Randy L. Buckner - US grants

DESCRIPTION (Applicant's Abstract): Repeated exposure to an item within a task shows clear effects on performance. After a single repetition, response times are decreased and response selection is biased -- a phenomenon referred to as priming. After many repetitions, response times become even faster, responses become stereotyped, and tasks requiring considerable attention resources in their naive state are performed effortlessly in their practiced state. While these patterns have been well characterized at the behavioral level, the functional-anatomic changes that take place to allow task facilitation are only beginning to be explored. Pilot data show that recently developed functional magnetic resonance imaging (fMRI) methods are able to observe activation changes in human brain regions as cognitive tasks are facilitated by repetition. The goal of the present research proposal is to use fMRI to track changes that allow cognitive task facilitation in normal subjects. Brain areas activated by word and picture categorization tasks will be characterized in their naive state and will be tracked during early and late phases of item-repetition. After a single item-repetition, task facilitation is predicted to be accompanied by FMRI activation reductions in certain brain areas reflecting the increased efficiency of processing. These early effects may parallel behavioral findings related to priming and show anatomic specificity in relation to the specific task processes being facilitated (as proposed by the components of processing framework). As the number of repetitions increases, brain areas allowing flexible processing(e.g., prefrontal areas) are predicted to become less involved. Other areas, in this highly practiced state, will begin to take over performance of the tasks and are predicted to demonstrate gradually developing fMRI activation increases. This more slowly evolving effect may obey properties similar to skill acquisition and represent a transition to qualitatively distinct processing pathways being used in the over learned task state. The significance of doing this research is that data will be generated in a much needed area of basic research: the exploration of functional-anatomic changes that allow cognitive task performance to be come facilitated. Such information can provide a backdrop for comparing compromised or compensatory functional anatomy that might be observed in patient populations. Recovery following brain damage, for example, occurs gradually and rehabilitation often relies on continuous practice with tasks. It thus seems likely that the principles by which normal brains are able to facilitate task performance and acquire new skills will extend to how the damaged brain acquires skills that were lost.

neural information processing; speech; frontal lobe /cortex; brain imaging /visualization /scanning; functional magnetic resonance imaging; human subject; behavioral /social science research tag; clinical research;

memory; Alzheimer's disease; aging; brain mapping; bioimaging /biomedical imaging; functional magnetic resonance imaging; human subject; clinical research;

Structural imaging provides a means to visualize change in anatomy associated with cognitive decline (e.g., Project 3 "Attention Profiles in Healthy Aging and Early Stage DAT") and also candidate surrogate markers for detection of early-stage DAT (e.g., Project 4 "Project 4 "Predicting Cognitive Decline in Healthy Elders"). The goal of the Core F: Neuroimaging is to collect, store, and disseminate imaging data for the use of the present program project investigations and also to facilitate the development of infrastructure to support future imaging projects. The following Specific Aims will be pursued. (1) Structural imaging data on demented and nondemented participants will be collected, in close coordination with Core A: Clinical, at two-year longitudinal intervals. The structural imaging battery will include (i) high-resolution T1-weighted FLASH images for measurement of the hippocampus, (ii) multiple acquisitions of high contrast MP-RAGE images for measurement of cortical atrophy, (iii) FLAIR images for assessment of white-matter, and (iv) diffusion tensor imaging also to assess white-matter integrity. (2) Research neuroradiological assessment will be made by board-certified neuroradiologists on all structural image data sets. (3) Structural data sets will be archived in conjunction with Core D: Biostatistics and made available via a web-based interface to investigators to pursue research projects. (4) Quantitative structural assessment will be provided for correlating imaging data with project-specific data including (i) automated estimates of whole-brain atrophy, (ii) manual estimates of hippocampal, entorhinal, frontal, and other cortical volumes, and (iii) diffusion tensor measures of tissue integrity. (5) Working closely with Core D: Biostatistics and Core E: Administration, data will be managed to integrate the Core's function with the scientific goals of the program project.

