Whose Signals Are Being Amplified? Toward a More Equitable Clinical Psychophysiology

Modality-level obstacles and initiatives to improve representation in fetal, infant, and toddler neuroimaging research samples

Fetal, infant, and toddler (FIT) neuroimaging researchers study early brain development to gain insights into neurodevelopmental processes and identify early markers of neurobiological vulnerabilities to target for intervention. However, the field has historically excluded people from global majority countries and from marginalized communities in FIT neuroimaging research. Inclusive and representative samples are essential for generalizing findings across neuroimaging modalities, such as magnetic resonance imaging, magnetoencephalography, electroencephalography, functional near-infrared spectroscopy, and cranial ultrasonography. These FIT neuroimaging techniques pose unique and overlapping challenges to equitable representation in research through sampling bias, technical constraints, limited accessibility, and insufficient resources. The present article adds to the conversation around the need to improve inclusivity by highlighting modality-specific historical and current obstacles and ongoing initiatives. We conclude by discussing tangible solutions that transcend individual modalities, ultimately providing recommendations to promote equitable FIT neuroscience.

The Go/No-Go P3 and Depressive Symptoms in Adolescents: Trial-Level Change and Mean Amplitude Relate Differently to Anhedonic Versus Negative Mood Symptoms

Prior studies have found an association between reduced P3 brain responses-a neural marker of task engagement-and increased depressive symptoms during adolescence. However, it is unclear whether P3 correlates with depression globally, or with certain facets. Existing depression studies have also typically quantified P3 as a cross-trial average, neglecting possible trial-by-trial effects. Among 72 adolescents (44% female), the current study evaluated relations of distinct depression symptom facets-anhedonia and negative mood-with P3s from a three-stimulus go/no-go task, quantified both in average- and trial-level terms. Although no relationship was evident between overall depressive symptoms and average P3 amplitudes, opposing relations were found for each symptom facet with P3 to frequent and infrequent 'go' stimuli: higher anhedonia predicted smaller P3, whereas increased negative mood predicted larger P3. Single-trial, multilevel modeling analyses clarified these effects by showing reduced P3 across stimuli types at task outset, along with greater trial-to-trial attenuation of P3 to infrequent-go stimuli, for adolescents experiencing greater anhedonia. Conversely, increased negative mood was distinctly related to larger P3 at task onset but was unrelated to amplitude change across trials. Results demonstrate differential relations for anhedonic and negative mood symptoms with P3-indicative of task disengagement versus heightened vigilance, respectively-that may be obscured in analyses focusing on overall depressive symptoms. The divergent associations for anhedonia and negative mood with P3 underscore the need to consider these distinct symptom facets in research aimed at clarifying the nature of neural-circuitry dysfunction in depression.

Impact of ERP Reliability Cutoffs on Sample Characteristics and Effect Sizes: Performance-Monitoring ERPs in Psychosis and Healthy Controls

In studies of event-related brain potentials (ERPs), it is common practice to exclude participants for having too few trials for analysis to ensure adequate score reliability (i.e., internal consistency). However, in research involving clinical samples, the impact of increasingly rigorous reliability standards on factors such as sample generalizability, patient versus control effect sizes, and effect sizes for within-group correlations with external variables is unclear. This study systematically evaluated whether different ERP reliability cutoffs impacted these factors in psychosis. Error-related negativity (ERN) and error positivity (Pe) were assessed during a modified flanker task in 97 patients with psychosis and 104 healthy comparison participants, who also completed measures of cognition and psychiatric symptoms. ERP reliability cutoffs had notably different effects on the factors considered. A recommended reliability cutoff of 0.80 resulted in sample bias due to systematic exclusion of patients with relatively few task errors, lower reported psychiatric symptoms, and higher levels of cognitive functioning. ERP score reliability lower than 0.80 resulted in generally smaller between- and within-group effect sizes, likely misrepresenting effect sizes. Imposing rigorous ERP reliability standards in studies of psychotic disorders might exclude high-functioning patients, which raises important considerations for the generalizability of clinical ERP research. Moving forward, we recommend examining characteristics of excluded participants, optimizing paradigms and processing pipelines for use in clinical samples, justifying reliability thresholds, and routinely reporting score reliability of all measurements, ERP or otherwise, used to examine individual differences, especially in clinical research.

