This work was supported by the Australian Research Council grants CE110001021, DP170103148 and DP170102407. Wei He was supported by a Macquarie University Research Fellowship (MQRF, IRIS Project: 9201501199). Hannah Rapaport was supported by the Australian Government&#39;s Research Training Program (RTP) and the Macquarie University Research Excellence Scholarship (MQRES). Robert A Seymour was supported by PhD scholarships from Aston University, Birmingham, UK and Macquarie University, Sydney, Australia. Paul F. Sowman was supported by the National Health and Medical Research Council (1003760) and the Australian Research Council (DE130100868). The authors acknowledge the collaboration with the Kanazawa Institute of Technology and the Yokogawa Electric Corporation in establishing the KIT-Macquarie Brain Research Laboratory.

This research protocol has been approved by the Macquarie University Human Research Ethics Committee.
1. MEG Familiarization Resources
<ol>
	<li>Provide families with resources to learn about MEG prior to visiting the MEG laboratory, such as a child-friendly scientific article7 explaining MEG and the MSR, a story-board detailing the steps involved in completing the MEG experiment (e.g., Supplementary Figure 1 and an MEG information sheet for parents or caregivers (e.g., Supplementary Figure 2).</li>
</ol>
2. MEG Familiarization Session
NOTE: The familiarization session typically runs for 30 min, including an introduction to the MSR (5 minutes), a practice digitization (5 min), and MEG simulator training, including practice on the experimental task (20 min). Conduct the familiarization session between one-to-seven days prior to data acquisition.
<ol>
	<li>MSR introduction
	<ol>
		<li>Take the child on a tour of the MSR (&#34;spaceship&#34;) which is decorated in space-related wall art to reinforce the space mission theme.</li>
		<li>Ask the child to practice lying back with their head in the helmet dewar.</li>
		<li>Tell the child to lie as still as possible so that the spaceship stays on course and can reach its final destination.</li>
	</ol>
	</li>
	<li>Digitization:
	<ol>
		<li>Seat the child on a high chair and fit them with a polyester swimming cap (&#34;astronaut helmet&#34;) containing five marker coils. Adapt loose-fitting caps by folding up the sides. NOTE: The coils send data to a continuous motion tracking unit.</li>
		<li>Place a transmitter and three receivers around the child&#39;s neck.</li>
		<li>Ask the child to demonstrate their best &#39;statue&#39; pose and offer frequent positive reinforcement when they stay still. 
		NOTE: This serves to minimize head movement during digitization that may compromise the accuracy of the subsequent co-registration with the MEG sensors8.</li>
		<li>Use a pen digitizer (see Table of Materials) to record the position of three fiducial points (the nasion and left and right pre-auricular points) and the five marker coils, as well as the shape of the surface of the head. NOTE: This data is used to later determine the position of the child&#39;s head in relation to the MEG sensors.</li>
		<li>Remove the cap, transmitter and three receivers from the child&#39;s neck.</li>
	</ol>
	</li>
	<li>MEG simulator:
	<ol>
		<li>Take the child to the room housing the MEG simulator (see Table of Materials and steps 9 and 10 in Supplementary Figure 1), a full-size replica of an MEG system. The MEG simulator is decorated with space-themed stickers and is equipped with a mock helmet dewar, a bed, a button box and, for visual displays, a screen situated above the mock dewar</li>
		<li>Briefly describe the MEG scanning procedures (i.e., lying still and participating in the practice experimental task) through the narrative of a practice space mission.</li>
		<li>Fit the child with an &#39;astronaut helmet&#39; &#8212; a polyester swimming cap which has a motion detector attached at the front (see Table of Materials).</li>
		<li>Invite the child to lie in the simulator and watch a video of their choosing. If the child appears nervous, first demonstrate the experimental procedures with a toy. 
		NOTE: Whenever the child&#39;s head movement exceeds a pre-determined threshold (e.g., 5 mm), the motion tracking system (see Table of Materials) will automatically pause the video and wait for the experimenter to manually restart the video and restore the movement baseline.</li>
		<li>When the child completes this part of the simulator training, provide the child with training on the experimental task using a separate set of unique stimuli.</li>
		<li>At the end of the task training, offer the child an astronaut training certificate.</li>
	</ol>
	</li>
</ol>
3. MEG Data Acquisition Session
NOTE: The data acquisition session typically runs for approximately 30 min, including digitization (5 min), setting up the participant inside the MSR (5 min) and data acquisition (approximately 20 min, depending on the length of the experimental paradigm).
<ol>
	<li>Preliminary procedures
	<ol>
		<li>Conduct a 30-to-60 s empty room recording approximately 15 min before the child arrives to identify any significant external noise that is detected by the MEG system8.</li>
		<li>When the child arrives, confirm that they are not wearing any magnetic material on their clothes or carrying any in their body, as magnetic materials can distort the MEG signal (see Figure 1B for an example of signal noise due to metal on the participant). 
		NOTE: If the parent or caregiver wishes to accompany their child inside the MSR, the removal of magnetic materials applies to them too.</li>
	</ol>
	</li>
	<li>Digitization
	<ol>
		<li>Check whether the child needs to go to the toilet before commencing digitization, as once the digitization step is completed, the cap cannot be removed until the MEG acquisition session has finished.</li>
		<li>Repeat the digitization procedure outlined in the &#34;MEG familiarization session&#34; section above. 
		NOTE: If the cap moves more than 5 mm over the course of the experiment, perform a second digitization at the end of the experiment</li>
	</ol>
	</li>
	<li>MSR set-up
	<ol>
		<li>Take the child to the MSR (&#34;the spaceship&#34;). 
		NOTE: Two researchers are required for this procedure &#8212; one to accompany the child inside the MSR as the &#34;assistant researcher&#34; (along with the parent or caregiver, if desired) and one to run MEG data acquisition outside the MSR as the &#34;main researcher&#34;. The MSR set-up typically takes 5 min.</li>
		<li>Set up equipment inside the MSR (assistant researcher)
		<ol>
			<li>Ask the child to place their head into the helmet dewar.</li>
			<li>Check that the child&#39;s head is centrally aligned such that the crown of the head is as close as possible to the back of the helmet dewar without touching.</li>
			<li>Ensure that the child is comfortable, relaxed, and remains as still as possible during MEG recording.</li>
			<li>During the set-up, keep the child entertained by playing a video of their choosing on a screen above the dewar.</li>
		</ol>
		</li>
		<li>Set up equipment outside the MSR (main researcher)
		<ol>
			<li>Conduct a pre-experiment/baseline marker coil measurement to record the initial head position with respect to the helmet dewar.</li>
			<li>Conduct a co-registration between the child&#39;s head and the sensor array using both the initial marker coil measurement and the digitization head shape data. 
			NOTE: These preparatory measurements enable visual inspection of head position inside the dewar to ensure that the child&#39;s head is correctly positioned. If these conditions are not met, re-position the child and conduct another co-registration before starting data acquisition.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Data acquisition
	<ol>
		<li>Once satisfied with the head position with respect to the helmet dewar, start the MEG recording and the experimental task.</li>
		<li>Record ongoing head movements with a pediatric MEG software system called Real-Time Head Movement (ReTHM)9.</li>
	</ol>
	</li>
	<li>Ending the experiment
	<ol>
		<li>When the experimental task is finished, turn off ReTHM and end the MEG recording. Conduct a post-experiment marker coil measurement to measure the final head position with respect to the helmet dewar. 
		NOTE: This measurement provides a simple visual inspection of overall head movements during the experiment.</li>
		<li>Offer the child a gift bag (&#34;astronaut kit&#34;) for their participation and remunerate the family for their time and travel costs.</li>
	</ol>
	</li>
</ol>

