Trustees Of Indiana University

NIH Research Projects · FY 2024 · 2023-07

PROJECT SUMMARY The rapid adoption of genetically modified animals and fluorescently labeled biocompatible nanoparticles for drug delivery in biomedical science have increased demand for imaging technologies capable of fast volumetric imaging to enable longitudinal investigations of cell dynamics in their natural environment. The complexity of information required to understand tissue response to injury and treatment has also generated increased interest in multimodal imaging systems that combine complementary performance strengths. In this regard, we have developed an integrated dual-modality imaging system that combines optical coherence microscopy (OCM) and dual-channel confocal fluorescence microscopy (CFM) to enable the simultaneous measurements of fluorescence and reflectance from deep tissue layers. The combined system provides a unique opportunity to inform cells’ behavior in their natural environment by offering complementary information not available with either system alone. CFM interogates the distribution of fluorescently labeled molecules in cells. OCM is a label-free, episcopic method providing information about the cell boundaries, extracellular matrix, and thickness changes in layers of normal and pathogenic tissues. Despite its potential, the integration of these technologies is incomplete without the capability of concurrent volumetric imaging allowing the tracking of cell dynamics progressively in the same specimen. As for scanning- based systems, fast volumetric imaging in OCM and CFM requires dynamic focusing at the level of individual scanning points, which is challenging due to the limited temporal resolution of dynamic focusing devices. This project aims to establish the capability of the tunable acoustic gradient lens, the fastest dynamic focusing technology to date, in OCM and CFM to enable a fast volumetric and concurrent imaging of depth-resolved reflectance and fluorescence from deep tissue layers in vivo. This integration will have a tremendous impact on biomedical research as OCM and CFM technologies remain the most affordable, flexible, and the latter is readily available in many research facilities. We propose the following two specific aims: Aim 1: Enable fast volumetric imaging in confocal fluorescence microscopy. Aim 2: Enable extended depth-of-field in optical coherence microscopy. Significance The ability to concurrently acquire volumetric information such as reflectance and fluorescence rapidly from deep tissue layers will provide a powerful tool for longitudinal investigations into developmental and pathophysiological mechanisms in various research fields and facilitate in vivo cell tracking in the same specimen while increasing the rigor and reproducibility of studies by decreasing the inter-subject variability that can affect the outcomes of cellular processes.

NIH Research Projects · FY 2025 · 2023-06

ABSTRACT Unmet sexual and reproductive healthcare (SRH) needs are a significant problem in the United States and are associated with a broad spectrum of negative sexual and reproductive health outcomes. Consequently, it is essential to understand the factors associated with unmet SRH needs and the characteristics of women who are most vulnerable to unmet SRH needs. Existing research has been limited in two ways. First, quantitative research on unmet SRH needs is often constrained by a lack of available information on women who do not receive care, by virtue of their absence from care. Second, the paucity of robust, longitudinal data has prohibited researchers’ ability to specify how SRH experiences (and unmet needs) are connected throughout women’s lives. The objective of this project is to elucidate the connection between unmet SRH needs over time and to identify the factors associated with and disparities in levels of unmet SRH needs over time. To do so, this project will leverage an innovative mixed-methods dataset from the Person to Person (P2P) Health Interview study, a large omnibus health study, including: (1) new in-depth interviews with reproductive-aged women in the P2P sample (N=40), (2) linked electronic health records (EHR) of women in the P2P sample (N=1,462), and (3) associated P2P survey data. To achieve the overall objective, the proposed project addresses two specific aims. Aim 1: Identify women’s perceptions of unmet SRH needs across their lives and the conditions that contribute to those unmet needs using in-depth interviews guided by participant’s EHR. These interviews will elicit women’s narratives of their experiences with SRH over time and contextualize SRH events in their EHR with information about their social circumstances and the connections between each experience and subsequent SRH utilization decisions. Furthermore, these interviews will identify instances of unmet need and utilization not included in the EHR. Aim 2: Classify patterns in SRH usage over time using sequence analysis to compare (2a) factors and resources associated with unmet SRH needs and (2b) sociodemographic disparities in patterns of SRH utilization. I will evaluate the elements in each pattern against standards of preventative and acute care and women’s accounts of their unmet needs (gathered in Aim 1) to assess the level of unmet need. I will use multinomial logistic regression to examine the association between (a) measures of predisposing factors and enabling resources (healthcare access, racism, trust in doctors, and social support), (b) sociodemographic characteristics and patterns of SRH utilization with differing levels of unmet SRH need. Results from this study will generate valuable information that can be used to develop targeted interventions to reduce unmet SRH needs, eliminate racial and socioeconomic disparities in SRH utilization, and improve sexual and reproductive health outcomes over women’s lives.

