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How Modern Life Shapes Our Brains

Explore the effects of technology and environment on brain function.

John-Mary Vianney Sr., Shailender Swaminathan, Jennifer Jane Newson, Dhanya Parameshwaran, Narayan Puthanmadam Subramaniyam, Swaeta Singha Roy, Revocatus Machunda, Achiwa Sapuli, Santanu Pramanik, John Victor Arun Kumar, Pramod Tiwari, G Nelson Mathews Mathuram, Laurent Boniface Bembeleza, Joyce Philemon Laiser, Winifrida Julius Luhwago, Theresia Pastory Maduka, John Olais Mollel, Neema Gadiely Mollel, Adella Aloys Mugizi, Isaac Lwaga Mwamakula, Raymond Edwin Rweyemamu, Upendo Firimini Samweli, James Isaac Simpito, Kelvin Ewald Shirima, Anand Anbalagan, Suresh Kumar Arumugam, Vinitha Dhanapal, Kanimozhi Gunasekaran, Neelu Kashyap, Dheeraj Kumar, Durgesh Pandey, Poonam Pandey, ArunKumar Panneerselvam, Sonam Rai, Porselvi Rajendran, Santhoshkumar Sekar, Oliazhagan Sivalingam, Prahalad Soni, Pushpkala Soni, Tara C. Thiagarajan

― 7 min read


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Table of Contents

Over the past few decades, our world has changed a lot. Technology has advanced, social interactions have shifted, and our environments have evolved. But how do all these changes affect our brains? Surprisingly, we still have a lot to learn about this connection.

The human brain is like a sponge, soaking up information from the world around it. It responds to different experiences, environments, and even the people we meet. For example, researchers have studied brain activity using tools like electroencephalography (EEG). This technology measures electrical activity in the brain by placing small sensors on the scalp. Different studies have shown that our brain activity can vary based on factors like age, lifestyle, and even where we live.

The Need for Bigger Studies

To really grasp how modern life impacts our brains, we need large studies that include many people from different backgrounds. Several large studies are currently looking into this, such as projects focused on how the brain develops in adolescents or how different environments affect brain connections. These studies are often very expensive and require a lot of resources, making it challenging for them to gather data from broad populations.

Typically, these projects can only include around 10,000 Participants at a time, mainly due to high costs, limited locations, and the complexity of the technology they use. For instance, one impressive study involving 11,000 children in the United States costs about $41 million each year. That's a hefty price tag!

Fortunately, more affordable EEG devices are becoming available, but they still need experts to run them. This can be a problem, particularly in low-income countries where funding and trained staff are scarce.

To overcome these challenges, we need to find ways for non-experts to collect high-quality data. In many cases, the data collected by field researchers can suffer from various quality issues. These problems can range from inaccurate surveys to bad quality EEG recordings. To tackle this, we can set up solid systems and processes to train researchers, monitor Data Quality in real time, and ensure good participant recruitment and logistics.

A Case Study: Sapien Labs

One organization, Sapien Labs, has already started creating these systems in India and Tanzania. They are Training field researchers who might not be experts in EEG technology but can collect valuable data about how our brains work in different environments.

In their pilot projects, researchers captured EEG data from over 2,000 participants, recording their brain activity while in various settings. They used a low-cost EEG device that can be managed by researchers with minimal training. This approach opens doors to gathering valuable information about brain function across different populations.

These researchers faced challenges, such as movement artifacts and noise from the environment. However, they were able to use specific techniques to clean up the data and enhance its quality. The studies also emphasized the importance of ongoing training and feedback for researchers, allowing them to improve their skills as they collect data.

What is EEG?

EEG is a technique that measures brain activity through electrodes placed on the scalp. These electrodes capture the electrical signals in the brain, allowing researchers to analyze how our brains respond in different situations.

An EEG session can involve sitting quietly with one's eyes closed or open, depending on what researchers want to measure. For example, during a resting-state EEG session, participants may be asked to relax and focus on their breathing for a few minutes. This can help researchers observe how the brain behaves when it's not actively engaged in tasks.

Overall, EEG can provide insights into brain functions such as attention, memory, and emotional responses.

Data Quality Matters

In the field, ensuring data quality is crucial. Researchers need to monitor how well they're capturing data throughout the process. For example, they can use daily reports to track how many participants they have recorded, and they can keep an eye on the quality of the EEG signals they gather.

Two common methods for analyzing EEG data quality are called FASTER and PREP. These techniques help researchers identify any bad signals that might interfere with their analysis. For instance, problematic data could come from power line noise or movement artifacts. By cleaning up this data, researchers can get a more accurate picture of brain activity.

Comparing Field Data with Lab Data

After collecting EEG data from participants, the field data is often compared with data obtained in controlled laboratory settings. This helps researchers understand if their methods are yielding reliable results.

In one study, researchers compared their field data quality to three benchmark datasets. Interestingly, while the field data had some challenges—like more bad channels—the results were still comparable to those gathered in labs. This indicates that with the right systems in place, high-quality data can be collected outside traditional lab settings.

Recruitment and Logistics

Recruiting participants is a vital part of conducting research that relies on EEG data. Field researchers must be strategic in finding participants that represent diverse backgrounds and age groups. This may involve working within local communities to ensure a broad spectrum of participants.

Once researchers find participants, they must also coordinate logistics. This could include arranging transportation to the recording sites or ensuring participants understand what to expect during the EEG session.

To aid this, organizations often recruit local managers who can help connect researchers with potential participants. These managers can leverage their community relationships to engage people in the study and navigate any regulatory hurdles.