[unreadable] DESCRIPTION (provided by applicant): Presented with changing task goals, healthy young adults can flexibly process and expand upon task relevant information in a controlled manner. At a functional-anatomic level, such cognitive control is associated with selective recruitment of specific prefrontal regions that interact with posterior cortical regions to constrict task-appropriate representations and drive task performance. The present proposal begins an exploration of how these processes develop in childhood, change in advanced aging, and what the significance of their developmental stage is to behavioral task performance. Two hypotheses are explored using this "Life span" approach. First, we predict that cognitive control develops in children concurrent with the ability to recruit frontal regions for task performance. Second, we predict that cognitive control breaks down in older adults when frontal regions are recruited, but in a non-selective manner. A further goal of this proposal is to explore the cognitive consequences of non-selective recruitment in advanced aging. By developing and using cognitive tests sensitive to component processes associated with cognitive control, the behavioral consequences of the emergence of cortical control processes and their breakdown will be explored. In addition, methodological challenges that confront between-group analyses including those surrounding possible anatomic (with development and atrophy), hemodynamic, and performance differences will be explored. Specific aims are (1) to refine methods and determine boundary conditions for making functional-anatomic comparisons across the life span including children, young adults, and older adults, (2) to explore activation patterns within frontal cortex during controlled verbal processing tasks across children, young adults, and older adults using a verbal task battery, (3) to measure, in individual subjects, their capacity for cognitive-control and associate such abilities with their absolute level of frontal recruitment and selectivity of frontal recruitment. If completed, the present proposal will provide (1) methods for functional/anatomic description across the life span from childhood to advanced aging, (2) a corpus of functional/anatomic findings describing developmental change with a particular focus on prefrontal cortex and other structures associated with cognitive control, and (3) data relating these functional-anatomic changes with behavioral correlates of cognitive control. [unreadable] [unreadable]

? DESCRIPTION (provided by applicant): This proposal requests funding for an upgrade of the current Siemens MAGNETOM Trio 3T Human MRI System in the Harvard Center for Brain Science to the new state-of-the- art Siemens MAGNETOM Prisma Fit System. This upgrade will have a significant impact on the neuroimaging research of our NIH-funded projects. The objectives of those funded projects include elucidating the relationship between brain deposits of amyloid, memory impairment, and Alzheimer's disease; studying the atrophy in the elderly of brain regions involved in social cognition, and the development and aging of cognitive control over behavior; delineating the contributions of the hippocampus to episodic simulation and constructive memory; studying the biological basis of emergent increases in daily-life anxiety, and clinical anxiety disorders, in late childhood and early adolescence; and understanding the neural mechanisms involved in object ensemble representation. The upgrade will greatly enhance image quality, reduce scan times, and enable powerful new methods such Simultaneous Multi-Slice (multiband) acquisitions.

Project Summary The goal of P3 is to explore methods for identifying OCD-relevant circuitry in individuals. As targets for invasive and non-invasive OCD treatments become available, a bottleneck for translation in clinical practice is the ability to robustly identify affected circuits in individual patients and measure network modulation. More broadly, focus on groups in neuroimaging studies has slowed translation of findings to the clinical arena where the focus is on the individual. If successful, the project will provide a general set of methods for identifying within-individual network measures that can guide interventions and serve as tailored biomarkers for clinical readouts. The central hypothesis of our Center is that OCD is characterized by hyperconnectivity between the amyg/vmPFC and dACC/ OFC and decreased connectivity between dlPFC/vlPFC and dACC/OFC. This change in balance between emotional processing and cognitive control systems results in a pathological heightened activity state in the dACC/OFC/vlPFC/DS circuitry. In this project we will explore core nodes of this circuitry within individuals and use these methods to explore neuromodulatory effects of OCD circuitry. Aim 1. Identify OCD- relevant circuitry in healthy individuals from the available data including the spatial variability in node location. We hypothesize that, while clustering around the group central tendency, the location of key nodes including the dACC and vlPFC will spatially shift across individuals. These measures will be used to build a variability map. Aim 2. Develop and validate an HCP-inspired connectomic acquisition and analysis strategy targeting diffusion and functional connectivity on a widely available MRI platform. Aim 3. Examine changes in OCD circuitry before and after neuromodulation, 3A. OCD circuitry will be measured in 12 individuals before and after cingulotomy. We hypothesize that coupling between DS and regions just rostral to the cingulotomy will be reduced in effective treatment and preserved in ineffective treatment. 3B. A within-subject TMS study motivated by P4 will analyze before vs after TMS stimulation to further explore whether connectivity measures can be used as a readout of circuit-level perturbations in the individual.

