Mark S. Cohen, Ph.D. - US grants

infection; drug adverse effect; biomedical resource; biological products; bacteria;

DESCRIPTION (Adapted from Applicant's Abstract): The investigators propose to develop software tools for fMRI data analysis that can be used easily and will provide much more reliable data. Further, using algorithms already developed and validated, they will produce fMRI activation maps in real-time at the full 10 image/sec frame rate of the fastest MR scanners. Their tools will detect, and correct in real-time, the most common imaging artifacts. By using a powerful set of methods inherited from the study of linear systems, the investigators are able to calculate activation maps of events with essentially arbitrary timing, so that events that are transient (e.g., epileptiform spikes) or otherwise beyond experimenter control (cluster headaches, seizures, response time data, etc) can be readily captured and mapped, adding considerable freedom to experimental designs. Because the technique will provide immediate feedback, it will be practical for the researcher or clinician to modify the study protocols based on current results, enabling an interactive brain mapping examination. The subject's own activation maps may be presented to him or her, while imaging, allowing a previously impossible class of feed back experiments. In order to make these tools available widely to the MRI user community, the investigators' tools will run, in real-time, on inexpensive (< $2000) desktop computer systems that are well within the means of most imaging centers. This work builds on considerable experience in designing, developing and characterizing high performance MR systems and takes particular advantage of the performance of their unique 3 Tesla functional imager. The investigators have already implemented the real-time technology in prototype. The focus of the continued development will be on extending the basic capabilities and in packaging the data analysis tools and disseminating them to other researchers and institutions.

Our proposed research will investigate the mechanisms involved in construction of an internal model of space by imposing a gross distortion on incoming visuospatial information and observing various areas of the brain for signs of adaptive plastic reorganization. For two weeks, subjects will wear an apparatus that inverts the visual world. Previous studies have shown that subjects exposed to chronically inverted vision undergo a remarkable adaptation, after which they are able to interact normally with the external world. During our research, the subjects will be observed intensively with functional MRI and behavioral testing. Areas studied will include striate and extrastriate occipital cortex, the superior and inferior colliculi, posterior parietal cortex, and superior temporal cortex. We will obtain detailed maps of the functional organization of these areas prior to inversion, repeatedly during adaptation to inverted vision, and after removal of the inverting device; we will pay special attention to changes in the spatiotopic organization of these areas. This work is designed to identify the site of the neural plasticity that permits adaptation to inverted vision. Plastic changes of the human brain are the essential process by which we recover from injuries such as stroke. Further, the physical plasticity of the human brain can be exploited in the development of training regimens to overcome such debilitating conditions as dyslexia, and following traumatic spinal transection. In adults, there remains sufficient capacity for local reorganization that individuals with severe brain or spinal damage can recover the ability to walk. In spite of the overwhelming clinical significance of the phenomena, little is yet known of the extent to which plastic changes can occur. Knowledge of the nature of plasticity in areas of the brain specifically concerned with external space may help in understanding conditions such as hemispatial neglect syndrome, in which damage to the parietal cortex causes an inability to perceive the left side of external space, and blindsight, in which subjects who lack conscious visual perception can still react to visual stimuli. Such knowledge will also be valuable in preparing humans for space travel, when people must adapt to the loss of gravitational clues to spatial orientation.

DESCRIPTION: (Adapted from applicant's abstract) While functional neuroimaging has made great inroads in neuroscience, the applications of functional Magnetic Resonance Imaging (fMRI) to the study of cigarette addiction have been limited. The applicants believe that this is the consequence, in large part, of technical issues that include the difficulty of creating a normal smoking environment (or even of administering cigarette smoke), and the unknown direct effects of the many components of cigarette smoke on the overall sensitivity of the imaging experiments (most of which depend on vascular effects for their signal). In the preliminary studies, The applicants have developed an approach to cigarette smoke delivery that is fully compatible with fMRI and can deliver much of the normal smoking experience during an imaging session. The applicants have shown that this device can mimic important features of normal smoking, including changes in CO, behavioral satisfaction and nicotine blood level. The applicants also demonstrate that we can examine brain signal changes during smoking and have a means to compare fMRI activation signals before and after smoking. In the research plan that follows, the applicants propose to characterize fully the psychological and physiological effects achieved with our in-magnet smoking device and to study carefully the fMRI activations before, during and after smoking. Further, in order to distinguish between effects of nicotine and smoking per se and to facilitate future experiments, the applicants will study these changes after smoking of normal (NIC+) and reduced nicotine (NIC-) cigarettes. With these data in hand, the applicants should be well positioned to use fMRI to probe many outstanding questions in the neurobiology of compulsive smoking. For example, what specific brain regions are involved in craving and its satisfaction by cigarette use? What is the neural basis for the changes in cognitive task performance that characterize withdrawal? What brain areas mediate the separable component effects of nicotine and other aspects of cigarette smoking? What physiological factors underlie shifts in brain lateralization associated with smoking and abstinence? The methods developed in this grant will give scientists new tools for exploring these questions; the answers they find may help to develop new treatments for nicotine addiction and to understand why some individuals are more vulnerable to this life-threatening disorder.

