Peter J. Basser - US grants

Tissue functional properties are governed by physical and chemical processes occurring at cellular and subcellular length scales. Specifically, the physical state of tissues (e.g., osmotic and mechanical properties, state of hydration, charge density) must be characterized on distance scales below 100 nm. Understanding the interaction of polyelectrolytes with ions is critical to clarifying the basic physics of ion binding as well as physical mechanisms affecting a large number of biological processes. To determine the effect of ions on the structure and dynamic properties of synthetic and biopolymers we developed a multi-scale experimental framework by combining high-resolution techniques, such as small-angle X-ray scattering (SAXS), small-angle neutron scattering (SANS), and static light scattering (SLS), with macroscopic methods (osmotic swelling pressure and mechanical measurements). We also use dynamic methods e.g., neutron spin echo (NSE), dynamic light scattering (DLS) to observe the relaxation response as a function of length scale. Additionally, we developed a method to determine the distribution of counterions in the ionic atmosphere surrounding charged macromolecules using anomalous small-angle X-ray scattering (ASAXS). In biology, osmotic pressure is particularly important in regulating and mediating physiological processes. Swelling pressure measurements probe the system in the large length scale range, thus providing information on the overall thermodynamic response. SANS and SAXS allow us to investigate biopolymer molecules and assemblies in their natural environment and to correlate the changes in the environmental conditions (e.g., ion concentration, ion valance, pH, temperature) with physical properties such as molecular conformation and osmotic pressure. These techniques simultaneously provide information about the size of different structural elements and their respective contribution to the osmotic properties. Combining these measurements allows us to determine the length scales governing the macroscopic thermodynamic properties. It is important to emphasize that this information cannot be obtained by other techniques. We have studied the effect of multivalent cations, particularly calcium ions, on the structure of various model systems mimicking soft tissues. Divalent cations are ubiquitous in the biological milieu, yet existing theories do not adequately explain their effect on and interactions with charged macromolecules. Moreover, experiments to study these interactions are difficult to perform, particularly in solution, because above a low ion concentration threshold multivalent cations generally cause phase separation or precipitation of charged macromolecules. Since macroscopic phase separation does not occur in cross-linked gels, we have overcome this limitation by cross-linking our biopolymers, greatly extending the range of ion concentrations over which the system remains stable. In previous studies, this new non-destructive procedure has been used to investigate cross-linked gels of a model synthetic polymer, polyacrylic acid, and different biopolymers such as DNA, hyaluronic acid and chondroitin sulfate (important components of extracellular matrix) to determine the size of the structural elements that contribute to the osmotic concentration fluctuations. We have combined SANS and SAXS to estimate the osmotic modulus of hyaluronic acid solutions in the presence of monovalent and divalent counterions. We studied the collective diffusion processes in these solutions by dynamic light scattering and determined the osmotic modulus from the relaxation response. We determined the distribution of counterions around charged biopolymer molecules using anomalous small-angle X-ray scattering measurements. We applied our approach to understand the binding mechanism in glucose sensors made from smart zwitterionic hydrogels containing boronic acid moieties. Based on systematic SANS and osmotic pressure measurements we provided a thermodynamic explanation for the enhanced selectivity of these gels for glucose relative to fructose. This class of material has a great potential in the development of implantable continuous glucose sensors for use in diabetes. We developed a procedure to control the size, compactness and stability of DNA nanoparticles by mediating the interaction between ions and DNA. We quantified the effects of salt, pH and temperature on their stability and biological activity. These polyplexes are pathogen-like particles having a size (70 300 nm) and shape resembling spherical viruses that naturally evolved to deliver nucleic acids to the cells. They contain the pDNA in the interior surrounded by synthetic polymer bearing sugar residues on the surface recognized by the M cells and dendritic cells as pathogens. Because we can control the stability and biological activity of DNA nanoparticles, we believe that this knowledge can provide a solid foundation for developing new DNA-based vaccines for the treatment of various diseases. We studied the effect of calcium ions on the larger scale structure of DNA solutions and gels in near-physiological salt conditions by SANS. Analysis of the SANS response revealed two characteristic length scales, the mesh size of the transient network, and the cross-sectional radius of the DNA double helix. In gels the mesh size is greater than in the corresponding solutions by approximately 50%, reflecting the increased heterogeneity of the crosslinked system. The cross-sectional radius of the DNA chain is practically independent of the polymer concentration and the calcium ion content, and is close to the value of the DNA double helix (10 A). This finding implies that bundle formation is negligible in the present DNA gels. The results of this study show that changes in the ionic environment offer a molecular level control of the interactions between DNA strands and allow us to tune the morphology of DNA-based assemblies. In recent studies we have investigated the mechanism of fiber formation from small hydrogelator molecules in biological cells. Fluorescent imaging revealed that self-assembly directly affects the distribution of these small peptidic molecules in a cellular environment. Cell viability tests suggested that the states and the spatial distribution of the molecular assemblies control the phenotypes of the cells. We demonstrated that enzyme instructed self-assembly makes it possible to modulate the spatiotemporal profiles of small molecules in a cellular environment.