<ol><li>Baillet, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Magnetoencephalography+for+brain+electrophysiology+and+imaging%5BTitle%5D)+AND+%22Nature+Neuroscience%22%5BJournal%5D)">Magnetoencephalography for brain electrophysiology and imaging.</a> Nature Neuroscience. 20, 327-339 (2017).</li>
<li>Gaetz, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Magnetoencephalography+for+clinical+pediatrics%3A+Recent+advances+in+hardware%2C+hethods%2C+and+clinical+applications%5BTitle%5D)+AND+%22Journal+of+Pediatric+Epilepsy%22%5BJournal%5D)">Magnetoencephalography for clinical pediatrics: Recent advances in hardware, hethods, and clinical applications.</a> Journal of Pediatric Epilepsy. 04, 139-155 (2015).</li>
<li>Stolk, A., Todorovic, A., Schoffelen, J. -M., Oostenveld, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Online+and+offline+tools+for+head+movement+compensation+in+MEG%5BTitle%5D)+AND+%22Neuroimage%22%5BJournal%5D)">Online and offline tools for head movement compensation in MEG.</a> Neuroimage. 68, 39-48 (2013).</li>
<li>Tesan, G., Johnson, B. W., Reid, M., Thornton, R., Crain, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Measurement+Of+Neuromagnetic+brain+function+in+pre-school+children+with+custom+sized+MEG%5BTitle%5D)+AND+%22Journal+of+Visualized+Experiments%22%5BJournal%5D)">Measurement Of Neuromagnetic brain function in pre-school children with custom sized MEG.</a> Journal of Visualized Experiments. (36), 2923-2934 (2010).</li>
<li>Johnson, B. W., Crain, S., Thornton, R., Tesan, G., Reid, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Measurement+of+brain+function+in+pre-school+children+using+a+custom+sized+whole-head+MEG+sensor+array%5BTitle%5D)+AND+%22Clinical+Neurophysiology%22%5BJournal%5D)">Measurement of brain function in pre-school children using a custom sized whole-head MEG sensor array.</a> Clinical Neurophysiology. 121, 340-349 (2010).</li>
<li>He, W., Brock, J., Johnson, B. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Face-sensitive+brain+responses+measured+from+a+four-year-old+child+with+a+custom-sized+child+MEG+system%5BTitle%5D)+AND+%22Journal+of+Neuroscience+Methods%22%5BJournal%5D)">Face-sensitive brain responses measured from a four-year-old child with a custom-sized child MEG system.</a> Journal of Neuroscience Methods. 222, 213-217 (2014).</li>
<li>Brock, J., Sowman, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Meg+for+kids%3A+listening+to+your+brain+with+super-cool+SQUIDs%5BTitle%5D)+AND+%22Frontiers+for+Young+Minds%22%5BJournal%5D)">Meg for kids: listening to your brain with super-cool SQUIDs.</a> Frontiers for Young Minds. 2, 10-13 (2014).</li>
<li>Gross, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Good+practice+for+conducting+and+reporting+MEG+research%5BTitle%5D)+AND+%22Neuroimage%22%5BJournal%5D)">Good practice for conducting and reporting MEG research.</a> Neuroimage. 65, 349-363 (2013).</li>
<li>Oyama, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Real-Time+coil+position+monitoring+system+for+biomagnetic+measurements%5BTitle%5D)+AND+%22Physics+Procedia%22%5BJournal%5D)">Real-Time coil position monitoring system for biomagnetic measurements.</a> Physics Procedia. 36, 280-285 (2012).</li>
<li>de Cheveigné, A., Simon, J. Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Denoising+based+on+spatial+filtering%5BTitle%5D)+AND+%22Journal+of+Neuroscience+Methods%22%5BJournal%5D)">Denoising based on spatial filtering.</a> Journal of Neuroscience Methods. 171, 331-339 (2008).</li>
<li>Cheyne, D., Jobst, C., Tesan, G., Crain, S., Johnson, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Movement-related+neuromagnetic+fields+in+preschool+age+children%5BTitle%5D)+AND+%22Human+Brain+Mapping%22%5BJournal%5D)">Movement-related neuromagnetic fields in preschool age children.</a> Human Brain Mapping. 35, 4858-4875 (2014).</li>
<li>Näätänen, R., Pakarinen, S., Rinne, T., Takegata, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+mismatch+negativity+%28MMN%29%3A+towards+the+optimal+paradigm%5BTitle%5D)+AND+%22Clinical+Neurophysiology%22%5BJournal%5D)">The mismatch negativity (MMN): towards the optimal paradigm.</a> Clinical Neurophysiology. 115, 140-144 (2004).</li>
<li>He, W., Brock, J., Johnson, B. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Face+processing+in+the+brains+of+pre-school+aged+children+measured+with+MEG%5BTitle%5D)+AND+%22Neuroimage%22%5BJournal%5D)">Face processing in the brains of pre-school aged children measured with MEG.</a> Neuroimage. 106, 317-327 (2015).</li>
<li>Wehner, D. T., Hämäläinen, M. S., Mody, M., Ahlfors, S. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Head+movements+of+children+in+MEG%3A+quantification%2C+effects+on+source+estimation%2C+and+compensation%5BTitle%5D)+AND+%22Neuroimage%22%5BJournal%5D)">Head movements of children in MEG: quantification, effects on source estimation, and compensation.</a> Neuroimage. 40, 541-550 (2008).</li>
</ol>

