We thank Ms Shuo Tian for the digital technology support. This study was supported by the Wu Jieping Foundation (Grant No. 320.6750.18456).

This study was approved by the Academic Ethics Committee of Inner Mongolia Medical University in Hohhot, China. The parents of all children included in this study provided signed and informed consent. In the study, we used the Actigraph GT3X+ device which is referred to as an accelerometer hereafter.
1. General aspects of method development
<ol>
	<li>Obtain accelerometers to evaluate PA. The accelerometer is a small (3.3 cm x 4.6 cm x 1.5 cm, 19 g), watch-like unobtrusive device that measures acceleration in three axes: vertical, antero-posterior, and medio-lateral.</li>
	<li>Connect the device to a laptop PC with USB cable. Use an exclusive software for data recording, processing, and analyzing.</li>
	<li>Select participants according to the following inclusion/exclusion criteria.
	<ol>
		<li>Include 20 children between 7-12 years of age who accept table tennis training as the Sports group. Include children who attend the table tennis club regularly, with three-to-five weekly training session,s with each training session lasting 2 h. Include children living majorly in a house or rented flat with their parents with a short home-to-club distance.</li>
		<li>Select 20 children from the same class as the Sports group as an age and gender matched Control group. Children of the Control group don&#39;t attend any sports club.</li>
	</ol>
	</li>
	<li>Exclude participants whose parents do not know their children&#39;s PA information at school and home.</li>
	<li>Exclude participants who were diagnosed to have any neurodevelopment disorder such as Attention Deficit and Hyperactivity Disorder (ADHD), autism, Developmental Coordination Disorder (DCD), etc.</li>
</ol>
2. Initialization of data collection using the accelerometer
<ol>
	<li>Download and run the software for the device.</li>
	<li>Type in the duration for collecting data by clicking the button Select Start Time and entering the date (e.g., 2022/2/9) and time (e.g., 13:00).</li>
	<li>Click the button Enter Subject Info to enter the next step about demographic information setting. Type in the demographic information of the participant, including name, gender, height, weight, date of birth, ethnic, side (right), limb (waist), and dominance (dominant). 
	NOTE: For the left-handed participants, in step 2.4 select the opposite side.</li>
	<li>Initialize the data collection by clicking Initialize 1 device. Make sure that the battery is charged to more than 80%, otherwise the initialization will fail. Initialize to record raw accelerations at a frequency of 30 Hz.</li>
	<li>Instruct the participants to wear the accelerometer on the right hip with an elastic waistband. Ensure that the accelerometer is positioned on the right mid-axilla line at the level of the iliac crest.</li>
	<li>Repeat step 2.2. Set the same start date (e.g., 2022/2/9) and time (e.g., 13:00), to ensure that the data from both devices is collected at the same time.</li>
	<li>Repeat 2.4 with the following modifications: side (left), limb (wrist), dominance (non-dominant). 
	NOTE: For the left-handed participants, in step 2.8 select the opposite side.</li>
	<li>Instruct the participants to wear the accelerometer on the wrist of the non-dominant hand on a watch belt.</li>
	<li>Remind the participants to wear the devices all day long, except while bathing, swimming, and showering. 
	NOTE: The duration of data collection should not be shorter than 7 days. (e.g., from 13:00, 2022/2/9 to 12:59, 2022/2/16).</li>
	<li>For the raw data collected, get the data confirmed by a physician, institutional researcher, or professional coach, according to the VM chart and counts (Figure 1).</li>
	<li>Delete any extreme data that is unexplained (e.g., from 21:41, 2022/2/12 to 22:07, 2022/2/12, the data was zero, and cannot be explained). Delete such data from the collected raw data.</li>
</ol>
3. Data collection from diary entries
<ol>
	<li>Ask the participants to wear the device all day long. Ask the trainers to maintain a diary of table tennis training, including the exact time schedule. For the children of the Control group, no diary of training is needed.</li>
	<li>Make sure that the participants performed their daily routines during data collection.</li>
	<li>Ask the parents to maintain a diary of leisure time at home. Instruct the parents to collect the data of sleep, the time to bed, and the time of waking up in the diary.</li>
</ol>
4. Accelerometer data output
<ol>
	<li>Take off the device from the right hip and connect it to a laptop/PC with a USB cable. Run the software of the device.</li>
	<li>Download the accelerometer data of the participant, by clicking Download. Analyze raw accelerometer data in 60 s epochs.</li>
	<li>Take off the device from the non-dominant hand and connect it to a laptop/PC with a USB cable. Repeat step 4.2.</li>
	<li>Raw acceleration outcome variables for the accelerometer are based on vector magnitude (VM) counts. Confirm the accelerometer data of LTPA according to the diary of training, leisure time, and sleep.</li>
</ol>
5. Scoring the data
<ol>
	<li>Open the scoring page of the software (Figure 2).</li>
	<li>Select Algorithms &#62; Cut Points and MVPA &#62; Puyau Children (2002) on the left of the page. 
	NOTE: Other algorithms for the cut points of PA can be selected if necessary.</li>
	<li>Click Calculate and then Export, and the scoring output will be displayed automatically, including SBs (sedentary behaviors), LPAs (light physical activities), MPAs (moderate physical activities), and MVPAs (moderate-to-vigorous physical activities).</li>
	<li>Obtain everyday-LTPA by adding diary timing and defining leisure time (e.g., the leisure time of 2022/2/9 is from 19:00, 2022/2/9 to 21:00 2022/2/6, according to the diary). Then, define the mean VM counts during this time as 715.75, and the LTPA for this epoch as 715.75.</li>
	<li>Average all the everyday-LTPAs, to get the LTPA for the participant.</li>
</ol>
6. Statistical analysis
<ol>
	<li>Use Student&#39;s t-test to measure group differences with a P value less than 0.05 considered statistically significant. Use a commercially available statistical software package to conduct all statistics.</li>
	<li>Use the Bland-Altman procedures to assess agreement for each PA, including MPA, VPA, and MVPA, between hip-worn and wrist-worn devices based on raw data and counts. Calculate the mean difference between the two methods of measurement and 95% limit of agreement for the mean difference calculated.</li>
</ol>