NIH Research Projects · FY 2024 · 2023-06

Young pregnancy and the behaviors that lead to it—penile-vaginal sexual intercourse and contraceptive non-use—have important long-term consequences for health and well-being. Religiosity plays an important role in these behaviors; more than half of U.S. states require that sex education curricula include an emphasis on abstinence, a faith-based approach to avoiding undesired pregnancy. We propose to build on existing research using cross-sectional and large-interval longitudinal datasets, which have dramatically advanced our understanding of how religious and non-religious youth differ in terms of overall pregnancy rates and related behaviors, but do not include detailed measures of the dynamic behaviors that lead to pregnancy. We will use the only available population-based dataset with repeated weekly measures of penile-vaginal sex and contraceptive behaviors and the intimate relationships in which they occur, combined with detailed questions about religious affiliation, beliefs, and behaviors. The questions about religion permit us to construct three distinct measures of religiosity across three domains: religious conservatism (affiliation with a conservative denomination, belief that the bible is the inerrant word of God), external religiosity (service attendance), and internal religiosity (praying, religious salience). We propose to estimate differences across these domains of religiosity in terms of an integrated set of sexual and contraceptive behaviors throughout the study period—time spent in an intimate partnership, time to first penile-vaginal intercourse within each intimate relationship, frequency of penile-vaginal intercourse after a relationship became sexual, whether any contraceptive method was used during each week that included penile-vaginal intercourse, whether a hormonal (vs. coital) method was used during each week of contraceptive use, whether a condom was used consistently (during each act of penile-vaginal intercourse) during weeks of condom use, and whether the male partner consistently withdrew the penis before ejaculation during each week withdrawal was used. We will also analyze pregnancy rates and undesired pregnancy rates and estimate the extent to which differences by religiosity are due to differences in penile-vaginal sexual behavior, differences in contraceptive use, or both. The combined detail of these analyses is unprecedented and will allow us to distinguish among multiple mechanisms through which religiosity influences behavior, such as conservative values about pre-marital sex, fear of pregnancy, lack of planning for penile-vaginal intercourse, beliefs about the beginning of life, social exposure, social interaction, and social control. We propose the ideal collaborative research team for these analyses. Barber was the PI of the original RDSL project, and Pearce designed the religiosity measures in the RDSL baseline survey. Their complementary expertise—Barber’s in intimate relationships, sexual behavior, and contraceptive use, and Pearce’s in religion and religiosity among youth—are ideal for the proposed project.

