Yunsuo Duan

Neural Systems Subserving Valence and Arousal During the Experience of Induced Emotions

The circumplex model of affect construes all emotions as linear combinations of 2 independent neurophysiological dimensions, valence and arousal. We used functional magnetic resonance imaging to identify the neural networks subserving valence and arousal, and we assessed, in 10 participants, the associations of the BOLD (blood oxygen level-dependent) response, an indirect index of neural activity, with ratings of valence and arousal during the emotional experiences induced by the presentation of evocative sentences. Unpleasant emotional experience was associated with increased BOLD signal intensities in the supplementary motor, anterior midcingulate, right dorsolateral prefrontal, occipito-temporal, inferior parietal, and cerebellar cortices. Highly arousing emotions were associated with increased BOLD signal intensities in the left thalamus, globus pallidus, caudate, parahippocampal gyrus, amygdala, premotor cortex, and cerebellar vermis. Separate analyses using a finite impulse response model confirmed these results and revealed that pleasant emotions engaged an additional network that included the midbrain, ventral striatum, and caudate nucleus, all portions of a reward circuit. These findings suggest the existence of distinct networks subserving the valence and arousal dimensions of emotions, with midline and medial temporal lobe structures mediating arousal and dorsal cortical areas and mesolimbic pathways mediating valence.

A virtual reality-based FMRI study of reward-based spatial learning

Although temporo-parietal cortices mediate spatial navigation in animals and humans, the neural correlates of reward-based spatial learning are less well known. Twenty-five healthy adults performed a virtual reality fMRI task that required learning to use extra-maze cues to navigate an 8-arm radial maze and find hidden rewards. Searching the maze in the spatial learning condition compared to the control conditions was associated with activation of temporo-parietal regions, albeit not including the hippocampus. The receipt of rewards was associated with activation of the hippocampus in a control condition when using the extra-maze cues for navigation was rendered impossible by randomizing the spatial location of cues. Our novel experimental design allowed us to assess the differential contributions of the hippocampus and other temporo-parietal areas to searching and reward processing during reward-based spatial learning. This translational research will permit parallel studies in animals and humans to establish the functional similarity of learning systems across species; cellular and molecular studies in animals may then inform the effects of manipulations on these systems in humans, and fMRI studies in humans may inform the interpretation and relevance of findings in animals.

Multimodal Magnetic Resonance Imaging: The Coordinated Use of Multiple, Mutually Informative Probes to Understand Brain Structure and Function

Differing imaging modalities provide unique channels of information to probe differing aspects of the brains structural or functional organization. In combination, differing modalities provide complementary and mutually informative data about tissue organization that is more than their sum. We acquired and spatially coregistered data in four MRI modalities—anatomical MRI, functional MRI, diffusion tensor imaging (DTI), and magnetic resonance spectroscopy (MRS)—from 20 healthy adults to understand how interindividual variability in measures from one modality account for variability in measures from other modalities at each voxel of the brain. We detected significant correlations of local volumes with the magnitude of functional activation, suggesting that underlying variation in local volumes contributes to individual variability in functional activation. We also detected significant inverse correlations of NAA (a putative measure of neuronal density and viability) with volumes of white matter in the frontal cortex, with DTI‐based measures of tissue organization within the superior longitudinal fasciculus, and with the magnitude of functional activation and default‐mode activity during simple visual and motor tasks, indicating that substantial variance in local volumes, white matter organization, and functional activation derives from an underlying variability in the number or density of neurons in those regions. Many of these imaging measures correlated with measures of intellectual ability within differing brain tissues and differing neural systems, demonstrating that the neural determinants of intellectual capacity involve numerous and disparate features of brain tissue organization, a conclusion that could be made with confidence only when imaging the same individuals with multiple MRI modalities. Hum Brain Mapp, 2013.

Improving the spectral resolution and spectral fitting of (1) H MRSI data from human calf muscle by the SPREAD technique.