Ion-polymer interactions have important consequences for the macroscopic mechanical/osmotic properties and the biological function of the tissue. Divalent cations, particularly calcium ions, are abundant in the biological milieu. In general, experiments to determine the interactions between ions and biopolymers are difficult to perform, because above a relatively low ion concentration multivalent cations cause phase separation (or precipitation) of the charged macromolecules. Since macroscopic phase separation does not occur in gels, we can overcome this limitation by cross-linking these polymers, i.e., extending the range of ion concentrations over which the systems can remain stable. In pilot studies, we used this new non-destructive procedure to investigate cross-linked gels of a model synthetic polymer, polyacrylic acid, and different biopolymers such as DNA and hyaluronic acid to determine the size of the structural elements that govern the osmotic concentration fluctuations. We combined SANS and SAXS to estimate the osmotic modulus of hyaluronic acid in the presence of both monovalent and divalent counterions. We also studied the dynamic properties (e.g., diffusion processes) of these systems by dynamic light scattering and determined the osmotic modulus from the relaxation response. We developed an experimental procedure to determine the distribution of counter-ions around charged biopolymer molecules using anomalous small-angle X-ray scattering measurements. We analyzed and compared a series of network elasticity models that address essential physical aspects of biopolymer systems. We are particularly interested in understanding the mechanisms of interactions of biologically important divalent cations like Ca+2 with negatively charged biopolymers. We believe that the study of water-ion-biopolymer interactions at a fundamental level is necessary to understanding of biological processes at the molecular, cellular and tissue length scales about which little is currently known. Better understanding of the structure and interactions among tissue components is also necessary to design and develop tissue models and novel tissue phantoms that mimic tissue behavior. For instance, we are developing a biomimetic model of cartilage ECM consisting of highly charged polyelectrolyte particles embedded in a crosslinked neutral gel. In this system charged particles mimic the behavior of proteoglycan assemblies and the neutral gel mimics the collagen matrix. We study the effect of the structural parameters on the macroscopic swelling and load bearing properties of this composite gel system. We systematically vary the properties of the polymeric components by changing the concentration and cross-link density of the dispersed particles in the continuous network. In addition, we can control the fixed charge density (FCD), by varying the degree of ionization of the charged groups on the polymer chains. Biomimetic phantoms with well-characterized physical (osmotic, mechanical, relaxation, etc.) are critically important in quantitative MRI to validate measurements and advanced MRI applications from bench to bedside (in vivo MRI histology). In the context of cartilage, the hierarchical bottlebrush organization of charged polymer molecules is of particular interest for understanding the biological function of the tissue, such as its load bearing ability and lubrication mechanism. In cartilage ECM the bottlebrush shaped aggrecan molecules are condensed on hyaluronic acid chains forming secondary bottlebrush structures. In collaboration with Prof. Xia (Department of Chemistry, Stanford University) we started a research collaboration to determine the physical properties of model bottlebrushes (neutralized polyacrylic acid polymers) having well controlled molecular architecture. We make systematic studies on a family of bottlebrush structures by varying (i) the length of the main chains (at constant length of the side chains) and (ii) the length of the side chains (at constant length of the main chains). The structural investigations are complemented by molecular dynamics modeling performed in collaboration with Dr. Jack Douglas (National Institute of Standard and Technology). These studies will reveal the role of the hierarchical bottlebrush organization of cartilage proteoglycans that gives rise to the unique mechanical properties of cartilage. Biomimetic studies provide vital insights to help understand how different factors (e.g., matrix stiffness, charge density) affect the macroscopic mechanical and swelling properties of tissues. For example, the knowledge obtained from systematic measurements on well-defined model systems is critically important to understand cartilage behavior and develop a realistic biomimetic cartilage model. Such information cannot be obtained from measurements made on biological tissues because their composition and physical properties cannot be independently and systematically varied. Biomimetic model systems have been shown in our hands to be extremely powerful means to calibrate and validate quantitative MRI measurements for microstructure imaging. We have developed a wide variety of NMR and MRI phantoms that possess various salient features of cell or tissue systems, providing 'ground truth' to test the validity of our models and experimental designs.