NIH Research Projects · FY 2024 · 2023-06

Controlling whether and when a pregnancy occurs is a human right. Yet, despite more than 40 years of the U.S. Department Health and Human Services prioritizing the reduction of undesired pregnancies, rates remain high [49]. This is at least in part because despite a great deal of research on this topic, we still have relatively little understanding of why some women are able to get what they want in terms of pregnancy while others are not. This study takes an innovative approach to understanding this puzzle in two ways, which allow me to overcome two persistent barriers to our understanding of undesired pregnancies. First, I apply a unique and innovative theoretical framework—the Traits-Desires-Intentions-Behavior (TDIB) framework—that has been largely neglected by demographers. The TDIB has great potential to contribute to our understanding of undesired pregnancies because it was specifically designed for this purpose; it focuses on the potential mismatches between desires and intentions, and between intentions and behaviors. Second, I use a unique longitudinal, mixed-method study of 18- and 19-year-old women, the Relationship Dynamics and Social Life (RDSL) study, which includes both prospectively measured pregnancy desires and semi-structured interviews (n=75) with subsequently pregnant and non-pregnant respondents. The semi-structured interviews, particularly the non-pregnancy interviews, remain almost entirely un-analyzed, and were designed specifically to generate innovative new hypotheses and evidence about undesired pregnancies. First, we interviewed a group of 40 RDSL respondents, (distributed evenly across white/Black and poverty/non-poverty groups) who experienced pregnancies during the 2.5-year study period. (The vast majority were undesired.) Second, we interviewed a comparison group (n=32) who were similarly distributed across race and poverty groups, but who avoided pregnancy during the study period. Using a systematic anomalous case analysis strategy [75], an abductive approach to generating new hypotheses with “surprising” (i.e., in this case, unpredicted by statistical models) cases, we selected respondents with high model-based propensity for pregnancy, based on a hazard model using the 2.5 years of survey data. We distributed these interviews across three additional groups, based on survey responses: those with zero or non-zero pregnancy desire, one or multiple intimate partners, and perfect or imperfect contraceptive use. I propose to use NVivo software and qualitative analysis techniques to analyze the semi-structured interviews by comparing the pregnant and non-pregnant respondents who differ in terms of three domains: pregnancy desires, intimate relationships, and contraceptive use. I will also compare pregnant and non- pregnant respondents who match in terms of these domains, to generate and evaluate new hypotheses that do not focus on these domains. Finally, I will use these analyses to further explicate and expand the TDIB theoretical framework and disseminate it more widely to demographers.

NIH Research Projects · FY 2026 · 2023-05

Project Summary The per-generation de novo mutation rate spans more than an order of magnitude among eukaryotes and at least a two-fold range among primates. While many studies focus on those mutations that arise during gametogenesis, experiments have shown that the rate of mutation is higher during embryogenesis, and that half of all mutations are already present in the germline at puberty. In this proposal we carry out multiple experiments using pedigrees from the model nonhuman primate, rhesus macaques (Macaca mulatta), to quantify the number and types of mutations produced during embryogenesis and gametogenesis. First, we detect embryogenic mutations in parents by sequencing the genomes of multiple of their offspring. Transmitted mutations produced during parental embryogenesis will appear mosaically, enabling us to detect them in some, but not all, offspring. By sequencing multiple siblings within a family, we will be able to measure the embryogenic mutation rate in an unbiased manner. Second, we will quantify male germline mosaicism with pooled sperm sequencing. The frequency of mosaic mutations reveals the timing of their genesis in development. By deeply sequencing sperm collected from individual sires of the same pedigrees, we will quantify the frequency of embryogenic mutations and they stage in which they arose. In addition, pooled sequencing of sperm from offspring will help to estimate the fraction of embryogenic mutations missed by pedigree studies. Both of these experiments together will lead to more accurate estimates of the mutation rate during embryogenesis. Third, we will uncover early embryogenic mutations in the offspring via paired comparisons with placenta. Mutations arising very early in an individual's development will appear in almost all cells. To quantify these early embryogenic mutations, we will sequence placentas from the same sequenced offspring. The placenta separates from the lineage leading to the embryo shortly after fertilization. Comparing mutations found in the placenta with those from blood samples of the developed embryo will allow us to delineate the timing of mutations. This experiment has many of the same advantages as studies of monozygotic twins, but with tissues that are readily available from a singleton birth.

