Over the past decade, the National Institute of Mental Health (NIMH) has invested several billion dollars for large-scale, multi-site, functional MRI (fMRI) cohort studies in pursuit of brain markers for mental illness, yet clinical translation of fMRI for diagnosis of mental illness is plagued with many challenges. Chief among them is the lack of reproducibility of findings at the individual level due to the suboptimal measurement reliability of short-quantity (<10 min) fMRI recordings. Research suggests that collecting hours ? not minutes ? of data per individual patient may be needed to fulfill the clinical promise of functional neuroimaging, but issues of cost, compliance and the ecological validity of tested paradigms render such fMRI studies impractical in patients with psychiatric conditions and contribute to the huge gap in the clinical utility of imaging technologies for mental health. To bridge the gap in translation of functional neuroimaging in clinical neuropsychiatry, we propose to optimize, test and validate a wearable imaging system based on functional near infrared spectroscopy (fNIRS) that is low-cost, accessible, reliable, and can be used at home for collecting highly- sampled brain activity in patients with mental illness, using the prefrontal activity of children with Attention Deficit Hyperactivity Disorder (ADHD) as a model illness to test the feasibility of this innovative paradigm. Compared with fMRI, fNIRS is inexpensive, portable, and more tolerant to subject movement, allowing for measurement of brain activity in naturalistic situations. Our central hypothesis is that collecting highly-sampled individual data will allow us to detect patterns of brain activity that can be reliably replicated at the individual level and that predict behavioral and clinical symptoms. A wealth of fMRI and fNIRS data already demonstrate (a) consistent hypoactivation in the prefrontal circuit in ADHD during executive functioning tasks and (b) association between hypoactivity in the prefrontal circuit in ADHD and behavioral and clinical symptoms. We will collect highly-sampled fNIRS data on the prefrontal activity of 30 children with ADHD and 30 typically developing controls. Data will be collected daily over three weeks while subjects are at rest and/or performing cognitive tasks on a smart-phone. Our interdisciplinary, multi-institutional team has already developed a very low-cost (<$100) prototype wearable, wireless fNIRS system for monitoring activity of the prefrontal cortex that we will refine (Aim 1) and deploy (Aim 2) through this proposal.
Aim 1 : Optimize a prototype wearable, wireless, multi-channel, smart-phone operated optical imaging system for regular monitoring of prefrontal activity at home.
Aim 2 : Test and validate the proposed system for reliable monitoring of prefrontal activity in children with ADHD. Successful completion of this first-of-a-kind study will help shift the current paradigm away from in-lab, small-quantity neuroimaging and pave the way for developing effective biomarkers that can be used clinically for diagnosis and early detection of mental disorders, monitoring the response to treatment.
Despite its substantial research utility, fMRI has not made its way into mainstream mental health clinics because of the low sensitivity of current fMRI studies to reliably detect individual brain activity patterns associated with mental illnesses. Accumulating evidence suggests that large quantities of artifact-free, individual neuroimaging data (i.e. highly-sampled individual data) are critical for determining whether differences in functional brain organization are behavior-related, disease-dependent, or epiphenomenal. We propose to refine a prototype wearable optical imaging system that can be used at home for collecting large- quantities of prefrontal activity data for differentiating individuals with ADHD and controls.
