PHI status as if they were patients. Specifically, data uploaded to Flywheel strips information from these fields:

* Patient ID field
* Date of Birth
* Medical Record Number
* Subject Name (first and last)

For PIs, please note we do look for PHI information and over the years we have found that users sometimes insert names, phone numbers and other information that might identify the subject. When we find such information, we delete it. The most likely places that RAs and others insert this information are these fields:

* Subject code (part of Patient ID)
* Exam description
* Series description

Thus, we ask all CNI users: '''Never use any PHI identifiers when entering data into the scanner!'''

It is permissible to include the subject's weight and age up to some precision.

At present, to describe the PHI methods in your publications, you might find this summary paragraph helpful.

''Data at Stanford's Center for Cognitive and Neurobiological Imaging are securely transferred from the MR scanner directly to a data management system (Flywheel.io) that is running within a Google platform space that is approved for research data. Prior to transfer the data file headers are stripped of fields that may contain subject information (patient id, DOB, MRN, name fields). These procedures meet the Stanford standard for anonymized research data for publication and can be shared without harm. See: [https://med.stanford.edu/irt/security/stanfordinfo/hipaa.html this Stanford site].

'''N.B.''' Flywheel is planning to provide a substantial enhancement of the anonymization protocol so that each lab will have the ability to control the details of its own anonymization protocol. We will send a note describing the capabilities when the feature is released - which is expected first quarter 2021.

= Data Processing =

Once data are uploaded to Flywheel those data are automatically processed according to a given Project's "[//docs.flywheel.io/hc/en-us/articles/360008553133-Project-Gear-Rules Gear Rules]". The Rules define which Gear will be run on a given piece of data when it lands in Flywheel. These rules do everything from metadata extraction from DICOM headers to execution of QA algorithms.

== Gear Rules (Default) ==

At CNI we have defined a default set of rules that are applied to every new project. Each rule defines the logic that must be satisfied in order for a given gear to be run on a data file.

The image below shows the default rules that every new project is provided with.

[[File:GearRules.png|600px|thumb|center|Gear Rule Template]]

=== A special note on DICOM to NIfTI Conversion (dcm2niix & dcm-convert) ===

Historically at CNI we have provided a tool that was developed in-house for DICOM to NIfTI conversion (dcm-convert). Recently users have expressed interest in having a very widely used and popular tool, dcm2niix, serve as the default tool to perform DICOM to NIfTI conversion in Flywheel. We are happy to say that Flywheel does provide a dcm2niix Gear and we have incorporated this into our default rule set. As of today the default is still dcm-convert, however for projects created recently you will see this rule available and in a disabled state. You can easily enable this rule, however it should be noted that if you do enable this rule you need to disable the existing dcm-convert rule so that you don't introduce a race condition which would result in a situation where you would not be able to predict which tool would be used to generate the NIfTI data.

=== Re-running DICOM to NIfTI conversion across a project ===

There are special considerations to be made if you desire to re-run DICOM to NIfTI conversion across an entire project, namely you need to ignore DICOM data that was generated by any of the MUX sequences, as those data are aliased and running either of the DICOM to NIfTI tools on those data will result in aliased NIfTI data. Special care is taken within the Gear rules to avoid this situation by specifically ignoring data that were collected with a mux sequence.

The best idea here is to coordinate with CNI staff (e.g., Michael Perry) prior to doing this.

= Downloading Data =
There are several ways to download data from Flywheel, including via the [//flywheelio.zendesk.com/hc/en-us/articles/360008622994-Downloading-sessions-or-acquisitions-from-the-Web-UI WEB UI], the [//flywheelio.zendesk.com/hc/en-us/sections/360001596834-Command-Line-Interface command line interface (CLI)], and the Flywheel SDK (which is available for both [//flywheel-io.github.io/core/branches/master/python/getting_started.html Python] and [//flywheel-io.github.io/core/branches/master/matlab/getting_started.html MATLAB]). The links below can help you get started with the various methods of export:

=== UI Downloads ===
* [//flywheelio.zendesk.com/hc/en-us/articles/360009256973-Downloading-a-file Download individual Files]
* [//flywheelio.zendesk.com/hc/en-us/articles/360008622994-Downloading-sessions-or-acquisitions-from-the-Web-UI Download session or acquisition containers]
* [//flywheelio.zendesk.com/hc/en-us/articles/360008629794-Downloading-an-entire-project Download a Project]

=== Flywheel SDK ===
* [//flywheel-io.gitlab.io/product/backend/sdk/branches/master/matlab/index.html MATLAB]
* [//flywheel-io.gitlab.io/product/backend/sdk/branches/master/python/index.html Python]
* [//gitlab.com/flywheel-io/public/flywheel-tutorials Support materials SDK examples (Jupyter notebooks)]

=== Flywheel CLI ===
* [//docs.flywheel.io/hc/en-us/search?utf8=%E2%9C%93&query=CLI Flywheel CLI Documentation]

=== CLI: Tips and Best Practices for CNI Users ===

This section focuses on a few tips for using the CLI to download your data. For a complete overview of the Flywheel CLI, including how to get started, please look through the [//docs.flywheel.io/hc/en-us/search?utf8=%E2%9C%93&query=CLI Flywheel CLI Documentation].

''Tip:'' ''' Download only the files you need'''
When downloading data from Flywheel using the CLI you can greatly speed up your downloads by excluding data types which are not needed for your analysis.

''Example: '''''Exclude pfile and DICOM data from a container download''': Most users do not need to download the raw scanner files (PFILES) or raw DICOM data. You can exclude certain data types from your downloads by using the `-e` flag with your CLI download, like so:
fw download "cni/testproject/subject1/session1" -e pfile -e dicom

This tells the CLI to exclude any pfile and dicom files in the container. Note that you can use consecutive -e flags to exclude multiple data types.

''Example:'' '''Download only NIfTI, BVEC, and BVAL files''': 
Most users are only interested in the data that will be input to their analysis pipelines. This is most often limited to three data types (nifti, bvec, and bval). You can use the following command with multiple include flags (`-i`) to accomplish exactly that:
fw download "cni/testproject/subject1/session1" -i nifti -i bvec -i bval

This will generate an archive (.tar) file containing the requested hierarchy with only those files you explicitly need.

''Example:'' '''Using quotes'''
Often times your source-path (that is the ''group/project/subject/session'' string the describes the location of your data in Flywheel) will have one or more spaces or special characters in it. To properly address that location using the CLI it's important to use quotes around the source path, like so:
fw download "cni/testproject/subject1/session1"

''Example'' ''Download a single file with the CLI''
So you have navigated to a container and your only desire is to download a single file from that container, the best way to do that is using the CLI with the 'files' spec filter.

''Example:'' '''Download a single NIfTI file from an acquisition container:'''
fw download "test/Unsorted/s001/18591/T1w 1mm/files/18591_13_1.nii.gz"

''The important bit here is the inclusion of "files" prior to the file name.''

= Using Sherlock and other Computers =
We suggest that you use the Flywheel Command Line Interface (CLI) to transfer data to other compute resources, like Sherlock.

To download and install the CLI on Sherlock we use the `wget` tool, then `unzip` to extract the CLI resource package, and finally modify our `.bashrc` file to add the fw binary as an alias in our environment.

'''Step 1:''' Get the URL for the CLI package, which can be found on the "Profile" page within the Flywheel interface. To grab the URL, find the CLI section on the Profile page, right-click the Linux CLI Download link, and choose "Copy Link Address" (or similar). Once you have the download link address move to the next step.

'''Step 2: ''' Log in to Sherlock and run the `wget` command, using the URL from ''Step 1'' to download the CLI package.
mkdir -p flywheel/cli
cd flywheel/cli
wget //storage.googleapis.com/flywheel-dist/cli/<version>/fw-linux_amd64.zip

'''Step 3:''' Unpack the CLI archive and cleanup the downloaded package.
unzip fw-linux_amd64.zip
mv linux_amd64/fw .
rmdir linux_amd64
rm -f fw-linux_amd64.zip

'''Step 4:''' Modify your `.bashrc` file to add the fw CLI command to your environment, and source it to make the alias active. ''Note that this only needs to be done once.''
echo -e "alias fw='$HOME/flywheel/cli/fw'" >> $HOME/.bashrc
source $HOME/.bashrc

'''Step 5:''' Once the above steps are complete, you should be able to log in using the CLI and use it as described in the official documentation: //flywheelio.zendesk.com/hc/en-us/sections/360001596834-Command-Line-Interface. The best way to do this is navigate to your [//cni.flywheel.io/#/profile profile page] in Flywheel, make sure that you have generated an API Key, and use the login command text that is provided for you there.

fw login <your API key>

= Data Migration from NIMS =
Before there was Flywheel, there was NIMS. Data have been preserved in NIMS and they can be migrated to Flywheel on an as-needed basis. Please inquire with Michael Perry for more information.

= Support =

Michael can help with most CNI Flywheel issues. If support is needed for Flywheel issues not related to the CNI, please email their help line: support@flywheel.io.

MR Simulator

2023-08-23T17:36:39Z

Wandell: /* General */

==General==

[[File:MR_simulator.jpg|thumb|MR simulator.]]
[[File:MR_simulator_display.jpg|thumb|MR simulator display.]]

The CNI has a [http://www.pstnet.com/hardware.cfm?ID=92 Psychology Software Tools MR simulator] available for pre-scan training. The MR simulator can be used to familiarize subjects with the scanning environment, and it is especially useful for subjects that need training in order to prevent excessive movement during scanning, such as children. 

===Location & Scheduling===
The mock scanner is located in room 062 of the CNI suite in the basement of Building 420l. Use the [https://www.stanford.edu/group/cni/cgi-bin/calendar/ CNI Scheduler] to reserve time on it, just as you do for the MR scanner and testing room.