The authors have nothing to disclose.

In recent years, MEG has been established as a valuable non-invasive neuroimaging technique for investigating the neural mechanisms underpinning brain development1. However, in-scanner head movements pose a notorious barrier to obtaining good quality MEG data, particularly when assessing pediatric populations. To overcome this problem, this article presented a pediatric MEG research protocol which builds upon procedures outlined in a previous paper from the KIT-Macquarie Brain Research Laboratory 4.
The critical procedures include (1) providing children with MEG familiarization resources from which they can learn about the MEG experiment prior to visiting the lab, which include a child-friendly research article7 explaining the MEG system and the magnetically shielded room (MSR), a story-board outlining 10 simple steps for completing the MEG experiment (Supplementary Figure 1), and an MEG information sheet for parents and caregivers (Supplementary Figure 2); (2) Preceding the MEG acquisition session with a familiarization session, wherein children are acquainted with MEG procedures and are trained to keep their heads still whilst lying inside an MEG simulator; (3) using passive or &#34;gamified&#34; experimental paradigms to minimize head movement due to boredom and restlessness; and (4) tracking ongoing head movements during online data acquisition using a Real-Time Head Movement (ReTHM) system9. Data obtained from ReTHM can be used to conduct offline correction of head movement artefacts when pre-processing the MEG data.
The acquisition of high-quality MEG data critically depends upon the child feeling at ease in the novel MEG environment. To foster this sense of ease, researchers are encouraged to devote time to familiarizing children and their families with the MEG environment and procedures prior to commencing data acquisition. This can be achieved through offering children and their parents MEG resources which explain the MEG procedures in simple, accessible language. Furthermore, families can be invited to visit the MEG laboratory before the data acquisition session to meet the researchers and practice the MEG testing procedures. Through training on the MEG simulator, children implicitly learn the importance of keeping their heads still whilst lying in the MEG. While the MEG familiarization requires both the researchers and the families to devote additional time to the data collection process, the advantages of improving MEG data quality, as well as minimizing the time and cost of conducting subsequent MEG data acquisition sessions, arguably outweighs this downside. Furthermore, performance and compliance during the familiarization session can be used to indicate whether the child is or is not suitable to invite back for an actual MEG data acquisition session.
To minimize in-scanner head movement due to restlessness, it is preferable to use a passive experimental paradigm which does not require instructions, overt attention or active participation. For example, a reliable evoked response can be obtained with an auditory oddball paradigm12, whereby the participant passively listens to a sequence of auditory tones whilst entertained by a silent video. For studies requiring an overt response, the researcher should aim to embed the experimental task in an engaging game-style paradigm11. This improves cooperation and minimizes restlessness during the task. In visual experiments, the use of an MEG-compatible eye-tracker entails little additional set-up time but is necessary in ensuring that children have fixated on the position of the visual stimulus13.
Any residual head movement artefacts can be corrected for using real-time head motion tracking. For example, data obtained from ReTHM can be stored in the MEG recording file and used to compensate for head movement during data acquisition in such a way that head-to-sensor localization can be restored to the pre-movement level to allow for an optimal source reconstruction which is essential for subsequent source level data analyses14.
The implementation of this protocol seeks to improve the quality of pediatric MEG data, minimize participant attrition rates in longitudinal studies, and ensure that families have an enjoyable experience of MEG research participation, with the overarching goal of improving our understanding of early brain development in both typical and atypical populations.