Project Summary The experiments proposed in the Center include extensive use of neuroimaging in both normal control participants and patient groups. Core C will support the individual projects in data acquisition and quality control, implementation of processing pipelines, and capture of raw data for cross-project analyses and eventual broader distribution to the community. Aim 1: The core will assist in implementation of MRI acquisition procedures and anticipated transitions in MR hardware. All project sites currently have available similar Siemens Trio scanners and anticipate transition to the PRISMA system in coming years. The uniformity of hardware and expected transitions provides an opportunity to unify data acquisition and facilitate transition to next-generation functional MRI data acquisition procedures. Optimization of target PRISMA sequences will be performed including direct analysis of comparability to existing Trio sequences. Aim 2: A centralized database will capture all neuroimaging data collected across sites. The neuroinformatics backbone will be based on a custom implementation of the Extensible Neuroimaging Archive Toolkit (XNAT; Marcus et al., 2007). The installation will store each subject's data with metadata about the data types, etc to allow future uses. These data will be accessible to project investigators and stored ready for wide data sharing. Aim 3: The core will provide quality control data assessments. Data quality and uniformity is important to MRI data acquisition, in particular for functional MRI data that is notorious plagued by artifacts of subject compliance and head motion. The core will assess all neuroimaging data acquired in P1-4 for artifacts and make recommendations to improve data quality. Quantitative quality control measures will include assessment of motion and overall signal-to-noise characteristics. The quality control procedures are modeled after those adopted by the NIMH EMBARC trial and implemented in the Simons VIP projects studying autism. Aim 4: The core will develop novel statistical models and computational tools for an fcMRI test for differences between populations (OCD vs healthy controls), effects of treatment (cingulotomy; TMS; direct and indirect modulation) while accounting for between-subject variation.

? DESCRIPTION (provided by applicant): The major technological and analytical advances in human brain imaging achieved as part of the Human Connectome Projects (HCP) enable examination of structural and functional brain connectivity at unprecedented levels of spatial and temporal resolution. This information is proving invaluable for enhancing our understanding of normative variation in young adult brain connectivity. It is now timely to use the tools and analytical approaches developed by the HCP to understand how structural and functional wiring of the brain changes during the aging process. Using state-of-the art HCP imaging approaches will allow investigators to push our currently limited understanding of normative brain aging to new levels. We propose an effort involving a consortium of five sites (Massachusetts General Hospital, University of California at Los Angeles, University of Minnesota, Washington University in St. Louis, and Oxford University), with extensive complementary expertise in human brain imaging and aging and including many investigators associated with the original adult and pilot lifespan HCP efforts. This synergistic integration of advances from the MGH and WU-MINN-OXFORD HCPs with cutting-edge expertise in aging provides an unprecedented opportunity to advance our understanding of the normative changes in human brain connectivity with aging. Aim 1 will be to optimize existing HCP Lifespan Pilot project protocols to respect practical constraints in studying adults over a wide age range, including the very old (80+ years). Aim 2 will be to collect high quality neuroimaging, behavioral, and other datasets on 1200 individuals in the age range of 36 - 100+ years, using matched protocols across sites. This will enable robust cross-sectional analyses of age-related changes in network properties including metrics of connectivity, network integrity, response properties during tasks, and behavior. Aim 3 will be to collect and analyze longitudinal data on a subset of 300 individuals in three understudied and scientifically interesting groups: ages 36-44 (when late maturational and early aging processes may co-occur); ages 45-59 (perimenopausal, when rapid hormonal changes can affect cognition and the brain); and ages 80 - 100+ (the `very old', whose brains may reflect a `healthy survivor' state). The information gained relating to these important periods will enhance our understanding of how important phenomena such as hormonal changes affect the brain and will provide insights into factors that enable cognitively intact function into advanced aging. Aim 4 will capitalize on our success in sharing data in the Human Connectome Project (HCP), and will use these established tools, platforms, and procedures to make this data publicly available through the Connectome Coordination Facility.