Training Field Researchers

A critical factor in gathering high-quality data lies in training field researchers. Groups like Sapien Labs recognize that even people without prior experience in EEG can be trained to collect data effectively. In one of their projects, they trained new college graduates as well as individuals with experience in survey methods.

The training process involves hands-on demonstrations, practice sessions, and continuous feedback on data quality. Within a short period of training, many individuals were able to reach high standards of data collection. This approach is particularly beneficial in regions where specialized training is scarce.

The Importance of Real-Time Monitoring

To minimize mistakes and ensure data quality, real-time monitoring is essential. Researchers can access dashboards that provide updates on their progress and data quality throughout the study.

These dashboards allow teams to quickly address any issues that may arise during the data collection process. For example, if a problem occurs with the EEG signals, researchers can take immediate action to correct it, rather than waiting until the study is complete to address any flaws.

What We Learned So Far

The ongoing research conducted by organizations like Sapien Labs seeks to gather as much information as possible about how our experiences affect brain function. So far, the initial findings suggest that it is indeed possible to gather high-quality EEG data across diverse environments and populations, even with limited resources.

By developing strong training programs and monitoring systems, researchers can ensure that people with varying levels of expertise can contribute to understanding brain health and function. This shift in approach can lead to significant benefits when studying populations in low- and middle-income countries.

What's Next?

So, what does the future hold for EEG research in diverse environments? By focusing on scaling data collection without compromising quality, researchers can continue to unlock valuable insights into brain health across different cultures and backgrounds.

As we learn more about how our brains react to modern life, we're opening doors for improved mental health treatments and support. Who knows? One day, we could be looking at our phones and thinking about how much our devices are affecting our brain activity!

In conclusion, the connection between our brains and the rapidly changing world around us is complex and fascinating. With continued efforts to gather quality data from diverse populations, we can better understand the impact of our modern lives on the brain and potentially enhance mental well-being for people everywhere. Remember, the more we understand about our brains, the better equipped we are to support healthy minds in a busy world.

And if further studies help us crack the code on brain function, we might just find a way to make "brain freeze" a thing of the past!

Original Source

Title: EEG data quality in large scale field studies in India and Tanzania

Abstract: There is a growing imperative to understand the neurophysiological impact of our rapidly changing and diverse technological, social, chemical, and physical environments. To untangle the multidimensional and interacting effects requires data at scale across diverse populations, taking measurement out of a controlled lab environment and into the field. Electroencephalography (EEG), which has correlates with various environmental factors as well as cognitive and mental health outcomes, has the advantage of both portability and cost-effectiveness for this purpose. However, with numerous field researchers spread across diverse locations, data quality issues and researcher idle time due to insufficient participants can quickly become unmanageable and expensive problems. In programs we have established in India and Tanzania, we demonstrate that with appropriate training, structured teams, and daily automated analysis and feedback on data quality, non-specialists can reliably collect EEG data alongside various survey and assessments with consistently high throughput and quality. Over a 30-week period, research teams were able to maintain an average of 25.6 subjects per week, collecting data from a diverse sample of 7,933 participants ranging from Hadzabe hunter-gatherers to office workers. Furthermore, data quality, computed on the first 2,400 records using two common methods, PREP and FASTER, was comparable to benchmark datasets from controlled lab conditions. Altogether this resulted in a cost per subject of under $50, a fraction of the cost typical of such data collection, opening up the possibility for large-scale programs particularly in low- and middle-income countries. Significance StatementWith wide human diversity, a rapidly changing environment and growing rates of neurological and mental health disorders, there is an imperative for large scale neuroimaging studies across diverse populations that can deliver high quality data and be affordably sustained. Here we demonstrate, across two large-scale field data acquisition programs operating in India and Tanzania, that with appropriate systems it is possible to generate high throughput EEG data of quality comparable to controlled lab settings. With effective costs of under $50 per subject, this opens new possibilities for low- and middle-income countries to implement large-scale programs, and to do so at scales that previously could not be considered.

Authors: John-Mary Vianney Sr., Shailender Swaminathan, Jennifer Jane Newson, Dhanya Parameshwaran, Narayan Puthanmadam Subramaniyam, Swaeta Singha Roy, Revocatus Machunda, Achiwa Sapuli, Santanu Pramanik, John Victor Arun Kumar, Pramod Tiwari, G Nelson Mathews Mathuram, Laurent Boniface Bembeleza, Joyce Philemon Laiser, Winifrida Julius Luhwago, Theresia Pastory Maduka, John Olais Mollel, Neema Gadiely Mollel, Adella Aloys Mugizi, Isaac Lwaga Mwamakula, Raymond Edwin Rweyemamu, Upendo Firimini Samweli, James Isaac Simpito, Kelvin Ewald Shirima, Anand Anbalagan, Suresh Kumar Arumugam, Vinitha Dhanapal, Kanimozhi Gunasekaran, Neelu Kashyap, Dheeraj Kumar, Durgesh Pandey, Poonam Pandey, ArunKumar Panneerselvam, Sonam Rai, Porselvi Rajendran, Santhoshkumar Sekar, Oliazhagan Sivalingam, Prahalad Soni, Pushpkala Soni, Tara C. Thiagarajan

Last Update: 2024-12-09 00:00:00

Language: English

Source URL: https://www.biorxiv.org/content/10.1101/2024.12.05.626951

Source PDF: https://www.biorxiv.org/content/10.1101/2024.12.05.626951.full.pdf

Licence: https://creativecommons.org/licenses/by-nc/4.0/

Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.

Thank you to biorxiv for use of its open access interoperability.

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