Proton magnetic resonance spectroscopic imaging (1H MRSI) has been used for the in vivo measurement of intramyocellular lipids (IMCLs) in human calf muscle for almost two decades, but the low spectral resolution between extramyocellular lipids (EMCLs) and IMCLs, partially caused by the magnetic field inhomogeneity, has hindered the accuracy of spectral fitting. The purpose of this paper was to enhance the spectral resolution of 1H MRSI data from human calf muscle using the SPREAD (spectral resolution amelioration by deconvolution) technique and to assess the influence of improved spectral resolution on the accuracy of spectral fitting and on in vivo measurement of IMCLs. We acquired MRI and 1H MRSI data from calf muscles of three healthy volunteers. We reconstructed spectral lineshapes of the 1H MRSI data based on field maps and used the lineshapes to deconvolve the measured MRS spectra, thereby eliminating the line broadening caused by field inhomogeneities and improving the spectral resolution of the 1H MRSI data. We employed Monte Carlo (MC) simulations with 200 noise realizations to measure the variations of spectral fitting parameters and used an F‐test to evaluate the significance of the differences of the variations between the spectra before SPREAD and after SPREAD. We also used Cramer–Rao lower bounds (CRLBs) to assess the improvements of spectral fitting after SPREAD. The use of SPREAD enhanced the separation between EMCL and IMCL peaks in 1H MRSI spectra from human calf muscle. MC simulations and F‐tests showed that the use of SPREAD significantly reduced the standard deviations of the estimated IMCL peak areas (p < 10−8), and the CRLBs were strongly reduced (by ~37%). Copyright

Study of the development of fetal baboon brain using magnetic resonance imaging at 3 Tesla

Direct observational data on the development of the brains of human and nonhuman primates is on remarkably scant, and most of our understanding of primate brain development is extrapolated from findings in rodent models. Magnetic resonance imaging (MRI) is a promising tool for the noninvasive, longitudinal study of the developing primate brain. We devised a protocol to scan pregnant baboons serially at 3 T for up to 3 h per session. Seven baboons were scanned 1-6 times, beginning as early as 56 days post-conceptional age, and as late as 185 days (term approximately 185 days). Successful scanning of the fetal baboon required careful animal preparation and anesthesia, in addition to optimization of the scanning protocol. We successfully acquired maps of relaxation times (T(1) and T(2)) and high-resolution anatomical images of the brains of fetal baboons at multiple time points during the course of gestation. These images demonstrated the convergence of gray and white matter contrast near term, and furthermore demonstrated that the loss of contrast at that age is a consequence of the continuous change in relaxation times during fetal brain development. These data furthermore demonstrate that maps of relaxation times have clear advantages over the relaxation time weighted images for the tracking of the changes in brain structure during fetal development. This protocol for in utero MRI of fetal baboon brains will help to advance the use of nonhuman primate models to study fetal brain development longitudinally.

Compressed sensing MRI combined with SENSE in partial k-space

Compressed sensing (CS), parallel imaging and partial Fourier (PF) acquisition are all effective methods to reduce k-space sampling and therefore accelerate MR acquisition. The combined use of these methods gives us more options to balance the needs for scan speed and image quality. We conducted simulations on full k-space data to demonstrate the potential use of combining CS-SENSE with PF acquisition in anatomical MRIs of the human brain. To test the accelerated acquisition of high-resolution T1-weighted images of brain, we modified a 3D FSPGR sequence on a GE 3T scanner to implement different undersampling schemes based on CS, including partial Fourier CS-SENSE. Partially sampled k-space data were acquired and then reconstructed to brain images. CS-SENSE combined with PF sampling is able to provide better reconstructed images than CS only, or than CS-SENSE without PF for the same total acceleration. Combining PF sampling with CS-SENSE enables us to further accelerate image acquisition or improve image quality while holding the acceleration rate constant.