Magnetoencephalography (MEG) is a non-invasive functional neuroimaging technique which measures magnetic fields produced by the electrical activity of the human brain1,2. MEG offers excellent temporal resolution and superior spatial resolution compared with electroencephalography (EEG) due to the lack of signal smearing from the biological tissues between the brain sources and the sensors. In addition, MEG does not involve exposure to loud noises, radiation or magnetic fields. Set-up time is rapid and participants can be accompanied by a parent or caregiver throughout testing. Taken together, these features make MEG a promising tool for investigating the development of typical and atypical brain function in young children2.
To measure brain responses using MEG, research participants must insert their heads into a helmet housing a fixed array of superconducting sensors. It is crucial that the participants keeps their heads still throughout the MEG recording, as changes in the head position relative to the sensors both degrade the neuromagnetic signal distribution and impede accurate source estimation. Inaccurate source estimation inevitably leads to inaccurate statistical inferences in source power, functional connectivity and network analyses3.
Minimizing head movement can be particularly challenging during pediatric MEG assessment for a number of reasons. First, assessing young children in an adult MEG system is problematic as children&#39;s heads are much smaller than those of adults, and the increased space between the helmet and the child&#39;s scalp allows for unconstrained head movement. Second, the novel MEG environment &#8212; a large machine locked inside a windowless magnetically shielded room &#8212; can be intimidating for young children, and head movement may be a consequence of anxiousness. Third, without training, children may not fully understand or comply with the requirement to remain still for the duration of the experiment. Finally, children who have a limited capacity to tolerate boredom may find that some MEG experiments take too long or are tedious, resulting in restlessness and head movement artefacts.
To tackle the long-standing challenge of head movement in pediatric MEG research, this article presents recent hardware and methodological advances that are implemented in the child-friendly MEG protocol used at the KIT-Macquarie Brain Research Laboratory (Macquarie University, Sydney, Australia). As outlined in a previous paper from this laboratory4, the problems involved in the use of a loose-fitting adult-sized helmet dewar have been addressed by installing a world-first, whole-head pediatric MEG system with a bespoke helmet dewar to better fit the heads of young children between approximately three-to-six years of age. This hardware adaptation improves the signal-to-noise ratio, as the sensors are physically closer, on average, to the child&#39;s scalp5,6. More recently, the KIT-Macquarie Brain Research Laboratory has developed several new and novel procedures to overcome the aforementioned antecedents of head movement and hence to improve data quality.
All of the procedures in this protocol are explained through a narrative in which the child participant actively engages in an &#34;astronaut space mission&#34;. This narrative ensures that the child&#39;s MEG research experience is not only less intimidating, but also exciting. Implementing these procedures into a child-friendly MEG protocol is important for improving data quality, minimizing participant attrition rates in longitudinal studies, and ensuring that families have a positive experience in their research participation.

<table><tbody><tr><td>5 marker Coil set</td><td>Kanazawa Institute of Technology (KIT) and Yokogawa Electric Corporation, Japan</td><td>PQ11MKA</td><td></td></tr><tr><td>Fastrak Digitizer &amp;ndash; 3D</td><td>Polhemus Cochester, VT, USA</td><td>1A0383-001</td><td>Pen digitizer</td></tr><tr><td>Magnetoencephalography (MEG)</td><td>Kanazawa Institute of Technology (KIT) and Yokogawa Electric Corporation, Japan</td><td>PQ1160C</td><td></td></tr><tr><td>MEG simulator</td><td>Fino, NSW, Australia</td><td></td><td></td></tr><tr><td>MoTrack system</td><td>Psychological Software Tools, PA, USA</td><td>MTK-09314-1307</td><td>Motion tracking system</td></tr><tr><td>Polyester caps</td><td>Speedo</td><td>N/A</td><td>product code: SPE11733.435</td></tr></tbody></table>

studying brain function in children using magnetoencephalography

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique which directly measures magnetic fields produced by the electrical activity of the human brain. MEG is quiet and less likely to induce claustrophobia compared with magnetic resonance imaging (MRI). It is therefore a promising tool for investigating brain function in young children. However, analysis of MEG data from pediatric populations is often complicated by head movement artefacts which arise as a consequence of the requirement for a spatially-fixed sensor array that is not affixed to the child's head. Minimizing head movements during MEG sessions can be particularly challenging as young children are often unable to remain still during experimental tasks. The protocol presented here aims to reduce head movement artefacts during pediatric MEG scanning. Prior to visiting the MEG laboratory, families are provided with resources that explain the MEG system and the experimental procedures in simple, accessible language. An MEG familiarization session is conducted during which children are acquainted with both the researchers and the MEG procedures. They are then trained to keep their head still whilst lying inside an MEG simulator. To help children feel at ease in the novel MEG environment, all of the procedures are explained through the narrative of a space mission. To minimize head movement due to restlessness, children are trained and assessed using fun and engaging experimental paradigms. In addition, children's residual head movement artefacts are compensated for during the data acquisition session using a real-time head movement tracking system. Implementing these child-friendly procedures is important for improving data quality, minimizing participant attrition rates in longitudinal studies, and ensuring that families have a positive research experience.

