Adam Anderson - US grants

Affective primacy refers to the notion that affective reactions are not dependent upon cognitive mediation, and thus affective and cognitive evaluations are to some degree dependent on functionally independent information processing streams with different behavioral dynamics. It is generally thought that affective information processing is endowed with special features: It is largely preattentive/automatic, can occur outside of awareness and prior to the appraisal of more general cognitive and perceptual features. These features of affective processing may be referred to as affective automaticity. The primary aim of this proposal is to apply functional magnetic resonance imaging (MRI) to examine the neural basis of affective automaticity by testing the following hypotheses: 1) Perceptual processing of affective but not neural stimulus dimensions is accomplished independent of attentional resource allocation, 2) Neural responses to affectively significant but not neutral stimuli are evoked prior to and independent of perceptual awareness, and 3) Neural responses to affectively significant stimuli support affective discriminations without awareness.

DESCRIPTION (provided by applicant): This work aims to develop and evaluate new tools for non-invasive analysis of white matter fiber bundles in the brain. Diffusion weighted magnetic resonance imaging (MRI) provides information on fiber orientation because the diffusion of tissue water is faster parallel than perpendicular to axons. In addition, the diffusion measurement is sensitive to cellular properties such as cell type, size, and volume fraction. Diffusion tensor imaging (DTI) has been widely used to assess white matter development and pathology, as well as to reconstruct fiber paths in the brain. However, it has become clear that the technique has two major limitations. First, image noise produces both noise and bias in the estimated diffusion tensor. This complicates comparisons of DTI parameters between subjects, and leads to errors in estimated fiber paths. Second, conventional DTI is based on the assumption that a single tensor describes the diffusion in each image voxel. The single-tensor model is inappropriate in regions of the brain with complicated fiber structure (e.g., crossing or splaying fibers). An alternative method, 'q-space' imaging, can be used to quantify diffusion using very few assumptions, but requires impractically long scans for most clinical or pediatric studies. Extended q-space experiments show that the single-tensor model is generally inappropriate, but at present there are no established alternatives suitable for routine clinical use. The studies in this proposal aim to evaluate and mitigate the effects of noise and partial volume averaging in DTI. Specifically, we propose the following: (1) to test theoretical predictions of the effects of noise on the diffusion tensor and estimated fiber paths, and to quantify the performance of a tensor denoising algorithm. (2) To develop high spatial resolution DTI using navigated, multiple shot echo planar imaging. (3) To develop a time-efficient approach to DTI that uses a multiple-tensor model of diffusion in each voxel, and test its reliability in phantom and human studies. (4) To develop approaches to fiber tracking and segmentation using the new multiple-tensor information, and test these in phantom and human subjects. We expect that the resulting methods will significantly improve the sensitivity of DTI studies. Overall this work will help to define the capabilities and limitations of fiber characterization using MRI, which represents a powerful new approach for studying the structure of neural tissue.

DESCRIPTION (provided by applicant): The human connectome is a description of all connections between neurons in the human brain. Advances in diffusion magnetic resonance imaging (DMRI) make it possible to image macroscopic fibers of axons in living humans, outlining major structural networks in the brain. It is believed that these networks are affected i a wide range of brain disorders and that mapping connectivity, and connectivity deficits, will advance our understanding of normal development and complex brain disorders. While some theoretical limitations of the imaging techniques are known, little work has been done to quantify the actual impact of these limitations on connectivity measurements in the brain. The project will address this problem using in vivo and ex vivo data from the squirrel monkey, acquired at multiple spatial scales. In Aim 1, DMRI estimates of long-range cortical connectivity will be compared to measurements based on neuroanatomical tracer injections. These studies will provide the first quantitative validation of DMRI measurements of cortical connectivity. In Aim 2, sources of error in DMRI connectivity will be determined by comparing DMRI data to axon distributions measured in the same brain and voxel locations using widefield and confocal microscopy. These experiments will determine the most important limitations in practice and evaluate new adaptive strategies for mitigating the leading sources of error. Although DMRI 'connection strength' is increasingly used as an end-point in human studies, its biophysical interpretation is unclear. The project will also identify the biophysical determinants of connectio strength in brain tissue. Aim 3 will focus on DMRI measurements in the cortex. Recent advances in high spatial resolution human imaging have shown that diffusion is significantly anisotropic in the cortex and can be reliably measured. This observation suggests that DMRI could become a useful method for detecting neurodegenerative disease. In Aim 3, DMRI and histological data from the squirrel monkey will be used to test the hypothesis that diffusion properties reflect myeloarchitecture, neuronal density, and total cell density in cortical tissue. Finally, in Aim 4, a web resource will be constructed to make available the project image data, analysis, and visualization tools. Several of the leading approaches to DMRI analysis will be tested in this project, however it is not feasible to include all current and future methods. Instead, we will provide a platform for future advances in connectomics-an atlas of spatially aligned DMRI and microscopy data to allow the neuroimaging community to evaluate and refine novel methods. In summary, the project will remove important barriers to non-invasive assessment of brain connectivity by identifying critical methodological limitations, testing promising solutions, and facilitating validation of advanced algorithms. The results will benefit current and future efforts to understand the connectome in animals and humans.

