Biology subjects

Parameshwaran, D.

Publications and source records attributed to Parameshwaran, D..

5 recordsLinked to original sources

bioRxiv2024

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

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.

neuroscience↗

bioRxiv2022

High Variability Periods in the EEG: A New Temporal Metric that Reflects Brain States

Here we define a new metric to characterize temporal patterns of amplitude variability in the EEG signal and demonstrate that this feature of the signal varies significantly with brain state. The metric uses the standard deviation of waveform amplitude in a short moving time window of 3-20 seconds with 50% overlap. We define "High Variability Periods" or "HVPs" as segments when the moving standard deviation of the waveform amplitude is continuously higher than a cutoff defined as the 25th percentile of variability. HVPs typically last on the order of tens of seconds and are punctuated by low variability periods or "LVPs" of shorter duration. We further show that the HVP characteristics differ between various conditions. HVPs in the resting state eyes closed condition are substantially and significantly shorter in duration and smaller in area relative to eyes open. In addition, in recordings from monkeys, HVPs disappear under anesthesia and do not reappear in early periods of recovery from anesthesia suggesting long term changes to the signal. Altogether this demonstrates that HVP metrics have discriminatory power and may therefore be important in predicting brain states and outcomes. Finally, they are fast to estimate and can be tracked in time, and therefore suited for near real-time monitoring in low-electrode configuration systems.

neuroscience↗

bioRxiv2017

Complexity Of EEG Reflects Socioeconomic Context And Geofootprint

The fine scale structure and resulting activity of the brain are largely shaped by experience, suggesting that the faster rate and complexity of experience offered by modern civilization may have significant impact on human brain dynamics. Here we defined a new measure of complexity of the EEG signal and compared it across populations spanning incomes from <$1/day to [~]$410/day with a wide range of access to features of modern life such as urban environments, higher education, electricity, motorized transport and telecommunication. Complexity across our sample spanned a 2.75-fold range, separating into two distinct distributions of pre-modern and modern experience. Furthermore, complexity scaled systematically with various technologies and experience factors, of which travel or geofootprint had the strongest relationship. Complexity also had a steep non-linear relationship with income that leveled out at an income of [~]$30/ day. Finally, it was strongly correlated to performance on a pattern completion task indicating its relevance as a cognitive measure. In light of growing income inequality and divergence in access to the tools of modern living across the globe, our findings have significant implications for social policy.

neuroscience↗

bioRxiv2017

Modernization, Wealth And The Emergence Of Strong Alpha Oscillations In The Human EEG

Oscillations in the alpha range (8-15 Hz) have been found to appear prominently in the EEG signal when people are awake with their eyes closed, and since their discovery have been considered a fundamental cerebral rhythm. While the mechanism of this oscillation continues to be debated, it has been shown to bear positive relation to memory capacity, attention and a host of other cognitive outcomes. Here we show that this feature is largely undetected in the EEG of adults without post-primary education and access to modern technologies. Furthermore, we show that the spatial extent and energy of the oscillation have wide variation, with energy ranging over a thousand fold across the breath of humanity with no centralizing mean. This represents a divergence in a fundamental functional characteristic of an organ demonstrating both that modernization has had a profound influence on brain dynamics and that a meaningful average human brain does not exist in a dynamical sense.

neuroscience↗

bioRxiv2017

Dynamical Features Of Human EEG Scale Systematically With Life Context

We have previously shown that the complexity of human brain activity and the emergence and strength of alpha oscillation as measured by EEG scale dramatically with access to the features of modernization. Here we show that these features of the EEG, while correlated to one another are distinct in their origin and that while complexity is most strongly related to travel or geofootprint, energy of the alpha oscillation scales more systematically with fuel consumption. Finally, composite EEG scores representing the dominant principal component scale in remarkable lockstep with the dominant component of the features of modernization. This demonstrates that human brain dynamics, and therefore cognitive outcome, are profoundly and systematically tied to the context of life experience. Indeed the implication is that normal brain function is not absolute and can only be considered in relation to or conditional on the context in which it is embedded.

neuroscience↗