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The authors have nothing to disclose.

As shown in Table 1, children in the Sports group exhibited a significantly higher VPA and MVPA (64.20 &#177; 2.33 vs 57.85 &#177; 3.36, P &#60; 0.001) relative to those in the Control group. According to the findings of previous reports in both adolescents25 and young adults26, accelerometer devices represent an accurate method for the estimation of PA, relative to subjective surveys.
Bland-Altman plots demonstrated that there were high levels of agreement for MPA, VPA, and MVPA between hip-worn and wrist-worn accelerometer data (shown in Figure 3). This result indicated that these devices can also be worn on the wrist to assess PA. However, we must highlight that the agreement between hip-worn and wrist-worn accelerometer data for MPA was lower than that of VPA. This is because in low strength PA, such as sitting in the classroom or doing homework, the hip-worn accelerometer graph mainly reflects the movement of the body&#39;s center of gravity, while the wrist-worn accelerometer graph mainly reflects the movement of the non-dominant upper extremity. In addition, considering the different levels of compliance between hip-worn and wrist-worn devices, it is important to select the most appropriate device to evaluate PA in children undergoing table tennis training in clubs.
The critical steps in the protocol are to confirm the availability of the raw VM count data and the accelerometer data for LTPA. In other words, the main challenge will be to ensure that the data undergo quality control in a strict manner. It is highly recommended to use data plotting to monitor the data from each participant. Periods in which the device was not worn can be identified as long strings of zero counts and must be removed from the final dataset, even if the participants do not report this period as a time when they were not wearing the device. Leisure time and sleep diaries are useful for identifying LTPA; consequently, it is necessary that the parents or caregivers acknowledge their children&#39;s daily information in a precise manner.
The software used by the accelerometer contains several algorithms that are suitable for children, including the Puyau Children (2002) algorithm, the Freedson Children (2005) algorithm, and the Mattock Children (2007) algorithm. The Everson Children (2008) algorithm was previously chosen to evaluate the PA of children and adolescents in Tibet27, while the Pate Preschool (2006) algorithm was chosen to evaluate PA in preschoolers residing in Shanghai, China28. In our present study, we used the Puyau Children (2002) algorithm because it is the most useful method with which to classify children according to body mass index and fat mass percentage29.
In addition, we needed to elucidate the exact equations to use; this was determined by the specific type of accelerometer device used to acquire the raw data (see the equation below).
VM = <img alt="Equation 1" src="/files/ftp_upload/63937/63937eq01.jpg" style="margin: auto;" />
In the equation, X, Y, and Z are the vector magnitude counts for the X-axis, Y-axis, and Z-axis, respectively. LTPA represents the average PA during leisure time.
The triaxial VM counts per minute cut-off for different PA intensities were determined by the Puyau Children (2002) algorithm, as follows: sedentary behaviors &#60;799; light PA = 800 to 3199; moderate PA = 3200 to 8199; vigor PA &#62;8200; and moderate and vigor PA &#62;3200. In future, different types of algorithms will be modified to provide an optimized algorithm for the specific characteristics of subjects.
The accelerometer device has three main limitations that need to be considered. First, the hip-worn method is thought to be the best choice for reflecting PA; however, this method shows poorer compliance relative to wrist-worn devices, especially for young children30. Second, the complexity and high price of the device (including software) can impede the utility of the accelerometer device and software in a home environment. Otherwise, clinical staff, institutional researchers, and sports-club coaches can easily manage this method, and the associated cost will decrease if the device is widely reused. Third, accelerometer devices only have a basic waterproof guarantee; thus, these devices should not be used for some sports participants, such as those undertaking sailing, rowing, and swimming.
There are some alternative methods that could be used instead of accelerometers. For example, many cell phones have similar functions for measuring PA, albeit with relatively low reliability and validity. Other studies have reported more cost-effective pedometers that are suitable for individuals31. Further research needs to identify the reliability and validity of all alternative methods.
Collectively, our results indicate that both hip-worn and wrist-worn accelerometers can effectively measure PA and are highly suitable for Chinese children undertaking table tennis training in clubs. These methods also can be used to evaluate PA in both healthy individuals and children with developmental disorders such as cerebral palsy32, autism33, and ADHD34.
The device used here is considered as the gold standard for measuring PA, as mentioned earlier. However, preliminary reports suggest that these devices can also measure sleep quality, circadian rhythm, and rest-activity rhythm in clinical practice35,36. Further investigations are now needed to widen the scope and application of these devices. These devices can also be helpful in monitoring PA in children undertaking table tennis training in clubs. Together with subjective questionnaires, such as the Health Behavior in School-aged Children Questionnaire and the International Physical Activity Questionnaire, this method is capable of demonstrating the PA of children in a highly effective manner.