? DESCRIPTION (provided by applicant): The major technological and analytical advances in human brain imaging achieved as part of the Human Connectome Projects (HCP) enable examination of structural and functional brain connectivity at unprecedented levels of spatial and temporal resolution. This information is proving crucial to our understanding of normative variation in adult brain connectivity. It is now timely to use the tools and analytical approaches developed by the HCP to understand how structural and functional wiring of the brain develops. Using state-of-the art HCP imaging approaches will allow investigators to push our currently limited understanding of normative brain development to new levels. This knowledge will critically inform prevention and intervention efforts targeting well known public health concerns (e.g., neurological and psychiatric disorders, poverty). The majority of developmental connectivity studies to date have used fairly coarse resolution, have not been multi-modal in nature, and few studies have used comparable methods to assess individuals across a sufficiently wide age range to truly capture developmental processes (e.g., early childhood through adolescence). Here we propose a consortium of five sites (Harvard, Oxford, UCLA, University of Minnesota, Washington University), with extensive complimentary expertise in brain imaging and neural development, including many of the investigators from the adult and pilot lifespan HCP efforts. Our synergistic integration of advances from the HARVARD-MGH and WU-MINN-OXFORD HCPs with cutting edge expertise in child and adolescent brain development will enable major advances in our understanding of the normative development of human brain connectivity. The resultant unique resource will provide rich, multimodal data on several biological and cognitive constructs that are of critical importance to health and well-being across this age range and allow a wide range of investigators in the community to gain new insights about brain development and connectivity. Aim 1 will be to optimize existing HCP Lifespan Pilot project protocols on the widely available Prisma platform to respect practical constraints in studying healthy children and adolescents over a wide age range and will also collect a matched set of data on the original Skyra and proposed Prisma HCP protocols to serve as a linchpin between the past and present efforts. Aim 2 will be to collect 1500 high quality neuroimaging and associated behavioral datasets on healthy children and adolescents in the age range of 5-21, using matched protocols across sites, enabling robust characterization of age-related changes in network properties including connectivity, network integrity, response properties during tasks, and behavior. Aim 3 will be to collect and analyze longitudinal subsamples, task, and phenotypic measures that constitute intensive sub-studies of inflection points of health-relevant behavioral changes within specific developmental phases. Aim 4 will capitalize on our success in sharing data in the HCP, and use established tools, platforms and procedures to make all data publically available through the Connectome Coordinating Facility (CCF).

A long-term goal of cognitive neuroscience is to understand which aspects of cognition are shared across individuals and which are unique to an individual. Studies of the latter are typically concerned with traits that are relatively stable over time, constituting what is referred to as a static phenotype. Phenotyping has proven to be a powerful approach for predicting behavior across time and tasks. For example, individual differences in the ability to delay gratification at age 4 years predict academic, verbal, and socioemotional competence in adolescence. But a major limitation to the predictability of such static approaches to phenotyping is that they do not capture within-individual variation. Static phenotypes are derived from performances on tasks measured at a specific time and context, whereas we know that cognitive performances (and brain measures of it) vary within individuals in relatively short time frames depending on such factors as sleep, stress, mood, alertness, and motivation. To predict an individual's cognitive performance across time, one needs to understand how the individual's cognitive state changes and what drives those changes. This research project, conducted by investigators at Harvard University, will fill this gap by collecting individual data repeatedly over time. By fitting computational models to the data, the researchers will extract a dynamic "computational phenotype? of each individual. They hypothesize that changes will be captured computationally by a relatively small set of dynamical parameters and that a small set of brain networks will be found to map onto those parameters. If this hypothesis is correct, then the project will have the potential to open the door to targeted, precise, and individual-specific training interventions to improve cognitive performance. This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NCS), a multidisciplinary program jointly supported by the Directorates for Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE).

