Systemic Racism in EEG Research: Considerations and Potential Solutions.

Area of Science:

• Neuroscience
• Affective Science
• Racial Bias Research

Background:

• Electroencephalography (EEG) is a popular neuroscience technique for measuring brain activity.
• High-quality EEG data requires good scalp electrode adherence, influenced by factors like hair.
• Existing EEG research practices present challenges for recruiting and retaining Black American participants due to common hairstyles and hair types.

Purpose of the Study:

• To examine unintended systemic racism and racial biases in neuroscience research, specifically within EEG studies.
• To highlight how common Black American hairstyles and hair types create barriers to data collection in EEG research.
• To discuss bioengineering innovations addressing these disparities and improving data generalizability.

Main Methods:

• Theoretical analysis of systemic issues in neuroscience research.
• Examination of factors affecting EEG data quality, including participant demographics and hair characteristics.
• Review of bioengineering solutions for inclusive EEG data acquisition.

Main Results:

• Systemic biases in EEG research disproportionately affect Black American participants.
• Hair characteristics common among Black Americans pose technical challenges for EEG electrode adherence.
• Lack of diverse participant data limits the generalizability of neuroscience findings and perpetuates disparities.

Conclusions:

• Addressing systemic racism and racial biases is crucial for equitable neuroscience research.
• Bioengineering innovations offer promising solutions to overcome recruitment and data collection barriers for Black Americans in EEG studies.
• Improving inclusivity in EEG research will enhance the generalizability of findings and reduce health disparities.