Timothy J. Gardner - US grants

heart surgery; myocardium;

[unreadable] DESCRIPTION (provided by applicant): Optimization of therapeutic drugs for safety and efficacy is a delicate balancing act requiring chemical modification of the drug candidate without altering it's therapeutic benefits. Knowledge of a drug's mechanism of action is critical for successful optimization. In prior work, we developed a novel approach for predicting drug mechanisms from gene expression profiles of drug activity. The method was pioneering in its use of a mathematical gene network model to analyze noisy, high-dimensional gene expression data. It was successfully applied in a preliminary study on yeast, but certain characteristics of our early work limit its accuracy and broader applicability. In particular, the modeling approach obscured biologically meaningful network relationships, and could not incorporate prior data on gene network structure to improve predictions. [unreadable] [unreadable] In this project, we will develop statistical, computational, and experimental methods to extend and broaden our previous work on predicting drug mechanism of action from gene expression data. In aims 1-3, we will adapt the framework of simultaneous equation models (SEMs) to our problem and, within this context, develop extensions of recent techniques for sparse inference, both frequentist and Bayesian variants. In aims 4-6, we will test and validate the sparse SEM methods on a database of expression profiles that we will obtain by treating yeast with a large set of stresses and bioactive compounds. The resulting methods will enable rapid and inexpensive discovery of the mechanism of action of both candidate therapeutic compounds and hazardous biological toxins. [unreadable] [unreadable] This proposal includes innovative contributions in biology, bioinformatics, statistics, chemical biology and pharmacology. The work will make valuable contributions to the fields of systems biology and bioinformatics by demonstrating unique methodology for design and analysis of microarray experiments and the practical utility of genome-scale modeling of gene regulation. To the statistics community, this work will offer powerful extensions of the SEM framework, through its pairing with adaptive, sparse inference tools. For the chemical biology and pharmacology communities, this work will offer a valuable new method to determine the biological activity of novel compound classes. [unreadable] [unreadable] In addition, this work could substantially accelerate the development of safe and effective therapeutic drugs. It could provide a novel computational tool for quickly and cost-effectively evaluating the mechanism of action of chemical and biological agents of potential therapeutic value. Moreover, some of the compounds that we propose to study in this project are novel anticancer and antifungal compounds with therapeutic potential. [unreadable] [unreadable] [unreadable] [unreadable]

? DESCRIPTION (provided by applicant): This project seeks to develop a high density, minimally invasive electrode array for long-term recording and control of brain activity. Multielectrode arrays are an essential tool in experimental and clinical neuroscience, yet current arrays are severely limited by a mismatch between large or stiff electrodes and the fragile environment of the brain. Chronically implanted electrodes cause ongoing damage to the brain, and an active process of rejection eventually silences neural signals. Failure of chronic implants over long time-scales makes it very challenging to study the neural basis of learning. It also limits the power of brain machine interfaces for human prosthetics or neural stimulation based therapeutics. To minimize electrode damage, the size of implants must be reduced, but multichannel arrays built from the smallest electrodes are impossible to implant due to buckling of the individual fibers as they enter the brain. The proposed recording and stimulating electrode array solves this mechanical problem - achieving a high channel with sub-cellular (5 micron) microfibers distributed in three-dimensional volumes of the brain. To implant the device, individual electrodes are bundled together, strengthening each fiber through mutual support. During implant, the bundle of fibers splays apart and each fiber follows its own separate path into the brain as it is deflected by tissue inhomogeneity. This process preserves the minimally invasive properties of a single fiber. Chronic recordings from prototype designs reveal stable signals, including multiunit recordings with time-scales of months that show minimal drift in neural firing patterns. This project builds on preliminary data to engineer a robust, high channel count (64 channel polyimide) device suitable for both recording and stimulation in basic science studies and eventually for clinical applications. However, due to the minimally invasive nature of this brain interface, the device will be scalable to even higher channel counts. To advance this technology, the project involves a series of aims to optimize the electrode insulator, apply high performance tip coatings, and develop scalable manufacturing processes on a polyimide cable platform. These engineering aims are followed by rigorous benchmarks in vitro and in vivo, including 18 month tests of stimulating electrode capabilities. The project will also demonstrate the potential of the high density, minimally invasive electrode array to trigger diverse activity patterns by shaping the geometry of current flowing through small volumes of the brain.

