2001 — 2005 |
Schnyer, David M |
K23Activity Code Description: To provide support for the career development of investigators who have made a commitment of focus their research endeavors on patient-oriented research. This mechanism provides support for a 3 year minimum up to 5 year period of supervised study and research for clinically trained professionals who have the potential to develop into productive, clinical investigators. |
Preserved and Disrupted Memory Processing in Amnesia @ Boston University Medical Campus
DESCRIPTION (provided by applicant): An intense and continuing debate about the nature of memory in the human brain was triggered by the discovery that amnesic patients, despite being unable to explicitly report a prior event, displayed changes in behavior due to that event. While behavioral research has illuminated many important aspects of this phenomenon, referred to as repetition priming, basic questions regarding brain mechanisms require functional brain imaging techniques. Recent developments in fMRI and its multimodal integration with EEG and MEG are beginning to provide sufficient spatial and temporal resolution to address questions about the neural basis of preserved priming in amnesia. The candidate, a Clinical Neuropsychologist with a published background in human EEG, is proposing a 5-year program of education, training and research focused on developing expertise in fMRI and MEG, their multimodal integration, and the application of these techniques to the study amnesia. Serving as a primary mentor, Dr. Mieke Verfaellie, Director of the Memory Disorders Research Center at Boston University, will provide her extensive research experience in the study of patients suffering non-progressive memory loss. As secondary mentors, Dr. Anders Dale (Associate Director, Massachusetts General Hospital NMR Center) and Dr. Eric Halgren (Director, MEG Core MGH-NMR Center) will contribute with expertise in the use and integration of fMRI, EEG and MEG as well as adding important access to the rapidly growing NMR research center at MGH. This unique team of mentors will provide the needed combination of expertise and resources for the candidate to carry out a 5-year program of research focused to address three specific aims. First, we propose to map the functional neuroanatomy of two forms of priming (with and without awareness of a priming stimulus) and determine the extent to which amnesics and normals recruit the same neural mechanisms. Secondly, we propose to examine the effect of time between events on priming, which we predict will affect amnesics and normals differentially. Finally, we will attempt to determine which neural processing events are crucial for priming to take place and how these relate to effects previously observed in neuroimaging studies of priming. These studies will integrate the training, education and research components of this proposal in order for the candidate to emerge as an independent and productive researcher with a unique set of methodological skills to apply towards the study of amnesia.
|
0.901 |
2014 — 2015 |
Allen, John J. [⬀] Schnyer, David (co-PI) |
R21Activity Code Description: To encourage the development of new research activities in categorical program areas. (Support generally is restricted in level of support and in time.) |
Identifying Eeg Indices of Neural Systems Underlying Risk For Mdd
DESCRIPTION (provided by applicant): Major Depressive Disorder (MDD) is unfortunately common with substantial burden of disease, economically and personally. Given the prevalence of depression and its debilitating course, [developing biomarkers that that have predictive value for the development, maintenance, and treatment of MDD and related disorders is of high scientific significance. Biomarkers that link deficits in neural systems to specific psychological processes that are dysfunctional in MDD] are especially valuable because they can reveal risk-to-symptom pathways that may be future targets for treatments and preventions. Although neuroimaging in MDD has generated impressive returns, imaging procedures such as functional magnetic resonance imaging (fMRI) are not well- suited for studying prospective of risk for MDD, given the relatively high cost of fMRI and the large samples required for prospective studies. A cost-effective and promising strategy would be to link less costly and more widely-available electroencephalographic (EEG) indices of brain activity to specific neural systems involved in MDD, [and subsequently to use these EEG biomarkers in assessing risk in research and clinical settings. Future prospective research using cost-effective EEG in large samples would have a clear link to established neural systems identified with fMRI approaches. Moreover, such easily-assessed biomarkers can promote premorbid risk assessment, facilitate early diagnosis, and lead to individually-tailored treatment and] prevention approaches for high-risk populations. With these goals in mind, [and motivated by a cognitive-neural emotion- regulation framework of depressive vulnerability,] we propose to collect simultaneous resting-state (RS) fMRI and 64-channel EEG data [from never-depressed and previously-depressed young adults], to identify associations between surface-recorded EEG and regional connectivity assessed via RSfMRI. We will apply cutting-edge approaches to the examination of RSfMRI networks and EEG data, including independent components analysis and multivariate vector approaches. We will examine EEG features motivated by extant EEG MDD literature, such as frontal EEG asymmetry, and also conduct broader exploratory analyses, to identify which EEG features index aspects of resting state network connectivity that have previously been identified as dysregulated in MDD. We can then assess whether these EEG features differentiate individuals with a lifetime history of MDD from those without - which would be expected of a risk indicator for MDD - using [the present sample and also] our extant sample of 306 individuals (143 with a history of MDD), all of whom have provided resting EEG data. In addition to the RSfMRI, high resolution T1 structural images as well as diffusion tensor images (DTI) will be collected to provide structural correlates of EEG and RSfMRI connectivity that can be examined in a highly exploratory manner. In this application we provide pilot data showing the feasibility o this approach, but consistent with the R21 mechanism, we consider our exploratory approach to be a strength of this proposal.