==Features==
The MRI Simulator includes:
<ul>
<li> ~60cm circular bore with cooling fans and lights.
<li> Speakers for scanner noise production.
<li> Movable subject table that can be operated from the control panel on the bore or by using the participant remote control.
</ul>
Accessories:
<ul>
<li> Mock head coil with rear facing mirror
<li> 30 inch flat panel LCD display, similar to the scanner display
<li> [[Media:FlockOfBirdsManual.pdf|Flock of Birds device]] for tracking head motion.
<li> Right and left hand button boxes with five buttons per hand.
<li> Massage Pad - To simulate the vibrations in diffusion sequences, particularly in children's studies, we now have massage pad. The massage pad measures 12 inches by 12 inches. To use the massage pad correctly, place the pad on the simulator bed and position the pad to be right below the shoulder blades of the subject. There are two heat and two massage levels on the Slide Control Box. Setting the massage level on LO simulates the diffusion sequence quite well. It is not necessary to use any heat settings. When you are finished using the pad, turn the controller off and unplug the pad from the wall socket. For now the pad is stored on the window ledge by the simulator bed.
</ul>
Software:
<ul>
<li> [http://www.pstnet.com/software.cfm?ID=95 SimEffects] software to simulate ambient and active scanner sounds.
<li> [http://www.pstnet.com/software.cfm?ID=96 MoTrak] tracking system that provides linear feedback of X,Y,Z movement and rotational feedback on X,Y,Z axis (Pitch, Roll, Yaw coordinate) based on user-defined thresholds.
<li> [http://www.pstnet.com/eprime.cfm E-Prime 2.0] experiment development and presentation software.
</ul>

==Procedure==
<ol>
<li> Make sure that the simulator and Flock of Birds device are both on. (Flock of Birds should be set to "Fly").
<li> Set up the bed with a clean sheet and pillow case from the cabinets.
<li> Place the head band with motion sensor on the subject along with the headphones, which are not yet connected to the computer.
* Make sure that the subject is comfortable, and send them into the bore of the simulator. You can also give them the remote control, which will give them control over moving the bed.
* Connect the headphone jack to the '''green''' plug on the small computer box.
<li> Open MoTrak. Once the subject is ready to stay still, reset their head position so that the cross hairs are in the center of the green circle. Begin the trial (see below).
*[[Image: MockScanner1.jpg| 650px]]
<li> Start the practice movie by going to '''Tools->Options'''. Click on the tab labeled '''"General"''' and load the movie file under '''"Movie Settings."''' You can also define the threshold for motion detection in this window, as well as load a sound file to play whenever the subject moves beyond the threshold.
*[[Image: MockScanner2.jpg| 550px]]
</ol>
===Playing Movies on MoTrak===
MoTrak will play any movie file that can be opened with Windows Media Player. Windows Media Player sometimes needs additional codecs to be installed in order to play certain movie extensions (such as .avi). You can find the additional codecs to download [http://www.codecguide.com/download_k-lite_codec_pack_mega.htm here.] 
 In order to play a movie, you should first go "Tools-> Options in the MoTrak menu. Under the "General" tab, you will find "Movie Settings". Click "Browse" to find the movie file on your computer. You can then set the desired circle for motion training. (i.e. the movie will pause when the subject's crosshairs move outside of the Middle Circle.)

MR Protocols

2023-08-23T17:35:59Z

Wandell: /* Get a PDF of all protocol parameters */

This page offers advice about how to set up your scan protocols and save the information. The wiki pages take you through the template protocols we think are most widely used. These protocols can be found on the the scanner console, saved under “CNI/head” within the protocol pool.

Screenshots to remind you about how to set specific MRI protocols can be found on the page [[Setting up protocols page | Setting up protocols]]

= General =

== Setting up an MR scan protocol ==
A basic MR scan session usually starts with the following scans:
* '''Localizer''' - a 3-plane localizer or 'scout' scan meant to find the subject's head. It is also be used for prescription for the subsequent scans. Doing some sort of localizer is necessary, and the '3planeloc SSFSE' (single shot fast spin echo) is the standard work-horse used by most CNI users.

* '''Anatomical''' - usually a 3D T1-weighted scan at 0.9mm or 1mm isotropic resolution. It is essential for image alignment and anatomical analysis. More choices of anatomical scans are listed in the Anatomical imaging section.

* '''ASSET calibration''' - a calibration scan for parallel imaging. It should be run before any scans that will use ASSET, such as GE's conventional fMRI and diffusion scans.

* '''Higher-order shim''' - measures the magnetic field inhomogeneity and corrects it with polynomial gradients up to 2nd order. It should be run after ASSET and before fieldmap, fMRI or diffusion scans.

* '''Field map''' - measures the magnetic field inhomogeneity that cannot be corrected by the shim and saves the inhomogeneity in a field map. It should be run immediately before or after the fMRI scan.

At this point you will want to add a number of '''functional''' scans, '''diffusion''' scans or other type of scans based on your experiment. In the [[#MRI Protocol Templates | next section]] we describe templates for different categories of MRI protocols. The protocol templates are organized by category. One set is based on conventional multislice (2D) or 3D methods, a second set is based on the new simultaneous multislice (SMS) protocols (also called mux or multiband), and a third set are some special methods (spectroscopy and qMRI).

You can get help in customizing the parameters from the CNI staff (ask Hua, Adam, or Laima).

== Saving your protocol parameters ==
=== Save screen-shots ===
At the GE console, you can save screen shots of the GE interface to show the main parameters that you have set in a protocol. Just get to the screen that you want to save, then press the 'Prnt Scrn' button on the keyboard. A little dialog will show up. You can choose to print, which will print on paper to the Laser printer in the control room. However, we strongly suggest that you save some trees and the toxic ink chemicals by saving a digital copy instead. To do this, type ina reasonable name in the filename field (default is 'screen') and hit the 'PNG" button. A PNG image will then magically appear in the 'screensaves' folder on the linux machine next to the console (cnirt). From there, you can email the images to yourself. Or, even better, create your own personal wiki page here that describes your protocol (just log in with your SUNet ID) and put the images in there. Then, you will always have them available when needed! THis is also a great way to share protocol information with your colleagues.
=== Get a PDF of all protocol parameters ===

You can get a complete PDF of all your protocol info with a few clicks of the mouse. It's not quite as easy as a screensave, so we outline the procedure here. Note - There is a change on figure 4 - The pdf file will now appear with some viewing options at the top of the pdf file. By clicking on the 4th option from the right (a square with three parallel lines) the drop down menu will display a "save a copy" option which will result in the pdf being saved in the screensaves folder on the Linux machine (voxel2) next to the scanner.

<gallery perrow=5>
Image:Export_protocol_button.png|Click the "Protocol Exchange" button under the Image Management tab.
Image:ExportMode.png|Select "Export Mode" and click OK in the dialog that comes up.
Image:ProtocolSelection.png|Find your protocol in the next dialog, drag it to the "Protocol Selection" panel, and make sure it is selected. Then press the "preview" button.
Image:SavePdf.png|You'll then see the PDF of your protocol. Right-click anywhere within the pdf and select "Save as..." from the drop-down menu.
Image:SaveAs.png|Type the path and filename. Be sure that the path is /usr/g/mrraw/screensaves/ so it'll magically appear in the "screensaves" directory on the linux box.
</gallery>

== MRI protocol templates ==
The CNI has stored example protocols for anatomical, fMRI, diffusion, spectroscopy and quantitative MR scans (named as "CNI Examples", stored under "CNI / Head"). Depending on the user's needs, there are several ways to run a scan session. The stored protocols are meant to be used as a 'menu' from which you select the sequence that you want, based on your needs. While there are many variations stored there, here we just highlight a couple of the most common versions. A detailed list of all parameters for all scans can be found in the PDF files for each protocol. Some suggested ways of selecting from and set up these scans for your own scan session are described below.

== Moving protocols from CNI to Lucas ==
If you plan to transfer scan protocols from the CNI to Lucas Center, please contact Hua and follow the steps below:

* Let CNI staff know the (a) name of the protocol(s) to transfer and (b) which Lucas scanner. It would be useful if you could include a list of scans in your protocol too. We will help transfer the protocol files over to Lucas.

* If your protocol contains pulse sequences provided by researchers outside CNI, then please let them know about the transfer so that they can prepare the sequences for you at Lucas. For example, if you run any spectroscopy sequences, then please let [mailto:mgu@stanford.edu Dr Meng Gu] know about the transfer plan.

* Follow up with Lucas staff about setting up peripheral devices, e.g. response box, scanner trigger, visual display, physio recording, etc. The visual display at both Lucas scanners uses a projector and a screen mounted on the head coil. Another thing to keep in mind is that '''Lucas scanners do not send out scan triggers in the same way as the CNI scanner does''', so it’s preferred to let the stimulation program trigger the scanner by writing out a byte through the usb-serial port. Lucas also provides their version of the functional sequences that send out triggers to the computer, if you prefer to let the scanner trigger your stimulation. For more details please seek advice from the Lucas staff.

* The Lucas center has its own instance of Flywheel [http://lucascenter.flywheel.io lucascenter.flywheel.io]. '''Prior to scanning at Lucas, please be sure to coordinate with Tom Brosnan, or [mailto:lmperry@stanford.edu Michael Perry], to have your group’s accounts and projects configured.''' Michael can help you make sure your projects have the correct gear rules configured to process your data, which is an important consideration to maintain consistency across the two sites. As a good first approximation you can map existing project gear rules at CNI to your new projects at Lucas. Our goal is to make the same gears available at Lucas as are available at CNI. This is a work in progress.

= Conventional imaging =

== Anatomical imaging ==

===T1 weighted ===
All the suggested T1-weighted scans use GE's "BRAVO" sequence. It is an IR-prep, fast SPGR sequence with parameters tuned to optimize brain tissue contrast. Unless you have good reason to do so, you probably don't want to play with any parameters other than slice orientation, voxel size, and bandwidth. And for those, most users just pick one of the suggested configurations:

* T1w 1mm ax (3:22): T1-weighted, 1mm^3 voxel size, 3D Bravo, axial slices. A single scan gives good signal-to-noise quality. If you just want a basic, fast, axial T1 weighted scan, go with this.

* T1w 1mm sag (3:43): T1-weighted, 1mm^3 voxel size, 3D Bravo, sagittal slices. A single scan gives good signal-to-noise quality. This is similar to the 1mm axial, but with sagittal slice orientation. Compared to axial, this orientation is slightly less efficient because you need a full phase FOV, but sagittal slices usually do better than axial with artifacts from large blood vessels (e.g., carotid artifacts land in non-brain regions rather than the temporal lobes) and with fat-shift artifacts, because the shifted scalp signal usually misses the brain while with axial it can sometimes overlap the occipital lobe gray matter, causing tissue segmentation problems.