Physical activity (PA) is very important in childhood and is positively associated with physical and mental health. It is well documented that PA is associated with beneficial effects in school-going children with regards to obesity, bone health, mental wellbeing, cognitive function, and academic achievements1,2,3. However, most children in China still experience lower levels of PA than recommended for their age4; furthermore, sedentary time is known to increase with age. According to the National Physical Fitness and Health Surveillance Study for Students in China, the number of students with obesity has remained significantly high over the first two decades of the 21st century5.
International PA guidelines for children and adolescents recommend at least 60 min of moderate-to-vigorous physical activity (MVPA) per day and vigorous physical activity (VPA) on 3 days/week6 in order to achieve health benefits. Similarly, the latest version of the Physical Activity Guidelines for Chinese (2021)7 highlights that accumulated sedentary behavioral time should not last for more than 60 min, based on international PA guidelines. Participation in sports clubs or school activities is a highly beneficial way by which children can meet PA guidelines8. Table tennis is a compound and technically difficult game that is popular in China. Recent studies have confirmed that regular table tennis training has a positive effect on the health-related physical fitness of children and adolescents9,10. As such, table tennis club/school-based training is a very suitable method for children to increase their levels of PA11.
It is important to consider several issues that might impede the fulfillment of the recommendations made by international PA guidelines. For example, most surveys of PA in children are based on parent-reported questionnaires12; there is a significant lack of data acquired by objective methods in China. Furthermore, the activity patterns of children are characterized by relatively short bouts of spontaneous, but intense PA13,14. This type of pattern is difficult to summarize and report by observation alone; additionally, questionnaires or parental reports are prone to error15. Secondly, children spend a significant amount of leisure time at home, for example, during the evenings and weekends, and tend to accumulate a substantial part of their daily PA in a home-based setting. It is difficult to collect or estimate leisure time physical activity (LTPA) in children outside of school hours. LTPA is essential for health and is one of the most important components of total PA16. Thirdly, the PA of children may be influenced by gender differences and parental life style8. Collectively, this information highlights the need to acquire accurate measurements of PA to evaluate overall health, its social impact, and its use in policy making. If the activity levels of specific subpopulations (e.g., children undergoing table tennis training) are not correctly estimated, it is possible that the data may even misdirect policies and public health priorities12.
As the most widely used objective measurement for PA patterns in youths, accelerometers have been recognized as the gold standard for measuring PA in children17,18,19,20. With technological improvements, actigraphic devices have progressed into cost-effective capacitive sensors. In most cases, these devices need to be attached to the right hip21, an issue that might be a potential risk factor and lowers compliance22. Over recent years, several research studies have indicated that PA data derived from devices worn at other anatomical locations can be comparable when set-up appropriately23,24.
In the present study, we aimed to develop a wrist-worn actigraphy accelerometer-based method to assess PA in children undergoing table tennis training.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Actigraph&#160;</td>
			<td>ActiGraph Corp</td>
			<td>&#160;GT3X+</td>
			<td>device</td>
		</tr>
		<tr>
			<td>ActiLife</td>
			<td>ActiGraph Corp</td>
			<td>&#160;v6.13.3</td>
			<td>software</td>
		</tr>
		<tr>
			<td>SPSS 22.0 software</td>
			<td></td>
			<td></td>
			<td>statistical analysis software</td>
		</tr>
	</tbody>
</table>