Common Magnetoencephalography signals 
Common MEG signals are displayed in Figure 1, including a normal MEG signal (Figure 1A), as well as MEG signal noise due to metal on the participant (Figure 1B), in which case unlock the sensors, open the MSR door and ask the participant to remove any metal from their body, then take the metal object out of the MSR and perform an auto-tune before repeating the procedures outlined in section 3.5; interference from an electronic device (Figure 1C, most often from a mobile phone), in which case turn off any electronic devices or move them away from the MSR; a clenched jaw (Figure 1D), in which case remind the participant to relax their jaw for the duration of the MEG recording; alpha waves (Figure 1E; these are defined by eight to 12 continuous waves in a 1 s interval), in which case check that the participant is not asleep (it is fine to continue if they are awake); and trapped magnetic flux (Figure 1F); in which case unlock the sensors and turn on the coil heaters on for 5 min. If the flux persists after a subsequent auto-tuning, mark affected channel for removal from subsequent data analysis.
Head movement during data acquisition 
Pediatric MEG data before and after ReTHM correction is displayed in Figure 2. Data was collected from a three-year-old boy who passively listened to auditory tones for 15 min. Data was de-noised10, band-pass filtered11 (1-15 Hz), baseline-corrected and averaged. Root-mean-square (RMS) magnetic waveforms (in the right column) were computed from all sensors. Averaged in-scanner head movements were 44.3 mm. As demonstrated, ReTHM compensated for motion-related artefacts, resulting in more focal isofield contour maps (at the peak of the RMS waveforms; (A), less distorted RMS magnetic waveforms (B), and more meaningful source reconstruction (C) in the bilateral auditory lobes.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/58909/58909fig1.jpg" /> 
Figure 1: Examples of common MEG signals. (A) A normal MEG signal. (B-F) MEG signal noise due to (B) metal on the participant (specifically, noise caused by a small metal buckle on a singlet strap), (C) interference from an electronic device, (D) a clenched jaw, (E) alpha waves, and (F) trapped magnetic flux. For panels C, E, and F, the time scale on the x-axis is in 10-second intervals, and amplitude scale on the y-axis is 32768 A/D. <a href="https://www.jove.com/files/ftp_upload/58909/58909fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/58909/58909fig2.jpg" /> 
Figure 2. Pediatric MEG data before and after Real-Time Head Movement (ReTHM) correction. Data was collected from a three-year-old boy who passively listened to auditory tones for 15 min. Averaged in-scanner head movements were 44.3 mm. (A) More focused isofield contour maps at the peak of the root mean square (RMS) waveforms; (B) less distorted RMS magnetic waveforms, and (C) more meaningful source reconstruction in the bilateral auditory lobes are revealed after ReTHM correction. <a href="https://www.jove.com/files/ftp_upload/58909/58909fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Supplementary Figure 1" src="/files/ftp_upload/58909/58909supfig1.jpg" /> 
Supplementary Figure 1: A story board outlining 10 simple steps for completing the &#34;astronaut training&#34; (i.e., the MEG experiment). This is sent to families prior to visiting the MEG laboratory in order to guide children&#39;s expectations for the acquisition session, as well as to build excitement in anticipation of the &#34;astronaut training&#34;. On data acquisition day, the children follow the story as the experiment progresses and collect stamps after completing each step. Photographs reproduced with informed written parental consent. <a href="https://www.jove.com/files/ftp_upload/58909/58909supfig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Supplementary Figure 2" src="/files/ftp_upload/58909/58909supfig2v2.jpg" /> 
Supplementary Figure 2: An MEG information sheet for parents or caregivers explaining the MEG, the MSR, what to expect on data acquisition day and what to wear. Photograph reproduced with informed written parental consent. <a href="https://www.jove.com/files/ftp_upload/58909/58909supfig2v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

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Studying Brain Function in Children Using Magnetoencephalography

This article introduces a child-friendly research protocol designed to improve data quality by reducing head movement during pediatric magnetoencephalography (MEG). We familiarize families with the MEG environment, train children to remain still using an MEG simulator, and correct for residual head movement artefacts using a real-time head movement detection system.

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique which directly measures magnetic fields produced by the electrical activity of the ...

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9.1K Views.  Macquarie University. This article introduces a child-friendly research protocol designed to improve data quality by reducing head movement during pediatric magnetoencephalography (MEG). We familiarize families with the MEG environment, train children to remain still using an MEG simulator, and correct for residual head movement artefacts using a real-time head movement detection system.

