Feasibility of assessing brain activity using mobile, in‐home collection of electroencephalography: methods and analysis

Troller‐Renfree, Sonya V.; Morales, Santiago; Leach, Stephanie C.; Bowers, Maureen E.; Debnath, Ranjan; Fifer, William P.; Noble, Kimberly G.

doi:10.1002/dev.22128

Cited by 16 publications

(9 citation statements)

References 17 publications

(32 reference statements)

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“…The utility, feasibility, and cultural appropriateness of mobile EEG were evaluated prior to the commencement of data collection through a series of pilot visits and focus groups [see Troller-Renfree et al. ( 56 ) for full details of piloting and interviewer training]. Following this piloting process, a team of interviewers was trained to collect in-home EEG.…”

Section: Methodsmentioning

confidence: 99%

The impact of a poverty reduction intervention on infant brain activity

Troller‐Renfree

Costanzo

Duncan

et al. 2022

Proc. Natl. Acad. Sci. U.S.A.

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166

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Early childhood poverty is a risk factor for lower school achievement, reduced earnings, and poorer health, and has been associated with differences in brain structure and function. Whether poverty causes differences in neurodevelopment, or is merely associated with factors that cause such differences, remains unclear. Here, we report estimates of the causal impact of a poverty reduction intervention on brain activity in the first year of life. We draw data from a subsample of the Baby’s First Years study, which recruited 1,000 diverse low-income mother–infant dyads. Shortly after giving birth, mothers were randomized to receive either a large or nominal monthly unconditional cash gift. Infant brain activity was assessed at approximately 1 y of age in the child’s home, using resting electroencephalography (EEG; n = 435). We hypothesized that infants in the high-cash gift group would have greater EEG power in the mid- to high-frequency bands and reduced power in a low-frequency band compared with infants in the low-cash gift group. Indeed, infants in the high-cash gift group showed more power in high-frequency bands. Effect sizes were similar in magnitude to many scalable education interventions, although the significance of estimates varied with the analytic specification. In sum, using a rigorous randomized design, we provide evidence that giving monthly unconditional cash transfers to mothers experiencing poverty in the first year of their children’s lives may change infant brain activity. Such changes reflect neuroplasticity and environmental adaptation and display a pattern that has been associated with the development of subsequent cognitive skills.

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Section: Methodsmentioning

confidence: 99%

The impact of a poverty reduction intervention on infant brain activity

Troller‐Renfree

Costanzo

Duncan

et al. 2022

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

166

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“…Electroencephalography (EEG) is widely used in research and medical routine for the monitoring of brain activity by the acquisition of biopotentials on the human head surface. The advancement in the acquisition method from the gold standard gel-based electrode EEG caps to the more recent dry electrode EEG caps supported the considerable broadening of the field of applications, such as for clinical purposes [ 1 , 2 ], in brain–computer interfaces (BCI) [ 3 , 4 , 5 , 6 , 7 ], in mobile EEG [ 8 , 9 , 10 , 11 ], in neurofeedback applications [ 5 , 12 , 13 ], and for emergency situations [ 14 , 15 ]. The new fields of application have previously been considered challenging or impossible due to the inherent limitations of gel-based electrodes.…”

Section: Introductionmentioning

confidence: 99%

Multi-Center Evaluation of Gel-Based and Dry Multipin EEG Caps

Fiedler

Kuhlmann

et al. 2022

Sensors

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Dry electrodes for electroencephalography (EEG) allow new fields of application, including telemedicine, mobile EEG, emergency EEG, and long-term repetitive measurements for research, neurofeedback, or brain–computer interfaces. Different dry electrode technologies have been proposed and validated in comparison to conventional gel-based electrodes. Most previous studies have been performed at a single center and by single operators. We conducted a multi-center and multi-operator study validating multipin dry electrodes to study the reproducibility and generalizability of their performance in different environments and for different operators. Moreover, we aimed to study the interrelation of operator experience, preparation time, and wearing comfort on the EEG signal quality. EEG acquisitions using dry and gel-based EEG caps were carried out in 6 different countries with 115 volunteers, recording electrode-skin impedances, resting state EEG and evoked activity. The dry cap showed average channel reliability of 81% but higher average impedances than the gel-based cap. However, the dry EEG caps required 62% less preparation time. No statistical differences were observed between the gel-based and dry EEG signal characteristics in all signal metrics. We conclude that the performance of the dry multipin electrodes is highly reproducible, whereas the primary influences on channel reliability and signal quality are operator skill and experience.

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“…It is likely that gel‐based systems do offer an advantage in this regard, and they have been associated with generally better signal quality (Troller‐Renfree et al., 2021). Morphological, physical, and mechanical properties associated with different hair types may also affect how different systems perform.…”

Section: Discussionmentioning

confidence: 99%

The effect of hair type and texture on electroencephalography and event‐related potential data quality

Lees,

Ram,

Swingler

et al. 2023

Psychophysiology

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Research utilizing event‐related potential (ERP) methods is generally biased with regard to sample representativeness. Among the myriad of factors that contribute to sample bias are researchers' assumptions about the extent to which racial differences in hair texture, volume, and style impact electrode placement, and subsequently, study eligibility. The current study examines these impacts using data collected from n = 213 individuals ages 17–19 years, and offers guidance on collection of ERP data across the full spectrum of hair types. Individual differences were quantified for hair texture using a visual scale, and for hair volume by measuring the amount of gel used in cap preparation. Electroencephalography data quality was assessed with multiple metrics at the preprocessing, post‐processing, and variable generation stages. Results indicate that hair volume is associated with small, but systematic differences in signal quality and signal amplitude. Such differences are highly problematic as they could be misattributed to cognitive differences among groups. However, inclusion of gel volume as a covariate to account for individual differences in hair volume significantly reduced, and in most cases eliminated, group differences. We discuss strategies for overcoming real and perceived technical barriers for researchers seeking to achieve greater inclusivity and representativeness in ERP research.

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Feasibility of assessing brain activity using mobile, in‐home collection of electroencephalography: methods and analysis

Cited by 16 publications

References 17 publications

The impact of a poverty reduction intervention on infant brain activity

The impact of a poverty reduction intervention on infant brain activity

Multi-Center Evaluation of Gel-Based and Dry Multipin EEG Caps

The effect of hair type and texture on electroencephalography and event‐related potential data quality

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