Changes in children’s screen time during pandemic

JAMA Pediatrics

Peer-Reviewed Publication

JAMA NETWORK

About The Study: The largest increase in children’s recreational screen time during the pandemic was on weekdays, especially at the outset of the pandemic when schools were closed; this increase was greater than expected for age-related growth. Change in weekend screen time during the pandemic was not significant compared with weekday screen time. Once in-person school resumed, weekday screen time decreased versus that during the COVID-1 wave (spring 2020), although it remained consistently higher than pre-pandemic estimates and age-related expectations. 

Authors: Sheri Madigan, Ph.D., of the University of Calgary in Calgary, Canada, is the corresponding author.

 link https://media.jamanetwork.com/  (doi:10.1001/jamapediatrics.2023.0393)

Research Letter

April 10, 2023

Changes in Children’s Recreational Screen Time During the COVID-19 Pandemic

André Plamondon, PhD¹; Brae Anne McArthur, PhD²; Rachel Eirich, MSc²; et alNicole Racine, PhD³; Sheila McDonald, PhD²; Suzanne Tough, PhD²; Sheri Madigan, PhD²

Author Affiliations Article Information

JAMA Pediatr. Published online April 10, 2023. doi:10.1001/jamapediatrics.2023.0393

The COVID-19 pandemic changed children’s daily lives, including their sedentary behavior.¹ A meta-analysis comparing the screen time duration of 29 017 children reported daily screen time increased from 1.4 hours prepandemic to 2.7 hours during the pandemic.² However, studies on children’s screen time compared differences from prepandemic to early in the pandemic, when restrictions and closures (eg, schools and gyms) were more prevalent.² It remains unknown if increases in screen time were sustained as pandemic restrictions changed. We compared children’s prepandemic screen time with screen time during 3 pandemic waves and assessed whether increases were greater than age-expected changes.

Methods

Participants were from All Our Families,^3,4 an ongoing pregnancy cohort of mothers and children from Calgary, Alberta, Canada (Table). Data included a 2018 survey of mothers and surveys of mothers and children during 3 pandemic waves: COVID 1 (spring 2020); COVID 2 (winter 2021), and COVID 3 (fall 2021). Screen time (ie, smartphone, tablet, gaming, or computer device use “for fun [outside of schoolwork]”) was reported in hours per typical weekday and weekend day. Schools were closed during the COVID-1 wave but were open during subsequent waves. The University of Calgary Institutional Ethics Board approved this cohort study. Written consent was obtained from participants. We followed the STROBE reporting guideline.

We performed multilevel modeling to compare waves of data collection while controlling for age (as a linear effect) using MPlus, version 8.8 (Muthén & Muthén). Two-sided P < .05 was considered significant. Data were analyzed from July 25 to November 11, 2022.

Results

Participants included 2123 mothers (mean [SD] age at pregnancy, 30.8 [4.4] years) and 1288 children (mean [SD] child age prepandemic, 7.9 [0.6] years; COVID-1 wave, 9.7 [0.8] years; COVID-2 wave, 10.4 [0.9] years; COVID-3 wave, 11.1 [0.8 years). We examined conditional means and 95% CIs across waves according to each participant type (Figure), controlling for age using a daily screen time of 0.12 to 0.15 hours per year of age.

For weekdays, mothers reported 1.35 (95% CI, 1.23-1.47) more mean daily hours of screen at COVID-1 wave vs prepandemic. At the COVID-2 wave, mothers and youths reported fewer hours in daily screen time vs the previous wave (Figure). Mothers reported a larger decrease than youths (−1.06 [95% CI, −1.15 to −0.97] hours vs −0.55 [−0.69 to −0.42] hours). Mean screen time did not differ between the COVID-2 and COVID-3 waves (Figure), although mean screen time was higher for both waves compared with that of prepandemic.

For weekends, participants reported increased mean daily screen time that did not differ significantly at each subsequent wave. However, when averaged, the increase in mean hours per day across waves reported by mothers (0.14 [95% CI, 0.07-0.21] hours) and youth (0.18 [95% CI, 0.10-0.26] hours) was significant. Compared with weekdays, on weekends mean hours of screen time did not significantly differ between prepandemic and COVID-1 wave, and concurrent maternal and youth reports of weekend screen time did not differ significantly.