physical activity measurement in children accepting table tennis training

An increasing body of evidence now shows that the majority of children in China experience lower levels of physical activity (PA) than the recommended guideline. Table tennis is a compound and technically difficult game that is popular in China; undertaking table tennis training in clubs can help children to elevate their levels of PA. Given that children cannot complete self-evaluated questionnaires themselves and caregiver-based observations are not suitable for children, we hypothesized that an actigraphy-based method can be an objective method to measure PA. In the present study, we describe a procedure that can be used to evaluate PA levels using an actigraphic device and software. Furthermore, since hip-worn devices are known to reduce compliance, we attempted to assess the agreement between hip-worn and wrist-worn device data. Collectively, our results indicate that these devices are suitable for measuring PA and leisure time physical activity (LTPA) levels. Together with subjective questionnaires, both hip-worn and wrist-worn devices are highly suitable for evaluating PA in Chinese children undergoing table tennis training in clubs.

Demographic data are shown in Table 1, including&#160;gender, age, height, weight, ethnicity, and dominant hand. As shown in Table 1, there were no significant differences between the groups with regards to gender, age, height, weight, and dominant hand. Furthermore, participants from the Sports group did not exhibit any significantly different parameters in terms of sedentary behaviors (SB; 441.05 &#177; 31.80 vs 442.25 &#177; 30.74, P = 0.904), LPA (213.10 &#177; 15.00 vs 215.65 &#177; 17.41, P = 0.623), MPA (42.55 &#177; 3.80 vs 40.70 &#177; 2.85, P = 0.090), as well as LTPA (1514.20 &#177; 146.10 vs 1587.70 &#177; 182.25, P = 0.167). In contrast, children in the Sports group exhibited a significantly higher VPA (21.65 &#177; 3.43 vs 17.15 &#177; 4.01, P = 0.0001) and MVPA (64.20 &#177; 2.33 vs 57.85 &#177; 3.36, P &#60; 0.001) than those in the Control group.
The Bland-Altman plot was originally developed to compare data with two sets of measurements on one occasion. It was expected that 95% of the differences between the two measurement methods would fall within the 95% limit of agreement. As shown in Figure 3, Bland-Altman plots suggested that the agreement between hip-worn and wrist-worn accelerometer data was acceptable for MPA, VPA, and MVPA. There were two (10%), zero (0%), and three (15%) outliers from the 1.96 standard deviation value for MPA, VPA, and MVPA, respectively.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/63937/63937fig01.jpg" /> 
Figure 1: Vector magnitude counts (raw data) depicted as plots. The graphs on the left show the vector magnitude counts per day. The table on the right provides the exact vector magnitude count for each epoch (60 s). Four graphs for VM are magnified and shown at the bottom. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63937/63937fig01large.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/63937/63937fig02.jpg" /> 
Figure 2: The scoring page shown in the device software. The Puyau Children (2002) options for Cut Points and MVPA are accessible in the Algorithms section on the left. Scoring output can be obtained automatically by clicking the Calculate and Export buttons. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63937/63937fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/63937/63937fig03.jpg" /> 
Figure 3: Bland-Altman plot for physical activities using hip-worn and wrist-worn actigraphic devices. (A) Bland-Altman plot for MPA using hip-worn and wrist-worn actigraphic devices. (B) Bland-Altman plot for VPA using hip-worn and wrist-worn actigraphic devices. (C) Bland-Altman plot for MVPA using hip-worn and wrist-worn actigraphic devices. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63937/63937fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td></td>
			<td>Sports group</td>
			<td>Control group</td>
			<td>P value</td>
		</tr>
		<tr>
			<td>Gender (male/female)</td>
			<td>10 male/ 10 female</td>
			<td>8 male/ 12 femal</td>
			<td>0.537</td>
		</tr>
		<tr>
			<td>Age (years)</td>
			<td>9.85&#177;1.34</td>
			<td>9.80&#177;1.36</td>
			<td>0.908</td>
		</tr>
		<tr>
			<td>Height (cm)</td>
			<td>135.3&#177;9.41</td>
			<td>135.8&#177;9.43</td>
			<td>0.881</td>
		</tr>
