Dana H. Brooks - US grants

9309359 Brooks The objective of this Research Initiation Award is to develop improved methods to extract maximal information about cardiac electrical activity from non-invasive measurements on the torso surface. Both time-domain and frequency domain characterizations will be used to develop realistic constraints for a refined inverse solution. This research is important since it has the potential to substantially improve noninvasive diagnosis of cardiovascular disease. The research may also have applications in solving other inverse problems in other areas that are ill- conditioned. ***

ABSTRACT
EEC-9812924
Dimarzio/Northeastern

This is an Exploratory Research Project to augment the Industry/University Cooperative Research Center
for Electromagnetics Research

The research objective is to advance the basic knowledge in maximizing the potential for non-invasive optical imaging of the human body. It is anticipated that the project will result in improved in improved penetration, resolution, accuracy and diagnostic capability of diffusive-wave imaging to that it will become a safe and effective tool of medical diagnosis. Specific objectives include (1) understanding the behavior of diffusive waves ins complicated tissues where the diffusion approximation is not valid, (2) inventing novel advanced imaging systems for improving spatial resolution, and (3) developing new algorithms to extract information from available data.

This proposal describes a three year collaborative research program by a multi-university team of device, electronics, and biomedical investigators applying and extending newly emerging technologies for monolithic optoelectronic integration to address problems and needs of biomedical research and diagnosis. Researchers at MIT have recently demonstrated unique monolithic optoelectronic integrated circuits (OEICs) of unprecedented complexity and performance, and their ability now to monolithically integrate light sources and detectors with complex high density, high performance electronic circuitry opens the way to the invention and realization of a wide variety of sensors and measurement arrays for medical research and diagnostics. It is this area which the proposed effort will address.
The technologies for monolithic optoelectronic integration which are under development at MIT are sufficiently advanced that they can be applied immediately to solve a variety of problems, and one area that is ripe with applications and needs that are addressable with the current technology is biomedical research and practice. From the numerous possible target applications in biomedicine, we have identified as an initial vehicle for applying this technology a integrated source/detector array for diffuse optical tomography (DOT). The proposed unit will permit DOT observations with a resolution exceeding that of present techniques and will lead to the use of DOT in procedures and situations in which it is currently unfeasible.
Stated in the most general terms, the proposed effort will be directed at developing, applying, and making available a technology to monolithically integrate III-V optical emitters and detectors with commercially fabricated, custom-designed integrated circuits to produce high resolution two-dimensional arrays of individually addressable smart excitor/sensor pixels tailored for biomedical research applications and studies. A representative pixel might measure 250 to 500 microns on a side, and contain, for example, a diode light emitter (LED or laser), one or more light sensors, and a significant amount of electronic signal processing circuitry. This basic unit is a building block from which a wide variety of biomedical optical measurement systems can be realized in a very rugged, compact chip-size format. It promises to lead, in the future, to totally new sensor geometries and measurement procedures.
The challenges that the program will face include continuing development of the OEIC technology and adapting this technology for biomedical research; developing suitable signal processing algorithms and designing compact, high performance signal processing circuit arrays in the relevant electronics technologies to interface with the optoelectronic devices; and suitably packaging the OEIC chips for their biomedical utilization.
The project team will be aided in this effort by its strong links with the Northeastern University Center for Subsurface Sensing and Imaging Systems, the Massachusetts General Hospital NMR Center, the University of Utah NIH/NCRR Center for Bioelectric Field Modeling, Simulations and Visualization, and the MIT Microsystems Technology Laboratory, and by integrated circuit processing support from Vitesse Semiconductor Corporation.