Computational and experimental optimization of a double-tuned (1)H/(31)P four-ring birdcage head coil for MRS at 3T.

To optimize the homogeneity and efficiency of the B1 magnetic field of a four‐ring birdcage head coil that is double‐tuned at the Larmor frequencies of both 31P and 1H and optimized to acquire magnetic resonance spectroscopy (MRS) data at 3T for the study of infants.

Neural Correlates of Reward-Based Spatial Learning in Persons with Cocaine Dependence

Dysfunctional learning systems are thought to be central to the pathogenesis of and impair recovery from addictions. The functioning of the brain circuits for episodic memory or learning that support goal-directed behavior has not been studied previously in persons with cocaine dependence (CD). Thirteen abstinent CD and 13 healthy participants underwent MRI scanning while performing a task that requires the use of spatial cues to navigate a virtual-reality environment and find monetary rewards, allowing the functional assessment of the brain systems for spatial learning, a form of episodic memory. Whereas both groups performed similarly on the reward-based spatial learning task, we identified disturbances in brain regions involved in learning and reward in CD participants. In particular, CD was associated with impaired functioning of medial temporal lobe (MTL), a brain region that is crucial for spatial learning (and episodic memory) with concomitant recruitment of striatum (which normally participates in stimulus-response, or habit, learning), and prefrontal cortex. CD was also associated with enhanced sensitivity of the ventral striatum to unexpected rewards but not to expected rewards earned during spatial learning. We provide evidence that spatial learning in CD is characterized by disturbances in functioning of an MTL-based system for episodic memory and a striatum-based system for stimulus-response learning and reward. We have found additional abnormalities in distributed cortical regions. Consistent with findings from animal studies, we provide the first evidence in humans describing the disruptive effects of cocaine on the coordinated functioning of multiple neural systems for learning and memory.

Assessment of a PML Boundary Condition for Simulating an MRI Radio Frequency Coil

Computational methods such as the finite difference time domain (FDTD) play an important role in simulating radiofrequency (RF) coils used in magnetic resonance imaging (MRI). The choice of absorbing boundary conditions affects the final outcome of such studies. We have used FDTD to assess the Berengers perfectly matched layer (PML) as an absorbing boundary condition for computation of the resonance patterns and electromagnetic fields of RF coils. We first experimentally constructed a high-pass birdcage head coil, measured its resonance pattern, and used it to acquire proton ( 1 H ) phantom MRI images. We then computed the resonance pattern and B 1 field of the coil using FDTD with a PML as an absorbing boundary condition. We assessed the accuracy and efficiency of PML by adjusting the parameters of the PML and comparing the calculated results with measured ones. The optimal PML parameters that produce accurate (comparable to the experimental findings) FDTD calculations are then provided for the birdcage head coil operating at 127.72 MHz, the Larmor frequency of 1 H at 3 Tesla (T).

Automated assessment of the quality of diffusion tensor imaging data using color cast of color-encoded fractional anisotropy images

Diffusion tensor imaging (DTI) data often suffer from artifacts caused by motion. These artifacts are especially severe in DTI data from infants, and implementing tight quality controls is therefore imperative for DTI studies of infants. Currently, routine procedures for quality assurance of DTI data involve the slice-wise visual inspection of color-encoded, fractional anisotropy (CFA) images. Such procedures often yield inconsistent results across different data sets, across different operators who are examining those data sets, and sometimes even across time when the same operator inspects the same data set on two different occasions. We propose a more consistent, reliable, and effective method to evaluate the quality of CFA images automatically using their color cast, which is calculated on the distribution statistics of the 2D histogram in the color space as defined by the International Commission on Illumination (CIE) on lightness and a and b (LAB) for the color-opponent dimensions (also known as the CIELAB color space) of the images. Experimental results using DTI data acquired from neonates verified that this proposed method is rapid and accurate. The method thus provides a new tool for real-time quality assurance for DTI data.