Video: Studying Brain Function in Children Using Magnetoencephalography

Functional Mapping with Simultaneous MEG and EEG

We use magnetoencephalography (MEG) and electroencephalography (EEG) to locate and determine the temporal evolution in brain areas involved in the processing of simple sensory stimuli. We will use somatosensory stimuli to locate the hand somatosensory areas, auditory stimuli to locate the auditory cortices, visual stimuli in four quadrants of the visual field to locate the early visual areas. These type of experiments are used for functional mapping in epileptic and brain tumor patients to locate eloquent cortices. In basic neuroscience similar experimental protocols are used to study the orchestration of cortical activity. The acquisition protocol includes quality assurance procedures, subject preparation for the combined MEG/EEG study, and acquisition of evoked-response data with somatosensory, auditory, and visual stimuli. We also demonstrate analysis of the data using the equivalent current dipole model and cortically-constrained minimum-norm estimates. Anatomical MRI data are employed in the analysis for visualization and for deriving boundaries of tissue boundaries for forward modeling and cortical location and orientation constraints for the minimum-norm estimates.

We use magnetoencephalography (MEG) and electroencephalography (EEG) to map brain areas involved in the processing of simple sensory stimuli.

We use magnetoencephalography (MEG) and electroencephalography (EEG) to locate and determine the temporal evolution in brain areas involved in the ...

How to Detect Amygdala Activity with Magnetoencephalography using Source Imaging

In trace fear conditioning a conditional stimulus (CS) predicts the occurrence of the unconditional stimulus (UCS), which is presented after a brief stimulus free period (trace interval)1. Because the CS and UCS do not co-occur temporally, the subject must maintain a representation of that CS during the trace interval. In humans, this type of learning requires awareness of the stimulus contingencies in order to bridge the trace interval2-4. However when a face is used as a CS, subjects can implicitly learn to fear the face even in the absence of explicit awareness*. This suggests that there may be additional neural mechanisms capable of maintaining certain types of "biologically-relevant" stimuli during a brief trace interval. Given that the amygdala is involved in trace conditioning, and is sensitive to faces, it is possible that this structure can maintain a representation of a face CS during a brief trace interval.
It is challenging to understand how the brain can associate an unperceived face with an aversive outcome, even though the two stimuli are separated in time. Furthermore investigations of this phenomenon are made difficult by two specific challenges. First, it is difficult to manipulate the subject's awareness of the visual stimuli. One common way to manipulate visual awareness is to use backward masking. In backward masking, a target stimulus is briefly presented (&lt; 30 msec) and immediately followed by a presentation of an overlapping masking stimulus5. The presentation of the mask renders the target invisible6-8. Second, masking requires very rapid and precise timing making it difficult to investigate neural responses evoked by masked stimuli using many common approaches. Blood-oxygenation level dependent (BOLD) responses resolve at a timescale too slow for this type of methodology, and real time recording techniques like electroencephalography (EEG) and magnetoencephalography (MEG) have difficulties recovering signal from deep sources.
However, there have been recent advances in the methods used to localize the neural sources of the MEG signal9-11. By collecting high-resolution MRI images of the subject's brain, it is possible to create a source model based on individual neural anatomy. Using this model to "image" the sources of the MEG signal, it is possible to recover signal from deep subcortical structures, like the amygdala and the hippocampus*.

This article describes how to record amygdala activity with magnetoencephalography (MEG). In addition this article will describe how to conduct trace fear conditioning without awareness, a task that activates the amygdala. It will cover 3 topics: 1) Designing a trace conditioning paradigm using backward masking to manipulate awareness. 2) Recording brain activity during the task using magnetoencephalography. 3) Using source imaging to recover signal from subcortical structures.

In trace fear conditioning a conditional  stimulus (CS) predicts the occurrence of the unconditional stimulus (UCS),  which is presented after a brief ...

Behavior

Cortical Source Analysis of High-Density EEG Recordings in Children

EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2, because the composition and spatial configuration of head tissues changes dramatically over development3.&#160;
In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how&#160;EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis.&#160;

In recent years, there has been increasing interest in estimating the cortical sources of scalp measured electrical activity for cognitive neuroscience experiments. This article describes how high density EEG is acquired and how recordings are processed for cortical source estimation in children from the age of 2 years at the London Baby Lab.

EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and ...

Brain State-dependent Brain Stimulation with Real-time Electroencephalography-Triggered Transcranial Magnetic Stimulation

The effect of a stimulus to the brain depends not only on the parameters of the stimulus but also on the dynamics of brain activity at the time of the stimulation. The combination of electroencephalography (EEG) and transcranial magnetic stimulation (TMS) in a real-time brain state-dependent stimulation system allows the study of relations of dynamics of brain activity, cortical excitability, and plasticity induction. Here, we demonstrate a newly developed method to synchronize the timing of brain stimulation with the phase of ongoing EEG oscillations using a real-time data analysis system. This real-time EEG-triggered TMS of the human motor cortex, when TMS is synchronized with the surface EEG negative peak of the sensorimotor &#181;-alpha (8-14 Hz) rhythm, has shown differential corticospinal excitability and plasticity effects. The utilization of this method suggests that real-time information about the instantaneous brain state can be used for efficacious plasticity induction. Additionally, this approach enables personalized EEG-synchronized brain stimulation which may lead to the development of more effective therapeutic brain stimulation protocols.

This paper describes real-time electroencephalography-triggered transcranial magnetic stimulation to study and modulate human brain networks.

The effect of a stimulus to the brain depends not only on the parameters of the stimulus but also on the dynamics of brain activity at the time of the ...