DESCRIPTION (provided by applicant): Humans maintain learned motor skills over long time-scales-for days, years or even decades. However, little is known about how the brain achieves this stability. Some studies indicate that while motor skills can remain stable for years, the individual neurons controlling them may significantly change their firing properties over the course of hours. In another view, the tuning of individual neurons is as stable as the motor skill itself. The central hypothesis of this project is that the brain encodes learned behaviors on two distinct levels - a mesoscopic level that is highly stable, and a microscopic level in which single neurons change and are influenced by the recent history of motor performance errors. In other words, the stability of a memory is rooted not in single neuron stability, but in network patterns that persist in spite of drifting activity in individual neurons. This project investigates this hypothesis by examining the neural basis of song in zebra finches. The neural circuits that underly song behavior are well defined, extensively studied, and in key respects homologous to the cortico-basal ganglia circuits that underly sensory-motor learning in mammals. For this project, the key value of the songbird is the stability of its behavior. A songbird can sing the same learned song with great precision for years providing a unique opportunity to examine how motor skills are preserved over long time-scales. Using new tools for stable recording from neurons, the project examines single neuron tuning and network patterns underlying song over time scales of days to months. To accelerate changes in the song motor program the project uses a brain-machine interface that generates brief bursts of noise during singing whenever the brain activates specific groups of neurons. Preliminary data reveals that birds can learn to reduce this interfering noise, and improve the quality of their songs by controlling the pattern of activity in the targeted neurons. Through the brain-machine interface and other experiments, significant preliminary data reveals that whereas mesoscopic dynamical patterns in premotor cortex are stable, individual neurons can drift in and out of the ensemble pattern, and adjust their activity to minimize performance errors. This project will reveal the rules of this process with cellular resolution. Insights gained from these experiments have the potential to impact human health. If single neurons drift in motor control, then knowing the rules that govern this drift will be critical to therapeutic interventions that promote recovery after injury, or create sable brain- machine interfaces for human prosthetics.

DESCRIPTION (provided by applicant): This project seeks to develop a minimally invasive electrode array for long term recording of brain activity, with single cell resolution. Multielectrode arrays are an essential tool in experimental neuroscience, yet current arrays are severely limited by a mismatch between large or stiff electrodes and the fragile environment of the brain. Chronically implanted electrodes cause ongoing damage to the brain, and an active process of rejection eventually silences neural signals. Failure of chronic implants over long time-scales makes it very challenging to study the neural basis of learning, and prohibits the implementation of long term stable brain machine interfaces for human patients. To minimize electrode damage, the size of implants must be reduced, but multichannel arrays built from the smallest electrodes are impossible to implant due to buckling of the individual fibers. The proposed electrode array solves this mechanical problem - achieving large channel count and sub-cellular (5 micron) individual electrode size in an bundle that strengthens each fiber through mutual support. During implant, however, the bundle splays apart and each fiber follows its own separate course into the brain, preserving the minimally invasive properties of the single fibers. Chronic recordings from prototype designs reveal stable signals, including multiunit recordings with time-scales of months that show minimal drift in neural firing patterns. This project seeks t document how the electrodes interact with vasculature during implant, what damage they cause over three month time-scales, and how these factors relate to the yield and stability of chronic recordings gathered continuously for three months. The methods involve in-vivo imaging of electrode insertion, chronic recording of neural signals in freely behaving animals, and histological analysis of neuronal health and signs of local immune activation near the implant. The anticipated result is that during insertion, individual fibers travel along their own paths of least resistance into the brain, leading to reduced vascular damage. On the timescales of chronic recordings, the anticipated result is improved tissue health and stable neural signals in close proximity to the electrode. Specific variations in experiments proposed here will inform future designs that seek to scale up the number of channels in the tunneling fiber array, providing an opportunity to track large ensembles of cells simultaneously. The near term application of this project will be seen in small animal studies where it is virtually impossible t track the firing patterns of ensembles of neurons through learning with existing large-scale electrodes. Advances focussed on this deliverable are likely to also translate into more stable recordings in larger organisms, with potential direct benefits to human brain machine interfaces.

