PROJECT SUMMARY/ABSTRACT
A major challenge in mental health care includes inconsistent outcomes of current psychotherapeutic,
pharmacologic, and brain stimulation interventions. We theorize that across individuals, heterogeneous neural
underpinnings manifest at a systems level, leading to impaired domains of function and specific diagnoses.
This heterogeneity causes the same intervention to produce different outcomes across individuals. To
overcome this challenge, we hypothesize that systems-level brain activity (neural oscillations) contains the
information necessary to predict both individual variation in a domain of brain function and identify biomarkers
to guide the individualized implementation of an intervention. To test these hypotheses, a model brain system
is needed with sufficient variation and complexity to produce heterogeneity in behavior and intervention
outcomes. Prior work, including our own preliminary data, demonstrates such behavioral variation exists
across individuals and sexes in an outbred rat strain (Sprague Dawley) performing the delay discounting task
(DDT) and risk discounting task (RDT). When brain stimulation (Aim 1), pharmacologic (Aim 2) or
chemogenetic (Aim 3) interventions have been implemented in these rats, they produce heterogeneous effects
on task performance across individuals making this an excellent model system to evaluate our hypotheses.
Our proposed proof-of-concept study will determine the potential utility of neural oscillations as biomarkers
reflecting individual variation in the neural underpinnings of delay and risk discounting and the predisposition of
those individuals to respond to interventions. We will use machine learning to determine if: 1) oscillations can
predict variation in task performance across individuals and time; 2) oscillations can predict individual
intervention outcomes; and 3) changes in oscillations induced by interventions are predictive of corresponding
changes in DDT or RDT performance.
Further enhancing the translational relevance of this proposal, the neural systems that modulate the
value of rewards associated with delay and risk discounting share homology between rodents and humans and
have been linked to important clinical outcomes. For instance, the excessive reduction of reward value by
delay relates to a significant risk for poor outcomes in multiple psychiatric conditions (e.g., ADHD,
schizophrenia and borderline personality disorder). Abnormal delay and risk discounting have also been linked
to specific behaviors, including suicide, violence and risky substance use, enhancing the impact of the
proposed studies. As an early-career investigator, funding for this proposal would allow me to launch an
innovative translational research program aligned with NIMH strategic goals focused on developing systems-
level brain activity biomarkers to guide the individualized implementation of interventions for patients with
mental illness.
