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The Cortical Organization of Syntax: Insights into Grammatical Deficits in Aphasia

open

NIDCD - National Institute on Deafness and Other Communication Disorders

PROJECT SUMMARY Syntax, the ability to combine words into phrase and sentence structures, is a central component of language that is commonly impaired in aphasia. Deficits in sentence production are common in post-stroke aphasia, and sentence comprehension deficits are typically more persistent and severe than word comprehension deficits. Sentence comprehension often show little to no recovery by one year post-stroke, whereas word comprehension deficits typically recover well. Finally, people with chronic aphasia express a strong desire for greater fluidity of connected speech in fully structured sentences. Altogether, syntactic deficits are a major barrier to communication and participation in society for people with post-stroke aphasia. However, dominant neurocognitive models of syntax are supported by indirect measures of syntactic processing which do not segregate out effects of semantic processing and working memory. These models also do not account for the distinct patterns of syntactic deficits and patterns of recovery that emerge from different patterns of brain damage. Finally, these models do not account for the syndrome of paragrammatism, or syntactic deficits in in fluent aphasia, which has overall received highly limited attention in the research literature. We recently established a theoretical model of the cortical organization of syntax that addresses these issues and makes predictions that we will assess in the following research Aims. Specific Aim 1 will identify lesion correlates of receptive syntax in chronic post-stroke aphasia using grammaticality judgments and lesion mapping, Specific Aim 2 will identify lesion correlates and behavioral profile of agrammatic and paragrammatic speech in chronic post-stroke aphasia using a novel elicitation task, objective coding scheme and lesion mapping. We predict that that results will support models which make fundamental distinctions between syntactic and semantic processing and ascribe distinct syntactic functions to frontal and posterior temporal cortex and provide evidence against models which do not make the same distinctions. This work will clarify how distinct syntactic production and comprehension deficits result from damage to different specific brain networks and how these syndromes relate to each other, thereby providing a foundation for future treatment approaches. This proposal is innovative because of the novel theoretic approach informed by neuroscience in aphasia and healthy individuals, and will advance state-of-the-art neuroimaging techniques using arterial spin labeling and graph-theoretic connectivity analyses that account for lesion effects. This proposal is significant because it address poorly understood yet prevalent and persistent syntactic deficits in aphasia which are a priority for treatment as expressed by people who suffer from this condition.

Up to $513K
2031-06-30
health research

Free to search & build · $99 one-time to unlock the application pack · No subscription

The Dynamics of Human Atrial Fibrillation

open

NHLBI - National Heart Lung and Blood Institute

Project Summary Atrial fibrillation (AF) is a major cause of morbidity, stroke and mortality affecting 2-5 million Americans. Recent trials have revolutionized the field, by showing that treating patients classified early in their AF process with anti-arrhythmic strategies can reduce morbidity and increase survival versus treatment with rate control medications. Unfortunately, current definitions of `early AF' are highly inconsistent, so that many patients may be excluded from rapid therapy while others may be treated who are unlikely to benefit. This proposal focuses on developing novel computational phenotypes for patients with early stage atrial fibrillation. This proposal builds on preliminary data from our last funded cycle, novel tools we have developed and datasets we have curated in thousands of AF patients. Aims 1 and 2 will develop computational phenotypes for various forms of early stage AF, which address actionable clinical treatment with non-interventional or ablation therapy. For this, we will develop state-of-the-art machine learning models that we apply to very large datasets from our medical records. For Aim 2, we will integrate body surface mapping, imaging and rich clinical data. We will test models in independent cohorts to test the generalizability of our results across populations. Aim 3 will test models prospectively in a pilot study. Our studies address academic rigor, specifically including a broad range of patients, and we will study sex as a biological variable. This study will deliver immediate clinical and translational impact, accelerating personalized medicine for patients with AF. Results from the project will enable clinicians to classify patients with early-stage AF that are amenable to therapy, versus forms of AF which are less amenable. The project will provide translational insights which could inform future mechanistic studies. We will develop unique datasets and novel computational tools which we will share with the research community through our github and established Institutional portals. Our multi-disciplinary team comprises experts in electrophysiology, imaging, computer science, artificial intelligence and biostatistics. The proposal is thus highly feasible.