EEG Mu Rhythm in Typical and Atypical Development

Electroencephalography (EEG) is an effective, efficient, and noninvasive method of assessing and recording brain activity. Given the excellent temporal resolution, EEG can be used to examine the neural response related to specific behaviors, states, or external stimuli. An example of this utility is the assessment of the mirror neuron system (MNS) in humans through the examination of the EEG mu rhythm. The EEG mu rhythm, oscillatory activity in the 8-12 Hz frequency range recorded from centrally located electrodes, is suppressed when an individual executes, or simply observes, goal directed actions. As such, it has been proposed to reflect activity of the MNS. It has been theorized that dysfunction in the mirror neuron system (MNS) plays a contributing role in the social deficits of autism spectrum disorder (ASD). The MNS can then be noninvasively examined in clinical populations by using EEG mu rhythm attenuation as an index for its activity. The described protocol provides an avenue to examine social cognitive functions theoretically linked to the MNS in individuals with typical and atypical development, such as ASD.&#160;

Assessment of the EEG mu rhythm provides a unique methodology for examining brain activity and when combined with behaviorally based assays, can be a powerful tool for elucidating aspects of social cognition, such as imitation, in clinical populations.

Electroencephalography (EEG) is an effective, efficient, and noninvasive method of assessing and recording brain activity. Given the excellent temporal ...

Medicine

Measurement Of Neuromagnetic Brain Function In Pre-school Children With Custom Sized MEG

Magnetoencephalography is a technique that detects magnetic fields associated with cortical activity [1]. The electrophysiological activity of the brain generates electric fields  - that can be recorded using electroencephalography (EEG)- and their concomitant magnetic fields  - detected by MEG. MEG signals are detected by specialized sensors known as superconducting quantum interference devices (SQUIDs). Superconducting sensors require cooling with liquid helium at -270 &deg;C. They are contained inside a vacumm-insulated helmet called a dewar, which is filled with liquid. SQUIDS are placed in fixed positions inside the helmet dewar in the helium coolant, and a subject's head is placed inside the helmet dewar for MEG measurements. The helmet dewar must be sized to satisfy opposing constraints. Clearly, it must be large enough to fit most or all of the heads in the population that will be studied. However, the helmet must also be small enough to keep most of the SQUID sensors within range of the tiny cerebral fields that they are to measure. Conventional whole-head MEG systems are designed to accommodate more than 90% of adult heads. However adult systems are not well suited for measuring brain function in pre-school chidren whose heads have a radius several cm smaller than adults. The KIT-Macquarie Brain Research Laboratory at Macquarie University uses a MEG system custom sized to fit the heads of pre-school children. This child system has 64 first-order axial gradiometers with a 50 mm baseline[2] and is contained inside a magnetically-shielded room (MSR) together with a conventional adult-sized MEG system [3,4]. There are three main advantages of the customized helmet dewar for studying children. First, the smaller radius of the sensor configuration brings the SQUID sensors into range of the neuromagnetic signals of children's heads. Second, the smaller helmet allows full insertion of a child's head into the dewar. Full insertion is prevented in adult dewar helmets because of the smaller crown to shoulder distance in children. These two factors are fundamental in recording brain activity using MEG because neuromagnetic signals attenuate rapidly with distance. Third, the customized child helmet aids in the symmetric positioning of the head and limits the freedom of movement of the child's head within the dewar. When used with a protocol that aligns the requirements of data collection with the motivational and behavioral capacities of children, these features significantly facilitate setup, positioning, and measurement of MEG signals.

The advent of MEG systems sized for young children opens important new opportunities to study brain development. The new system, together with a protocol that aligns experimental requirements with the capacities of children, can be used to study cognitive and language processes in healthy, awake children aged three to six.

Magnetoencephalography is a technique that detects magnetic fields associated with cortical activity [1]. The electrophysiological activity of the brain ...

Biology

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

Crucial to the success of epilepsy surgery is the availability of a robust biomarker that identifies the Epileptogenic Zone (EZ). High Frequency Oscillations (HFOs) have emerged as potential presurgical biomarkers for the identification of the EZ in addition to Interictal Epileptiform Discharges (IEDs) and ictal activity. Although they are promising to localize the EZ, they are not yet suited for the diagnosis or monitoring of epilepsy in clinical practice. Primary barriers remain: the lack of a formal and global definition for HFOs; the consequent heterogeneity of methodological approaches used for their study; and the practical difficulties to detect and localize them noninvasively from scalp recordings. Here, we present a methodology for the recording, detection, and localization of interictal HFOs from pediatric patients with refractory epilepsy. We report representative data of HFOs detected noninvasively from interictal scalp EEG and MEG from two children undergoing surgery.
The underlying generators of HFOs were localized by solving the inverse problem and their localization was compared to the Seizure Onset Zone (SOZ) as this was defined by the epileptologists. For both patients, Interictal Epileptogenic Discharges (IEDs) and HFOs were localized with source imaging at concordant locations. For one patient, intracranial EEG (iEEG) data were also available. For this patient, we found that the HFOs localization was concordant between noninvasive and invasive methods. The comparison of iEEG with the results from scalp recordings served to validate these findings. To our best knowledge, this is the first study that presents the source localization of scalp HFOs from simultaneous EEG and MEG recordings comparing the results with invasive recordings. These findings suggest that HFOs can be reliably detected and localized noninvasively with scalp EEG and MEG. We conclude that the noninvasive localization of interictal HFOs could significantly improve the presurgical evaluation for pediatric patients with epilepsy.