		<tr>
			<td>Weight (kg)</td>
			<td>36.65&#177;7.25</td>
			<td>35.10&#177;4.84</td>
			<td>0.432</td>
		</tr>
		<tr>
			<td>Dominant hand (right%)</td>
			<td>15%</td>
			<td>10%</td>
			<td>0.643</td>
		</tr>
		<tr>
			<td>SBs (minutes)</td>
			<td>441.05&#177;31.80</td>
			<td>442.25&#177;30.74</td>
			<td>0.904</td>
		</tr>
		<tr>
			<td>LPA (minutes)</td>
			<td>213.10&#177;15.00</td>
			<td>215.65&#177;17.41</td>
			<td>0.623</td>
		</tr>
		<tr>
			<td>MPA (minutes)</td>
			<td>42.55&#177;3.80</td>
			<td>40.70&#177;2.85</td>
			<td>0.090</td>
		</tr>
		<tr>
			<td>VPA (minutes)</td>
			<td>21.65&#177;3.43</td>
			<td>17.15&#177;4.01</td>
			<td>0.001</td>
		</tr>
		<tr>
			<td>MVPA (minutes)</td>
			<td>64.20&#177;2.33</td>
			<td>57.85&#177;3.36</td>
			<td>&#60;0.000</td>
		</tr>
		<tr>
			<td>LTPA (VM counts/)</td>
			<td>1514.20&#177;146.10</td>
			<td>1587.70&#177;182.25</td>
			<td>0.167</td>
		</tr>
	</tbody>
</table>
Table 1: Demographic and actigraphic data. The table provides the demographic and actigraphic data collected from the Sports group and the Control group.&#160;Abbreviations:cm = centimeters; kg = kilograms; SBs = sedentary behaviors; LPA = light physical activity; MPA = moderate physical activity; VPA = vigorous physical activity; MVPA = moderate-to-vigorous physical activity; LTPA = leisure time physical activity; VM = vector magnitude.

Watch this Scientific Journal Video about Physical Activity Measurement in Children Accepting Table Tennis Training at JoVE.com

Physical Activity Measurement in Children Accepting Table Tennis Training

This study proposes an accelerometer-based method to objectively measure physical activity (PA) and leisure time physical activity (LTPA) in Chinese children accepting table tennis training in clubs.

An increasing body of evidence now shows that the majority of children in China experience lower levels of physical activity (PA) than the recommended ...

physical-activity-measurement-children-accepting-table-tennis

Nanyang Technological University

Research

JoVE Journal

Behavior

1.8K Views.  Inner Mongolia Medical University. This study proposes an accelerometer-based method to objectively measure physical activity (PA) and leisure time physical activity (LTPA) in Chinese children accepting table tennis training in clubs.

Video: Physical Activity Measurement in Children Accepting Table Tennis Training

Training Synesthetic Letter-color Associations by Reading in Color

Synesthesia is a rare condition in which a stimulus from one modality automatically and consistently triggers unusual sensations in the same and/or other modalities. A relatively common and well-studied type is grapheme-color synesthesia, defined as the consistent experience of color when viewing, hearing and thinking about letters, words and numbers. We describe our method for investigating to what extent synesthetic associations between letters and colors can be learned by reading in color in nonsynesthetes. Reading in color is a special method for training associations in the sense that the associations are learned implicitly while the reader reads text as he or she normally would and it does not require explicit computer-directed training methods. In this protocol, participants are given specially prepared books to read in which four high-frequency letters are paired with four high-frequency colors. Participants receive unique sets of letter-color pairs based on their pre-existing preferences for colored letters. A modified Stroop task is administered before and after reading in order to test for learned letter-color associations and changes in brain activation. In addition to objective testing, a reading experience questionnaire is administered that is designed to probe for differences in subjective experience. A subset of questions may predict how well an individual learned the associations from reading in color. Importantly, we are not claiming that this method will cause each individual to develop grapheme-color synesthesia, only that it is possible for certain individuals to form letter-color associations by reading in color and these associations are similar in some aspects to those seen in developmental grapheme-color synesthetes. The method is quite flexible and can be used to investigate different aspects and outcomes of training synesthetic associations, including learning-induced changes in brain function and structure.