Miniature head-mounted fluorescence microscopes allow neuroscientists to record from populations of neurons longitudinally at cellular resolution in freely moving animals. However, off-the-shelf devices currently lack a number of desirable features such as easy modification, wireless interfacing, and flexible real-time analysis software. This project will disseminate an open-source miniature microscope (?miniscope?) that meets these needs. New features realized in the miniscope include a 3D-printed housing for easy microscope reconfiguration, wireless telemetry, and color CMOS sensors for simultaneous recording of multiple fluorescence indicators. In addition to the microscope, this project disseminates open-source software for controlling the microscope. This software is capable of real-time image processing and feedback for closed-loop experiments that trigger stimulation or other events in response to patterns of recorded neural activity. The strategy for dissemination is two-fold. First, the project provides fully functioning miniscopes and associated components and training for 14 collaborating labs. These end-users will use the microscopes to address a wide range of questions in surface and deep brain nuclei, focused on many distinct cell types. These groups will study learning in normal brain functioning and pathological activity patterns in multiple disease models. Second, the project will create a public web repository containing resources and documentation necessary to reproduce the microscope in other laboratories. Finally, the project will implement a number of design variations requested by end-users. These design variations include changes in the field of view, specialized microscope housings, adaptations for simultaneous electrophysiology, new color imaging strategies, and user-defined changes to the real-time software. These design variations will also be described in the public web resources. Ultimately, the goal of the project is to provide a platform for innovation in the use of customized miniature microscopes.

Project Summary This project seeks to develop a high density, minimally invasive optical micro?ber array for long-term recording and manipulation of brain activity. Optical methods have become a cornerstone of modern brain science in animal models, and hold great potential for future human prosthetic devices. However, light scattering severely limits optical approaches for deep brain recording and stimulation. Current photometry methods of implanting optical ?bers into deep brain areas work with relatively large ?bers designed for the communications industry (125 ?m). This project builds an optical micro?ber array to record from and stimulate deep brain areas. The device achieves a high channel count with sub-cellular (7 ?m) optical micro?bers distributed in three- dimensional volumes of the brain. To implant the device, individual micro?ber light guides are bundled together, strengthening each ?ber through mutual support. During insertion into the brain, the bundle of micro?bers splays and each micro?ber follows a distinct path into the brain as it is de?ected by tissue inhomogeneity. This process is hypothesized to preserve the minimally invasive properties of a single 7 ?m ?ber. Prototype designs reveal healthy neurons in close proximity to the implanted micro?bers, and high signal to noise recordings in vitro. The project builds on preliminary data to test high channel count devices for both recording and stimulation. To advance this technology, the project involves a series of aims to characterize tissue response to high channel count implants, develop a rotary ?uorescence microscope to interface with the array, and benchmark the performance of the device for both recording and stimulation of genetically encoded constructs in deep brain regions.

ABSTRACT A major goal in clinical neuroscience is to develop efficient treatments to prevent or minimize the loss of brain function caused by pathological decreases or increases of neuronal activity, which are hallmarks of a wide variety of neurological disorders. Interestingly, in some instances, the brain has evolved mechanisms to partially correct abnormal neuronal function. Understanding the adaptive mechanisms that restore brain function would not only provide insight into the functioning of the normal brain but also guide future approaches to ameliorate loss of brain function caused by disease or injury. We propose to start a research program to investigate the cellular and circuit mechanisms by which the brain maintains constant behavioral output, even when neuronal activity is naturally variable or it is perturbed. Our preliminary evidence with songbirds indicate that the brain circuits involved in song production demonstrate a high level of behavioral resilience both at short and long timescales. At the short timescale the patterns of firing of premotor neurons directly involved in song production vary from day to day, although there is no measurable variability in the song. At the long timescale, we genetically perturbed the activity of these premotor neurons and this caused a dramatic disruption of song. However, manipulated birds fully recovered from the perturbation, and were able to produce their original song after around 10 days. We will build on these results to explore the neuronal mechanisms that ensure behavioral resilience in a brain circuit involved in a complex behavior using gene delivery, optogenetics, in vivo functional imaging, behavioral analysis, and computational modelling.