22 resultados para structural magnetic resonance imaging (sMRI)


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Adult humans, infants, pre-school children, and non-human animals appear to share a system of approximate numerical processing for non-symbolic stimuli such as arrays of dots or sequences of tones. Behavioral studies of adult humans implicate a link between these non-symbolic numerical abilities and symbolic numerical processing (e.g., similar distance effects in accuracy and reaction-time for arrays of dots and Arabic numerals). However, neuroimaging studies have remained inconclusive on the neural basis of this link. The intraparietal sulcus (IPS) is known to respond selectively to symbolic numerical stimuli such as Arabic numerals. Recent studies, however, have arrived at conflicting conclusions regarding the role of the IPS in processing non-symbolic, numerosity arrays in adulthood, and very little is known about the brain basis of numerical processing early in development. Addressing the question of whether there is an early-developing neural basis for abstract numerical processing is essential for understanding the cognitive origins of our uniquely human capacity for math and science. Using functional magnetic resonance imaging (fMRI) at 4-Tesla and an event-related fMRI adaptation paradigm, we found that adults showed a greater IPS response to visual arrays that deviated from standard stimuli in their number of elements, than to stimuli that deviated in local element shape. These results support previous claims that there is a neurophysiological link between non-symbolic and symbolic numerical processing in adulthood. In parallel, we tested 4-y-old children with the same fMRI adaptation paradigm as adults to determine whether the neural locus of non-symbolic numerical activity in adults shows continuity in function over development. We found that the IPS responded to numerical deviants similarly in 4-y-old children and adults. To our knowledge, this is the first evidence that the neural locus of adult numerical cognition takes form early in development, prior to sophisticated symbolic numerical experience. More broadly, this is also, to our knowledge, the first cognitive fMRI study to test healthy children as young as 4 y, providing new insights into the neurophysiology of human cognitive development.

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© 2015 Young, Smith, Coutlee and Huettel.Individuals with autistic spectrum disorders exhibit distinct personality traits linked to attentional, social, and affective functions, and those traits are expressed with varying levels of severity in the neurotypical and subclinical population. Variation in autistic traits has been linked to reduced functional and structural connectivity (i.e., underconnectivity, or reduced synchrony) with neural networks modulated by attentional, social, and affective functions. Yet, it remains unclear whether reduced synchrony between these neural networks contributes to autistic traits. To investigate this issue, we used functional magnetic resonance imaging to record brain activation while neurotypical participants who varied in their subclinical scores on the Autism-Spectrum Quotient (AQ) viewed alternating blocks of social and nonsocial stimuli (i.e., images of faces and of landscape scenes). We used independent component analysis (ICA) combined with a spatiotemporal regression to quantify synchrony between neural networks. Our results indicated that decreased synchrony between the executive control network (ECN) and a face-scene network (FSN) predicted higher scores on the AQ. This relationship was not explained by individual differences in head motion, preferences for faces, or personality variables related to social cognition. Our findings build on clinical reports by demonstrating that reduced synchrony between distinct neural networks contributes to a range of subclinical autistic traits.

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Interest in structural brain connectivity has grown with the understanding that abnormal neural connections may play a role in neurologic and psychiatric diseases. Small animal connectivity mapping techniques are particularly important for identifying aberrant connectivity in disease models. Diffusion magnetic resonance imaging tractography can provide nondestructive, 3D, brain-wide connectivity maps, but has historically been limited by low spatial resolution, low signal-to-noise ratio, and the difficulty in estimating multiple fiber orientations within a single image voxel. Small animal diffusion tractography can be substantially improved through the combination of ex vivo MRI with exogenous contrast agents, advanced diffusion acquisition and reconstruction techniques, and probabilistic fiber tracking. Here, we present a comprehensive, probabilistic tractography connectome of the mouse brain at microscopic resolution, and a comparison of these data with a neuronal tracer-based connectivity data from the Allen Brain Atlas. This work serves as a reference database for future tractography studies in the mouse brain, and demonstrates the fundamental differences between tractography and neuronal tracer data.