The load bearing behavior of cartilage is sensitive to both biochemical and microstructural changes occurring in development, disease, degeneration, and aging. Cartilage hydration is a key determinant of its load bearing properties. To study cartilage hydration, an array of complementary techniques is required that probe not only a wide range of length and time scales, but are also statistically representative of the heterogeneous sample. Controlled hydration or swelling using the osmotic stress technique provides a direct means of determining functional properties of cartilage and of other extracellular matrices (ECM). Our earlier measurements revealed the role of the collagen network in limiting the hydration of normal (healthy) cartilage and ensuring a high PG concentration in the matrix, which is essential for effective load bearing. We also demonstrated that the loss of collagen network stiffness is consistent with the degradation of cartilage observed in osteoarthritis (OA). To quantify the effect of hydration on cartilage properties we developed a tissue micro-osmometer to perform experiments in a practical and rapid manner. This instrument is capable to measure very small changes in the amount of water absorbed by small tissue samples (less than 1 microgram tissue) as a function of the equilibrium activity (vapor pressure) of the surrounding tissue water. A quartz crystal detects the water uptake of a specimen attached to its surface. The high sensitivity of its resonance frequency to small changes in the amount of adsorbed water makes it possible to determine the water uptake of the tissue with high precision. We used osmotic pressure measurements to determine the contributions of individual components of ECM (e.g., aggrecan, hyaluronic acid (HA), and collagen) to the total tissue swelling pressure. Our measurements on aggrecan/HA systems revealed that the osmotic modulus of the aggrecan-HA complex is enhanced with respect to that of the random assemblies of aggrecan bottlebrushes, providing direct evidence that complex formation among aggrecan and HA molecules improves the load-bearing ability of cartilage. Our combined static and dynamic scattering measurements (SAXS, SANS, SLS, DLS, neutron spin-echo) demonstrated that aggrecan-HA assemblies exhibit microgel-like behavior and remarkable insensitivity to changes in the ionic environment, particularly to Ca+2 concentration. The results are consistent with the role of aggrecan as an ion reservoir mediating calcium metabolism in cartilage and bone. We have developed a method for mapping the local elastic and osmotic properties of cartilage using the Atomic Force Microscope (AFM) together with the tissue micro-osmometer. Many of the impediments that previously hindered the use of AFM to probe inhomogeneous samples, particularly biological tissues, were addressed by this new approach that utilizes the precise scanning capabilities of a commercial AFM to generate large volumes of compliance data from which the relevant elastic properties can be extracted. In conjunction with results obtained from high-resolution scattering measurements, micro-osmometry, and biochemical analysis, this technique allows us to map the spatial variations in the osmotic modulus within tissue specimens. Knowledge of the local osmotic properties of cartilage is particularly important, given that the osmotic modulus determines the compressive resistance of the tissue to external load. We have begun noninvasive in vitro applications of critical tissue-sciences understanding of structure/function relationships of ECM components to develop and design novel MR imaging methods, which has the potential for early diagnosis of cartilage diseases. Specifically, we are developing imaging methods directed at measuring key compositional and structural features of cartilage ECM, which we can use to estimate functional properties of the tissue with the aid of a biophysical modeling framework. In collaboration with Uzi Eliav (Tel Aviv University) we developed a novel magnetization transfer (MT) MRI method, which is capable to detect immobile protons (e.g., protons on the collagen backbone), which are not detectable by conventional MRI owing to their short T2. To visualize these invisible protons the magnetization of these molecules is transferred to the free water, which is visible by MRI. In a pilot study we have compared the results obtained for the concentrations of the main cartilage constituents by our MT MRI method and high definition infrared spectroscopic (HDIR) imaging measurements made on the same samples. The results show that our novel approach has the potential to map tissue structure and functional properties in vivo and noninvasively.