|
0.964 |
2017 — 2019 |
Beevers, Christopher G [⬀] Schnyer, David (co-PI) |
R33Activity Code Description: The R33 award is to provide a second phase for the support for innovative exploratory and development research activities initiated under the R21 mechanism. Although only R21 awardees are generally eligible to apply for R33 support, specific program initiatives may establish eligibility criteria under which applications could be accepted from applicants demonstrating progress equivalent to that expected under R33. |
Development of Attention Bias Modification For Depression @ University of Texas, Austin
Abstract The overall goal of this project is to continue development of an attention bias modification (ABM) intervention that targets and reduces negative attention bias among adults with elevated symptoms of depression. Our prior work indicates that attention bias for negative information is associated with the maintenance of depression and that neural circuitry within frontal-parietal brain networks supports biased attention for negative information, thus allowing us to develop specific and targeted interventions that directly alter the neurobiology of negative attention bias. The proposed R33 study builds upon our prior NIMH funded work (R21MH092430), which examined whether ABM reduces negative attention bias and improves symptoms of depression. Findings indicate that compared to placebo ABM, active ABM reduced negative attention bias and increased resting state connectivity within a neural circuit (i.e., middle frontal gyrus and dorsal anterior cingulate cortex) that supports control over emotional information. Further, change in negative attention bias from pre- to post-ABM was significantly correlated with depression symptom change but only in the active training condition. Importantly, a 40% decrease in symptoms was observed in the active training condition; however, similar symptom reduction was also observed in the ?placebo ABM? condition. Exploratory analyses indicated that placebo training may have promoted depression improvement by enhancing sustained attention. Although these preliminary findings are encouraging and demonstrate that ABM successfully alters the treatment target (i.e., negative attention bias), our prior work is among the first to document efficacy of ABM among adults with clinically significant depression. We believe it is prudent and necessary to obtain additional efficacy evidence for ABM before moving forward with large-scale clinical trials of ABM for depression. Aim 1 is to conduct a randomized clinical trial among adults with elevated symptoms of depression and a negative attention bias that compares the efficacy of active ABM to placebo ABM and an assessment-only control condition that does not involve any ABM procedures. Aim 2 is to examine whether ABM alters negative attention bias and functional connectivity within frontal-parietal neural circuitry that support negative attention bias. Aim 3 is to identify mechanisms responsible for the putative efficacy of active and placebo ABM. Study Impact: The current project proposes to target and reduce negative attention bias with a novel intervention grounded in basic psychopathology research. We believe this experimental medicine approach will lead to the development of a highly specific and targeted intervention, using cutting- edge cognitive neuroscience to inform treatment development, and improve the quality of life of people whose psychopathology is maintained by negative attention bias.
|
1 |
2018 — 2019 |
Schnyer, David Worthy, Darrell A. (co-PI) [⬀] |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
A Computational Neuroscience Approach to Frontal Compensation in Decision-Making @ University of Texas, Austin
DESCRIPTION (provided by applicant): Age-related deficits in decision making are well documented and these decisions often have huge social implications for individuals and their family members, leading to significant pressure to make the best decisions. Much of the previous research on aging focused on history-independent decision-making tasks for which current rewards are independent of previous decisions. This research ignores situations where the current rewards available from each option are influenced by previous decisions. History-dependent decisions are ubiquitous and they are often accompanied by various forms of pressure. Recent work in our labs suggests that older adults perform better in history-dependent situations while younger adults perform better in history- independent situations. However, the precise neural and computational mechanisms associated with these age-based differences remain unclear. Additionally, virtually no research has examined how older adults respond to pressure despite its prevalence. Recent work suggests that normal aging is associated with declines in the neuromodulation of the frontostriatal limbic network associated with decision-making. Other work provides evidence for compensatory over- activation in brain regions, particularly lateral frontal brain regions, for older relative to younger adults in a variety of cognitive tasks. This over-activation is seen as compensatory for neural declines associated with aging and is known as the compensation-related utilization of neural circuits hypothesis (CRUNCH). We hypothesize that compensatory over-activation can account for the age-related advantage in history-dependent decision-making. In addition, compensation related frontal activity in older adults may follow an inverted U- shape as cognitive demand increases. With increased cognitive demand, under-activation in older adults, relative to younger adults might result when the crunch point is reached. Increased pressure in decision- making situations may force older adults to hit such a crunch point. The goal of this proposal is to examine the effects of aging on history-dependent and history-independent decision-making, and to systematically test predictions of the CRUNCH hypothesis as it applies to decision- making under pressure. Our research team is highly qualified to achieve these aims given our expertise in brain imaging, computational modeling, and behavioral studies of normal aging and pressure. We will apply models that assume qualitatively different strategies to the data and prediction errors from these models will be used as regressors with neural activity. We predict that older adults will show greater activation in DLPFC and LOFC, compared to younger adults under no pressure conditions but that older adults will show under- activation in these same regions under pressure conditions. Aims 1 and 2 examine the neurobiological underpinnings of age-related changes in history-dependent and history-independent decision-making. Aim 3 extends Aims 1 and 2 by examining decision-making under pressure.
|
1 |