NIH Research Projects · FY 2026 · 2023-05

Project Summary/Abstract Proteins are the molecular machines of a cell that orchestrate virtually all processes. Like a macroscopic machine, their function requires that they move to adopt different states. Thus, a modern view of protein biophysics has expanded from the structure-function paradigm to include dynamics - population of ensembles of protein states (conformational heterogeneity) and their interconversion. Fully delineating the dynamics that underlie function is however complicated by the immense complexity of proteins, due to both their large size with spatial heterogeneity of their chemistry and the broad timescales over which states may interconvert, ranging from large-scale processes such as aggregation that occur over days to years to the picosecond fluctuations of side chains and solvent. Among these scales, the local small-scale changes in proteins that involve rapidly interconverting states are perhaps among the most challenging to characterize and least well understood. However, such motions are argued to be central to many aspects of protein function, such as main contributors to the entropy of reactions, allosteric communication within domains, catalytic and binding specificity, et al. This research program is directed at developing rigorous methodologies to advance understanding of fundamental protein biophysics in important biological processes. We are developing infrared (IR) spectroscopy as an approach with inherently high spatial and temporal resolution for accessing all involved conformational ensembles and dynamics. By incorporating vibrational groups with frequencies within a transparent window of protein IR spectra we avoid the complexity of spectral congestion to enable inspection of single vibrational modes at local sites anywhere throughout proteins. We are combining modern approaches in biochemistry for selective labeling with state-of-the-art methods in multidimensional spectroscopy to provide rigorous analysis of frequency heterogeneity, coupling, and dynamics. The application and development of new biochemical and spectroscopic methods should elucidate the biophysical foundations of protein function with unprecedented detail, providing information with promise to buttress advances in broad areas of biology and medicine. In addition, through execution of this project, undergraduate, graduate, and postdoctoral researchers will be broadly trained in multidisciplinary science, strengthening the nation’s scientific workforce.

NIH Research Projects · FY 2026 · 2023-02

Abstract Nociception, the sensory mechanism that allows animals to sense and avoid potentially tissue-damaging stimuli, is critical for survival across species. Nociceptors are specialized neurons that detect and respond to potentially damaging factors through the expression of molecules that function to detect and signal the presence of potential harm. The primary focus of the research in my laboratory has been the study of nociception, however, we have also explored mechanisms underlying the sense of gentle touch, and most recently, the sense of proprioception. We have found that each of these senses relies on specific classes of non-ciliated multidendritic sensory neurons. The multidendritic neurons that are dedicated to a specific sensory modality are morphologically distinct from one another, and they have diverse patterns of gene expression. We seek to define how these distinct morphologies relate to function, and how ensembles of genes expressed within the distinct morphological types of neurons control sensory pathways of somatosensation with a primary focus on nociception. The overarching theme of our research program is understanding the molecular, cellular, and circuit, mechanisms underlying nociception. The primary goal of our research program in the next 5 years will be to further characterize the function of the nociception genes that we have identified using forward genetics. Our focus is on evolutionarily conserved genes that are not already understood to play important roles in nociception. These studies provide the greatest impact in creating new knowledge. In addition, we plan to begin to understand the neuronal network for nociception behavior.