Discussion

The largest increase in children’s recreational screen time during the pandemic was on weekdays, especially at the outset of the pandemic when schools were closed; this increase was greater than expected for age-related growth. Change in weekend screen time during the pandemic was not significant compared with weekday screen time. Once in-person school resumed, weekday screen time decreased vs that during the COVID-1 wave, although it remained consistently higher than prepandemic estimates and age-related expectations.

Participant agreement varied. Mothers and children reported similar time estimates when schools were closed, but differences in estimates were observed for weekdays when schools were open. If children are the best informants of their screen time, as they often are for their mental health,⁵ mothers may have underestimated daily weekday screen time or schools may have allowed more screen time when in-person learning resumed.

Study limitations include screen time measurement via self-report only and exclusion of other indicators of screen use: context (ie, connecting with others), content (eg, violent gaming), and type (eg, gaming vs smartphone) of screen use. These limitations warrant future research.

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Article Information

Accepted for Publication: January 22, 2023.

Published Online: April 10, 2023. doi:10.1001/jamapediatrics.2023.0393

Corresponding Author: Sheri Madigan, PhD, Department of Psychology, University of Calgary, 2500 University Ave, Calgary, AL T2N 1N4, Canada (sheri.madigan@ucalgary.ca).

Author Contributions: Drs Plamondon and Madigan had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Tough and Madigan are senior authors.

Concept and design: Plamondon, Eirich, Madigan.

Acquisition, analysis, or interpretation of data: Plamondon, McArthur, Racine, McDonald, Tough, Madigan.

Drafting of the manuscript: Plamondon, Madigan.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Plamondon, McArthur.

Obtained funding: Tough, Madigan.

Administrative, technical, or material support: Eirich, Tough, Madigan.

Supervision: Tough, Madigan.

Conflict of Interest Disclosures: Dr Tough reported receiving grants from Alberta Children’s Hospital Foundation outside the submitted work during the conduct of the study. No other disclosures were reported.

Funding/Support: The All Our Families study was funded by an Alberta Innovates Health Solutions Interdisciplinary Team grant 200700595 and the Alberta Children’s Hospital Foundation (Dr Tough). Funding for the data collection for the COVID-19 pandemic waves was provided by the Canadian Institutes of Health Research and the Children and Screens Institute of Digital Media and Child Development COVID-19 grant (Dr Madigan) and an Alberta Innovates grant (Dr Tough).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See the Supplement.

Additional Contributions: We acknowledge the contributions of the All Our Families research team who were compensated for their contributions to this work, and we thank the participants who took part in the study.

References

1.

Neville  RD, Lakes  KD, Hopkins  WG,  et al.  Global changes in child and adolescent physical activity during the COVID-19 pandemic: a systematic review and meta-analysis.   JAMA Pediatr. 2022;176(9):886-894. doi:10.1001/jamapediatrics.2022.2313
ArticlePubMedGoogle ScholarCrossref

2.

Madigan  S, Eirich  R, Pador  P, McArthur  BA, Neville  RD.  Assessment of changes in child and adolescent screen time during the COVID-19 pandemic: a systematic review and meta-analysis.   JAMA Pediatr. 2022;176(12):1188-1198. doi:10.1001/jamapediatrics.2022.4116
ArticlePubMedGoogle ScholarCrossref

3.

Tough  SC, McDonald  SW, Collisson  BA,  et al.  Cohort profile: the All Our Babies pregnancy cohort (AOB).   Int J Epidemiol. 2017;46(5):1389-1390k. doi:10.1093/ije/dyw363PubMedGoogle ScholarCrossref

4.

McDonald  SW, Lyon  AW, Benzies  KM,  et al.  The All Our Babies pregnancy cohort: design, methods, and participant characteristics.   BMC Pregnancy Childbirth. 2013;13(Suppl 1)(suppl 1):S2. doi:10.1186/1471-2393-13-S1-S2PubMedGoogle ScholarCrossref

5.