More than 50% of VKC investigators conduct clinical or translational research. The overarching goal of Core D is to meet the needs of VKC investigators to characterize brain structure, function, and circadian rhythm in their study participants. Core D focuses on major technological resources to which no single lab has access. VKC investigators work with Core faculty and staff to assess neurodevelopment, as well as providing related consulting services. The Core offers neuroimaging, psychophysiology, and polysomnography services. Core D thus remains an important bridge and interdisciplinary crossroad for users, including basic scientists who are adding a human component to their studies and behavioral scientists who are adding a neurological component to their clinical research. Core D helps researchers examine behavioral and neurological aspects of such complex disorders as autism, learning and communication disorders, and IDD syndromes.

The objective of this research is to develop a cyber-physical system capable of displaying the in vivo surgical area directly onto patients' skin in real-time high definition. This system will give surgeons an ?x-ray? vision experience, since they see directly through the skin, and remove a spatial bottleneck and additional scarring caused by laparoscopes in minimally invasive surgery. The approach is to develop micro-cameras that: occupy no space required by surgical tools, produce no additional scarring to the patient, and transfer wireless high-definition video images. A virtual view generating system will project the panoramic videos from all cameras to the right spot on the patient?s body with geometry and color distortion compensation. A surgeon-camera-interaction system will be investigated to allow surgeons to control viewpoint with gesture recognition and finger tracking. Novel techniques will be developed for zero-latency high-definition wireless video transfer through the in vivo/ex vivo medium. Image viewpoint alignment and distortion compensation in real time will also be investigated. The results will be a potential paradigm shift in minimally invasive surgery.

The proposed work benefits the millions of surgeries capable of being performed through a single incision in the abdomen by providing virtually transparent skin to surgeons who will enjoy all the visual benefits of open-cavity surgery without all the associated risks to the patient. The goals of this research are extremely ?hands-on? and immediately applicable to outreach activities that can excite youth, minority students, and others about the science, medicine a and engineering careers.

The wireless infrastructure of the United States is often considered key to the country's economic prosperity and national security. The data rate per link has increased exponentially over the last 20 years and is expected to continue to do so into the future if the problem of congested radio frequency spectrum can be solved. Paradoxically, the issue of congested licensed wireless spectrum, in modern networks, is at odds with the sparsity of the entire spectrum usage - as little as 10% use at any given moment. One possibility for next-generation wireless is to employ cognitive intelligent radios that can "socially" share the wireless spectrum without disruption of preexisting systems in hopes of increasing the overall usage of available spectrum. These intelligent radios will weave through spectral "traffic" as one might envision autonomous vehicles doing someday in the near future; however, unlike vehicles, two of these intelligent radios must meet somewhere in spectrum in order to form a link. This work proposes a universal spectral language to enable rendezvous of cognitive intelligent radios.

The objective of this project will be to create such a language where any wireless device that can sense or "look" at spectrum can also communicate via spectrum. This approach is a passive and noninvasive method for spectrum usage optimization with device-to-device communication. The universal language lets heterogeneous devices form networks and mismatched networks share the spectrum without centralized control. This intelligent cognition causes conflict among users and networks which affects efficient and fair spectrum access similar to the human behavior. The behavior of autonomous networks can then mimic this social behavior, leading to a possible solution to sharing spectrum. The algorithms developed on this project will foster a new wireless environment that mimics stable social behavior, using cognitive intelligent radios and universal communication that can lead naturally to intelligent and social solutions to network spectrum sharing.