Up to $761K
2031-03-31
health research

Free to search & build · $99 one-time to unlock the application pack · No subscription

The EEG spectrum as a marker of severity, burden, and psychiatric diagnosis

open

NIMH - National Institute of Mental Health

Summary There is an urgent need for objective and robust diagnostic indices related to psychiatric illnesses, including obsessive-compulsive and anxiety disorders. Brain-based indices are particularly suited for this purpose, but many of the available brain-based markers have limited scope, require specialized equipment, or have unknown reliability and validity. The proposed research aims to examine the value of data-based, quantitative, and objective markers of dysfunctional electrocortical processes associated with obsessive-compulsive and anxiety psychopathology. The proposed research aims to establish advanced computational indices based on resting electroencephalogram (EEG) recordings that are capable of (1) discriminating between diagnostic categories but also (2) predict transdiagnostic variables such as severity and comorbidity. Specifically, we use state-of-the- art data transformations to extract mechanistically informative indices of spectral shape and alpha-frequency phenomena inherent in EEG recordings during resting states. We will then establish their reliability and internal consistency—prerequisites for using them as markers of inter-individual differences. The indices will then be related to clinical data collected in a large sample of individuals presenting with symptoms on the obsessive- compulsive and anxiety spectrum. A Bayesian Hierarchical Model will be used to aid in data reduction and to measure and heighten reliability of the EEG-derived variables. Finding reliable and valid biomarkers of electrocortical processes has the potential of transforming diagnostic assessment by providing continuous indices of cortical dysfunction. If the goals of this application are met, then reliable and valid indices of electrocortical (dys)function may help to significantly shift clinical practice: In assessment, objective measures of EEG alpha reactivity could be used, for example, to objectively identify patients with perception/attention dysfunction, versus those with generally delayed oscillatory activity and thus more general cortical dysfunction. These inter-individual differences may in the future guide how patients are assigned to individualized treatment protocols as well as for predicting treatment outcome.

Up to $152K
2028-05-14
health research

Free to search & build · $99 one-time to unlock the application pack · No subscription

The growth factor meteorin-like and its receptor KIT in heart failure

open

NHLBI - National Heart Lung and Blood Institute

DESCRIPTION (provided by applicant): Heart failure (HF) is a prevalent healthcare concern associated with unacceptably high mortality rates and significant decreases in quality of life. Chronic inflammation contributes to HF pathogenesis; however, the precise role of the immune response during disease is not fully understood. Acute pressure overload, imposed in the mouse by transverse aortic constriction surgery (TAC), evokes a strong local inflammatory response. Signals emitted from stressed cardiomyocytes trigger the inflammatory cascade and cardiac expression of proinflammatory cytokines and chemokines increases. While most immune-targeting therapies have shown attenuating effects on HF after TAC, depletion of macrophages promoted functional decline, suggesting there may also be beneficial effects from the inflammatory response. One macrophage-derived cytokine that might have favorable effects during HF is meteorin-like (METRNL). METRNL is secreted by myeloid cells and was shown by our group to have a proangiogenic effect after myocardial infarction by binding to the KIT receptor on endothelial cells (ECs). The interaction between METRNL-producing inflammatory cells and KIT+ ECs is a prime example of the importance of paracrine communication in tissue repair after heart injury and opens up a new therapeutic approach. Considering that myeloid cells swiftly accumulate in the pressure-overloaded myocardium and may release protective factors, and that myocardial angiogenesis helps preserve heart function during persistent afterload stress, we hypothesize myeloid cell-derived METRNL may play an important, adaptive role in this context. This proposal aims to investigate the beneficial aspects of inflammation in HF by defining, specifically, the role of METRNL and its receptor, KIT, after pressure-overload. We want to determine if METRNL is involved in the pathogenesis of HF and assess its use as a therapy for disease amelioration. Our preliminary work supports that METRNL attenuates pressure overload-induced HF. Metrnl and Kit transcriptional expression increase significantly following TAC, and Metrnl-deficient mice have reduced survival and heart function after TAC. Our preliminary data show that patients with severe aortic stenosis have elevated METRNL plasma concentrations, indicating pressure overload also triggers METRNL release in humans. We will use genetic gain- and loss-of-function approaches to study the role of myeloid cell-derived METRNL and its receptor KIT in the pressure-overloaded heart. Our goal is to elucidate the role of METRNL in regulating HF progression (Aim 1), to define the major cell types producing and targeted by METRNL (Aim 2), and to assess METRNL’s therapeutic potential in HF (Aim 3). Successful completion of these aims will shed light on the role of crosstalk between the immune system and heart tissue during HF, and evaluate potential protein and gene transfer-based therapeutic approaches for attenuating disease progression. Our work plan and the state-of-the-art research environment emphasize technical and nontechnical training in skills that are highly relevant in contemporary cardiovascular research. The envisioned training will efficiently prepare me for a career as an independent scientist.

Up to $5K
Rolling
health research

Free to search & build · $99 one-time to unlock the application pack · No subscription

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