De Los Reyes  A, Youngstrom  EA, Swan  AJ, Youngstrom  JK, Feeny  NC, Findling  RL.  Informant discrepancies in clinical reports of youths and interviewers’ impressions of the reliability of informants.   J Child Adolesc Psychopharmacol. 2011;21(5):417-424. doi:10.1089/cap.2011.0011PubMedGoogle ScholarCrossref

Internet2 Community Exchange 2023 convenes research and education technology leaders in Atlanta

Sessions highlight digital inclusion and equity, automation, cloud strategy, cybersecurity, and more

Meeting Announcement

INTERNET2

 

IMAGE: INTERNET2 LOGO view more 

CREDIT: INTERNET2

Emerging and established leaders from the U.S. and global research and education (R&E) technology community will convene in Atlanta for the 2023 Internet2 Community Exchange, May 8-11.

Attendees will share perspectives, shape policy, and influence the development of services and infrastructures in support of their educational, research, and community-service missions. The program includes inspiring keynotes, expert-led talks, and workshops on topics including digital transformation, digital inclusion and equity, accessibility, cybersecurity, cloud strategy, trust and identity, advanced network modernization and automation, and collaborative projects to move the community forward.

Thought-Provoking Keynotes Set to Celebrate and Inspire

Claire L. Evans, author of Broad Band and co-founder of VICE’s Terraform, will present the opening keynote, “The Untold Story of the Women Who Made the Internet,” at 8:45 a.m. ET Tuesday, May 9. Evans will offer an insightful social history of the women visionaries at the vanguard of technology and innovation who made the internet what it is today.

A panel of leaders from historically underserved higher education institutions will take center stage to deliver the closing keynote, “Reframing our Perspective: Centering HBCU and TCU Voices to Reimagine a Stronger R&E Community,” at 1:15 p.m. ET Thursday, May 11. Panelists will spotlight their institutions’ lasting impacts and ask to reimagine together how to ensure equal participation in the national and global R&E communities.

More Program Highlights

The Internet2 Community Exchange event program includes 44 presentations led by subject-matter experts, 29 working meetings for community groups, three technical workshops on network automation and security, and an invitation-only Leadership Exchange for executive leaders in the Internet2 community.

With dozens of sessions to choose from, here are some of the don’t-miss highlights:

• Building a Cohesive Cloud Community – Higher ed panelists will discuss a joint effort by the EDUCAUSE Cloud Community Group, its co-chairs, Internet2, and the community at large that has led to interesting and potentially transformative outcomes.
• CIO Perspectives on Federated Cybersecurity for NIH Research – The National Institutes of Health will host a panel discussion about the critical importance of secure credentials in trust federations to enable and protect highly collaborative research environments.
• What is Happening in Network Services? – Internet2’s new vice president of Network Services will share about the new Insight Console, community discussions around automation tools and methods, efforts to improve routing security across the research and education community, and support for data-intensive science in the U.S. and around the world.
• MS-CC - Bridging the Digital Divide – Panelists will discuss the Minority Serving – Cyberinfrastructure Consortium’s plans to affect change so students and faculty at HBCUs, TCUs, and other MSIs have access to advanced cyberinfrastructure capabilities.
• Research IT Strategic Planning – Panelists will discuss a free assessment tool and complementary resources used by institutions of all sizes and complexity to aid in the research IT strategic planning needs of CIOs and senior executive leadership.
• Enabling RPKI – A speaker from the American Registry for Internet Numbers (ARIN) will talk about how network operators can strengthen their routing security through Resource Public Key Infrastructure services.
• InCommon Futures 2.0 – The InCommon Steering Committee chair will review the InCommon visioning process and implementation timeline for identity tools and services used by the community.
• Aiming High: Internet2’s Five-Year Roadmap – Leaders of the five-year roadmap process will provide an update on steps being taken to categorize the input and feedback received to date, and will share how Internet2 plans to work with the community to validate priorities and future direction.