Reading in color is a new method for training letter-color associations that are typically found only in grapheme-color synesthetes. It involves an implicit form of training that has potential for long-term associative training methods&#160;because the training is a byproduct of reading and any text can be colored.

Synesthesia is a rare condition in which a stimulus from one modality automatically and consistently triggers unusual sensations in the same and/or other ...

Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia

Adolescence is a critical developmental period where the early symptoms of schizophrenia frequently emerge. First-degree relatives of people with schizophrenia who are at familial high risk (FHR) may show similar cognitive and emotional changes. However, the neurological changes underlying the emergence of these symptoms remain unclear. This study sought to identify differences in frontal, striatal, and limbic regions in children and adolescents with FHR using functional magnetic resonance imaging. Groups of 21 children and adolescents at FHR and 21 healthy controls completed an emotional oddball task that relied on selective attention and the suppression of task-irrelevant emotional information. The standard oddball task was modified to include aversive and neutral distractors in order to examine potential group differences in both emotional and executive processing. This task was designed specifically to allow for children and adolescents to complete by keeping the difficulty and emotional image content age-appropriate. Furthermore, we demonstrate a technique for suitable fMRI registration for children and adolescent participants. This paradigm may also be applied in future studies to measure changes in neural activity in other populations with hypothesized developmental changes in executive and emotional processing.

This paper describes how to use the emotional oddball task and fMRI to measure brain activation in children and adolescents at familial high risk for schizophrenia (FHR).&#160;FMRI was used to measure differences in fronto-striato-limbic regions during an emotional oddball task. Children with FHR exhibited abnormal functional activation during adolescence.

Adolescence is a critical developmental period where the early symptoms of schizophrenia frequently emerge. First-degree relatives of people with ...

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 ...

Measuring Attentional Biases for Threat in Children and Adults

Investigators have long been interested in the human propensity for the rapid detection of threatening stimuli. However, until recently, research in this domain has focused almost exclusively on adult participants, completely ignoring the topic of threat detection over the course of development. One of the biggest reasons for the lack of developmental work in this area is likely the absence of a reliable paradigm that can measure perceptual biases for threat in children. To address this issue, we recently designed a modified visual search paradigm similar to the standard adult paradigm that is appropriate for studying threat detection in preschool-aged participants. Here we describe this new procedure. In the general paradigm, we present participants with matrices of color photographs, and ask them to find and touch a target on the screen. Latency to touch the target is recorded. Using a touch-screen monitor makes the procedure simple and easy, allowing us to collect data in participants ranging from 3 years of age to adults. Thus far, the paradigm has consistently shown that both adults and children detect threatening stimuli (e.g., snakes, spiders, angry/fearful faces) more quickly than neutral stimuli (e.g., flowers, mushrooms, happy/neutral faces). Altogether, this procedure provides an important new tool for researchers interested in studying the development of attentional biases for threat.

Here we describe a touch-screen visual search paradigm that can be used to study threat detection across the lifespan. The paradigm has already been used in various studies demonstrating that both children and adults detect threatening stimuli like snakes, spiders, and angry faces faster than non-threatening stimuli.

Investigators have long been interested in the human propensity for the rapid detection of threatening stimuli. However, until recently, research in this ...

Pavlovian Conditioned Approach Training in Rats

Cues that are contingently paired with unconditioned, rewarding stimuli can acquire rewarding properties themselves through a process known as the attribution of incentive salience, or the transformation of neutral stimuli into attractive, &#34;wanted&#39; stimuli capable of motivating behavior. Pavlovian conditioned approach (PCA) develops after the response-independent presentation of a conditioned stimulus (CS; e.g., a lever) that predicts the delivery of an unconditioned stimulus (US; e.g., a food pellet) and can be used to measure incentive salience. During training, three patterns of conditioned responses (CRs) can develop: sign-tracking behavior (CS-directed CR), goal-tracking behavior (US-directed CR), and an intermediate response (both CRs). Sign-trackers attribute incentive salience to reward-related cues and are more vulnerable to cue-induced reinstatement of drug-seeking as well as other addiction-related behaviors, making PCA a potentially valuable procedure for studying addiction vulnerability. Here, we describe materials and methods used to elicit PCA behavior from rats as well as analyze and interpret PCA behavior in individual experiments.