DESCRIPTION (provided by applicant): Fluorescent Proteins (FP) have become essential reporter molecules for the elucidation of the function of proteins within cells, the bio-distribution of immune and stem cells and for evaluation of drug candidates in vivo. Volumetric detection and accurate quantification of Fluorescent Proteins in entire animals would greatly enhance our ability to monitor biological processes in vivo. Currently however, whole body fluorescent protein imaging is largely facilitated by photographic techniques that compromise the quantification and any volumetric imaging ability. The overall goal of this proposal is therefore to develop whole body, quantitative Fluorescence Protein Tomography (FPT) in entire animals. This development necessitates 1) the use of novel scanning technologies, 2) the advancement of theoretical models of photon propagation appropriate for imaging in the visible and far-red, 3) the design of computationally efficient inversion techniques with multispectral characteristics and 4) the interrogation of appropriate fluorescent proteins that can yield high detection sensitivity. Of particular importance for achieving high imaging performance is the utilization of freespace 360 degree projection tomographic principles and appropriate auto-fluorescent subtraction schemes that lead to unprecedented imaging performance compared to the current state of the art. Overall we hypothesize that the imaging accuracy imparted by FPT, combined with the high specificity and versatility achieved by fluorescent protein reporters and the high detection sensitivity afforded by novel red-shifted constructs can revolutionize biological imaging and propagate FPT as the method of choice in the biological laboratory for volumetric whole animal imaging.

Optical imaging is increasingly used in biomedical research for its unique advantages in terms of sensitivity, specificity, resolution, and versatility, as compared with other imaging modalities. Optical imaging spans multiple scales, from macroscopic imaging using bioluminescence and fluorescence which collect data at millimeter level to microscopic imaging at the micrometer level in both 2D and 3D spaces. Combined with high-throughput and staining techniques, optical images are often acquired in large numbers over several channels. As a result, for optical imaging methods to be of maximal use in biomedical research, computational enhancement of optical imaging has become a necessity for data management and effective information extraction.

This project initializes and adopts a multi-disciplinary approach to planning the creation of a community infrastructure for computationally enhanced optical imaging. The planning stage includes a larger workshop and smaller, targeted meetings, and discussions to solicit input from computational scientists, biomedical researchers, and engineers concerning the establishment, functionality, operational processes and user access of a computationally enhanced optical imaging infrastructure. The planned community infrastructure features a multi-institutional collaboration including hospitals, research laboratories, and universities. The infrastructure can provide students and researchers in biomedicine, mathematics, computer science, and engineering a platform for interaction and collaboration on development and use of computational techniques to model, process, quantify, and analyze various types of optical images. In addition the infrastructure offers training opportunities to students and early career researchers to apply their knowledge and skills in practice and to collaborate with investigators with different backgrounds.

Proteins are molecular machines that contribute to virtually every activity of every biological system. Regulation of their activity is a principal goal of drug and protein design. But we do not yet know enough about how proteins function to efficiently design molecules that modulate their activities. We know that to function they need to change their shape - alter their conformation - but visualizing these changes in shape is a substantial experimental challenge. The approach we will take here is to attempt to characterize the set of all shapes a protein can take on - its full conformational ensemble. This will provide a critical link between structure, dynamics and function. The problem is that in a drop of solution, there is a multitude of proteins, each of which may have a different conformation. We will alter the relative abundance of each conformation under many different experimental conditions and collect wide-angle x-ray solution scattering (WAXS) data from the protein under each of those conditions. Using advanced signal processing techniques, we will then extract from these data the scattering due to each conformation individually. This will provide direct structural information on the conformations of functional intermediates that never occur in solution in the absence of other conformations. The result will be a map of the conformational changes that occur during protein action, providing direct experimental evidence for understanding the way proteins use conformational changes to carry out their functions.

The project will make extensive use of state-of-the-art signal processing techniques that are well known in engineering but used sparingly in biophysics. This exemplifies a rapidly accelerating trend to data-rich scientific inquiry powered by increasing use of automatic data capture. Science is becoming ever more dependent on sophisticated methods of signal and data analysis. Training of scientists in advanced data processing techniques will be an essential part of this transition. In this project, success will depend on cross-disciplinary training of both scientists and engineers; training that starts with the PI's - who are already learning from one another - continues with graduate students involved in the research, and extends to graduate students and undergraduates who will benefit from the cross-disciplinary courses that we will create. Underrepresented groups will be introduced to this approach through research experiences for undergraduates and K12 teachers and outreach to K12 students - activities that will constitute an integral part of this project and be designed to encourage and prepare students for careers in science or science teaching.