Two co-located events will also take place during Community Exchange: the Higher Education Cloud Forum and the first MS-CC Annual Meeting.

More information can be found on the 2023 Internet2 Community Exchange website.

About Internet2

Internet2® is a non-profit, member-driven advanced technology community founded by the nation’s leading higher education institutions in 1996. Internet2 delivers a diverse portfolio of technology solutions that leverages, integrates, and amplifies the strengths of its members and helps support their educational, research, and community service missions. Internet2’s core infrastructure components include the nation’s largest and fastest research and education network that was built to deliver advanced, customized services that are accessed and secured by the community-developed trust and identity framework. For more information, visit https://internet2.edu or follow @internet2 on Twitter.

For chatbots and beyond: Improving lives with data starts with improving machine learning

Grant and Award Announcement

VIRGINIA TECH

 

IMAGE: RUOXI JIA. view more 

CREDIT: PHOTO BY CHELSEA SEEBER FOR VIRGINIA TECH.

You’d be hard pressed to find an industry today that doesn’t use data in some capacity. Whether it's health care workers using data to report the rate of flu infections in a certain state, manufacturers using data to better understand average production times, or even a small coffee shop owner flipping through sales data to learn about the previous month’s bestselling latte, data can reveal patterns and offer insights into our everyday behavior.

All of this data plays a critical role in artificial intelligence (AI) decision-making. Further, it creates a serious need for people to understand the value of data in the first place. By understanding how individual data sources contribute to technology-based decision-making processes, we can create a more effective and improved experience for all AI users. 

For instance, studies have shown that prevalent facial recognition software performs less reliably in identifying women and people of color compared with white men, reflecting imbalances in facial data representing diverse populations. Measuring the value of data enables us to eliminate inputs that might contribute to biased models. Furthermore, understanding the value of data allows us to assign appropriate pricing to data sources, thereby facilitating data sharing. This is particularly important to industries where certain data is difficult to obtain or for small businesses grappling with limited data access.

Assistant Professor Ruoxi Jia in the Bradley Department of Electrical and Computer Engineering at Virginia Tech has received an National Science Foundation (NSF) Faculty Early Career Development (CAREER) award to investigate fundamental theories and computational tools needed to measure the value of data. 

The five-year $500,000 grant will allow Jia and her team to develop scalable and reliable data valuation techniques that support strategic data acquisition and improve machine learning based data analytics.

“Right now, there is a lot of excitement about machine learning and AI, especially after the emergence of ChatGPT,” said Jia. “But what’s under the hood is a lot of data. That’s what enables this kind of machine, and that’s what we’re aiming to improve.”

ChatGPT, an AI chatbot launched this fall, allows users to ask for help with things such as writing essays, drafting business plans, generating code, and even composing music. As of Dec. 4, ChatGPT already had over 1 million users.

Open AI built its auto-generative system on a model called GPT 3, which is trained on billions of tokens. These tokens, used for natural language processing, are similar to words in a paragraph. For comparison’s sake, the novel “Harry Potter and the Order of the Phoenix” has about 250,000 words and 185,000 tokens. Essentially, ChatGPT has been trained on billions of data points, making this kind of intelligent machine possible. 

Ruoxi Jia works with Ph.D. student Feiyang Kang (at left) on data valuation techniques for their research.

CREDIT

Photo by Chelsea Seeber for Virginia Tech.

Jia noted the importance of data quality and how it can impact machine learning results. 

“If you have bad data feeding into machine learning, you will get bad results,” said Jia. “We call that 'garbage in, garbage out.' We want to get an understanding, especially a quantitative understanding, of which data is more valuable and which is less valuable for the purpose of data selection.” 

The importance of more quality-based data has been noticed by ChatGPT developers as they just announced the release of GPT-4. The latest technology is “multimodal,” meaning images as well as text prompts can spur it to generate content.

A large amount of data is required to develop this type of machine intelligence, but not all data is open sourced or public. Some data sets are owned by private entities and there is privacy involved. Jia hopes that in the future, monetary incentives can be introduced to help acquire these types of data sets and improve the machine learning algorithms that are needed in all industries. 