We are continuing to invent, develop, and translate novel Magnetic Resonance Imaging (MRI) methods from the bench to bedside. Specifically, we continue to develop new ways to assess tissue structure and architecture in vivo and non-invasively, primarily by following the water, with the aim of enabling applications in the neurosciences and biomedical research communities, and translating these novel approaches to the clinic to improve clinical outcomes. Diffusion Tensor MRI (DT-MRI or DTI) is the best-known imaging method we invented, developed, and successfully translated clinically. It measures and maps a diffusion tensor of mobile tissue water. It produces scalar parameters that are intrinsic features of tissues without introducing contrast agents or dyes, but by following endogenous tissue water protons. One DTI-derived quantity, the orientationally-averaged diffusion coefficient (or mean ADC), successfully visualizes an acute stroke in progress. The mean ADC is also widely used in cancer imaging worldwide to monitor tumor cellularity. Our development of novel diffusion anisotropy metrics, like the Fractional Anisotropy (FA), enabled white matter pathways to be visualized for the first time. The development direction-encoded color (DEC) maps of axon orientation allowed us to map white matter pathway orientation. DEC maps first revealed the main association, projection, and commissural white matter pathways in the human brain. To assess anatomical connectivity between different functional regions in the brain, we invented, proposed, and developed DTI streamline tractography, made possible by a general mathematical framework to continuously and smoothly approximate measured discrete, noisy, diffusion tensor field data. Collectively, these methods and approaches have enabled detailed anatomical and structural analyses of the brain in vivo, which was only possible previously using laborious, invasive histological methods performed on excised tissue specimen. Our contributions to the invention and development of streamline tractography was an impetus for the creation of NIH's Human Connectome Project (HCP). As DTI migrated to large, multi-center trials and studies, we began developing a battery of quantitative statistical tests to determine the statistical significance of ROI and population differences observed in our data. We developed empirical Monte Carlo and Bootstrap methods for determining features of the statistical distribution of the diffusion tensor from experimental DTI data and a novel tensor-variate Gaussian distribution that describes the variability of the diffusion tensor in an ideal DTI experiment. More recently, we developed approaches to measure uncertainties of many tensor-derived quantities, including the direction of axonal pathways using perturbation and statistical approaches. These developments collectively provide the foundation for applying powerful statistical hypothesis tests to address a wide array of important biological and clinical questions that previously could only be tackled in an ad hoc manner, if at all. More recently, we have been developing sophisticated mathematical/physical models of water diffusion profiles to relate these to the MR signals we measure. This activity enables us to drill down into the voxel to infer new microstructural and architectural features of tissue (primarily white matter in the brain). One example is our composite hindered and restricted model of diffusion (CHARMED) MRI framework to measure a mean axon radius within a pack of axons, and an estimate of the intra and extracellular volume fractions. A refinement of CHARMED, AxCaliber MRI, enabled us to measure the axon diameter distribution (ADD) within white matter pathways. Sophisticated multiple pulsed field gradient (PFG) NMR and MRI sequences help us characterize microscopic anisotropy within tissues like gray matter, which are macroscopically isotropic (like a homogeneous gel). We have developed physical MRI phantoms to test and interrogate our various mathematical models describing water diffusion in complex tissues and infer features of size, shape, and distribution of pores in biological tissue and other porous media from their MR data. Our group has applied novel fractal models to characterize anomalous diffusion processes that reveal underlying hierarchical structures. These also yield novel sources of MR contrast we plan to apply in neuroscience applications, such as in vivo (Brodmann or cytoarchitechtonic) parcellation of the cerebral cortex or clinical diagnostic applications, such as mild TBI detection, improved cancer diagnosis or brain tumor staging. An important development has been a way to characterize non-Gaussian features of the displacement distribution measured using MRI. To this end, our group continues to work on reconstructing the average propagator (displacement distribution) and features derived from it, using a relatively small number of DWIs to enable their clinical migration. The average propagator is the holy grail of displacement or diffusion imaging, which subsumes DTI as well as other higher-order tensor (HOT) methods. One approach we used previously was an iterative reconstruction scheme along with a priori information and physical constraints to infer the average propagator from DWI data. Another approach was to use a CT-like reconstruction method to estimate the displacement profile from DWI data. The most successful method to date, however, uses Hermite basis functions to represent the average propagator, which compresses the amount of DWI data required while providing a plethora of new imaging parameters or stains with which to characterize microstructural features in tissues. A significant new initiative in our group has been the invention and development of several efficient and accurate 2D-MRI relaxometry/diffusometry/exchange methods. These include ways to measure correlations between diffusion, T1 and T2, as well as exchange between and among them. From the standpoint of microstructure imaging, these approaches provide increasing evidence of the existence of multiple distinct water compartments within neural tissue which have been previously invisible. Collectively, these novel methods and methodologies represent a pathway to realizing in vivo MRI histology--providing detailed microstructural and microarchitectural information about cells and tissues that otherwise could only be obtained using laborious and invasive histological or pathological techniques applied on biopsied or excised specimens. We are migrating the field of microstructure imaging to microstructure and microdynamic imaging, and in the process, are making the invisible visible.