* T1w 0.9mm sag (4:49) T1-weighted, 0.9mm^3 voxel size, 3D Bravo, sagittal slices. A single scan gives good signal-to-noise quality. As with the above scan, but a little higher spatial resolution. If you can afford to take 5 minutes for a T1 scan, this one is a great choice. This is our work-horse. Note: to get true .9 isotropic voxels, enter '23.04' for the FOV. The scanner GUI will display this as '23.0', but will store and use the full-precision that you type!

* T1w 0.8mm sag (4:57 X 2): T1-weighted, 0.8mm^3 voxels, 3D Bravo, sagittal slices. Two scans (averaged in post-processing) are advised for good signal-to-noise quality. If you want to get better resolution, do two of these.

* T1w 0.7mm sag (5:41 X 3): T1-weighted, 0.7mm^3 voxels, 3D Bravo, sagittal slices. 3-4 scans (averaged in post-processing) are advised for good signal-to-noise quality. If you can afford the time, and make use of high-quality anatomical images, this is the sequence to use.

===T2 weighted ===

* 3D T2 (5:03): T2-weighted, 0.8mm^3 voxel size, 3D Cube T2, sagittal slices. A single scan gives good signal-to-noise quality.

* 3D T2 FLAIR (6:17): T2-weighted, 1 mm^3 voxel size, 3D Cube T2, sagittal slices. An additional inversion-recovery pulse is applied in the 3D T2 CUBE sequence to suppress the CSF signal in the T2 weighted images.

* 3D T2 PROMO (5:42): T2-weighted, 0.8mm^3 voxel size, 3D Cube T2, sagittal slices. PROMO (PROspective MOtion correction) adjusts the scan parameters during the scan to prospectively correct for patient motion and thus reducing the image artifacts.

=== T2w/PDw ===

2D T2w/PDw FSE (4:25): A standard 2D T2-weighted scan. You also get a bonus proton-density scan. Note that the two datasets will be interleaved; you'll want to separate them in post-processing.

=== Technical Notes ===

In general, using a higher pixel bandwidth can help reduce chemical shift effects that push the fat signal from the scalp into the brain.

The 3D Geometry Correction option uses a 3D correction for gradient non-linearity, over the 2D correction that is performed when the option is not checked. By including the slice direction in the correction, the resulting images are closer to geometric truth. The model used to represent gradient nonlinearity is the same as the 2D correction ("gradwarp") and it uses the same cubic interpolation function as the 2D correction.

== Functional imaging ==

=== BOLD EPI (Full brain) ===

BOLD EPI 2.9mm 2sec: gradient echo EPI, 2.9mm^3 voxel size, 45 slices (~13 cm), TR/TE 2s/30ms, 2x in-plane acceleration. This sequence gives you full coverage of the brain. The 2x in-plane acceleration reduces the EPI distortion. This is a standard sequence for fMRI scans.

=== BOLD EPI (High resolution, partial brain) ===

BOLD EPI 1.8mm 2sec (partial coverage): gradient echo EPI, 1.8mm^3 voxel size, 25 slices (~4.5 cm), TR/TE 2s/30ms, 2x in-plane acceleration. This sequence gives you partial coverage of the brain at a higher resolution. It is a good choice if you are interested in a particular part of the brain.

===Technical Notes ===
If your protocol has multiple long-duration functional scans, you may consider doing additional field map measurements between the functional scans to access any field drift. See the [[Improving EPI]] page for information on fixing some common image problems with EPI images.

There is a field map template protocol within the CNI/Head/CNI Example fMRI: Spiral fieldmap (0:27): 2D spiral, 1.75 x 1.75 x 2mm^3 voxel size. Copy the slice coverage of the BOLD scan. This scan generates a B0 field map in Hz (along with a magnitude image).

The optimal echo time (TE) for BOLD fMRI at 3T is 30ms, where the difference in T2* decay of oxy/deoxy hemoglobin gives the highest contrast in the measured MR signals between the oxy/deoxy-genated blood.

When doing BOLD fMRI, we prefer reading out the data at the optimal echo time quickly. When the TR (the repetition time) is shorter than the longitudinal relaxation time (T1) of the tissue of interest, we want to adjust the flip angle to optimize the SNR by maximizing the magnetization recovery along the z-axis (T1) during successive excitations of the same tissue. The optimal flip-angle is found by the Ernst equation:

''flip-angle = acos(exp(-TR/T1)) ''

[Note: this formula will return values in radians, which then need to be converted to degrees. Alternatively, if using Matlab, use the acosd function which will return degrees.]

* A typical T1 value for gray matter is (3T): 1.33 seconds (Kruger, et al, 2001). (At 1.5T, it is closer to 0.9 seconds.)

*Or use the following values for typical TRs at 3T:

{|style="border-collapse: collapse; border-width: 1px; border-style: solid; border-color: #000"
|-
|style="border-style: solid; border-width: 1px; text-align: right"| '''TR (s):'''
|style="border-style: solid; border-width: 1px; text-align: center"| 1
|style="border-style: solid; border-width: 1px; text-align: center"| 1.5
|style="border-style: solid; border-width: 1px; text-align: center"| 2
|style="border-style: solid; border-width: 1px; text-align: center"| 2.5
|style="border-style: solid; border-width: 1px; text-align: center"| 3
|style="border-style: solid; border-width: 1px; text-align: center"| 3.5
|style="border-style: solid; border-width: 1px; text-align: center"| 4
|style="border-style: solid; border-width: 1px; text-align: center"| 5
|style="border-style: solid; border-width: 1px; text-align: center"| 6
|style="border-style: solid; border-width: 1px; text-align: center"| 7
|-
|style="border-style: solid; border-width: 1px; text-align: right"| '''flip (deg):'''
|style="border-style: solid; border-width: 1px; text-align: center"| 61.9
|style="border-style: solid; border-width: 1px; text-align: center"| 71.1
|style="border-style: solid; border-width: 1px; text-align: center"| 77.2
|style="border-style: solid; border-width: 1px; text-align: center"| 81.2
|style="border-style: solid; border-width: 1px; text-align: center"| 84.0
|style="border-style: solid; border-width: 1px; text-align: center"| 85.9
|style="border-style: solid; border-width: 1px; text-align: center"| 87.2
|style="border-style: solid; border-width: 1px; text-align: center"| 88.7
|style="border-style: solid; border-width: 1px; text-align: center"| 89.4
|style="border-style: solid; border-width: 1px; text-align: center"| 89.7
|}

== Diffusion weighted imaging ==

=== DTI ===
* DTI 2mm b1000 60dir (9:21): 2mm^2 voxel size, 60-70 axial slices, b-value 1000, 60 diffusion directions.

=== HARDI ===
* DTI 2mm b2500 96dir (16:58): 2mm^2 voxel size, 60-70 axial slices, b-value 2500, 96 diffusion directions.
If you are pressed for time, you can drop the b-value to 2000 and/or reduce the number of directions to 80:
* DTI 2mm b2000 96dir (16:26): 2mm^2 voxel size, 60-70 axial slices, b-value 2000, 96 diffusion directions.
* DTI 2mm b2000 80dir (12:37): 2mm^2 voxel size, 60-70 axial slices, b-value 2000, 80 diffusion directions.

=== Technical Notes ===
Diffusion imaging at the CNI uses a modified version of GE's DW-EPI sequence. The sequence was modified so that for dual-spin-echo scans, the polarity of the second 180 degree pulse is inverted relative to the first 180. This causes off-resonance signal from fat to get defocused and thus help reduce fat-shift artifacts (See Sarlls et. al. Robust fat suppression at 3T in
high-resolution diffusion-weighted single-shot echo-planar imaging of human brain. MRM 2011, PubMed PMID: [http://www.ncbi.nlm.nih.gov/pubmed/21604298 21604298] and Reese et. al. Reduction of eddy-current-induced distortion in diffusion MRI using a twice-refocused spin echo. MRM 2003, PubMed PMID: [http://www.ncbi.nlm.nih.gov/pubmed/12509835 12509835]).

To decide on an optimal High Angular Resolution Diffusion Imaging (HARDI) acquisition protocol, see:
* [http://www.ncbi.nlm.nih.gov/pubmed/19603409 White and Dale (2009)] Optimal diffusion MRI acquisition for fiber orientation density estimation: an analytic approach. HBM. (Calculated optimal b-values for maximum FOD estimation efficiency with SH expansion orders of L = 2, 4, 6, and 8 to be approximately b = 1,500, 3,000, 4,600, and 6,200 s/mm^2; demonstrated how scanner-specific hardware limitations generally lead to optimal b-values that are slightly lower than the ideal b-values.)
* [http://www.ncbi.nlm.nih.gov/pubmed/18583153 Tournier et al. (2008)] Resolving crossing fibres using constrained spherical deconvolution: validation using diffusion-weighted imaging phantom data. NeuroImage. (For a 45 degrees crossing, the minimum b-value required to resolve the fibre orientations was ... 2000 s/mm^2 for CSD, and 1000 s/mm^2 for super-CSD.)
* [http://www.ncbi.nlm.nih.gov/pubmed/17379540 Tournier et al. (2007)] Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution. NeuroImage.

HARDI data analysis tools include Camino, dipy, mrTrix etc.