The University of California-Berkeley grad has had conversations with Google Research and Sony AI Research, among others, who are interested in the research benefits. Jia hopes these companies will adopt the technology developed and serve as advocates for data sharing. Sharing data and adopting improved machine learning algorithms will greatly benefit not only industries but individual consumers as well. For instance, if you’ve ever had a bad experience with a customer service chatbot, you’ve experienced low-quality data and poor machine learning algorithm design. 

Jia hopes to use her background and area expertise to improve these web-based interactions for all. As a school-aged child, Jia always enjoyed math and science, but her decision to enter the electrical and computer engineering field stemmed from her desire to help people.

“Both of my parents are doctors. It was amazing to grow up seeing them help patients with some kind of medical formula,” said Jia. “That’s why I chose to study math and science. You can have a concrete impact. I’m using a different kind of formula to help, but I like that pursuing this career has made me feel like I can make a difference in someone’s life.”

The CAREER award is the National Science Foundation’s most prestigious award for early-career faculty with the potential to serve as academic role models in research and education and to lead advances in their organization’s mission. Throughout this project, Jia has demonstrated her desire to serve as an academic role model for graduate, undergraduate, and even K-12 students.

She is a core faculty in the Sanghani Center for Artificial Intelligence and Data Analytics, formerly known as the Discovery Analytics Center. The center has more than 20 faculty members and 120 graduate students, two of whom are working directly with Jia to conduct the planned research.

Jia plans to implement an education plan that equips students with the skills to harness data to improve decision-making impacting society. This educational plan will start with new machine learning courses for undergraduate students in the first two years of the project and focus on K-12 engagement in years three through five. 

“There was a famous statistician named John Tukey,” Jia said. “He had a saying that the best thing about being a statistician is that you get to play in everyone's backyard. Machine learning is very much the same. It touches many areas of my colleagues’ work so it is easy for me to build connections and collaborate with other people. I really feel that my research is a privilege. It's a privilege to work in this area that many people care about.”

Kids judge Alexa smarter than Roomba, but say both deserve kindness

Four to 11-year-olds deem it wrong to attack either semi-intelligent robot

Peer-Reviewed Publication

DUKE UNIVERSITY

 

IMAGE: KIDS AGREE THAT IT’S WRONG TO BE ATTACK SMART TECHNOLOGIES LIKE ROOMBA OR AN ALEXA, DESPITE RANKING AMAZON’S VIRTUAL ASSISTANT AS SAVVIER THAN ITS VACUUMING COUNTERPART. view more 

CREDIT: VERONIQUE KOCH, DUKE UNIVERSITY

DURHAM, N.C. –- Most kids know it’s wrong to yell or hit someone, even if they don’t always keep their hands to themselves. But what about if that someone’s name is Alexa?

A new study from Duke developmental psychologists asked kids just that, as well as how smart and sensitive they thought the smart speaker Alexa was compared to its floor-dwelling cousin Roomba, an autonomous vacuum.

Four- to eleven-year-olds judged Alexa to have more human-like thoughts and emotions than Roomba. But despite the perceived difference in intelligence, kids felt neither the Roomba nor the Alexa deserve to be yelled at or harmed. That feeling dwindled as kids advanced towards adolescence, however. The findings appear online April 10 in the journal Developmental Psychology.

The research was inspired in part by lead author Teresa Flanagan seeing how Hollywood depicts human-robot interactions in shows like HBO’s “Westworld.”

“In Westworld and the movie Ex Machina, we see how adults might interact with robots in these very cruel and horrible ways,” said Flanagan, a visiting scholar in the department of psychology & neuroscience at Duke. “But how would kids interact with them?”

To find out, Flanagan recruited 127 children aged four to eleven who were visiting a science museum with their families. The kids watched a 20-second clip of each technology, and then were asked a few questions about each device.

Working under the guidance of Tamar Kushnir, Ph.D., her graduate advisor and a Duke Institute for Brain Sciences faculty member, Flanagan analyzed the survey data and found some mostly reassuring results.