In principle, the signal-to-noise ratio of magnetic resonance imaging (MRI) increases with the strength of the static magnetic field, B0. This increase can be used to detect smaller image features and subtler signal changes, for example in earlier stages of disease. However, due to practical limitations in image quality, high field MRI has found only limited application in both research and clinical studies. The most severe limitation is due to inhomogeneities in the radio frequency (RF) magnetic field, B1, required for spin excitation. These inhomogeneities are caused by shorter wavelengths and increased conductive losses at the higher frequencies required for spin resonance in higher static fields. When the wavelength of the RF field is not large compared to the region of interest, it is no longer possible to generate a uniform B1 field over that region. This typically leads to strong variations in signal and contrast over the field of view and hence relatively low overall image quality. Although progress has been made to mitigate these effects, e.g., with new pulse designs and/or multiple transmit coils, there is still no general solution for arbitrary field strengths, excitation flip angles, and volumes of interest. This project will develop and evaluate a new approach to the problem. The electromagnetic fields transmitted by a coil array and generated within the body can be described in terms of discrete modes. The coupling between transmitted and internal modes will be determined and used to solve the inverse problem, ?what combination of transmitted field modes is required to generate a desired internal target field?? The RF coil array is designed to provide independent control over all modes of the transmitted field (through 6th order modes). This provides control over the internal field through the same maximum order. In dielectric samples, a candidate target field is a traveling plane wave, which subjects all spins in the sample to the same magnitude RF magnetic field. Hence the new method is called Traveling Internal Plane-wave Synthesis (TIPS). For dielectric conducting samples (such as tissues), a focused wave compensates for conductive losses and can provide excellent uniformity over the sample volume. The project has two specific aims. The first is to build the RF system for full control of the transmitted field (through 6th order), using a dense array of steerable magnetic dipoles. This provides the maximum possible control over internal fields (to the same order). The second aim is to evaluate the system?s performance in human volunteers in a 7 Tesla human scanner. The new method will be compared to conventional RF shimming, using the uniformity of the magnitude of B1 and specific absorption rate (SAR) over the volumes of interest as figures of merit. The outcome of the project will be a radically new approach to the design of RF pulses and hardware and the removal of a critical barrier to progress in magnetic resonance imaging.

PROJECT SUMMARY    We are facing a growing crisis of a greater number of seniors living with a decline in cognitive function as a  common consequence of aging. Once an impairment has reached a level of clinical significance, treatment  options are limited. We propose to examine age-­related differences in trait and state autonomic control of heart  rate and their relation to cognitive performance humans and rats. While cognitive changes may be masked by  compensatory efforts, autonomic measures may be more revealing of the underlying age-­related changes in the  neural substrates and neurochemistry of aging and its clinical course. We will examine these autonomic  regulation of heart rate, its relation to and modulation by cognitive performance, as a peripheral proxy of early  central alteration of the cholinergic basal forebrain (BF), a progenitor of system-­wide neuroanatomical and  neurochemical changes related to aging. To understand the underlying neural mechanistic bases of these  autonomic indices, we will apply a cross-­species approach, including human functional neuroimaging as well as  nonhuman neurochemical examinations. Specific Aim 1 will examine whether age-­related differences in  cognitive control are associated with altered autonomic regulation of the heart. Approach: We will employ  a cross-­sectional examination of inhibitory cognitive control tasks, which we have shown to depend on the  cholinergic BF in rats, in a diverse sample of male and female young, middle-­aged, and older adults, examining  how cognitive performance relates to autonomic parasympathetic influences on the heart, reflected in vagally-­ mediated heart rate variability(phasic, beat-­to-­beat heart rate variability). Specific Aim 2 will examine the  specific role of the BF, and its afferent networks, in connecting age-­related differences in cognitive  control and autonomic regulation of the heart.  Approach: We will employ multi-­echo fMRI to acquire high  SNR signal from BF nuclei and autonomic phasic parasympathetic influences on heart, and their relation to  neurocognitive aging, while characterizing and controlling for age-­related differences in cerebral blood flow with  arterial spin labelling. Specific Aim 3 will test the hypothesized parallel causal contributions of BF  cholinergic neurons to central cognitive regulation and peripheral autonomic regulation of the heart.  Approach: Using cholinergic immunotoxic lesions, a rat model of cognitive aging will assess the causal role of  the BF to cognitive control and parasympathetic autonomic regulation of heart rate (vmHRV) in male and female  young, middle-­aged, and older rats. Revealing peripheral autonomic aspects of age-­related differences in brain  integrity and cognitive status would advance our understanding of normative and potentially pathological  neurochemical changes in aging.  It will further advance the use of a noninvasive, low-­cost peripheral biomarker  for identifying those who may progress to mild neurocognitive disorder (mNCD). Such a readily administered  screen for early mNCD could better afford early detection, monitoring, and potential intervention before the  onset of mNCD and potential conversion to Alzheimer?s Disease.