We use a modified version of the stock GE DWI-EPI pulse sequence. The resulting dicoms contain the diffusion parameters in these fields:
* b-value (in sec/mm^2): 0043 1039 (GEMS_PARMS_01 block, item 1039)
* gradient direction: [0019 10bb, 0019 10bc, 0019 10bd] (GEMS_ACQU_01 block, items 10bb - 10bd)
In mrTrix (mapper.cpp), the following code is used to convert the dicom gradient values to the saved gradient directions:

// M is the image transform
M(0,0) = -image.orientation_x[0];
M(1,0) = -image.orientation_x[1];
M(2,0) = image.orientation_x[2];
M(0,1) = -image.orientation_y[0];
M(1,1) = -image.orientation_y[1];
M(2,1) = image.orientation_y[2];
M(0,2) = -image.orientation_z[0];
M(1,2) = -image.orientation_z[1];
M(2,2) = image.orientation_z[2];
M(0,3) = -image.position_vector[0];
M(1,3) = -image.position_vector[1];
M(2,3) = image.position_vector[2];
M(3,0) = 0.0; M(3,1) = 0.0; M(3,2) = 0.0; M(3,3) = 1.0;
H.DW_scheme(s, 0) = M(0,0)*d[0] + M(0,1)*d[1] - M(0,2)*d[2];
H.DW_scheme(s, 1) = M(1,0)*d[0] + M(1,1)*d[1] - M(1,2)*d[2];
H.DW_scheme(s, 2) = M(2,0)*d[0] + M(2,1)*d[1] - M(2,2)*d[2];

If you get the data from the CNI Neurobiological Image Management System (NIMS), then the b-values and b-vectors have already been extracted for you and are provided along with the NIFTI file containing your data. These three files (the NIFTI, bvals, and bvecs files) can be send directly into most diffusion data analysis packages, such as the Stanford Vita Lab [[http://vistalab.stanford.edu/newlm/index.php/MrDiffusion mrDiffusion]] or FSL's [[http://www.fmrib.ox.ac.uk/fsl/fdt/index.html FDT]]. The b-values file contains a set of numbers (one for each acquired volume) that describe the b-value of the corresponding volume. The b-vecs file contains a triplet of numbers for each acquired volume, describing the diffusion-weighting direction for the corresponding volume. E.g., if you run our 60-direction scan, you will get 6 non-DW volumes followed by 60-DW volumes. Thus, you nifti file will contain 66 volumes. The b-vals file will contain 66 numbers (six 0's, fllowed by 60 1000's) and the b-vecs files will contain 66 triplets describing the DW directions for each volume (the triplets for the first 6 non-DW volumes are meaningless and can be ignored).

=Simultaneous Multi-Slice (SMS)=
The CNI, in collaboration with GE, implemented [http://www.sciencedirect.com/science/article/pii/S1090780713000311 simultaneous multi-slice EPI] (also known as multiband EPI). GE has integrated the SMS EPI into its product software platform, and since CNI's scanner upgrade to the UHP system, the SMS sequence is available as part of the GE product sequences, called the Hyperband. The Hyperband option is available for both BOLD EPI and diffusion EPI.

Previously CNI has provided the SMS sequence using our research PSD, the one we referred to as the "mux" sequence. We recommend everyone who has been using the "mux" sequence to transition to the Hyperband sequence. For a comparison of features and performances between the "mux" and Hyperband sequence, please see this CNI blog [http://cni.stanford.edu/hyperband-transition/ Hyperband transition]. More information about the legacy "mux" sequence is described on the [[MUX EPI]] page.

== SMS fMRI ==
The Hyperband sequence uses a calibration process that is integrated in the prescan. It is not necessary to set up a separate calibration scan or account for additional calibration volumes in the EPI time series. The calibration data is not saved in the final images. By default all the volumes in the EPI time series are reconstructed and saved in the final images, so the number of volumes in NIFTI is exactly the same amount as specified in the protocol (in the Multi-Phase page). However, the first few volumes in the time series may have different intensity because the spin magnetization has not yet reached steady state. In the BOLD analysis it may be necessary to discard the first few volumes in order to get to the steady state. Alternatively, there is an option in the Hyperband sequence to allow users to specify a number of dummy volumes, in which case the scanner will not reconstruct the first few volumes, but the scan timing is still the same, i.e. data acquisition starts right after the scan trigger.

=== BOLD EPI ===
* Hyperband 6, voxel size 2.4mm^3, FOV 21.6cm, number of slices 60, TR 710ms (scan protocol in the Connectome project)
* Hyperband 6, voxel size 1.8mm^3, FOV 23.0cm, number of slices 81, TR 1386ms
* Hyperband 8, voxel size 3.0mm^3, FOV 22.2cm, number of slices 48, TR 415ms
* Hyperband 8, voxel size 2.0mm^3, FOV 22.0cm, number of slices 72, TR 760ms

=== Multi-echo EPI ===
* Hyperband 3, 2x in-plane acceleration, 3 EPI echoes, voxel size 2.8mm^3, FOV 22.4cm, number of slices 51, TR 1.49s, shortest TE 14.6ms, TE interval 23ms

== SMS DWI ==
For SMS diffusion scans we generally recommend 2x to 3x slice acceleration, which will bring down the scan time by 2 to 3 times while maintaining the SNR of the diffusion weighted images. Partial Fourier acquisition is usually used to keep the TE as short as possible. The in-plane acceleration in addition to the slice acceleration is not always recommended because even though it can further reduce the EPI distortion but the SNR loss can be harmful for diffusion model fitting.

Diffusion Spectrum Imaging (DSI) ([http://onlinelibrary.wiley.com/doi/10.1002/mrm.20642/full Magn. Reson. Med., 2005, 54: 1377–1386]) and multi-shell diffusion ([http://onlinelibrary.wiley.com/doi/10.1002/mrm.24736/full Magn. Reson. Med., 2013, 69: 1534–1540]) scans can be realized by designing gradient tables that specify direction and amplitude of the b-vectors. We set up a several customized gradient tables that are optimized for DTI, HARDI, 2 or 3-shell diffusion scans. Consult with us if you would like to set up your own diffusion gradient scheme.

=== HARDI ===
* DTI 80dir 2mm (4:45): SMS factor 3, axial slices, 2mm^3 voxel size, number of slices 69, b-value 2500, 80 diffusion directions, 8 b=0 images
* DTI 96dir 2mm (5:50): SMS factor 3, axial slices, 2mm^3 voxel size, number of slices 69, b-value 3000, 96 diffusion directions, 10 b=0 images

=== Multi-shell diffusion ===
* DTI g79/81 b3k 2-shell (4:33+4:40): 2-shell with 10 b=0 images, 75 directions at b=1500, 75 directions at b=3000. SMS factor 4, voxel size 1.5mm^3, number of slices 84 (scan protocol in the Connectome project)
* DTI g103 b2k 2-shell (4:50): 2-shell with 9 b=0 images, 30 directions at b=700, 64 directions at b=2000. SMS factor 3, 2x in-plane acceleration, voxel size 2mm^3, number of slices 75
* DTI g150 b3k 3-shell (6:15): 3-shell with 10 b=0 images, 30 direction at b=1000, 45 direction at b=2000, 65 direction at b=3000. SMS factor 3, 2x in-plane acceleration, voxel size 2mm^3, number of slices 63

= Scientific Protocols for Tissue and Chemistry =

== Quantitative MR ==
These template protocols make quantitative measurements of MR parameters (e.g. T1 in seconds, and proton density (PD) as a fraction of the voxel) of brain tissue. Some 1 - PD is called the macromolecular tissue volume.

=== T1 map ===
The SS-SMS T1 scan is a quantitative T1 scan using slice-shuffled inversion-recovery SMS EPI sequence. This scan gives you a T1 measurement at 2mm isotropic resolution in a minimum time. It uses in-plane acceleration therefore it's not necessary to run a separate pe1 scan for distortion correction unless you have enough time. For processing the NIFTI file from either pe0 or pe1 scan to get the T1 map, you can use [http://github.com/cni/t1fit/blob/master/t1_fitter.py this Python script]. If you acquired both pe0 and pe1, then you can use [http://github.com/cni/t1fit/blob/master/t1fit_unwarp.py this script] to process both NIFTI files to get the T1 map -- this includes an extra step for distortion correction using FSL's TOPUP before fitting the T1 relaxation.

* SS-SMS T1 pe0 (pe1) (2:03): Gradient echo IR EPI, 2mm^3 voxel size, number of muxed slices 25 (75 unmuxed slices, 15cm), SMS factor 3, 2x in-plane acceleration, TR 3s.

=== T1 map + PD map ===
The four SPGR scans, together with the four IR EPI scans, are set up for calculating T1 and PD maps using the [http://github.com/mezera/mrQ mrQ analysis package]. If you want a high resolution T1 map, or if you are interested in getting PD in addition to T1, then you should use this group of scans.

* SPGR 1mm 30(4/10/20) deg (5:19 X 4): 3D SPGR, 1mm^3 voxel size, flip angle 30/4/10/20. The first scan should be run with Auto Prescan + Scan, and the following three should be run using Manual Prescan (do not change any parameters) + Scan.

* IR EPI TI=50(400/1200/2400) (1:15 X 4): Gradient echo IR EPI, 1.875 x 1.875 x 4mm^3 voxel size, 2x in-plane acceleration. The first scan should be run with Auto Prescan + Scan, and the following three should be run using Manual Prescan (do not change any parameters) + Scan.

Note that you could also choose to use only the four IR EPI scans to get a quantitative T1 map at a lower resolution. The working principle and model fitting procedure is explained [http://www-mrsrl.stanford.edu/~jbarral/t1map.html here].

== Spectroscopy ==
In-vivo spectroscopy sequences and analysis methods available and used at CNI are described [[GABA spectro | on this CNI spectroscopy page]].

= Additional information (deprecated) =
== Device specific processing ==
The [[GE Processing | General Electric processing]] includes various steps that can influence the signal-to-noise of your data. We explain what we have learned about this and how to control it in the [[GE Processing]] page.

== Technical notes ==
* [[media:bob_spatialRes_111216.pdf|Slides on spatial resolution]] from CNI tutorial
* [[MR Signal Equations]]

== Session Running Script ==

We advise you to put together a session running script that outlines set up of the scanner and peripherals and positioning of and communications with the participant. You can find an example [[media:Session_Running_Script.pdf|here]] (courtesy of Nanna Notthoff, Carstensen Lab).

== CNI's Quality Assurance protocol ==
Weekly QA scans include:
# BOLD EPI sequence (analyze mean and variance over time)
# DW EPI sequence (analyze eddy current distortion stability)
# Spiral field map (analyze long-term B0 stability)
All QA scans are done on the fBIRN agar phantom. The phantom is positioned in the same orientation with the same padding each week. The landmark must be set to the same. The Rx should be not touched (use the same stored Rx). We should do HO shim and set the shim VOI to exactly cover the sphere.