We have been investigating several biophysical mechanisms associated with neuronal excitation that may be possible to measure and map using MRI. Having successfully constructed and tested an experimental system in our lab to interrogate organotypic cultured brain cortical slices using diffusion MRI, we showed promising preliminary results, relating changes in the measured apparent diffusion coefficient (ADC) map to environmental challenges to which these cultured tissues were subjected. One hypothesis that emerged from these studies is that active water transport processes occurring at many different length scales (cell streaming, water flow across membranes, etc.) could be the basis of a new biophysically based fMRI method. This insight prompted the development of a theory to explain how microscopic fluid flows affect the measured diffusion weighted MRI signal and possibly the ADC measured in tissues (i.e., pseudo-diffusion) as well as an experimental model test system, a modified Rheo-NMR instrument, in which well-characterized flow field distributions can be produced that result in a predictable amount of pseudo-diffusion. The importance of these combined theoretical and experimental studies is that if such microscopic motions, like streaming, water flow across membranes, etc., manifest themselves as additional signal loss in diffusion weighted MRI, then we could use this information to infer distinct aspects of cell function and vitality, including features of excitability by judiciously analyzing MRI data. This idea represents a significant advance over the prior Intravoxel Incoherent Motion (IVIM) concept proposed by Le Bihan et al, which only considers the effect of random water motions caused by microcirculatory blood flow as contributing to observed pseudo-diffusion in vivo. We continued to expand and amplify these studies with former Visiting Fellow, Ruiliang Bai, who investigated possible relationships between neuronal excitation and MRI contrasts. Among other things, Dr. Bai's work, while showing that diffusion imaging was sensitive to changes caused by stroke and epilepsy-like perturbations, non-pathological changes in neuronal firing associated with normal activity could not be detected by diffusion fMRI. Another area of interest has been in improving our measurement of relaxation/diffusion/exchange processes in living tissue, particularly taking advantage of advanced data compression techniques to obtain 1D and 2D relaxation spectra suitable for in vitro and in vivo studies. We have actively been developing methods to make migrate 2D relaxation spectroscopic imaging into viable pre-clinical and clinical methods which may be valuable in assessing water transport in different compartments within neurons or axons. We have also been involved in complementary studies to understand how induced electric and magnetic fields are distributed within the brain and how they could selectively affect different neuronal populations. We have performed detailed calculations using the finite element method (FEM) to predict the electric field and current density distributions induced in the brain during Transcranial Magnetic Stimulation (TMS). Previously, we found that both tissue heterogeneity and anisotropy of the electrical conductivity (i.e., the electrical conductivity tensor field) distort these induced fields, and even create excitatory or inhibitory hot spots in some brain regions that were previously not predicted. More recently, we developed realistic FEM models of cortical folds, containing gyri and sulci, showing that this more complicated cortical anatomy can also significantly affect the induced electric field distribution within the tissue, and the location and types of nerve cells that could be excited or depressed by such stimuli. More recently, we have been developing full 3D models of electric field deposition within the brain, obtained from 3D diffusion tensor MRI data. We are continuing to marry our macroscopic FEM models of TMS with microscopic models of neuronal excitability in the CNS in order to predict the locus of excitation in TMS and even the populations of neurons that are excited or depressed. This knowledge is important to have in addressing, for instance, the safety and basis of efficacy of TMS for the treatment of clinical depression--an application we helped pioneer in the early '90s with our colleagues Mark George (NIMH) and Eric Wassermann (NINDS). Despite its growing use and subsequent FDA approval for treating persistent clinical depression and migraines, it is still not known what action induced electromagnetic fields have in the brain in therapeutic TMS, and specifically which and what populations of neurons or axons TMS might trigger or depress when applied. Our research attempts to provide a biophysical basis for understanding the physiology of this and other clinical applications of TMS to help in part assess its safety and efficacy. More recent studies of ours have focused on the microscopic effects