Here, we present a protocol to elicit Pavlovian conditioned approach behavior in rats. This procedure can be used to measure individual differences in the tendency to approach and attribute incentive salience to reward-related cues and investigate addiction vulnerability.

Cues that are contingently paired with unconditioned, rewarding stimuli can acquire rewarding properties themselves through a process known as the ...

Assessing Working Memory in Children: The Comprehensive Assessment Battery for Children &#8211; Working Memory (CABC-WM)

The Comprehensive Assessment Battery for Children - Working Memory (CABC-WM) is a computer-based battery designed to assess different components of working memory in young school-age children. Working memory deficits have been identified in children with language-based learning disabilities, including dyslexia1,2 and language impairment3,4, but it is not clear whether these children exhibit deficits in subcomponents of working memory, such as visuospatial or phonological working memory. The CABC-WM is administered on a desktop computer with a touchscreen interface and was specifically developed to be engaging and motivating for children. Although the long-term goal of the CABC-WM is to provide individualized working memory profiles in children, the present study focuses on the initial success and utility of the CABC-WM for measuring central executive, visuospatial, phonological loop, and binding constructs in children with typical development. Immediate next steps are to administer the CABC-WM to children with specific language impairment, dyslexia, and comorbid specific language impairment and dyslexia.

Working memory predicts a significant amount of variance for a variety of cognitive tasks, including speaking, reading, and writing. However, few tools are available to assess working memory in children. We present an innovative, computer-based battery that comprehensively assesses different components of working memory in school-age children.

The Comprehensive Assessment Battery for Children - Working Memory (CABC-WM) is a computer-based battery designed to assess different components of ...

Paradigms of Lower Extremity Electrical Stimulation Training After Spinal Cord Injury

Skeletal muscle atrophy, increased adiposity and reduced physical activity are key changes observed after spinal cord injury (SCI) and are associated with numerous cardiometabolic health consequences. These changes are likely to increase the risk of developing chronic secondary conditions and impact the quality of life in persons with SCI. Surface neuromuscular electrical stimulation evoked resistance training (NMES-RT) was developed as a strategy to attenuate the process of skeletal muscle atrophy, decrease ectopic adiposity, improve insulin sensitivity and enhance mitochondrial capacity. However, NMES-RT is limited to only a single muscle group. Involving multiple muscle groups of the lower extremities may maximize the health benefits of training. Functional electrical stimulation-lower extremity cycling (FES-LEC) allows for the activation of 6 muscle groups, which is likely to evoke greater metabolic and cardiovascular adaptation. Appropriate knowledge of the stimulation parameters is key to maximizing the outcomes of electrical stimulation training in persons with SCI. Adopting strategies for long-term use of NMES-RT and FES-LEC during rehabilitation may maintain the integrity of the musculoskeletal system, a pre-requisite for clinical trials aiming to restore walking after injury. The current manuscript presents a combined protocol using NMES-RT prior to FES-LEC. We hypothesize that muscles conditioned for 12 weeks prior to cycling will be capable of generating greater power, cycle against higher resistance and result in greater adaptation in persons with SCI.

Spinal cord injury is a traumatic medical condition that may result in elevated risks of chronic secondary metabolic disorders. Here, we presented a protocol using surface neuromuscular electrical stimulation-resistance training in conjunction with functional electrical stimulation-lower extremities cycling as a strategy to ameliorate several of these medical problems.

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Classical Short-Delay Eyeblink Conditioning in One-Year-Old Children

Classical eyeblink conditioning (EBC) refers to the learned association between a conditioned stimulus (an auditory tone) and an unconditioned stimulus (a puff of air to the cornea). Eyeblink conditioning is often used experimentally to detect abnormalities in cerebellar-dependent learning and memory that underlies this type of associative learning. While experiments in adults and older children are relatively simple to administer using commercial equipment, eyeblink conditioning in infants is more challenging due to their poor compliance, which makes correct positioning of the equipment difficult. To achieve conditioning in one-year-old infants, a custom-made or an adapted commercial system can be used to deliver the air puff to the infant's cornea. The main challenge lies in successfully detecting and classifying the behavioral responses. We report that automated blink detection methods are unreliable in this population, and that conditioning experiments should be analyzed using frame-by-frame analysis of supplementary video camera recordings. This method can be applied to study developmental changes in eyeblink conditioning and to examine whether this paradigm can detect children with neurological disorders.