MR Hardware

2023-08-23T17:35:23Z

Wandell: /* Lensometer */

= MR Scanner =
The [[MR Scanner]] is in room 065 of the CNI suite in Building 420. It has its [[MR Scanner|own wiki page]].

= The Laima Box (In Process) =
[[File:LB_Overview_Annotate.jpg|thumb|Overview of Laima Box]]
As you may guess from the title, the Laima Box came into being on the urging of Laima to find a solution to reduce the number of frequent issues caused by a complicated display switching system, frequently loose connections to the [[#fORP Response Box|fORP]] or [[#USB-to-Serial Port Trigger|Serial Trigger Box]] and unstable scanner signals. The Laima Box provides a stable and flexible interface to all the display devices, scanner signals, and other peripheral devices that are commonly used during studies.

== HDMI Matrix Switch ==
[[File:HDMI_Switch_Schematic.jpg|thumb|HDMI switch schematic.]]
[[File:LB_HDMI_Switch.jpg|thumb|HDMI switch in Laima Box.]]
We use an 8x8 HDMI Matrix Switch to distribute video signals to all the various displays. This is a [https://keydigital.org/category/4k-18g-hdmi-matrix-switchers/KD-MS8x8G Key Digital KD-MS8x8G] switch capable of connecting any of 8 input HDMI inputs to any/all of 8 HDMI outputs. The switch is capable of handling 4K HDCP2.2 video signals. The [[Media:HDMI_Switch_Schematic.jpg|schematic]] of the switch connections are shown here with all 8 inputs and outputs in use. In order to make a connection to a particular output display, you choose the particular input under the labeled output row of 8 LEDs. This is done by pressing the button under the labeled output (see HDMI Matrix switch [[Media:LB_HDMI_Switch.jpg|image]]) in order to progress left-to-right through the various inputs. Unfortunately, the blue LEDs on this switch that show what input is currently connected have been burning out, so it's sometimes necessary to count your button presses from a visible LED to know what input you are on.

The default output display for each input is nominally the same number as the input. As you'll note, we have the GE Host computer and GE Table Driver on inputs 1 & 2 -- this is so we can send the GE Host Display to any other display connected to the HDMI matrix switch, or use the GE Table Monitor to display other output -- such as the Eyelink computer output when adjusting the Eyelink camera at the front of the scanner.

The HDMI matrix switch allows for fairly elaborate configuration as described in the [[Media:KD-MS4x4_8x8G_Manual.pdf|manual]] via a Key Digital PC application that is available on the CNI PC laptop when connected to the internal private ethernet network.

Troubleshooting: The HDMI matrix switch is generally fairly stable but if you're having odd behavior a good first step is to cycle the main power to the Laima Box -- this will reset the HDMI matrix switch.

= Stimulus Presentation =
The CNI offers several display options, depending on your visual stimulus needs. All use a digital interface (DVID or HDMI) and can be connected by selecting the appropriate options on the HDMI matrix switch. The mirror on the 32-channel coil is a double mirror design. (See [[32-channel_double_mirror]].)

== 3D LCD display (49") ==
We have a 49" 4K 3D LCD display from Resonance Technology.
* 640x480@60Hz up to 4096x2160@50Hz resolution
* 1000:1 contrast ratio
* screen size: 107.2cm high x 60.3cm wide
* visual distance from Nova coil: 267cm from mirror2, 6cm mirror2 to mirror1, 15cm from eye to mirror1 = 288cm
* visual distance from NFL coil: 263cm from mirror1, 13cm from eye to mirror1 = 276cm

To see 3D effects, subjects will need to wear passive polarized lenses. The screen can, of course, present non-3D stimuli too.

As described in our Slack [https://stanford-cni.slack.com/archives/C011V1M2FRN/p1639611006023100 channel], the TV monitor has varying latency depending on the mode it is in. We conducted tests using a 1920x1080p@60Hz signal comparing the mirrored display on a laptop while simultaneously viewing the display on the scan room monitor. By capturing these displays simultaneously with a high-speed video acquisition we were able to calibrate the latency between the laptop and scan room monitor display. Assuming the laptop display latency is 0, when in General mode the monitor processing creates about 133ms (8 video frames) of latency, as compared to Game mode where the latency is only 33ms or 2 frames. In order to switch modes, the remote control must be used inside the scan room but care must be taken as the batteries are slightly ferromagnetic so be sure to hold on the remote firmly and keep it as far from the scanner as possible. Choose Options->Scene Select->Game in order to select Game mode. It should be in this mode by default -- we ask any users that switch the monitor mode to please return to Game mode after their experiment.

== LCD Projector ==
We also have a rear-projection LCD projector ([http://www.eiki.com/usa/products/projectors/hd-widescreen/lc-wul100 Eiki LC-WUL100L Projector]). This projector can be used by placing the large mirror on the back of the scanner bed in front of the LCD panels. You also need to place the rear-projection screen on the head coil. Set-up of this system is a bit more involved than the flat panel displays, but it offers a much brighter display and a larger field of view. If you need that, let us know and we'll show you how to set up the projector system.

Here are the specs on the projector:
* 5,000 lumens
* 1920x1200
* 2000:1 contrast
* 10-bit color resolution
* brighter and larger field of view than the LCD displays

If you try the projector (via HDMI) and nothing happens, you can try cycling power to the [[#The Laima Box|Laima Box]. If this doesn’t work, troubleshoot the projector as you normally would (check the input cable on the projector is connected and cycle inputs). There is also a remote control for the Eiki projector that can be used by pointing it at the IR sensor on the front of the Laima Box (which is relayed to an IR emitter inside the projector enclosure. This is useful for adjusting the off-axis lens position, setting menu options, etc.






== MRI Compatible Glasses ==
[[File:mri-glasses.jpg|thumb|mri frames and lenses]]
For participants who wear glasses, CNI has a set of interchangeable lenses that are used with an MRI compatible plastic frame. The frame and lenses are located in the open shelving above and to the left of where the screening forms are located. We have lenses for both near-sighted (-0.5 to -8.0 in .5 step increments) and far-sighted (+.5 to +8.0 in .5 step increments) vision corrections. The lenses are made of hard polycarbonate plastic and are not breakable. The easiest way to install the lenses into the frame is insert the lens from the back first into the edge by the ear piece and then snap in the lens by the nose. If the participant does not know his/her glasses prescription we have a lensometer that can determine that. Basic instructions for use of the lensometer are in the next section. There is also an eye chart posted on the door to the equipment room where participants can test their vision with the MRI glasses. Have the participant stand right in front of the lensometer (about 10 feet from the chart) to use the chart.
[[File:eye-chart.jpg|thumb|eye chart]]

== Lensometer ==
To determine glass prescription strengths for MRI participants CNI has the AL200 Auto Lensometer. Is is located in the CNI control room area. There is both a User's guide and a quick reference sheet next to the lensometer. The lensometer is currently set up to read a single vision lens. There are settings available to read either bifocal or progressive lenses, but they are not typically used as only the distance portion of the lens needs to be measured.

Here is a basic how-to from the Reichert user's guide.

<gallery perrow=4>
Image:Lensometer-parts.png|The key parts of the lensometer.
Image:Lensometer-back.png|Turn on the lensometer using the switch on the back panel. The AL200 will do a calibration check; do not place any lenses or obstructions in front of the aperture during calibration.
Image:Step2.png|The AL200’s default measurement mode is Single Vision, Automatic. This mode is used for fast, easy measurement of a pair of single vision spectacle lenses. You're now ready to measure the right lens, indicated by the 'R' on the upper left side of the screen.
Image:Glass-placement1.jpg|Place the spectacles on the lens table and secure the right lens with the lens holder. Using the table base levers and your hand, move the lens until the large cross is positioned directly over the small cross in the middle of the centering target.
Image:Glass-placement2.jpg|If you insert a progressive lens in single vision mode, the progressive icon may flash to indicate that the mode should be changed. NOTE: Place the glasses so that lenses are toward the front and the ear pieces toward the back.
Image:Step3.png|When optical center has been located, the AL200 tone will sound and the measurements will be locked on the screen. Upon removal of the lens the AL200 will automatically switch to the left lens, indicated by the highlighted L on the upper right side of the screen.
Image:Step4.png|Repeat the measurement process for the left lens. All measurements will remain on the screen until the operator chooses to print or clear the data.
Image:Lensometer-screen.png|The number that appears in the Sphere location is the correction number that you will use in choosing the lenses for the MRI glasses.
</gallery>

== Auditory System ==
[[File:skullShakers.jpg|thumb|Bone-conduction transducers.]]
[[File:newmatic.jpg|thumb|Newmatic audio amplifier.]]
The auditory system at the CNI uses the Newmatic audio amplifier to drive piezo transducers. Normal sound-attenuating headphones (even those marketed as 'slim'), do not fit in our Nova 32-channel head coil. So, we installed two different sets of ultra-slim transducers. Our primary system uses [http://en.wikipedia.org/wiki/Bone_conduction bone conduction] to deliver sound to the subject. For this system, we place piezoelectric transducers directly on the scan subject's cheeks, just in front of the ear. The subject wears sound-attenuating earplugs as usual, and hears the audio stimuli via bone conduction. This system is the only one that reliably fits in the 32-channel head coil. We have found it to be ideal in terms of subject comfort as well, since they can wear ear plugs to block the scanner noise. We recommend that you use the light-weight memory foam pads (the red or white ones) for padding around the ears/head (if padding is needed – the participant may already be snug enough in the head coil). Using the thicker/heavier-weight memory foam pads can push the headphones against the participant’s head in a painful way. Also, please be sure to use sanitary covers. They can be found in the shelves in the scanner room. Use some medical tape to secure them.

The second system uses air tubes that penetrate earplugs and operate much like earbud headphones, except that the sound is delivered through the tubes. Most groups prefer the bone conduction system, but some have found that it is difficult to properly place the transducers for a few subjects, and thus revert to the air-tube system for these subjects.

We have not calibrated the frequency response of either system, but from our own qualitative experience, both have significant attenuation of the higher frequencies (as expected for these kinds of transducers). However, speech stimuli come through fine and both male and female voices sound clear and are fully intelligible.

