NEUROIMAGING RESEARCH BRANCH

Branch Sections

• Cognitive Neuroscience and Psychopharmacology
  
• Magnetic Resonance Imaging and Spectroscopy
  
• Preclinical (Translational) Imaging Unit
  

NRB Lab Page

• Lab Page for the NRB
  

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Section of Cognitive Neuroscience and Psychopharmacology

Section Chief: Elliot A. Stein, Ph.D.

Research projects:

• To apply multimodal imaging technologies (DTI, fMRI, PET, MRS, EEG) to understand the neurobiological substrates of human drug abuse. Specifically, we are examining the effects of nicotine, cocaine, marijuana and ecstasy on, among other constructs, response inhibition, reward processes, decision making, attention, and working memory.
  
• To understand the neurobiological substrates and behavioral consequences of drug related cues.
  
• To develop real time fMRI biofeedback to understand the localization of and circumstances under which regional brain signals can come under individual control. Since craving intensity is related to drug seeking and taking, our goal is to develop behavioral strategies, with the aid of such biofeedback, to train subjects to better control drug cravings and reduce recidivism.
  
• To apply functional connectivity analysis methods to determine the neuronal circuitry critically altered in drug dependence.
  
• To apply advanced structural imaging and analysis techniques (e.g. DTI, DBM) to understand the consequences of long term drug use on brain structures.
  
• To understand drug use comorbidity in patients with Schizophrenia.

Section of Magnetic Resonance Imaging and Spectroscopy

Section Chief: Yihong Yang, Ph.D.

Research projects:

• To develop functional magnetic resonance imaging (fMRI) techniques to measure evoked and resting activity of the brain. In evoked-fMRI, brain activation is detected using multiple parameters that provide complementary and quantitative measurements. In resting-state fMRI, new acquisition and analysis strategies are being developed to assess alterations of brain circuitry in drug users.
• To investigate structural MRI techniques used to assess tissue integrity related to brain dysfunction. Diffusion tensor imaging (DTI) and beyond DTI techniques are being developed to examine microstructural changes in white and gray matter, and fiber bundles delineated by tractography techniques. Novel image registration methods based on an implicit reference are being developed for more accurate group analysis. We are also developing voxelwise methods to evaluate structural changes in the brain, and evaluating these methods in substance abuse populations.
• To develop magnetic resonance spectroscopy (MRS) techniques to measure metabolite and neurotransmitter concentrations in the brain. Specifically, we are focusing on the detection and quantification of glutamate, glutamine and GABA levels. New methods are being developed to reliably measure these compounds and evaluate their applications in neuropharmacological studies.
• To investigate underlying neuronal mechanisms of fMRI signal using preclinical models. Electrophysiological and fMRI signals from the brain are integrated to reveal the neuronal origins of the ongoing fMRI signal.

Preclinical (Translational) Imaging Unit

Investigators: Hanbing Lu, Ph.D., Yihong Yang, Ph.D., Elliot A. Stein, Ph.D.

Research projects:

• To determine, at a systems level, the neurobiological consequences following acute and chronic administration of, and withdrawal from, psychostimulant drugs such as nicotine and cocaine in preclinical models of drug dependence.
  
• Applying several NHP models to understand the long term consequences of early developmental stress and chronic methamphetamine administration on brain structure, function and biochemistry.
  
• To develop and apply the use of manganese enhanced MRI (MEMI) to determine neuronal pathways mediating the acute and long term plastic effects of abused drugs.
  
• To develop novel structural, functional and biochemical techniques in preclinical models of drug dependence, including CBV, ASL, MRS, MEMRI.
  
• To develop and apply quantitative cerebral blood flow measures in preclinical models of stroke.