Bioethical and critical consciousness in clinical translational neuroscience

Clinical translational neuroscience (CTN) is positioned to generate novel discoveries for advancing treatments for mental health disorders, but it is held back today by the siloing of bioethical considerations from critical consciousness. In this article, we suggest that bioethical and critical consciousness can be paired to intersect with structures of power within which science and clinical practice are conducted. We examine barriers to the adoption of neuroscience findings in mental health from this perspective, especially in the context of current collective attention to widespread disparities in the access to and outcomes of mental health services, lack of representation of marginalized populations in the relevant sectors of the workforce, and the importance of knowledge that draws upon multicultural perspectives. We provide 10 actionable solutions to confront these barriers in CTN research, as informed by existing frameworks such as structural competency, adaptive calibration models, and community-based participatory research. By integrating critical consciousness with bioethical considerations, we believe that practitioners will be better positioned to benefit from cutting-edge research in the biological and social sciences than in the past, alert to biases and equipped to mitigate them, and poised to shepherd in a robust generation of future translational therapies and practitioners.

Untangling bias: Racial and phenotypic bias in neuroimaging methods must be addressed

Racial and phenotypic bias in neuroimaging methods must be addressed.

Racial and ethnic socioenvironmental inequity and neuroimaging in psychiatry: a brief review of the past and recommendations for the future

Neuroimaging is a major tool that holds immense translational potential for understanding psychiatric disorder phenomenology and treatment. However, although epidemiological and social research highlights the many ways inequity and representativeness influences mental health, there is a lack of consideration of how such issues may impact neuroimaging features in psychiatric research. More specifically, the potential extent to which racialized inequities may affect underlying neurobiology and impact the generalizability of neural models of disorders is unclear. The present review synthesizes research focused on understanding the potential consequences of racial/ethnic inequities relevant to neuroimaging in psychiatry. We first discuss historical and contemporary drivers of inequities that persist today. We then discuss the neurobiological consequences of these inequities as revealed through current research, and note emergent research demonstrating the impact such inequities have on our ability to use neuroimaging to understand psychiatric disease. We end with a set of recommendations and practices to move the field towards more equitable approaches that will advance our abilities to develop truly generalizable neurobiological models of psychiatric disorders.

Pilot Evaluation of Sevo Systems for Epilepsy: Equitable EEG for Coarse, Dense, and Curly Hair

Collecting electroencephalography (EEG) data from individuals with coarse, curly, or afro-textured hair can be challenging, leading to noisier data, negative clinical outcomes (e.g., risk of misdiagnosis, discomfort, longer setup times, unsavory treatment, hair shaving, and microaggressions), and unreliable basic science conclusions due to the disproportionate exclusion of people with this physical feature worldwide. Our prior work demonstrated that strategically braiding hair to expose the scalp at standard locations improves impedance and that novel electrode adapters that we developed called "Sevo" can further lower impedance by more than 15x. In this article, we further quantify the signal quality of Sevo EEG compared to traditional EEG on a cohort of pediatric epileptic patients and health adult volunteers. We assessed the influence of braiding and the use of Sevo adapters on signal quality and found that Sevo reduces noise in two key metrics of the power spectra, especially for the pediatric epilepsy group. We conclude by outlining best practices for preparing coarse, curly hair for use by EEG technicians, researchers, and patients.

The Necessity of Taking Culture and Context into Account When Studying the Relationship between Socioeconomic Status and Brain Development

Decades of research has revealed a relationship between childhood socioeconomic status (SES) and brain development at the structural and functional levels. Of particular note is the distinction between income and maternal education, two highly correlated factors which seem to influence brain development through distinct pathways. Specifically, while a families' income-to-needs ratio is linked with physiological stress and household chaos, caregiver education influences the day-to-day language environment a child is exposed to. Variability in either one of these environmental experiences is related to subsequent brain development. While this work has the potential to inform public policies in a way that benefits children, it can also oversimplify complex factors, unjustly blame low-SES parents, and perpetuate a harmful deficit perspective. To counteract these shortcomings, researchers must consider sociodemographic differences in the broader cultural context that underlie SES-based differences in brain development. This review aims to address these issues by (a) identifying how sociodemographic mechanisms associated with SES influence the day-to-day experiences of children, in turn, impacting brain development, while (b) considering the broader cultural contexts that may differentially impact this relationship.