Both systems are driven by the black [http://www.newmaticmedical.com/mri-audio-systems/p/PatientAmplifier/ Newmatic amplifier box]. To set up the audio, plug in the audio cable into your computer’s headphone jack. Make sure that your computer’s sound is turned on. We recommend that you turn your computer’s sound to a high volume, and then use the volume control on the Newmatic amp to adjust the subject's volume. For speech stimuli, we recommend setting the volume to about 6 or 7 to start with, and then adjust as needed. You can use the volume on the black speaker to adjust the volume in the control room (i.e., what you hear). This won’t impact the volume settings for the participant.

We recommend that you test the sound before your participant comes in and also with your participant before you start your experiment (ask them to position the headphones such that they can hear optimally). The Carstensen lab has had good experience using an online violin tuner as the sample sound, for example, this one: [http://www.get-tuned.com/online_violin_tuner.php].

For information about how to build an MR-compatible bone-conduction system, see the [[CNI Bone Conduction Audio System]] page.

If you need to talk to your participant during the experiment WHILE the sound is also playing, you will want to use the “Talk” button on the black microphone to the left of the GE console, rather than the regular “Talk” button for the intercom. If you are using audio for your experiment, but you want to talk to the participant while the sound is not playing, you can use the regular intercom “Talk” button.

Troubleshooting the audio: If you/your participant cannot hear a sound through the headphones, and you have made sure that the audio cable is plugged in, that both your computer's volume is set to high, and that the Newmatic sound system is turned on and set to a reasonable volume level.

Contact the CNI staff if you need help setting up the auditory system.

= Subject measurement =

== fORP Response Box ==
We have a modular response box system ([http://www.curdes.com/index.php/mainforp/interfaces/fiu-933.html fORP 932]) from [http://www.curdes.com/ Current Designs]. With ths system, you can swap out various response devices. The output from any of these devices is available from the fORP box via USB. The device emulates a USB keyboard. (Note that we have found more reliable operation with PsychToolbox by using the "USB HID NAR" mode rather than the "USB HID KEY" mode. With KEY mode, some keypresses are missed.) We have confirmed that the fORP 932 USB interface is polled at 1kHz. The device itself has sub-millisecond time resolution (see the [http://www.curdes.com/index.php/support/faqs.html fORP FAQ]). We estimate that this system provides response time measurements with a precision and reliability of about one millisecond.

Note that the fORP can send keypresses every time the scanner acquires a slice (or a volume, in the case of fMRI EPI). If you want this (e.g., to trigger the start of your stimulus), make sure the 'scope trigger' cable is connected to the fORP, because it is often disconnected by some users (it's a BNC-style cable; ask Laima, Michael, Hua, or Adam if you are not sure). You will also want to configure the fORP to allow these keypresses by selecting a configuration that does *not* say "no 5" or "no t". If you *do not* want to get these pulses (most users actually do not want these), then select a configuration that includes "no 5" (if you are doing numbers) or "no t" (if you are doing letters. (Please don't disable these keys by disconnecting the BNC cable; there is already too much wear-and-tear on that cable.

[[File:fORP_trigger.jpg|thumb|fORP (silver box) and trigger box with the red manual trigger button.]]

The response devices that we currently have are:
# [https://www.curdes.com/mainforp/responsedevices/hhsc-scrl-1.html scroll-wheel device]
# [http://www.curdes.com/mainforp/responsedevices/buttonboxes/hhsc-2x4-c.htmlhtml 2X4 bimanual button boxes]
# [http://www.curdes.com/mainforp/responsedevices/hhsc-1x4-cyl-2.html 4-buttonstick-style response device]
# [http://www.curdes.com/mainforp/responsedevices/hhsc-1x5-d.html 5-button diamond button box]
# [http://www.curdes.com/mainforp/custom.html 5-button curved button box]
# [https://www.curdes.com/mainforp/responsedevices/hhsc-trk-2.html trackball device]
# [http://www.curdes.com/mainforp/responsedevices/buttonboxes/hhsc-1x5-n4.html PYKA 5 button box]
# [http://www.curdes.com/mainforp/responsedevices/variabledevices/hhsc-joy-5.html joystick]
# [http://www.curdes.com/mainforp/responsedevices/buttonboxes/foot-pedal.html foot pedal]

If you have a need for a different response device, just let us know.

To use a response device at the CNI:
# Plug the desired device into the black fiber-optic connector on the right side of the front of the magnet bore
# Locate the silver box (labeled fORP) in the control room to the right of the GE console.
# Push in the knob on the right front side of the fORP box to enter menu mode. For the following instructions, you will turn the knob to scroll through the menu choices, and then push in on the knob to select your choice. (See [http://www.curdes.com/technical/932-Getting-Started this guide] for more details on using the fORP 932.)
# Turn the knob until the word "yes" is underlined then push the knob to select "yes"
# In the "mode select" menu that appears next, you can select "manual config" We recommend, however, that you pick the AUTOCONFIGURE choice which tells the interface to determine as much as it can about the connected handheld device and the cabling to the host computer. This should simplify the choices that need to be made by you. If you have used the AUTOCONFIGURE option you can skip steps 6 and 7 below and proceed directly to step 8.
# In the response device menu, turn the knob to scroll through the choices until you find the device that you connected in step 1 (examples include):
## 4-button cylinder: select HHSC-cyl-5
## 5-button diamond: select HHSC-1x5-D
## 5-button curved: select HHSC-1x5-C
## bi-manual 4-button keypads: select HHSC-2x4c
## scrollwheel: select HHSC-SCRL1
## trackball: select HHSC-TRK-2 (for mouse emulation)
# Select USB in the next display by pushing in the knob.
# Select the desired output mode. For the cylinder or keypads, this determines the mapping between the buttons and the keypress that is generated. E.g., HID-NAR-12345 will map the 4 cylinder buttons to the four number keys, 1-4, and send a '5' for each each pulse received by the scanner (if you don't want these pulses, select the 'no 5' mode, as noted above). NAR means "no auto release". In NAR mode, the keypress is maintained as long as the button is pressed. In the non-NAR mode, a brief keypress is generated, even if the button is held down. We find that NAR mode works better with PsychToolbox. In non-NAR mode, it can miss the very brief keypresses produced by auto release. For a description of other modes, see [http://www.curdes.com/technical/cat/900customers/post/900responsedevices/ Current Designs support site].
# Setup is now complete.

For more technical details about the fORP, see the [[fORP|fORP wiki page]].

'''NOTE:''' Please do not disconnect the slice trigger cable to disable the slice triggers! The connector on this cable is delicate and has been broken from the frequent use. If you do not want the slice trigger key-presses ('5', 't', or '6', depending on the forp settings), then please select a option that disables these keypresses. E.g., 'HID-NAR no 5'.

== CNI Touch-pad ==
[[File:cni_touch.jpg|thumb|x80px|CNI touch-pad.]]
We designed and built this MR-compatible touch pad. It uses a [http://www.magictouch.com/addon.html KEYTEC] [http://www.atmel.com/Images/doc8091.pdf 4-wire resistive touch] glass connected to a [http://www.pjrc.com/teensy/ Teensy 2.0] with [https://github.com/cni/widgets/blob/master/touch/touch.pde custom firmware]. The CNI Touch Pad connects to a host via USB and will show up as a serial port on your machine. It will continuously stream the absolute position of the subject's touch using a simple serial protocol. Here is [[codeserialport|some sample code]] to get coordinates in Matlab.

== Eye Tracker ==
[[File:cni_eye_tracker_camera.jpg|thumb|Eye tracker camera.]]
[[File:cni_eye_tracker_ir.jpg|thumb|Eye tracker IR illuminator.]]

We have an [http://www.sr-research.com/EL_1000.html SR Research EyeLink 2000] eye tracker with remote optics installed at the CNI. It has a frame rate of up to 2000Hz, up to 1/2 degree accuracy, and is fairly easy to set up and use. We found that the standard IR light source from SR Research did not adequately focus the light onto the subject's eye, so we built a small MR-safe IR source using a [http://www.superbrightleds.com/moreinfo/component-leds/315mw-850nm-infrared-led-with-star-heatsink-125-degree-viewing-angle/653/ single high-power IR LED] epoxied to a [http://www.digikey.com/product-detail/en/D10850-40/345-1077-ND/340370 non-metallic heat sink]. The illuminator is mounted on the head coil using a loc-line stalk and can be positioned to nicely illuminate the target eye. It's powered from the same 5v source that powered the original SR illustrator (and that powers the camera) via a simple circuit based around a 1.8v linear regulator (it turns out that 1.8v drives this LED with just the right amount of current). We did have an issue with the RF pulses from the scanner causing some flicker in the illuminator, but a few big capacitors managed to minimize the flicker.

The camera is permanently mounted to the cover over the patient bed mechanism at the back of the bore, just in front of the LCD display. The camera position and focus should not need to be adjusted if your subject is positioned with their eyes close to isocenter. However, if you have a prescription that is centered far from iso-center, you may need to adjust the focus a bit. To do that, you can use the video switch under the counter (next to the FORP) to show the eye tracker video on the large LCD at the back of the bore so that you can adjust the camera and easily see what you are doing.

The infrared light source is mounted on a blue loc-line stalk that attaches to the head coil and is usually left unattached and hanging on the side of the scanner next to the response devices; you will need to mount it to the head coil using the blue loc-line pliers that you can find under the shelf with all the padding. Once mounted, make sure the light source is directed toward the subject's eye by aiming it through the gap between the two mirrors.

The eye tracker host computer is mounted in the equipment room. However, the display, keyboard, and mouse for that computer are to the right of the GE console. You can connect to the host computer by a direct TCP connection through the ethernet cable located in the cable bundle next to the GE console. This cable is, not surprisingly, labeled "eye tracker". If you use psych toolbox for stimulus presentation, you can use the [http://psychtoolbox.org/eyelinktoolbox EyeLink Toolbox]. For those who use python (e.g., [http://www.psychopy.org/ Psychopy]), try the [http://www.psychopy.org/api/hardware/pylink.html PyLink module]. If you use E-Prime, check out the [https://www.sr-support.com/showthread.php?149-E-Prime-integration E-Prime integration info] on the SR Research support site. In any case, the IP address of the Eyelink is on our private network and thus is NOT the default IP, so you need to explicitly set it to 10.0.3.2. This private network has a DHCP server, so your stimulus computer should automatically get assigned an IP address on the same subnet. Please don't hard-code an IP address for your stimulus computer! Note that older versions of psychtoolbox don't allow you to specify the IP address, so be sure to get the latest Eyelink mex file from [https://github.com/kleinerm/Psychtoolbox-3/commit/aa04b821e975e0e61978377bb05aa1e216f3382e github].