Functional MRI (fMRI) has become a dominant tool in the physiological studies of human cognition and behavior. The moment- to-moment signaling within the brain, however, is understood to be fundamentally electrical. Despite over a decade of applied fMRI research the precise relationship the vascular signals in fMRI and the electrical activity of the brain is largely unknown. In this CEBRA application, we propose to complete development of our methods of simultaneous EEG and fMRI and to adapt these to the recording of extracellular potentials. We believe that we have come up with robust solutions for recording microVolt EEG signals in the presence of milliVolt MR-generated artifacts and are now prepared to enter a development phase for this technology during which we can complete the construction of apparatus appropriate for human research applications. It has long been clear that the problems of concurrent EEG and fMRI are similar to those in concurrent extracellular recording and fMRIas the sources of artifacts are essentially the same. In fact, the signal to noise ratio for the latter should be somewhat better. There are however, significant hurdles to overcome in studying and controlling the safety of such recordings, which are the focus of much of this grant proposal. We believe that this is an exceptionally significant project, in that these tools will enable us to perform crucial validation experiments that will be important in firming the very foundations on which the interpretation of functional MRI is based. Within the limited confines of the budget for the CEBRA program, the project will stop short of actual human experimentation with depth electrodes - the human work will be limited to scalp EEG to stay within the limited scope of the stage I mechanism. On its successful completion, the project will be followed immediately by an application for Stage II support to begin animal experimentation and shortly thereafter to initiate human studies.

[unreadable] DESCRIPTION (provided by applicant): We seek sponsorship from the NIH to support a new and innovative program in the fundamentals and applications of neuroimaging. It is premised on the belief that neuroscientists of tomorrow are likely to require mastery of neuroimaging methods and principles in their work to address the growing burden of neurological disease and to perform the studies that will best advance our understanding of human behavior and cognition. This application includes both T-90 and R-90 components for our pre-doctoral students. The UCLA Comprehensive Neuroimaging Training Program (NITP) seeks to train pre-doctoral students in principles of neuroimaging that are fundamental - common to most or all neuroimaging - in recognition of the rapid changes that have occurred and will continue in imaging technology. They will be exposed to an unusually complete range of imaging approaches from cellular to whole brain, from structural to dynamic and inclusive of advanced multi-modality imaging. Our students will be full participants in the neurosciences interdepartmental program at UCLA, but will benefit from additional specialized course work and experience. The NITP will be both complementary to, and participatory in, existing programs in neurosciences and computational biology already well-established at UCLA. The students will benefit from the large and experience neuroimaging faculty and from courses newly-developed for this program. Responsive to the Short Course opportunities the NITP will sponsor an annual one-week fellowship in functional neuroimaging and an outreach program where the faculty and trainees will deliver content to local schools. We also will hold an annual seminar, directed principally to the lay audience, intended to educate the public on the results and important limitations of neuroimaging. Each of these short course programs will serve important educational objectives for the NITP students, who will serve as facilitators and instructors. [unreadable] [unreadable] [unreadable] [unreadable]