Fostering inclusion in EEG measures of pediatric brain activity

The past two decades have seen a rapid increase in neuroscientific evidence being used to characterize how contextual, structural, and societal factors shape cognition and school readiness. Measures of functional brain activity are increasingly viewed as markers of child development and biomarkers that could be employed to track the impact of interventions. While electroencephalography (EEG) provides a promising tool to understand educational inequities, traditional EEG data acquisition is commonly limited in some racial and ethnic groups due to hair types and styles. This ultimately constitutes unintentional systemic racism by disproportionately excluding participants from certain racial and ethnic groups from participation and representation in neuroscience research. Here, we provide a comprehensive review of how cultural considerations surrounding hair density, texture, and styling consistently skew samples to be less representative by disproportionately excluding Black and Latinx participants. We also provide recommendations and materials to promote best practices.

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

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.

Adaptive thresholding increases sensitivity to detect changes in the rate of skin conductance responses to psychologically arousing stimuli in both laboratory and ambulatory settings

Psychophysiologists recording electrodermal activity (EDA) often derive measures of slow, tonic activity-skin conductance level (SCL)-and faster, more punctate changes-skin conductance responses (SCRs). A SCR is conventionally considered to have occurred when the local amplitude of the EDA signal exceeds a researcher-determined threshold (e.g., 0.05 μS), typically fixed across study participants and conditions. However, fixed SCR thresholds can preferentially exclude data from individuals with low SCL because their SCRs are smaller on average, thereby reducing statistical power for group-level analyses. Thus, we developed a fixed plus adaptive (FA) thresholding method that adjusts identification of SCRs based on an individual's SC at the onset of the SCR to increase statistical power and include data from more participants. We assess the utility of applying FA thresholding across two independent samples and explore age and race-related associations with EDA outcomes. Study 1 uses wired EDA measurements from 254 healthy adults responding to evocative images and sounds in a laboratory setting. Study 2 uses wireless EDA measurements from 20 children with autism in a clinical environment while they completed behavioral tasks. Compared to a 0.01, 0.03, and 0.05 μS fixed threshold, FA thresholding at 1.9% modestly increases statistical power to detect a difference in SCR rate between tasks with higher vs. lower subjective arousal and reduces exclusion of participants by up to 5% across both samples. This novel method expands the EDA analytical toolbox and may be useful in populations with highly variable basal SCL or when comparing groups with different basal SCL. Future research should test for reproducibility and generalizability in other tasks, samples, and contexts. IMPACT STATEMENTS: This article is important because it introduces a novel method to enhance sensitivity and statistical power in analyses of skin conductance responses from electrodermal data.

Auditory evoked potentials in adolescents with autism: An investigation of brain development, intellectual impairment, and neural encoding

Limited research has evaluated neural encoding of sounds from a developmental perspective in individuals with autism (ASD), especially among those with intellectual disability. We compared auditory evoked potentials (AEPs) in autistic adolescents with a wide range of intellectual abilities (n = 40, NVIQ 30-160) to both age-matched cognitively able neurotypical adolescent controls (NT-A, n = 37) and younger neurotypical children (NT-C, n = 27) to assess potential developmental delays. In addition to a classic measure of peak amplitude, we calculated a continuous measure of intra-class correlation (ICC) between each adolescent participant's AEP and the age-normative, average AEP waveforms calculated from NT-C and NT-A to study differences in signal morphology. We found that peak amplitudes of neural responses were significantly smaller in autistic adolescents compared to NT-A. We also found that the AEP morphology of autistic adolescents looked more like NT-A peers than NT-C but was still significantly different from NT-A AEP waveforms. Results suggest that AEPs of autistic adolescents present differently from NTs, regardless of age, and differences cannot be accounted for by developmental delay. Nonverbal intelligence significantly predicted how closely each adolescent's AEP resembled the age-normed waveform. These results support an evolving theory that the degree of disruption in early neural responses to low-level inputs is reflected in the severity of intellectual impairments in autism.

Interdisciplinary views of fNIRS: Current advancements, equity challenges, and an agenda for future needs of a diverse fNIRS research community

Functional Near-Infrared Spectroscopy (fNIRS) is an innovative and promising neuroimaging modality for studying brain activity in real-world environments. While fNIRS has seen rapid advancements in hardware, software, and research applications since its emergence nearly 30 years ago, limitations still exist regarding all three areas, where existing practices contribute to greater bias within the neuroscience research community. We spotlight fNIRS through the lens of different end-application users, including the unique perspective of a fNIRS manufacturer, and report the challenges of using this technology across several research disciplines and populations. Through the review of different research domains where fNIRS is utilized, we identify and address the presence of bias, specifically due to the restraints of current fNIRS technology, limited diversity among sample populations, and the societal prejudice that infiltrates today's research. Finally, we provide resources for minimizing bias in neuroscience research and an application agenda for the future use of fNIRS that is equitable, diverse, and inclusive.