Electrical stimulation of the surface of the brain is used to map functions, such as hand movement. This stimulation is vital for both brain research and patient care. Better methods are needed to precisely direct the electrical current on the brain surface. Precise stimulation will help research in restoring damage after neurological injury. Stimulation and recording from the brain surface have also been used to study memory and attention processes. Research in the development of neuro-prosthetics and the study of how the brain interacts with brain-controlled devices may also benefit from more precise stimulation. This project uses advanced computer modeling to determine better ways of stimulating the brain. One can predict where the stimulation will go based on these models. It will be tested whether using these models can precisely steer the stimulation to target specific brain functions.

This US-German collaborative project combines expertise from the University of Washington (PI: J. Ojemann, Neurosurgery), Northeastern University (D. Brooks, Electrical Engineering), the University of Utah (R. McLeod, Center for Integrative Biomedical Computing) and, in Germany, the University of Freiburg (T. Ball, Computational Neuroscience and Neurotechnology). The optimization protocols developed at Northwestern and Utah can predict the distribution of current delivery, which will be validated in a sheep model and subsequently used to predict current delivery in human data. For instance, complex geometries of brain surface (electrocorticography) electrodes may give varying patterns of current across the brain. By using simultaneous stimulation and recording data from the cortical surface (in either sheep or human brain in vivo), the model and optimization algorithms can be assessed. Successful methods for "current steering" would be applicable across a broad range of research and patient care applications in neuroscience.

A companion project is being funded by the German Ministry of Education and Research (BMBF).

This project addresses a question that has vexed scientists for more than a century: how does the motor cortex (the part of the brain where nerve impulses initiate voluntary muscular activity) represent and coordinate multiple muscles in order to produce a vast range of movements? To answer this question, this project will harness the unique strengths of non-invasive, navigated, transcranial magnetic stimulation (TMS) mapping to establish causal links between brain physiology and behavior. TMS is achieved by placing a coil of wires near the scalp, which when activated with an electrical current will create a magnetic field across the scalp and skull to stimulate the brain. TMS is the only non-invasive method available to stimulate the brain like invasive stimulation. However, to use TMS-based motor mapping to understand multi-muscle physiology and control, innovations in three areas are critically needed: 1) drastically improving the efficiency, efficacy and reliability of the TMS-based motor cortex mapping processes, 2) characterizing and validating TMS-based mapping as a probe for understanding the relationship between multi-muscle activation and voluntary movement, and 3) applying a neural network computational method to improve understanding of motor control and organization. Enhanced understanding of motor cortex physiology through TMS mapping of motor representations has the potential to better map the brain in applications such as surgical removal of tumors, assessing brain injury due to concussions or stroke, and identifying cortical networks needed for successful brain-machine interactions for controlling prostheses. Students involved with this project will be trained to address multidisciplinary challenges at the intersection of neuroscience, non-invasive brain stimulation, software design, control theory, machine-learning, statistical signal processing, data dimensionality reduction and visualization. Partnership with Boston-based leaders in the technology industry will provide state-of-the-art training to undergraduate, graduate, and post-graduate trainees. Through cooperative educational programming at Northeastern University and internships with Mass General Hospital, STEM-based learning opportunities will be provided for middle- and high-school students, inspiring a diverse body of students to pursue STEM careers. To promote STEM careers and demonstrate impact, the team will reach out to local venues that promote public awareness and appreciation of science, such as science fairs and the Boston Museum of Science.

