Email

junghwan.kim@bcm.edu

Positions

Assistant Professor

Neuroscience
Baylor College of Medicine
Houston, TX US

Addresses

BCM-Smith Medical Research Bldg (Office)

Room: BCMS-T115A
Houston, TX 77030
United States
Phone: (713) 798-6502

Education

Post-Doctoral Fellowship at The University of Texas at Austin

08/2013 - Austin, Texas United States

Transient Hemodynamic Response in Cerebral Cortex during Brief Neural Stimulation

PhD from University of Florida

12/2010 - Gainesville, Florida United States

Development of Diffusion Tensor Imaging Based-Computational Models of Direct Infusion into the Central Nervous System

Professional Interests

• Neurovascular coupling
• fMRI
• Hemodynamic response function
• Oxygen transport model
• Cerebrovascular physiology
• Computational Fluid Dynamic
• Traumatic brain injury

Professional Statement

Dr. Jung Hwan Kim’s career is marked by a multitude of pioneering contributions to both the mechanical engineering and neuroscience fields, specifically in the area of computational fluid modeling. He has conducted investigations aimed at understanding the transport phenomena in the central nervous system (CNS).

Dr. Kim’s primary research goals is to investigate neurovascular coupling in human brain from the blood oxygen level dependent (BOLD) response evoked by a brief stimulus, called the hemodynamic response function (HRF) with high-resolution fMRI. Dr. Kim developed a new model that is an excellent tool to interpret transient oxygen transport and hemodynamic mechanisms in the brain. The model shows how cerebral blood flow (CBF) and cerebral metabolic oxygen consumption (CMRO2) responses compete to produce the observed features of the HRF, which can tremendously expand our understanding of neurovascular coupling and the corresponding physiology. The ability to non-invasively characterize neural activity using fMRI will be of huge utility in research for normal human brain functions. A detailed understanding of neurovascular & neurometabolic coupling/decoupling, in turn, will enable its use as a diagnostic of brain pathologies (e.g. traumatic brain injury and Alzheimer’s disease).

Dr. Kim's early-stage research was related to convection enhanced delivery (CED), a fairly new drug delivery approach to deliver drugs to targets in the CNS. The main difficulty researchers had encountered when trying to deliver drugs to the brain is the blood brain barrier (BBB), which protects the brain from foreign substances. Penetrating the BBB had proven to be a problem for conventional drug delivery methods. Dr. Kim created a novel image-based computational model that optimizes local targeting of CED in the CNS. The transport properties and anatomical boundaries are assigned on a voxel-by-voxel basis using geometrical structure information from in vivo and excised rat spinal cord and brain after magnetic resonance (MR) diffusion tensor imaging.

Websites

Selected Publications

• J. H. Kim, G.W. Astary, T. L. Nobrega, S. Kantorovich, P. R. Carney, T. H. Mareci "Dynamic Contrast-enhanced MRI of Gd-albumin Delivery to the Rat Hippocampus In vivo by Convection-Enhanced Delivery." J Neurosci Methods. 2012;209(1):62-73.
• J. H. Kim, G. W. Astary, S. Kantorovich, T. H. Mareci, P. R. Carney, M. Sarntinoranont "Voxelized Computational Model for Convection Enhanced Delivery in the Rat Ventral Hippocampus: Comparison with In Vivo MR Experimental Studies." Ann Biomed Eng. 2012;40(9):2043-2058.
• J. H. Kim, R. Khan, J. Thompson, D. Ress "Model of the transient neurovascular response based on prompt arterial dilation." J Cereb Blood Flow Metab. 2013;33(9):1429-1439.
• J. H. Kim, D. Ress "Arterial impulse model for the BOLD response to brief neural activation." Neuroimage. 2016 Jan 1;124:394-408.

Memberships

International Society of Cerebral Blood Flow

Member (04/2013)

Organization for Human Brain Mapping

Member (01/2012)

Society for Neuroscience

Member (01/2011)

Biomedical Engineering Society

(01/2007)

Funding

Quantitative characterization of human subcortical hemodynamic response - #K25HL131997

$616,534.00 (01/01/2017 - 01/09/2022)

Grant funding from NIH NHLBI

Subcortical human brain regions play critical roles in functions from homeostasis to cognition. However, there has been a dearth of research on full assessments of human subcortical health. Quantitative characterization of subcortical responses has a great potential to unveil the mechanisms of various neurodegenerative disorders including Alzheimer’s, Huntington’s, and Parkinson’s Disease and cerebrovascular pathology such as traumatic brain injury (TBI). Here, we use functional magnetic resonance imaging (fMRI) to measure the blood oxygen level dependent (BOLD) response in subcortical regions. We will create simple multisensory integration tasks that produce BOLD response evoked by this brief brain activation – so called BOLD hemodynamic response function (HRF). We will also use various MRI methods such as proton-density weighted imaging (PDWI), and diffusion tensor imaging (DTI) for structural assessments. BOLD HRF combined with PDWI and DTI will enable remarkably complete assessments of subcortical neurovascular health, including quantification of nuclear volumes, white matter connectivity, and correlations among these metrics. In the proposed research study, we will obtain health control database for this novel metrics. We will develop a novel biomechanical transport model to predict underlying cerebral blood flow and oxygen metabolism corresponding to BOLD HRFs. We will also develop a simple but effective linear flow model based on an electrical circuit analogy to show mechanisms of blood flow response driven by local neural activity. This flow network model will be validated with flow measurement from arterial spin labelling perfusion MR imaging. The proposed model will address a critical gap in our knowledge of subcortical cerebrovascular physiology.

Characterization of neurovascular and neurometabolic coupling of the negative BOLD response in human - #1R01NS121040

$2,019,583.00 (12/01/2021 - 11/30/2026)

Grant funding from NIH NINDS

For task-based functional magnetic resonance imaging (fMRI), the positive blood-oxygen-level-dependent (BOLD) response has been widely used and often assumed that it linearly reflects local neural activity. However, a significant portion of brain regions responds with signal decreases upon activation, known as the negative BOLD response (NBR). Although the negative BOLD response (NBR) and its origin have been explored extensively, temporal characteristics and spatial structure of the NBR, and corresponding underlying physiological dynamics are still poorly understood. We propose to investigate dynamics of the NBR evoked by a brief stimulus –the negative hemodynamic response function (nHRF) and its underlying neurovascular and neurometabolic responses using our novel experimental paradigms with high spatiotemporal resolution BOLD and arterial spin labelling (ASL) fMRI modalities. High spatial and temporal resolution BOLD measurements will resolve temporal dynamics of the nHRF as a functional of cortical depth and distance from adjacent positive BOLD responses along the cortical surface. We also evaluated shift-invariant temporal linearity by measuring dynamics of the NBR for varying stimulus durations. Fine spatiotemporal sampling ASL measurements in conjunction with a novel stimulus- onset-time dithering scheme will provide accurate quantification of the cerebral blood flow associated with the NBR within gray matter. We advance our novel computational model based on prompt arterial dynamics observed in recent experimental studies, enabling estimation of realistic neurometabolic response associated with the nHRF. The model will offer a better detailed interpretation of the underlying physiological components associated with the nHRF. Our proposed research will provide a detailed understanding of neurovascular and neurometabolic (de-)coupling associated with nHRF, expanding our knowledge of normal brain functions. Such details with precision to understand the NBR and its physiology was not available in previous studies. Ultimately, success of our proposed research will motivate use of the proposed fMRI approaches and modeling schemes for brain pathologies that involve neurovascular and neurometabolic coupling.