Project Summary/Abstract Neurofeedback by real time functional MRI (rt-fMRI) has potential for addiction research and treatment that will be realized only if the feedback given the subject is related meaningfully to the cognitive states that must be controlled. The mental operations of the brain are too distributed to be represented by the raw rt-fMRI signal in any one brain region or small group of regions. Our aims are to: 1) Use computational machine learning to rapidly detect patterned activation in the rt-fMRI signal that better expresses cognitive state; 2) augment these data with concurrently-collected electroencephalographic (EEG) data; 3) develop an atlas of brain data that identifies brain patterns with cognitive states relevant to addiction and drug abuse research and 4) to explore rt-fMRI neurofeedback using this rt-fMRI/EEG machine learning method. Our approach will be to first create rapid algorithms for pattern matching that are fast compared with the imaging, thereby allowing real-time application. To do so we will select features from the images that express the differences among state concisely (more technically, we will use a method known as independent components analysis to reduce the data dimensionality.) We will similarly condense the EEG features by studying them by the location of their sources within the brain, and by examining the frequencies that they contain. We will run experiments on volunteers designed to help us see their tendency to make impulsive choices - which is known to relate to their likelihood to become drug users, as well as experiments that track changes in their brain as they control their craving urges. For these studies we will look at heavy cigarette users. Cigarette use on its own is a serious health burden to the nation, and it is also an excellent model for addiction more generally, as it is known to have many neural features in common with use of other drugs of abuse, such as cocaine and methamphetamine. This is a phased innovation proposal. The first phase will be focused on the developments of the rt-fMRI analysis and instrumentation technology. On its successful completion, based on specific milestones, we will move to the more applied work with human subjects.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The rate of melanoma skin cancer is increasing yearly with 60000 new cases in 2007 in the US alone. Melanoma is highly curable if treated before it has spread from the primary site on the skin, but 5-year survival rates drop to only 29% once disease has spread to lymph nodes and fall even lower (down to 7%) if tumors metastasize to major organs. The goal of this proposal is to devetop and optimize a new drug-delivery and imaging platform for melanoma staging and treatment. Since melanomas naturally spread initially through local lymphatic channels and lymph nodes, this delivery and imaging system will specifically target the lymphatics. Using nanotechnology, hyaluronic acid, a compound naturally found in the body, is combined with drugs like melphalan normally used in regional therapy for melanoma, and delivered through the lymphatics. By lymphatic drug-delivery, the tumor is treated in a targeted manner, decreasing the amount of drug absorbed systemically which should result in a lower toxicity profile than the way it is currently administered. In addition to treating early melanoma through the lymphatics, this nanocarrier can be combined with gadolinium and imaged by MRI. Utilizing intralyrnphatic delivery for a contrast agent, this proposal will also explore novel ways to image lymphatically spread tumors such as melanoma. If successful, this research will result in an improved method for treating and imaging early to intermediate stage melanoma avoiding the morbidity of current treatment modalities and advancing the field of cancer imaging and therapeutics for lymphatically spread tumors.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Neurofeedback by real time functional MRI (rt-fMRI) has potential for addiction research and treatment that will be realized only if the feedback given the subject is related meaningfully to the cognitive states that must be controlled. The mental operations of the brain are too distributed to be represented by the raw rt-fMRI signal in any one brain region or small group of regions. Our aims are to: 1) Use computational machine learning to rapidly detect patterned activation in the rt-fMRI signal that better expresses cognitive state;2) augment these data with concurrently-collected electroencephalographic (EEG) data;3) develop an atlas of brain data that identifies brain patterns with cognitive states relevant to addiction and drug abuse research and 4) to explore rt-fMRI neurofeedback using this rt-fMRI/EEG machine learning method. Our approach will be to first create rapid algorithms for pattern matching that are fast compared with the imaging, thereby allowing "real-time" application. To do so we will select features from the images that express the differences among state concisely (more technically, we will use a method known as independent components analysis to reduce the data dimensionality.) We will similarly condense the EEG features by studying them by the location of their sources within the brain, and by examining the frequencies that they contain. We will run experiments on volunteers designed to help us see their tendency to make impulsive choices - which is known to relate to their likelihood to become drug users, as well as experiments that track changes in their brain as they control their craving urges. For these studies we will look at heavy cigarette users. Cigarette use on its own is a serious health burden to the nation, and it is also an excellent model for addiction more generally, as it is known to have many neural features in common with use of other drugs of abuse, such as cocaine and methamphetamine. This is a phased innovation proposal. The first phase will be focused on the developments of the rt-fMRI analysis and instrumentation technology. On its successful completion, based on specific milestones, we will move to the more applied work with human subjects. PUBLIC HEALTH RELEVANCE: Our research aims to develop and characterize a means of rapidly detecting brain states relevant to addiction research through the use of magnetic resonance imaging and electroencephalography. We are interested specifically in states and markers of impulsivity and cigarette craving. Our goal ultimately is to have a tool that can be used in the context of neurofeedback, allowing human subject or patient to receive an indication of activity in their brains associated with these states and to enable them to learn to control these cognitive/affective states by controlling the brain activity.

DESCRIPTION (provided by applicant): Nearly every neuropsychiatric disorder (e.g., depression & schizophrenia, attention deficit disorder, obsessive compulsive disorder and bipolar disorder) shows deficits in attention control: the ability to attend to behaviorally relevat sensory stimuli and ignore irrelevant stimuli. Attentional control is, of course, a central factor n the attention deficit disorders and is thought to play a significant role in addictive behaviors. These deficits can occur because of impaired suppression of distractions or because of fluctuations in sustaining of attention, when the mind wanders. We propose to develop measures that will allows us to distinguish between these deficits at the neural level, describe their interactions and facilitate tracking of attention performance that is imperative for accurate diagnosis and monitoring of treatment efficacy. To achieve this we will combine the complementary methods of electroencephalography (EEG) (especially relevant to short term processes and spectral specificity) and functional MRI (relevant to slow evolutions in sustained attention and providing spatial specificity not readily observed with EEG) to measure fast and slow changes in attention. These measures will ultimately allow us to explain when and why internal state and distractibility impair behavior.

Abstract The development of new methods to treat cancer is greatly needed. In this application, we have identified a macrocyclic small molecule that exhibits high differential selectivity for cancer cells vs. normal cells and aim to develop more simplified analogs of this molecule in an effort to maximize efficiency as well as to decrease the overall number of steps, which will likely lead to clinically useful molecules for the treatment of cancer. In addition, we aim to interrogate the activity manifested by these compounds in both cellular and animal models of cancer, with the goal of providing preclinical data to support the use of such compounds for translational development.