High Frequency Oscillations (HFOs) have emerged as presurgical biomarkers for the identification of the epileptogenic zone in pediatric patients with medically refractory epilepsy. A methodology for the noninvasive recording, detection, and localization of HFOs with simultaneous scalp electroencephalography (EEG) and magnetoencephalography (MEG) is presented.

Crucial to the success of epilepsy surgery is the availability of a robust biomarker that identifies the Epileptogenic Zone (EZ). High Frequency ...

Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography

Pre-stimulus oscillatory brain activity influences upcoming perception. The characteristics of this pre-stimulus activity can predict whether a near-threshold stimulus will be perceived or not perceived, but can they also predict which one of two competing stimuli with different perceptual contents is perceived? Ambiguous visual stimuli, which can be seen in one of two possible ways at a time, are ideally suited to investigate this question. Magnetoencephalography (MEG) is a neurophysiological measurement technique that records magnetic signals emitted as a result of brain activity. The millisecond temporal resolution of MEG allows for a characterization of oscillatory brain states from as little as 1 second of recorded data. Presenting an empty screen around 1 second prior to the ambiguous stimulus onset therefore provides a time window in which one can investigate whether pre-stimulus oscillatory activity biases the content of upcoming perception, as indicated by participants&#39;&#160;reports. The spatial resolution of MEG is not excellent, but sufficient to localise sources of brain activity at the centimetre scale. Source reconstruction of MEG activity then allows for testing hypotheses about the oscillatory activity of specific regions of interest, as well as the time- and frequency-resolved connectivity between regions of interest. The described protocol enables a better understanding of the influence of spontaneous, ongoing brain activity on visual perception.

This article describes how to set up an experiment that allows detecting pre-stimulus source-level influences on object perception using magnetoencephalography (MEG). It covers stimulus material, experimental design, MEG recording, and data analysis.

Pre-stimulus oscillatory brain activity influences upcoming perception. The characteristics of this pre-stimulus activity can predict whether a ...

Integrating MEG and HD-EEG in Pediatric Epilepsy Localization

Electromagnetic Source Imaging in Presurgical Evaluation of Children with Drug-Resistant Epilepsy

For children with drug-resistant epilepsy (DRE), seizure freedom relies on the delineation and resection (or ablation/disconnection) of the epileptogenic zone (EZ) while preserving the eloquent brain areas. The development of a reliable and noninvasive localization method that provides clinically useful information for the localization of the EZ is, therefore, crucial to achieving successful surgical outcomes. Electric and magnetic source imaging (ESI and MSI) have been increasingly utilized in the presurgical evaluation of these patients showing promising findings in the delineation of epileptogenic as well as eloquent brain areas. Moreover, the combination of ESI and MSI into a single solution, namely electromagnetic source imaging (EMSI), performed on simultaneous high-density electroencephalography (HD-EEG) and magnetoencephalography (MEG) recordings has shown higher source localization accuracy than either modality alone. Despite these encouraging findings, such techniques are performed in only a few tertiary epilepsy centers, are rarely recorded simultaneously, and are underutilized in pediatric cohorts. This study illustrates the experimental setup for recording simultaneous MEG and HD-EEG data as well as the methodological framework for analyzing these data aiming to localize the irritative zone, the seizure onset zone, and eloquent brain areas in children with DRE. More specifically, the experimental setups are presented for (i) recording and localizing interictal and ictal epileptiform activity during sleep and (ii) recording visual-, motor-, auditory-, and somatosensory-evoked responses and mapping relevant eloquent brain areas (i.e., visual, motor, auditory, and somatosensory) during visuomotor task, as well as auditory and somatosensory stimulations. Detailed steps of the data analysis pipeline are further presented for performing EMSI as well as individual ESI and MSI using equivalent current dipole (ECD) and dynamic statistical parametric mapping (dSPM).

Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization

Magnetoencephalography (MEG) and high-density electroencephalography (HD-EEG) are rarely recorded simultaneously, although they yield confirmatory and complementary information. Here, we illustrate the experimental setup for recording simultaneous MEG and HD-EEG and the methodology for analyzing these data aiming to localize epileptogenic and eloquent brain areas in children with drug-resistant epilepsy.

For children with drug-resistant epilepsy (DRE), seizure freedom relies on the delineation and resection (or ablation/disconnection) of the epileptogenic ...

Electro-encephalography (EEG)

EEG is a non-invasive technique that can measure brain activity. The neural activity generates electrical signals that are recorded by EEG electrodes placed on the scalp. When an individual is engaged in performing a cognitive task, brain activity changes and these changes can be recorded on the EEG graph. Therefore, it is a powerful tool for cognitive scientist aiming to better understand the neural correlates associated with different aspects of cognition, which will ultimately help them devise improved treatments for patients with cognitive deficits.
Here, JoVE presents a brief overview of EEG and its applications in cognitive research. First, we discuss where and how EEG signals are generated. Then, we explain the use of EEG in studying cognition along with a detailed step-by-step protocol to perform an EEG experiment. Lastly, the video reviews some specific cognitive experiments that use EEG in combination with other techniques such as functional Magnetic Resonance imaging (fMRI) or transcranial direct current stimulation (tDCS).

EEG: EEG Signal Origin, Even Related Potentials &amp; Cognition

EEG is a non-invasive technique that can measure brain activity.  The neural activity generates electrical signals that are recorded by EEG electrodes ...