NIH Research Projects · FY 2025 · 2023-01

PROJECT SUMMARY Hypertension is a disease defined as blood pressure that is greater than 130/80mmHg. Hypertension contributes significantly to cardiovascular disease morbidity and mortality. While the importance of blood pressure control has become abundantly clear, we are still far from understanding the true etiology of hypertension. In recent years, inflammation was determined to play a causal role in hypertension. Specifically, immune cells invade target organs during the course of the disease and release cytokines that cause end- organ damage. Several studies have determined antigen presentation by dendritic cells (DCs) and monocytes is important for initiation of hypertension. In addition, pro-inflammatory T cells perpetuate the disease. Anti- inflammatory T regulatory cells (Treg) can control the hypertensive response. Interestingly, evidence suggests that long-lasting use of cyclooxygenase inhibitors, which prevent metabolism of arachidonic acid (AA) to prostaglandins and thromboxane, increases blood pressure. Prostaglandin I2 (PGI2) is an AA metabolite that our laboratory has determined has immunomodulatory effects. Our group has demonstrated that PGI2 acts to directly inhibit the functionality of pro-inflammatory DCs and CD4+ Th1 and Th2 cells, while promoting the function of tolerogenic DCs. However, the impact of PGI2 on the functionality of immune cells in hypertension is unknown. A previous study has demonstrated that mice deficient in the receptor for PGI2, IP, develop elevated blood pressure in response to high salt diet, suggesting that PGI2 signaling is important for controlling blood pressure elevation in response to stimuli. Further, I have preliminary data which suggests that PGI2 controls the inflammatory response to hypertensive stimuli. Specifically, mice deficient in IP have increased infiltration of T cells into their aortas compared to wild-type (WT) mice in response to angiotensin II (Ang II). In addition, infusion of the PGI2 analog treprostinil during the course of Ang II infusion prevents the infiltration of T cells, monocytes/macrophages and DCs into the aorta of WT mice compared to WT mice that received Ang II and the vehicle for treprostinil. Thus, these recent studies and my preliminary data lead me to hypothesize that PGI2 promotes anti-inflammatory responses during hypertension. To test this hypothesis we will use mouse models of hypertension and primary cells from normotensive and hypertensive mice and humans to: Aim 1 (K99): Test the hypothesis that PGI2 promotes Treg function and stability during hypertension, thereby counteracting pro-inflammatory subsets of T cells; and Aim 2 (R00): Test the hypothesis that PGI2 restrains pro-inflammatory DC and promotes tolerogenic DC function during hypertension. Determining the mechanisms by which PGI2 controls the immune response to hypertension will greatly advance the field and result in new therapeutic directions for the treatment of hypertension. These proposed studies, along with my proposed career development plan, will provide a foundation for my career as an independent investigator in an outstanding environment.