Overall, kids decided that both the Alexa and Roomba probably aren’t ticklish and wouldn’t feel pain if they got pinched, suggesting they can’t feel physical sensations like people do. However, they gave Alexa, but not the Roomba, high marks for mental and emotional capabilities, like being able to think or getting upset after someone is mean to it.

“Even without a body, young children think the Alexa has emotions and a mind,” Flanagan said. “And it’s not that they think every technology has emotions and minds -- they don’t think the Roomba does -- so it’s something special about the Alexa’s ability to communicate verbally.”

Regardless of the different perceived abilities of the two technologies, children across all ages agreed it was wrong to hit or yell at the machines.

“Kids don’t seem to think a Roomba has much mental abilities like thinking or feeling,” Flanagan said. “But kids still think we should treat it well. We shouldn't hit or yell at it even if it can't hear us yelling.”

The older kids got however, the more they reported it would be slightly more acceptable to attack technology.

“Four- and five-year-olds seem to think you don't have the freedom to make a moral violation, like attacking someone," Flanagan said. “But as they get older, they seem to think it's not great, but you do have the freedom to do it.”

The study’s findings offer insights into the evolving relationship between children and technology and raise important questions about the ethical treatment of AI and machines in general, and as parents. Should adults, for example, model good behavior for their kids by thanking Siri or its more sophisticated counterpart ChatGPT for their help?

For now, Flanagan and Kushnir are trying to understand why children think it is wrong to assault home technology.

In their study, one 10-year-old said it was not okay to yell at the technology because, “the microphone sensors might break if you yell too loudly,” whereas another 10-year-old said it was not okay because “the robot will actually feel really sad.”

“It’s interesting with these technologies because there's another aspect: it’s a piece of property,” Flanagan said. “Do kids think you shouldn't hit these things because it's morally wrong, or because it's somebody's property and it might break?”

This research was supported by the U.S. National Science Foundation (SL-1955280, BCS-1823658).

CITATION: “The Minds of Machines: Children’s Beliefs About the Experiences, Thoughts, and Morals of Familiar Interactive Technologies,” Teresa M. Flanagan, Gavin Wong, Tamar Kushnir. Developmental Psychology, April 10, 2023. DOI: 10.1037/dev0001524.

 

Alexa, You're my Friend

 

Kids agree that it’s wrong to be attack smart technologies like Roomba or an Alexa, despite ranking Amazon’s virtual assistant as savvier than its vacuuming counterpart.

CREDIT

Veronique Koch, Duke University

JOURNAL

Developmental Psychology

DOI

10.1037/dev0001524 

METHOD OF RESEARCH

Survey

SUBJECT OF RESEARCH

People

ARTICLE TITLE

The Minds of Machines: Children’s Beliefs About the Experiences, Thoughts, and Morals of Familiar Interactive Technologies

ARTICLE PUBLICATION DATE

10-Apr-2023

Penn Medicine study reveals new insights on brain development sequence through adolescence

Brain maturation sequence renders youth sensitive to environmental impacts through adolescence

Peer-Reviewed Publication

UNIVERSITY OF PENNSYLVANIA SCHOOL OF MEDICINE

PHILADELPHIA—Brain development does not occur uniformly across the brain, but follows a newly identified developmental sequence, according to a new Penn Medicine study. Brain regions that support cognitive, social, and emotional functions appear to remain malleable—or capable of changing, adapting, and remodeling—longer than other brain regions, rendering youth sensitive to socioeconomic environments through adolescence. The findings were published recently in Nature Neuroscience.

Researchers charted how developmental processes unfold across the human brain from the ages of 8 to 23 years old through magnetic resonance imaging (MRI). The findings indicate a new approach to understanding the order in which individual brain regions show reductions in plasticity during development.

Brain plasticity refers to the capacity for neural circuits—connections and pathways in the brain for thought, emotion, and movement—to change or reorganize in response to internal biological signals or the external environment. While it is generally understood that children have higher brain plasticity than adults, this study provides new insights into where and when reductions in plasticity occur in the brain throughout childhood and adolescence.