Computational phenotyping has recently emerged as a powerful technique for characterizing variation between individuals. By fitting computational cognitive models to behavioral data, investigators can use the resulting parameter estimates as a cognitive ?fingerprint? for an individual. Computational phenotypes have the advantage over other kinds of phenotypes (e.g., those based on surveys) of being more closely linked to underlying cognitive and neural mechanisms. Research has shown the utility of computational phenotyping in predicting individual-level outcomes, designing interventions, and providing an alternative to traditional diagnostic criteria. A critical limitation of this approach is that it has typically conceptualized the phenotype as a trait?a static descriptor of an individual. In the first aim, the investigators will formalize and experimentally validate a dynamic conceptualization of the computational phenotype. To accomplish this aim, the investigators will have participants complete a battery of behavioral tasks? weekly over three months ? for which established computational models exist. Data from this longitudinal study will be used to estimate how each participant?s computational phenotype uniquely changes over time, and the investigators will employ statistical methods to extract low-dimensional structure in the phenotype. In the second aim, the investigators will use longitudinal neuroimaging in conjunction with the behavioral battery to identify networks in the brain that track the low-dimensional phenotype structure, allowing them to pinpoint the neural locus of intra-individual variation.

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.

PROJECT ABSTRACT/SUMMARY Alzheimer's disease and other forms of dementia affect over five million Americans. Alzheimer's disease begins with changes in the brain more than a decade before the disease can be diagnosed from memory and cognitive impairment in a clinic. The goal of this work is to provide a way to measure early signs of neurodegeneration in individual people. The historical barrier to measure change in individuals is that each person's brain is different with change accumulating too slowly to be picked over short intervals. As a result, most research focuses on tracking averaged subject groups or tracking change over multiple years. The present work optimizes new brain imaging techniques using MRI to make extremely fast, highly precise repeated measurements of brain regions all within the same individual. The work then seeks to use the novel imaging approach to measure neurodegeneration in individuals with early stages of Alzheimer's disease in six months or less and also differentiate changes in people with Alzheimer's disease from less common forms of dementia that have distinct anatomical changes in the brain. If successful, the present work will provide a new means to track the early stages of neurodegeneration as would be used in clinical trials and translational medical research.

PROJECT ABSTRACT/SUMMARY The cerebellum is the second largest structure in the human brain. Until recently, the cerebellum was considered solely a motor structure. Discoveries from neuroanatomy, study of patients with cerebellar lesions, and human neuroimaging have all converged to suggest that major zones of the cerebellum participate in advanced forms of cognition. Relevant to mental health, cerebellar dysfunction has been implicated in psychiatric illness and preliminary reports suggest noninvasive stimulation of the cerebellum may benefit symptoms in schizophrenia. However our detailed understanding of cerebellar organization is far behind that of the cerebral cortex, leading to debates about the spatial organization of cerebellar zones linked to human thought and emotion, and even debate about the degree to which the functional organization of the cerebellum is consistent from one person to the next. The goal of the present work is to provide a detailed understanding of cerebellar organization with particular focus on zones implicated in higher-order cognition that include regions accessible to neuromodulation. (1) First, advanced human high-field MRI methods will be used to map networks across the cerebellum fully within individuals preserving the anatomical details that would otherwise be lost with lower resolution approaches or by averaging findings across individuals. To achieve this level of precision each individual will be imaged repeatedly. (2) Second, to establish that the spatially separate regions of the cerebellum are functionally distinct, the same individuals will be administered challenging tasks that probe language, social, and memorial functions to rigorously establish separation between cerebellar zones that may be as little as a few millimeters apart. (3) Enabled by the precision maps of cerebellar organization, open debates will be resolved that include questions about how many times high-order cognitive zones repeat across the cerebellum and whether small, difficult to map, isolated zones of function contribute to the uniqueness of each person?s brain. (4) Critical to the long-term objective of this work to benefit patient care, the precision maps of each individual?s cerebellum will be used to model the possible effects of non-invasive stimulation. In doing so, a path from precision mapping of the cerebellum to neuromodulation will be provided openly as well as high-resolution maps and raw data that can be utilized by the community to further improve available methods for neuromodulation. Most broadly, the present work seeks to better understand the detailed organization of the human cerebellum to serve as a foundation for understanding and further developing novel interventions in the battle against mental illness.