Armen Bagdasarov

Clinical Intern at the Children's Hospital of Philadelphia and PhD Candidate in Clinical Psychology at Duke UniversityCurrently Seeking Research-Focused Post-Doctoral Fellowship or Faculty Position with Summer 2026 Start

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• Education & Training
• Program of Research
• Publications
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• Teaching & Mentoring Statement
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Program of Research

My program of research reflects both my work to date and what I hope to accomplish in the future. Broadly, I am committed to understanding how early brain development shapes risk and resilience for behavioral and mental health challenges, with the ultimate goal of informing interventions that support children’s healthy development.

Scalable Biomarkers for Early Identification of Psychopathology

My program of research centers on discovering objective brain-based biomarkers of psychopathology to improve risk stratification during early childhood (ages 0-8). Ultimately, my research aims to develop predictive models for identifying children in need of early intervention before psychiatric symptoms emerge. Critically, I am interested in scalable brain-based biomarkers that are affordable to implement in all communities and can be used to complement existing diagnostic tools in medical settings. Toward this end, I use a relatively affordable but very powerful neuroimaging tool for characterizing the spatial and temporal dynamics of brain activity: electroencephalography (EEG). My work focuses on (1) identifying associations between patterns of electrical brain activity measured with EEG and transdiagnostic processes relevant to psychopathology during early childhood, and (2) assessing the quality and reliability of EEG-based measures of behavior in young children.

EEG Microstates as Markers of Functional Brain Organization in Early Childhood

During graduate school, I developed expertise in analyzing EEG data with microstate analysis. Microstates are transient maps of electrical scalp potentials that reflect the activity of a network of brain structures working together when the brain is at rest (i.e., in the absence of external task demands). Each microstate lasts for approximately 100 milliseconds before switching to another of 4-6 microstates that explain the majority of variance in all spontaneous, intrinsic brain activity. I am especially interested in the “resting” brain during early childhood because it serves as the foundation for the emergence of increasingly complex behaviors. I have published four, first-author manuscripts to examine how microstates relate to cognitive functions and behavior during early childhood, and I have been awarded a National Science Foundation Graduate Research Fellowship in pursuit of this work. Together, my research suggests that the temporal properties of microstates are highly reliable with relatively small durations of data and reflect the brain’s functional integrity in key networks known to support higher-order cognitive functions and behavior, specifically attention and inhibitory control skills.

Infant Attention, Caregiving, and Early Neurobiological Predictors of Development

I am most excited by research with clear implications for early intervention and social policy. For example, in my most recent work with infants, I report that the duration of a microstate reflecting attention network activity is associated with sensitive infant-caregiver interactions–based on patterns of visual attention captured with dyadic, head-mounted eye tracking–and the duration of infant sustained attention during play. Critically, the duration of sustained attention during infancy is a known predictor of future executive and self-regulatory skills. Therefore, this work highlights the potential for developing neurobiological markers for identifying infants at risk for altered attention-related developmental outcomes (e.g., infants born premature) and measuring the neurobiological effects of early prevention and intervention strategies targeting caregiver behaviors for mitigating them.

Machine Learning with Longitudinal Cohorts to Identify Early Risk Pathways

In the future, I am interested in applying machine learning techniques to data from large, longitudinal studies to explore which biological and environmental factors from the prenatal period onward affect infant attention-related microstate activity. This work will help us understand the potentially cascading effects of very early life experiences on the development of behavioral challenges that begin to emerge for some children during early childhood (e.g., dysregulation) and may increase their risk for psychopathology. I am already starting to do this work with data from the YOUth Cohort Study in the Netherlands, a large-scale longitudinal project that follows children from pregnancy through early childhood with repeated assessments of brain, behavior, and environment.

High-Risk Infants as a Model for Neurodevelopment, Risk, and Resilience

Building on my work with normative samples, I hope to extend my program of research to include high-risk infants born preterm and/or with early medical complications. These infants often experience altered caregiving environments–long NICU stays, painful procedures, and heightened parental stress–and emerging evidence suggests that their brains develop differently as a result. Further, sensory-motor delays are often the first impairments identified and treated by medical providers. Together, altered caregiving environments and sensory-motor challenges can cascade into broader differences in not only how children interact with their world but also in how caregivers engage with them. As a result, these infants provide a particularly informative context for examining how early experiences shape the developing brain and developmental outcomes. Extending my expertise in EEG microstate analysis to this population will allow me to identify how early brain network dynamics differ in high-risk infants and whether they can serve as sensitive biomarkers of both vulnerability and plasticity. In doing so, this work may inform the design of interventions that capitalize on heightened plasticity during infancy by promoting responsive and attuned caregiving. Ultimately, I aim to establish a research program as faculty at an R1 university that integrates developmental neuroscience, early intervention, and translational approaches to improve outcomes for children at increased risk for behavioral and mental health challenges.

Publications

The following includes only first-authored publications that represent the core of my research program. Please see my CV or Google Scholar page for all other publications.

Clinical Interests

In line with my program of research, I am particularly interested in early childhood neuropsychological assessment, with the goal of supporting children and families during the earliest stages of development. I enjoy partnering with caregivers to better understand a child’s strengths and challenges, and to provide guidance that supports healthy growth. Of note, I have experience administering the Bayley Scales of Infant and Toddler Development to NICU graduates, and I am open to opportunities that include dedicated time to continue developing my clinical skills in early childhood neuropsychological assessment.

Teaching & Mentoring Statement

Neither of my parents grew up in the United States or attended college. As a first-generation college graduate, I understand how impactful it is to have teachers and mentors who make higher education accessible and supportive. This background shapes my commitment to fostering inclusive learning environments where students feel they belong and can grow.I take a developmental approach to teaching and mentoring: I meet students where they are, build on their strengths, and scaffold their learning toward independence. In the classroom, this means breaking down complex concepts, providing multiple entry points for engagement, and making the hidden curriculum of higher education explicit. In mentoring, it means tailoring guidance to each student’s goals and stage of training.Looking ahead, I see teaching and mentoring as a partnership in growth. Just as I challenge students to stretch beyond what they thought possible, they push me to refine my own thinking and practice. This reciprocal process keeps my work dynamic and underscores my commitment of supporting the next generation of learners.

Contact Armen

You can reach me by email using the button at the top of this page or by filling out the form below.