For a tutorial and troubleshooting information on the Eyelink system, see the [[EyelinkTracker]] page.

The old [http://www.mrivideo.com/product/products.asp?id=10&sub_id=14 MReyetracking system] from Resonance Technology is still available. This system uses the [http://www.arringtonresearch.com/viewpoint.html ViewPoint] software from Arrington Research. For more details on the old eye tracker, see the [[eye tracker]] page.

==Physio monitoring==
[[File:ppg_resp.jpg|thumb|Photo plethesmograph (PPG) and respiration belt.]]
[[File:physmon.png|thumb|[[CNI_widgets|CNI PPG pulse detector device]].]]
The scanner has the standard suite of physiological measures: pulse oximetry, respiration belt, and ECG. These can be used for scan triggering. Also, the digital data from these measurements are saved on the console and backed-up in the nims database. These data are also processed by the [[CNI_widgets|CNI PPG monitoring device]] and used for EEG ballisto-cardiogram artifact removal by the EGI NetStation software. (See also the [http://fmri.ucsd.edu/Howto/3T/physio.html UCSD fMRI group's site] for more information on using the GE physio files to remove physiological artifacts from fMRI data.) A recent paper is here - [https://doi.org/10.1016/j.jneumeth.2016.10.019 The PhysIO Toolbox for Modeling Physiological Noise in fMRI Data]

===Setting Up Physio Recording===

* Go to “Tools” -- Gating
[[File:Tools_1.png|thumb|Tools Button]]

* To record respiration/movement of the abdominal wall, select “Respiratory.”
[[File:Tools_gating.png|thumb|Tools Gating]]

* To record pulse/peripheral gating, select “PG.”

* Outfit your participant with the respiratory bellows and the PG sensor

===Respiratory Bellows===

The respiratory bellows goes around your participant’s diaphragm or abdomen. You will get the best signal in the area where the participant’s breathing motion is most visible when they are lying down. Use the Velcro to adjust the respiratory bellows; it should be snug and not move around much, but stretched as little as possible and not too tight. The bellows should expand and contract approximately 0.5 to 1 inches with the participant’s breathing. Do not place any padding over the respiratory bellows. You should be able to see the recording on the small screen on the scanner. Note that it’ll take about one minute for the system to stabilize. Your participant should remain still for the system to adjust. Check that the screen shows you a nice waveform without too much noise, and adjust the bellows if necessary.

===Pulse/Peripheral Gating (PPG) ===

The participant’s pulse is monitored by a photopulse sensor that detects blood oxygen levels (pulse oximetry) in the vascular bed of the participant’s finger/thumb or toe.

During the measurement, the participant’s hand or foot should remain cool and dry.

We recommend that you attach the sensor to the participant’s toe, especially if you are going to ask your participant to use one of the button boxes because hand movements will create noise in your PG signal.

Recording from the toe: Attach the sensor to the fastener for the toe (with the Velcro). Place the sensor on the vascular bed of the participant’s toe. To keep the sensor in place, tape it and the fastener to the participant’s foot using medical tape. It is also a good idea to tape the cable to the knee pillow or the participant’s leg to reduce the pull on the sensor.
Recording from the thumb/finger: Place the sensor on the participant’s finger or thumb. It is a good idea to avoid placing the sensor on the joint (the signal will be much noisier if you place the sensor on the joint). To keep the sensor in place it helps to tape it to the participant’s hand with some medical tape.

You should be able to see the recording on the small screen on the scanner. Note that it’ll take up to a minute for the system to stabilize. Your participant should remain still for the system to adjust. Check that the screen shows you a nice waveform without too much noise, and adjust the sensor if necessary.

Note: When you are done, please clean the sensor with alcohol wipes as it directly touches the participant’s skin.

===Recording Physio===

The default method for recording the physio is the CV control method. It is synchronized with scan start and stop. With default setting of CV control method, a recording of maximum length (25 minute) will require approximately 3 seconds to save to files to the hard disk after the end of the scan. You need to make sure that the next phys-recording scan starts after the previous recording finishes saving data to files. If the next phys-recording scan starts before the previous recording finishes, the new recording request will be ignored.

[[File:Physio_waveforms.png|thumb|Physio Waveforms on Console]]

===Parsing the physio files===

The physio data from the scanner can include three types of measurements: pulse, respiration, and electrocardiogram (ECG). The pulse data come from the PPG, the respiration data from the breathing-belt, and the ECG from the specialized electrodes attached to the chest.

The data recorded from these devices are written out into simple text-files. There are three files for each type of measurement. The file names start with PPG, RESP and ECG (we think) for the three types of measurements. The files have raw data ('Data'), the times of the local peaks ('PacTrig') and ('Trig', which has been empty in our experience).

* The temporal sampling rates differ between the three types of measurements
** ECG: 1ms,
** Pulse/Peripheral Gating: 10ms,
** Respiration: 40ms.
* The timeseries data
** start 30 seconds of baseline from before the start scan button was pressed
** have a variable duration between start scan button press and the actual start (pre-scan delays, external trigger delays, etc.)
** continue to the prescribed duration of the scan (even if you stopped the scan manually)
* The end of the timeseries in the file coincides with the '''prescribed''' end of the scan.
* The maximum duration of each file is 25 minutes.

The physio files are zipped and including in the Flywheel acquisition. We will be writing Gears to help extract, visualize, and summarize the data.

To reiterate-- the physio data stored in the physio files starts 30 seconds '''before''' you press the 'start scan' button (yes, it's psychic ;), which is almost always more than 30 seconds before scanning actually starts. It could be substantially longer if you do external triggering. In that case, you'll get some extra physio data recorded during the time between when you press start scan and you send your trigger. But the recording does '''stop''' when the scan is prescribed to stop (even if you abort the scan prematurely). So, to synchronize physio and scan data, chop off the extra physio data at the beginning of the file. And if the scan was prematurely aborted, you'll need to take that into account too.

At the CNI, we attempt to do the basic processing on the physio files generated by your scans. The files are read and regressors are computed. These regressors can be used to regress out the physio noise, or they can be used to de-noise the raw data. For details, see [https://github.com/cni/nims/blob/master/nimsproc/nimsphysio.py nimsphysio.py] in the NIMS repository.

===Biopac measures===
For measuring skin conductance and EMG, we have a Biopac with the [http://www.biopac.com/eda-gsr-amplifier-mri electro-dermal activity amplifier] and [http://www.biopac.com/emg-electromyogram-amplifier EMG amplifier] modules. The data from the Biopac are digitized with a [http://labjack.com/ue9 LabJack UE9] DAQ device and are available directly through a TCP stream (see [http://labjack.com/support/ue9/c-native-tcp-example the UE9 code samples]) or via our linux box voxel2, which can be used to trigger data acquisition that is synchronized with the scanner. The command to run the recording script is "testfix_labjack.py /data/biopac/[your experiment folder]/[run id] [recording duration]". The recording duration is in seconds. The output is a csv file at /data/biopac/[your experiment folder]/[run id]_[timestamp].csv. The data file records the voltage and raw ADC values. The skin conductance is stored in the second (voltage) and third (raw ADC) columns. You probably want the second column (with numbers like "1.60230098"). The skin conductance amplifier gain is set to five microsiemens per volt. So, if you multiply the numbers in the second column by 5, you will have the skin conductance in microsiemens. The EMG values are in the fourth (voltage) and fifth (raw ADC) columns. The EMG amplifier gain is set to 2000, so dividing the values in the fourth column by 2 will give you the EMG voltage in millivolts.

==Subject video==
You can monitor and record the subject's face or body using an infrared video camera. The camera is always on and streaming video to the linux box next to the scan console. An analog video signal is also sent to the large-screen tv in the control room (use the 'A/v input'). To use the camera, you can attach it to the head coil using the loc-line connectors. When not in use, the camera should be hung on the side of the scanner along with the response devices. To see the video feed, run the following from the command line: "ffplay -f video4linux2 /dev/video0". To record the video feed, you can use our video recording scripts. From the command line run "recordSubject 310", this will record subject video for 5 minutes and 10 seconds; to synchronize the recording to the start of the scan, run "recordSubjectTrigger 310" instead. The data files are saved to the "video" directory.

Troubleshoot: if you get an error "/dev/device0: busy or resource unavailable", then run "fuser /dev/device0" and you'll get the PID of the process that is currently occupying the video device. Then run "kill -9 [PID]". This should kill the process and you should be able to use the video camera again. Occasionally the camera feed fails and the recorded video files are empty. If this happens, check the video device setting with "v4l2-ctl -d /dev/video0 --all" and look for the "Video Standard" section. If it's something like "Video Standard = 0x000000ff PAL-B/B1/G/H/I/D/D1/K", then you'll need to change it to NTSC standard with "v4l2-ctl -d /dev/video0 -s ntsc". The returned message should be "Standard set to 0000b000 NTSC-M/M-JP/M-KR".

= Scan Triggers =
[[File:cni_epi_psd_usercvs_ss.png|thumb|UserCVs under the 'Advanced' tab for the cni_epi PSD.]]
The moment when the scanner starts acquiring image data can be controlled from the computer you use to control your experiment. To do this you need to be able to program your computer to send a pulse to the scanner at the planned moment.

At the CNI, we provide two methods for sending the pulse. Both use a USB connection, one using a USB DAQ device that has a nice Matlab driver available and the other uses a [[CNI widgets|USB-to-Serial port device]], which works well for E-Prime and Presentation. The notes below show how to set up the UserCV so that the scanner listens for the trigger, and how to send a trigger pulse using either the USB DAQ device or the USB-to-Serial device.