NIH Research Projects · FY 2025 · 2022-09

Summary Advanced single-cell sequencing techniques have enabled us to infer gene regulation at the single-cell level. We propose to develop computational methods to overcome obstacles for elucidating gene regulation at single-cell resolution. We first present an alignment-based computational framework to integrate single-cell multi-omics measurements. The alignment-based computational framework can effectively handle the cell type imbalance problem and is more robust to hyperparameters. Furthermore, we incorporate the integrated single-cell multi-omics measurements and advanced machine learning algorithms to infer transcriptional regulation, distal regulatory elements, and post-transcriptional regulation at the single-cell level. We expect to develop computational methods to better understand gene regulation, which would lay a solid foundation for disease diagnosis, treatment, and prevention.

NIH Research Projects · FY 2024 · 2022-09

PROJECT SUMMARY Dementia due to Alzheimer’s disease (AD) is a leading public health concern in the US with enormous care costs and no effective pharmacotherapy despite multiple clinical trials. Multiple studies have shown mild cognitive impairment (MCI) to be a precursor risk for AD and to be more amenable to intervention. While preclinical studies have shown that directly modulating activity in the dorsolateral prefrontal cortex (DLPFC) using non-invasive brain stimulation techniques, such as transcranial magnetic stimulation (TMS), can modulate cognitive function in healthy older adults, there is little evidence of reliable efficacy in MCI. We posit three reasons for this lack of efficacy. First, there is no established means of estimating a reliable dose–response relationship between TMS intensity and brain activity in the site associated with memory function (e.g., DLPFC); such a relationship is a fundamental means of titrating individualized responses to neuromodulation. Second, standard TMS protocols fail to capture the dynamic nature of cognitive states and the reaction of endogenous brain states to exogenous neuromodulation. By understanding the dynamic changes associated with a target brain state, it should be possible to manipulate DLPFC dynamically in a manner that enhances cognition. Third, no studies using TMS in AD-related populations have accounted for the influence of cerebrovascular disease in the response to TMS. We propose to address these shortcomings by using closed-loop TMS, based on individualized brain networks to establish parameters that can control brain states during memory functioning in healthy aging and MCI. To achieve this goal, we will study network activation and neural oscillatory mechanisms underlying the network that regulates working memory (WM), a cognition function with a reliable PFC-based network characterization. We will then target this network using closed-loop TMS to the PFC and measure the impact on WM performance and task-based neural activity. This approach, which builds on our existing K01, U01, and RF1 awards, uses concurrent TMS-fMRI to identify dose–response relationships in the working memory network, which can be used to identify neuroplasticity and optimize targeting for TMS (Aim 1). Next, we apply novel closed-loop TMS to perturb this network using temporally-precise TMS-EEG (Aim 2), optimizing the encoding of memory by minimizing endogenous alpha oscillations. Lastly, we will integrate information collected via fMRI and EEG into a single computational framework in order to model spatiotemporal dynamics of the global brain network, accounting for the influence of both connectivity and cerebrovascular pathology in predicting the success of the TMS-related response in our MCI cohort (Aim 3). In sum, the project will use cutting-edge brain stimulation and network modeling techniques to enhance WM in healthy older adults and MCI and will provide a demonstration of the value of closed-loop, network-guided TMS for future clinical applications.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY In eukaryotes, ribonucleotides are frequently incorporated into DNA during replication (1 ribonucleotide per every 1000-5000 deoxyribonucleotides). Canonically, RNase H2 is the protein responsible for the removal of these embedded ribonucleotides. However, it has been recently shown that topoisomerase 1 (Top1) also has its own genomic ribonucleotide processing activity. When this processing occurs in specific short repeat sequences, it can lead to 2-7 bp deletions. These deletions are the result of two sequential nicks by Top1 that releases a small single-stranded DNA segment and is then followed by a strand slippage and ligation across the formed gap. These deletions have been shown to be biased towards the non-transcribed strand (NTS) of highly transcribed genes, but the reasoning for this strand specificity is yet to be elucidated. With the help of our recent preliminary data, we propose that this strand specificity for Top1 activity is due to the formation of DNA topological structures, specifically negative supercoils, behind the RNA polymerase that bias the initial cleavage by Top1. This would re-define the way we think about Top1-mediated DNA relaxation by limiting the cleavage of Top1 mainly towards the NTS during transcription. This limitation also allowed us to hypothesize about a possible biological implication for Top1-catalyzed excision of ribonucleotides. When Top1 cleaves a ribonucleotide, it can generate a unique nick lesion known as 2’,3’-cyclic phosphate (CP). The bias of Top1 cleavage at the NTS and the formation of CPs lead us to hypothesize that this transient nick lesion could serve as a way of continually relieving transcriptional torsional stress, as CPs would be forming at a strand that would potentially not interfere with transcription, unlike nicks at the transcribing strand. We plan to investigate this by looking at mRNA expression after depleting genomic ribonucleotides in yeast. This investigation will provide us with potential roles of ribonucleotide incorporation in eukaryotes. Additionally, the processing of genomic ribonucleotides by Top1 produces PARP-trapping lesions, a chemotherapeutic target for BRCA1/BRCA2 deficient tumors. I will look at the interactions that could lead to the trapping of PARP1 after ribonucleotide cleavage by Top1 and its link to the ability of PARP1 to regulate CP formation (identified recently by us and shown in our preliminary data). The presence of either CPs or adducts between DNA and Top1 are likely candidates for the recruitment of PARP1. Overall, our findings will help clarify the relevance of ribonucleotide incorporation for transcriptional regulation by providing insight into a novel mechanism of DNA relaxation by Top1 through the processing of those genomic ribonucleotides. Our proposal will also aim to describe the regulation of CP formation by PARP1, and the physiological relevance of the interaction between Top1, PARP1, and genomic ribonucleotides.