of these electric and magnetic fields on cells in the nervous system, moving from the macro to the microscale in our modeling activities. Moreover, we have not limited ourselves to TMS. Recently, we have also been applying these advanced FEM models to explain the physical basis for Direct Current Excitation (DCE) as well as other therapeutic uses of AC electric fields at different frequencies on the brain. A surprising offshoot of this TMS project has been the recent study of the possible anti-mitotic effect of applied electric fields and their therapeutic use in treating brain cancers, particularly Glioblastoma Multiforme (GBM). The electric fields used in this application are in the 100-300 kHz frequency range and have an amplitude of approximately 1 V/cm or greater. According to our calculations, these fields will not cause neural stimulation, but enter cells and may interfere with mitotic spindle formation, required for cell division, or interfere with cell membrane pinching, which occurs just before two daughter cells are formed from one parent cell. We proposed that an efficient alternative means to deliver electric fields to brain regions is by electromagnetic induction rather than using electrodes placed on the skin. This idea resulted in a patent application for devices that could be used to assess the effect of electric fields on tissue as well as therapeutic devices for treating various brain cancers. Although in a preliminary stage of development, our group continues to work on advancing this technology by developing technology that can deliver such induced fields to in vitro cell and tissue cultures. We believe that in addition to its possibly clinical applications, it may provide us with a means to perturb normally developing cells to help better understand different biophysical forces and flows at work during different phases of the cell cycle.

SUMMARY We present Connectome 2.0, the next-generation human MRI scanner for imaging structural anatomy and connectivity spanning the microscopic, mesoscopic and macroscopic scales. This work builds upon our expertise in engineering the first human Connectome MRI scanner with 300 mT/m maximum gradient strength (Gmax), the highest ever achieved for a human system, for the Human Connectome Project (HCP). The goal of the HCP was to map the macroscopic structural connections of the in vivo healthy adult human brain using diffusion tractography. While this instrument has made important contributions to our understanding of macroscale connectional topology, our experience with the scanner over the last seven years has taught us that dedicated high-gradient performance scanners can also acquire a rich array of diffusion measurements that provide unparalleled in vivo assessment of neural tissue microstructure, such as the relative size and packing density of cells and axons. However, the current Connectome instrument is limited in its ability to resolve the full range of length scales needed to probe the microscopic and mesoscopic structure of the brain, due to basic design limitations, important technical elements, and biological interactions with the large rapidly switching gradients. Our experience with the first generation Connectome scanner and realization of its limitations motivates our multi-site proposal for the next generation human Connectome MRI scanner (Connectome 2.0) to achieve sensitivity to a broader range of cellular and axonal size scales, morphologies, and interconnections represented throughout the brain. Our goal here is to translate our initial experience into building a one-of-a-kind high-slew rate, ultra- high-gradient strength MRI scanner that is optimized for the study of neural tissue microstructure and neural circuits across multiple length scales. In order to maximize the resolution of this in vivo microscope for studies of the living human brain, we will push the diffusion resolution limit to unprecedented levels by (1) nearly doubling the current Gmax to 500 mT/m and tripling the maximum slew rate to 600 T/m/s; (2) pushing the limits of the RF receive coils and gradient characterization to enable maximum sensitivity with greatly reduced artifacts using real-time eddy current corrected dMRI acquisitions; (3) developing new pulse sequences to achieve the highest diffusion- and spatial-resolution ever achieved in vivo; and (4) calibrating the measurements obtained from this next generation instrument through systematic validation of the diffusion microstructural metrics in high-fidelity phantoms and ex vivo brain tissue at progressively finer scales. We envision creating the ultimate diffusion MRI machine capable of addressing the BRAIN 2025 mandate to image across scales, from the microscopic scale needed to probe cellular heterogeneity and plasticity, to the mesoscopic scale for enumerating the distinctions in cortical structure and connectivity that define cyto- and myeloarchitechtonic boundaries, to improvements in estimates of macroscopic connectivity.