The goal of this collaborative project is to develop a deeper mechanistic understanding of the role of the motor cortex (M1) in controlling single muscles and synergies in producing complex movements. This will be accomplished by developing several innovations in the use of non-invasive transcranial magnetic stimulation (TMS) to map the spatial distribution of synergies and single muscles. Transformative computational advances will be used to extract more accurate information about brain interaction with other physiological systems outside the motor domain and increase the rigor of analysis and data visualization to enhance interpretability, and repeatability. An enhanced understanding of corticomotor organization of complex movement will pave the way to studying motor system development across the lifespan, the basis of human performance enhancement, and the basis and characterization of neuromotor diseases. The research plan is organized under 3 aims. AIM 1 is to accelerate acquisition of TMS-based maps by developing an active learning process based on a Gaussian Process Model (GPM) of Muscle Evoked Potentials (MEPs) as a function of 2D spatial coordinates on the scalp. The developed Active-GMP learning algorithm is expected to speed up the mapping process by diverting time spent on loci with null data to loci where the model needs more samples to improve certainty. The efficacy and the accuracy of the new algorithm will be compared to three existing alternatives. AIM 2 is to test the behavioral relevance of synergies derived from human multi-muscle TMS mapping, i.e., to biologically validate the technical methods developed in Aim 1. Specifically, TMS and Voluntary (VOL) EMG data will be collected from 16 hand-arm muscles in healthy participants while subjects mimic hand postures for static letters and numbers of the American Sign Language alphabet. Non-negative matrix factorization-extracted synergies from VOL data and TMS data will be compared to determine if the TMS-elicited synergies match those utilized during movement production and if the adaptive Active-GMP and user-guided approaches more closely match synergies derived from VOL data compared to other approaches. AIM 3 is to develop generative and inverse topographic imaging models that allow forward modeling of M1 control and reverse mapping of M1 organization, respectively, of muscles and synergies. Hybrid models combining subject-specific FE modeling of TMS-induced cortical electric fields with neural network models trained to predict evoked muscle responses will be used to answer key questions: Q1) Are synergies dominant features of motor control? Q2) Do direct M1 motorneuron projections augment a synergy model of control? and Q3) Are muscles and synergies discretely organized in M1?

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Understanding the brain’s role in behaviors such as movement, cognition and emotion is paramount to progress in science and engineering, and to advancing improvements in health and wellness. Invasive approaches in animals cannot be readily adapted to humans, creating a technological barrier to causal study of the brain in awake behaving humans. One promising approach in humans, transcranial magnetic stimulation, uses magnetic pulses to noninvasively and safely modulate brain activity. However, stimulators modulate brain cells (neurons) indiscriminately, which prevents studying how distinct neurons drive behavior. This award will facilitate the acquisition of a cutting-edge stimulator that allows scientists to modulate specific neuron populations in the brain. The system includes an integrated positioning robot for precise localization and recording devices that read physiological signals from the brain or muscles to objectively quantify the effects on different neural populations and behavior. This instrumentation will enable discoveries that will catalyze new research in the study of brain and behavior. Crucially, the instrumentation paired with the proposed education plan will create unique training opportunities for students in STEM and health science, lowering the barrier of entry for underrepresented students, including persons of color and women. The project leverages Northeastern University’s experiential education model and various diversity/inclusion initiatives to support research by diverse (under)graduate and K-12 students and teachers.

The project proposes the acquisition of a controllable-pulse transcranial magnetic stimulator capable of differentially modulating specific neural populations in the human brain, with integrated robotic positioning and electroencephalography and electromyography recording. This instrumentation will be the only such system in the Northeastern US. As part of the Northeastern University Non-Invasive Brain Stimulation Center, it will enable unprecedented basic science research into human neurophysiology and brain-behavior relationships, and significant advances in fundamental engineering research in stimulator development, automated robotic positioning, stimulation-induced artifact removal in physiological recordings, closed-loop stimulation, and artificial intelligence / machine learning algorithms. Allowing researchers to control stimulus waveforms and to differentially activate distinct neural populations will enable a scientific scope of work that will transcend multiple disciplines including motor and affective neuroscience, cognition, memory, development, aging, and biophysical modeling of brain physiology. The proposed diversity and education plan enabled by this instrument will lower barriers for underrepresented minority students to engage in cutting-edge experiential STEM education. The project’s impact will be profound on science and technology innovation, as well as in training a new, diverse, interdisciplinary workforce to drive this field forward.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.