This protocol describes an eyeblink conditioning paradigm appropriate for experiments with one-year-old infants. Commercial or custom-made equipment can be used to deliver the stimuli, and data collection and analysis should be performed on the video recordings.

Classical eyeblink conditioning (EBC) refers to the learned association between a conditioned stimulus (an auditory tone) and an unconditioned stimulus (a ...

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity

Physical activity (PA) assessment needs tools that are inexpensive and easy to administer. Common questionnaires inquire time spent in light, moderate, and vigorous PA. However, inaccuracies may occur due to individually different understanding of PA intensity levels. Alternatively used direct measures (e.g., accelerometers) are susceptible to reactivity bias and may lack the ability to capture certain activities. Compared to accelerometer measurement, respondents report more time spent in higher-intensity PA. A video that visualizes PA intensity levels might help to overcome this problem. This report describes the design of a randomized controlled trial as a methodology to investigate the effect of a video on the difference between self-reported and directly measured PA. It is hypothesized that the video reduces the mean difference between the two measures. Individuals from the general population are recruited. Hip-worn accelerometers are used to collect directly measured PA data on seven consecutive days. Afterwards, participants are randomly allocated to the experimental and the control group. The experimental group receives a video demonstration on PA intensity levels and subsequent PA assessment via self-administered computer-assisted questionnaire. The control group receives PA assessment only. Thereafter, the data are processed to compare the difference between self-reported and accelerometer-based moderate-to-vigorous physical activity (MVPA) between the study groups using a two-sample t-test. This methodology is appropriate for investigating the effect of any existing or self-produced video on the difference between the two measurement methods. It can be used not only for persons from the general population, but for a variety of other populations and contexts as accurate measures are needed to evaluate PA levels.

This protocol describes a randomized controlled trial as a method to test the effect of a video demonstration on the intra-individual difference between self-reported and accelerometer-based moderate-to-vigorous physical activity.

Physical activity (PA) assessment needs tools that are inexpensive and easy to administer. Common questionnaires inquire time spent in light, moderate, ...

Investigation into Deep Breathing through Measurement of Ventilatory Parameters and Observation of Breathing Patterns

In this protocol, two deep breathing patterns were shown to 15 participants to determine an easy yet effective method of breathing exercise for future application in a clinical setting. The women in their twenties were seated comfortably in a chair with back support. They were fitted with an airtight mask connected to a&#160;gas analyzer. Three electrodes were placed on the chest connected to a wireless transmitter for relaying to the electrocardiograph. They executed a 5 min rest phase, followed by 5 min of deep breathing with a natural breathing pattern, terminating with a 5 min rest phase. This was followed by a 10 min intermission before commencing the second instruction phase of substituting the natural breathing pattern with the diaphragmatic breathing pattern. Simultaneously, the following took place: a) continuous collection, measurement and analysis of the expired gas to assess the ventilatory parameters on a breath-by-breath basis; b) measurement of the heart rate by an electrocardiograph; and c) videotaping of the participant&#8217;s thoracoabdominal movement from a lateral aspect. From the video capture, the investigators carried out visual observation of the fast-forward motion-images followed by classification of the breathing patterns, confirming that the participants had carried out the method of deep breathing as instructed. The amount of oxygen uptake revealed that, during deep breathing, the work of breathing decreased. The results from the expired minute ventilation, respiration rate and tidal volume confirmed increased ventilatory efficiency for deep breathing with the natural breathing pattern compared to that with the diaphragmatic breathing pattern. This protocol suggests a suitable method of instruction for assessing deep breathing exercises on the basis of oxygen consumption, ventilatory parameters, and chest wall excursion.

Here, we present a protocol to assess two deep breathing patterns of natural and diaphragmatic breathing for their effectiveness and ease of execution. Fifteen participants were selected, utilizing an electrocardiograph and expired gas analyzer for measurement of the ventilatory parameters, together with visual assessment by video capture of thoracoabdominal movement.

In this protocol, two deep breathing patterns were shown to 15 participants to determine an easy yet effective method of breathing exercise for future ...