The findings reveal that reductions in brain plasticity occur earliest in “sensory-motor” regions, such as visual and auditory regions, and occur later in “associative” regions, such as those involved in higher-order thinking (problem solving and social learning). As a result, brain regions that support executive, social, and emotional functions appear to be particularly malleable and responsive to the environment during early adolescence, as plasticity occurs later in development.

“Studying brain development in the living human brain is challenging. A lot of neuroscientists’ understanding about brain plasticity during development actually comes from studies conducted with rodents. But rodent brains do not have many of what we refer to as the association regions of the human brain, so we know less about how these important areas develop,” said corresponding author Theodore D. Satterthwaite, MD, the McLure Associate Professor of Psychiatry in the Perelman School of Medicine at the University of Pennsylvania, and director of the Penn Lifespan Informatics and Neuroimaging Center (PennLINC).

To address this challenge, the researchers focused on comparing insights from previous rodent studies to youth MRI imaging insights. Prior research examining how neural circuits behave when they are plastic uncovered that brain plasticity is linked to a unique pattern of “intrinsic” brain activity. Intrinsic activity is the neural activity occurring in a part of the brain when it is at rest, or not being engaged by external stimuli or a mental task. When a brain region is less developed and more plastic, there tends to be more intrinsic activity within the region, and that activity also tends to be more synchronized. This is because more neurons in the region are active, and they tend to be active at the same time. As a result, measurements of brain activity waves show an increase in amplitude (or height).

“Imagine that individual neurons within a region of the brain are like instruments in an orchestra. As more instruments begin to play together in synchrony, the sound level of the orchestra increases, and the amplitude of the sound wave gets higher,” said first author Valerie Sydnor, a Neuroscience PhD student. “Just like decibel meters can measure the amplitude of a sound wave, the amplitude of intrinsic brain activity can be measured with functional MRI while kids are simply resting in the scanner. This allowed our team to study a functional marker of brain plasticity safely and non-invasively in youth.”

Analyzing MRI scans from more than 1,000 individuals, the authors found that the functional marker of brain plasticity declined in earlier childhood in sensory-motor regions but did not decline until mid-adolescence in associative regions.

“These slow-developing associative regions are also those that are vital for children’s cognitive attainment, social interactions, and emotional well-being,” Satterthwaite added. “We are really starting to understand the uniqueness of human’s prolonged developmental program.”

“If a brain region remains malleable for longer, it may also remain sensitive to environmental influences for a longer window of development,” Sydnor said. “This study found evidence for just that.”

The authors studied relationships between youths’ socioeconomic environments and the same functional marker of plasticity. They found that the effects of the environment on the brain were not uniform across regions nor static across development. Rather, the effects of the environment on the brain changed as the identified developmental sequence progressed.

Critically, youths’ socioeconomic environments generally had a larger impact on brain development in the late-maturing associative brain regions, and the impact was found to be largest in adolescence.

“This work lays the foundation for understanding how the environment shapes neurodevelopmental trajectories even through the teenage years,” said Bart Larsen, PhD, a PennLINC postdoctoral researcher and co-author.

Sydnor elaborated, “The hope is that studying developmental plasticity will help us to understand when environmental enrichment programs will have a beneficial impact on each child’s neurodevelopmental trajectory. Our findings support that programs designed to alleviate disparities in youths’ socioeconomic environments remain important for brain development throughout the adolescent period.”

This study was supported by the National Institute of Health (R01MH113550, R01MH120482, R01MH112847, R01MH119219, R01MH123563, R01MH119185, R01MH120174, R01NS060910, R01EB022573, RF1MH116920., RF1MH121867, R37MH125829, R34DA050297, K08MH120564, K99MH127293, T32MH014654). The study was also supported by the National Science Foundation Graduate Research Fellowship (DGE-1845298).

Additional support was provided by the Penn-CHOP Lifespan Brain Institute and the Penn Center for Biomedical Image Computing and Analytics.

---

JOURNAL

Nature Neuroscience

DOI

10.1038/s41593-023-01282-y 

ARTICLE TITLE

Intrinsic activity development unfolds along a sensorimotor–association cortical axis in youth