== Protocol configuration ==
For BOLD EPI, be sure to use the cni_epi PSD to get the triggering options described here. The same options are also available for the spiral PSD. Under the 'Advanced' tab, make sure the "start scan trigger" CV is set to '1', which tells it to use the external trigger. Other options include '0' for no trigger (scan starts as soon as the scan button is pressed), and '2' for cardiac gating, which will synchronize to the cardiac cycle (measured via either the PPG pulse oximeter or ECG leads).

== USB-1208 HID trigger ==
'''NOTE: this trigger system is deprecated and has been removed. Please convert your scripts to use the [[#USB-to-Serial Port Trigger]].'''

At the CNI, we have a [[http://www.mccdaq.com/usb-data-acquisition/USB-1208-Series.aspx USB-1208]] HID device from Measurement Computing installed and wired into the scan trigger through pin 14. This device is supported by the PsychToolbox [[http://psychtoolbox.org/PTB-2/daq.html DAQ Toolbox]]. If you have PsychToolbox configured, just plug in the USB cable labeled "Matlab Trigger" and you can send a TTL pulse to the scanner by pulsing pin 14. See the VistaSoft [[http://vistalab.stanford.edu/trac/vistadisp/browser/trunk/exptTools2/experimentControl/StartScan.m StartScan]] function for example Matlab code.

== USB-to-Serial Port Trigger ==
The CNI also has a USB-to-Serial port device set up to send scan triggers. Just connect the USB cable labeled "EPrime Trigger" to your computer. On OS-X and Linux, the device is automatically recognized as a serial port (under /dev/ttyACM? on linux or /dev/ttyUSB??? on OS-X). On windows, you might need to install a driver the first time you connect it. Download the [[Media:CNI_serial.inf|CNI Serial driver]] and be sure that the file name has the correct extension. (Windows will probably add a ".txt" to the file name, which causes the driver manager to fail to recognize it as an inf file. Change your folder settings to not hide file extensions and edit the file name to remove the ".txt". In Windows 7, go to Windows Explorer and press the Alt key to show the menu, and click on Folder Options via Tools menu button. Click on View tab and remove the check from Hide extensions for known file types, and then press OK. Now you can see and edit the file extensions.) Then, go to the Windows 'device manager' and open the device properties for the unrecognized USB device. Find the 'update driver' button and browse to the directory containing the .inf file that you downloaded. Check the port settings and make sure the port is COM1, COM2, COM3 or COM4. If not, use the 'advanced' button under the "port settings" tab to change the com port to one of these. (This is an E-Prime limitation.)

When configuring the port, note that the device is expecting communication at 57600 bps and the scanner is triggered by sending a three-character string: "[t]" (without the quotes). In E-Prime, you need to add the serial port device to your experiment and then configure it by specifying the device (look in your device manager if you are not sure) and setting the baud rate to 57600. (Other settings can be left at their default values.) In your E-Prime script, add the following in-line code to send the trigger string to the port:

Serial.WriteString "[t]"

To use this device from Matlab, try:

s = serial('/dev/ttyS0', 'BaudRate', 57600);
fopen(s);
fprintf(s, '[t]');
fclose(s);

Note that you will need to replace '/dev/ttyS0' with the correct port on your machine. E.g., if you're on windows, the port might be 'com1', 'com2', etc. On a mac, type 'ls -lh /dev/tty.usbmodem*' in a terminal.

However, some older Matlab versions for OS-X system don't support the Matlab 'serial' command. If that happens to be you, don't lose hope! You can set up a simple python script to do the triggering. First, get the trigger working in python. In a terminal, try this:

wget http://pypi.python.org/packages/source/p/pyserial/pyserial-2.6.tar.gz#md5=cde799970b7c1ce1f7d6e9ceebe64c98
tar -xzf pyserial-2.6.tar.gz
sudo mv pyserial-2.6 /Library/Python/2.3/site-packages/
wget https://raw.github.com/cni/widgets/master/python/startScan.py
chmod a+x startScan.py
sudo mv startScan.py /usr/local/bin/

Then, in Matlab, you can call this python script with:

unix('/usr/local/bin/startScan.py /dev/tty.usbmodem123451');

If you are using PsychoPy, first make sure the pyserial package is installed (e.g., pip install pyserial). Then create two code blocks:

# Insert a 'Begin Experiment' code block to initialize (e.g., as part of your instructions)
import serial
import time
device = '/dev/ttyACM1' # NOTE: replace with your device identifier! On windows, the port might be 'com1', 'com2', etc.
def cni_trigger():
try:
ser = serial.Serial(device, 115200, timeout=1)
time.sleep(0.1)
ser.write('[t]\n')
ser.close()
except:
pass

# Insert a "Begin Routine" code block whenever you want to send a trigger:
send_trigger()

Alternate example from Christina Chung:
#################################################
### import modules
import serial
import time

### scanner trigger
### Set SCANNER_TRIGGER_NEEDED to False to bypass program abortion when scanner exception is thrown
SCANNER_TRIGGER_NEEDED = False
DEVICE_ID = 'com3'

### scanner trigger
def cni_trigger():
try:
ser = serial.Serial(DEVICE_ID, 57600, timeout=1)
time.sleep(2) ### wait for 2 sec to ensure scanner is ready; CNI wiki default 0.1
ser.write('[t][t][t]\n')
ser.close()
except:
if not SCANNER_TRIGGER_NEEDED:
pass
else:
core.quit()

The construction of our serial trigger device is described on the [[CNI widgets]] page.

= Capturing Scan Timing Pulses =
[[File:trigger_t-connector.jpg|thumb|If you are not getting the expected pulses, check the t-junction under the counter by the GE console and try disconnecting the cable with the orange flag.]]
Some researchers want to know the precise time when each slice or each volume is acquired. The scanner produces timing pulses that can be used to record this information. Additionally, a pulse sent by the scanner at the beginning of the scan can be used to trigger the start of an experimental task (reversing the direction of triggering discussed above). At the CNI, we have two methods of receiving these timing pulses. One method uses the USB-to-Serial trigger device and the other uses the fORP response box system. These two methods are described in more detail below.

== USB-to-Serial timing pulses ==
The emulated serial port device [[#USB-to-Serial Port Trigger|described above]] can also be used to receive timing pulses from the scanner. To enable this mode, send a "[p]" command. You will then receive a 'p' character every time a timing pulse is detected. The temporal accuracy of these pulses should be about 1 ms. These "scope trigger" pulses come at the beginning of every slice or the beginning of every volume, depending on how the PSD is configured. For the cni_epi and spiral PSDs, under the "Advanced" tab, you can change the "scope trigger" CV to send pulses for every slice or just for the first slice of each volume. To capture these trigger pulses, you can use this [[saveTriggers.py|python script]].

== Timing pulses as keypresses via fORP ==
To use the fORP response box system to receive timing pulses from the scanner, set up the system as described in the 'Response Box' section above. Note that timing pulses will be received via the same USB connection as subjects' responses, and that no additional USB cables need be plugged into your testing computer. However, you will need to plug a cable labeled 'Slice Trigger' into the back of the fORP box. Assuming that you have selected a numeric mapping between button presses and keys, the timing pulses sent to your testing laptop will be in the form of a '5'. (Note that use of the 5-button diamond-shaped response box will include the numbers 1-4 and 6, and thus will not include the number 5). Use caution when editing experimental scripts while using this method--if your script is open while the scanner sends pulses, a long series of 5's will be inserted into your script! Similarly, at the end of your scan session, please be sure to unplug the 'Slice Trigger' cable from the back of the fORP box so that the frequent pulses do not disrupt other users' experimental scripts.

= Subject Positioning =
There are many MR-safe pads available for subject positioning. (Add positioning advice?)

Also, there is a [http://www.magconcept.com/ Mag Design and Engineering] bite-bar holder on the 8-channel and 32-channel coils (both built by Ben Krasnow). We have a 200deg water source in the control room (the Cuisinart coffee machine) and are planning to get a little microwave for heating things like bite bars and EEG electrolyte.

Some labs have expressed interest in a vacuum pillow system for subject positioning. From: Ashley Shurick (Gross lab) is familiar with the SecureVacTM Immobilization System from Bionix Radiation Therapy. The system at NYU uses a customized pillow measuring 50 x 70 cm with 12.5L of fill. However, the size should depend on the head coil used, as pillows come larger or smaller, with more or less fill. They also have a vacuum pump system to remove air from the pillow, helping prevent movement. We are currently looking int this.

= General information =

==Power switch for peripherals==
[[File:cni_peripheral_power_switches.jpg|thumb|Push-button switches to power on and off the peripheral equipment. (hand model cameo by Jason Yeatman)]]
The stimulus displays, audio system, and the fORP response system are best kept turned off when not in use. We've found this to be particularly important for the LCD display, which can act up when it's been left on for too long. To make it easier to turn all these devices on and off, we have installed two switches on the column to the right of the GE console. Please turn all the equipment off when you finish scanning. The switches toggle the power and glow blue when the power is on.

Behind the scenes, these push buttons each control a [http://www.furmansound.com/product.php?id=MP-15 Furman MP-15 power relay], one in the equipment room that controls power to scan room devices and one in the console room. The switched labelled "LCD" toggles power to devices in the scanner room and must be on to use the LCD display. The switch labelled "fORP" toggles the devices in the console room and must be on to use the fORP response system. The goggles and audio system require both switches to be on because they have a component in both the control room and the scan room.

==The magnetic field==
<gallery perrow=4>
Image:mr750_gauss_lines_top.png|Gauss-lines for a generic install (top view).
Image:mr750_gauss_lines_side.png|Gauss-lines for a generic install (side view).
Image:mr750_gauss_lines_front.png|Gauss-lines for a generic install (front view).
Image:CNI_MR_fieldlines.png|Sketch of gauss-lines for our particular installation.
</gallery>
When positioning equipment in the scan room, it's useful to be aware of the magnetic field lines. All equipment in the CNI scan room is MR-safe, but not all equipment functions properly in very high-field regions. The diagrams show the estimated field lines in the MR suite area.

=Building your own MR center=
See the [[Hardware configuration]] page for details about setting up the equipment described here.

File:120px-Webauth.png

2023-08-23T17:31:37Z