Research

Brain, the final frontier

The complex neural network in our brain underpins our thoughts and behaviors. Understanding its structure and function (connectome) is a critical component for resolving the driving mechanism of our behavior and for developing novel intervention to improve brain function and performance. Recent advance in neuroimaging, such as functional magnetic resonance imaging (MRI), has revealed network deficit/atrophy unique to specific neurodegenerative and psychiatric disorders. This suggests that disease connectome may underlie the disease progression and mechanism.

Our approach

The long-term goal of the lab is to determine the link between brain network and behavior, and to use this knowledge to understand disease mechanism and to identify network targets for early diagnosis, prognosis and treatment. Our approach is to develop novel imaging methods to unveil the functional organization and plasticity of the brain network, and to identify biomarkers that associate the disease-driving molecules with the connectomic dysfunction and to use them as neuro-endophenotypes for the diagnosis and prognosis of diseases. We will use a translational research approach to develop and validate methods and biomarkers in rodent (especially transgenic mouse) models of brain disorders and then translated to human. We are using magnetic resonance imaging (MRI) as a primary tool for imaging of brain structure, function, connectivity and metabolism, and complemented with positron emission tomography (PET), spectroscopy, electrophysiology and optical imaging for molecular imaging and validation.

Research focus

The current focus of the lab is to understand the functional connectome in diseases with the following directions:

 1) Mechanism: understand the neural basis of resting-state fMRI and the functional role of resting-state networks in learning, memory and dementia;

 2) Technology: develop novel methods for imaging neural activity, connectivity and waste clearance, and new tools for intervention;

 3) Application: identify imaging biomarkers for neurodegenerative diseases, such as dementia, for early and precision diagnosis.

I. Neural basis and function of resting-state networks

Resting-state functional connectivity MRI has emerged as a new way to probe the functional networks of the brain in development, ageing, plasticity and disorders. Various intrinsic resting-state networks have been found in human brain, such as the default mode network. Due to the lack of direct electrophysiology correlate, the mechanism of this phenomenon is still under debate and what does the network pattern really mean is not known. We focus on understanding the underlying neurotransmission (receptor & transmitters) systems that regulate this large-scale synchronous activity. We approach using receptor-targeting neuropharmacological modulation in normal rodents and transgenic mice using BOLD and perfusion (CBF) fMRI and electrophysiology recording. We have identified a unique role of the adrenergic system, a major neuromodulatory system, plays an important role in the synchronous oscillation. To further understand the relationship between functional connectivity and neurotransmission, we utilize multi-fiber photometry with genetically encoded fluorescent reporters to measure cell-type specific (eg, inhibitory neurons) activities and/or receptor kinetics simultaneously with fMRI. We have also established optogenetic and chemogenetic tools to pinpoint the functional role of specific pathway.

In addition, the functional roles of the resting-state networks are largely unknown. We explored the behavioral induced change of resting-state networks after a spatial learning in the Morris water maze. It is found that drastically increased connectivity emerged after learning, included the default mode-like network. The network moved toward the cortex after a week, consistent with the current theory of memory consolidation. This highlights the potential roles of resting-state network in memory process and the use of fMRI to track it.

Since majority of transgenic models are based on mouse, we have demonstrated the world first resting-state functional connectivity MRI in the mouse brain. This technique has facilitated our understanding of connectivity in diseases and related treatment. Further application of this technique for transgenic mouse models of dementia, Huntington, autism, etc are ongoing.

Genetic tools, particularly optogenetics and chemogenetics (DREADDs), allows targeted neural modulation of specific cell type and pathway to understand the role of a network hub in the network function. Furthermore, combining calcium recording with fMRI simultaneously provides new ways to understand and validate the neural basis of the mysterious infra-slow synchrony.

Manganese, with its unique characteristic as a Ca2+ analog, has been used to map neuronal activation, track neuronal pathway, and enhance neural cytoarchitecture. We are further developing the MEMRI technique to allow better characterization of neural circuitry function at high resolution to understand responses of individual glomeruli in the olfactory bulb (Chuang, 2010) and nuclei in the hypothalamus (Ulyanova, 2017).

Glucose uptake & metabolism is a key marker of cellular function. Current imaging method relies on 18FDG-PET. Although 13C-MRS can detect glucose, the sensitivity is low. We have developed a novel method to image the glucose uptake and metabolism by 1H-MRI using chemical exchange saturation transfer (CEST) -- glucoCEST (Nasrallah, 2013). This technique is now widely applied in humans. We are now exploring using CEST for probing other metabolites in vivo.