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Prostate and breast cancers are two of the most common types of cancer in the United States, and those cancers metastasize to bone in more than two thirds of patients. Recent evidence suggests that thermal therapy is effective at treating metastatic bone cancer. For example, thermal therapy enables targeted drug delivery to bone, ablation of cancer cells in bone marrow, and palliation of bone pain. Thermal therapy of bone metastases would be greatly improved if it were possible to image the temperature of the tissue surrounding the disease, which is usually red bone marrow (RBM). Unfortunately, current thermal imaging techniques are inaccurate in RBM.

This dissertation shows that many of the difficulties with thermal imaging of RBM can be overcome using a magnetic resonance phenomenon called an intermolecular multiple quantum coherence (iMQC). Herein, iMQCs are detected with a magnetic resonance imaging (MRI) pulse sequence called multi-spin-echo HOMOGENIZED with off resonance transfer (MSE-HOT). Compared to traditional methods, MSE-HOT provided ten-fold more accurate images of temperature change. Furthermore, MSE-HOT was translated to a human MRI scanner, which enabled imaging of RBM temperature during heating with a clinical focused ultrasound applicator. In summary, this dissertation develops a MRI technique that enables thermal imaging of RBM during thermal therapy of bone metastases.

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The pKa values of ionizable groups in proteins report the free energy of site-specific proton binding and provide a direct means of studying pH-dependent stability. We measured histidine pKa values (H3, H22, and H105) in the unfolded (U), intermediate (I), and sulfate-bound folded (F) states of RNase P protein, using an efficient and accurate nuclear magnetic resonance-monitored titration approach that utilizes internal reference compounds and a parametric fitting method. The three histidines in the sulfate-bound folded protein have pKa values depressed by 0.21 ± 0.01, 0.49 ± 0.01, and 1.00 ± 0.01 units, respectively, relative to that of the model compound N-acetyl-l-histidine methylamide. In the unliganded and unfolded protein, the pKa values are depressed relative to that of the model compound by 0.73 ± 0.02, 0.45 ± 0.02, and 0.68 ± 0.02 units, respectively. Above pH 5.5, H22 displays a separate resonance, which we have assigned to I, whose apparent pKa value is depressed by 1.03 ± 0.25 units, which is ∼0.5 units more than in either U or F. The depressed pKa values we observe are consistent with repulsive interactions between protonated histidine side chains and the net positive charge of the protein. However, the pKa differences between F and U are small for all three histidines, and they have little ionic strength dependence in F. Taken together, these observations suggest that unfavorable electrostatics alone do not account for the fact that RNase P protein is intrinsically unfolded in the absence of ligand. Multiple factors encoded in the P protein sequence account for its IUP property, which may play an important role in its function.

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Biological macromolecules can rearrange interdomain orientations when binding to various partners. Interdomain dynamics serve as a molecular mechanism to guide the transitions between orientations. However, our understanding of interdomain dynamics is limited because a useful description of interdomain motions requires an estimate of the probabilities of interdomain conformations, increasing complexity of the problem.

Staphylococcal protein A (SpA) has five tandem protein-binding domains and four interdomain linkers. The domains enable Staphylococcus aureus to evade the host immune system by binding to multiple host proteins including antibodies. Here, I present a study of the interdomain motions of two adjacent domains in SpA. NMR spin relaxation experiments identified a 6-residue flexible interdomain linker and interdomain motions. To quantify the anisotropy of the distribution of interdomain orientations, we measured residual dipolar couplings (RDCs) from the two domains with multiple alignments. The N-terminal domain was directly aligned by a lanthanide ion and not influenced by interdomain motions, so it acted as a reference frame to achieve motional decoupling. We also applied {\it de novo} methods to extract spatial dynamic information from RDCs and represent interdomain motions as a continuous distribution on the 3D rotational space. Significant anisotropy was observed in the distribution, indicating the motion populates some interdomain orientations more than others. Statistical thermodynamic analysis of the observed orientational distribution suggests that it is among the energetically most favorable orientational distributions for binding to antibodies. Thus, the affinity is enhanced by a pre-posed distribution of interdomain orientations while maintaining the flexibility required for function.

The protocol described above can be applied to other biological systems in general. Protein molecule calmodulin and RNA molecule trans-activation response element (TAR) also have intensive interdomain motions with relative small intradomain dynamics. Their interdomain motions were studied using our method based on published RDC data. Our results were consistent with literature results in general. The differences could be due to previous studies' use of physical models, which contain assumptions about potential energy and thus introduced non-experimental information into the interpretations.