NIH Research Projects · FY 2024 · 2022-09

PROJECT SUMMARY/ABSTRACT Among patients with Alzheimer’s disease and related dementias (ADRD) and their informal caregivers, behavioral and psychological symptoms of dementia (BPSD) are a critical need requiring scalable, evidence- based intervention. As many as 97% of patients with ADRD will ultimately experience BPSD, yet they are poorly managed and remain the top source of caregiver burden. Technology may be a solution; indeed, the National Institute on Aging and others demand mobile technology-based behavioral interventions to support informal caregivers of patients with ADRD. Systematic reviews and market analyses of existing mobile technologies or “apps” demonstrate promise but critical limitations: lack of scientific foundation and evidence of efficacy; missing features and functions; and low to moderate quality. Our interdisciplinary team followed the NIH Stage Model for Behavioral Intervention Development to: 1) establish an evidence-based intervention model for BPSD management (NIH Model Stage 0); 2) apply user- centered design to embed this evidence-based model into Brain CareNotes, a mobile telehealth app (NIH Model Stage IA); and 3) conduct I-CARE, a set-up pilot study that established the feasibility and potential efficacy of Brain CareNotes (NIH Model Stage IB-II). The pilot study demonstrated that at the 6-month endpoint, Brain CareNotes reduced informal caregiver burden and reduced BPSD. Here we propose I-CARE 2, a Stage III randomized clinical trial (RCT), as the next step in the NIH Stage Model. I-CARE 2 will evaluate the real-world efficacy of Brain CareNotes on the primary outcomes of informal caregiver burden and BPSD at 12 months. We plan to enroll N=160 community-dwelling, English-speaking informal caregivers of patients with ADRD, across the state of Indiana. Informal caregivers will be randomized (stratified by sex and race) to 12 months of Brain CareNotes (n=80) or Attention Control education-only app (Dementia Guide Expert) (n=80). Follow-up will occur at 12 months, with additional assessments at 6 months to test for early effects. We will test primary hypotheses that, relative to Attention Control, informal caregivers randomized to Brain CareNotes will have: (H1) lower caregiver burden as measured by the Caregiver Distress sub-score on the Neuropsychiatric Inventory (NPI); and (H2) lower BPSD as measured by the NPI Total Score. Secondary hypotheses will be tested comparing groups on (H3) depressive symptoms as measured by the Patient Health Questionnaire (PHQ)-9 and (H4) acute care utilization as determined by the number of hospital and emergency room visits captured in the statewide regional health information exchange. If successful, this NIH Stage III RCT study will yield evidence of the efficacy of a highly scalable non- pharmacological intervention for BPSD, one of the most burdensome aspects of ADRD care. If our caregiver- facing mobile telehealth app is efficacious in real-world settings, subsequent Stage IV-V effectiveness and implementation research efforts can help relieve the critical public health burden of ADRD.

NIH Research Projects · FY 2026 · 2022-09

PROJECT SUMMARY The goal of this project is to identify epigenetic pathways underlying the effects of social connectedness on aging-related morbidity and mortality. We propose to examine the potential pathogenic and protective consequences of individuals’ habitual patterns of interaction with members of their egocentric, or personal, social networks (i.e., their social signatures). Meta- analyses have identified beneficial effects of social connectedness on all-cause mortality that are robust and larger in magnitude than the adverse effects associated with smoking, alcohol consumption, sedentary lifestyle, and obesity. However, the biological processes underlying these patterns have received insufficient empirical study relative to behavioral mechanisms, and little attention has focused on longer-term physiological or pathogenic mechanisms. To address these gaps, we examine the implications of social signatures for DNA methylation (DNAm), a biomarker of accelerated biological aging and an early predictor of later-life onset of diabetes, cardiovascular disease (CVD), stroke, dementia, and other complex diseases. We leverage a large, omnibus health survey, the Person to Person (P2P) Health Interview Study (N≈3,050), administered face-to-face to a stratified household probability sample. As part of this effort, DNA was extracted from saliva samples (n≈2,600) for future analysis. We address the following specific aims: Aim 1 examines associations between social signatures and DNA methylation-based profiles, including epigenetic age acceleration and polyepigenetic scores. Aim 2 assesses whether social signatures attenuate documented associations between early life, mid-life, and chronic exposures to stressful conditions and DNA methylation-based profiles. Aim 3 explores associations between social signatures and targeted DNA methylation sites documented to affect risk for obesity, inflammation, Alzheimer’s disease, and other specific complex diseases associated with aging. The proposed study is interdisciplinary, combines leading-edge methods from the social and biomedical sciences, and leverages considerable existing data and research infrastructure. By increasing our understanding of the specific biological pathways underlying the effects of social connectedness that unfold over the life course, this study could help identify novel targets for earlier social or biological intervention in aging-related complex diseases.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY/ABSTRACT Among patients with Alzheimer’s disease and related dementias (ADRD) and their informal caregivers, behavioral and psychological symptoms of dementia (BPSD) are a critical need requiring scalable, evidence- based intervention. As many as 97% of patients with ADRD will ultimately experience BPSD, yet they are poorly managed and remain the top source of caregiver burden. Technology may be a solution; indeed, the National Institute on Aging and others demand mobile technology-based behavioral interventions to support informal caregivers of patients with ADRD. Systematic reviews and market analyses of existing mobile technologies or “apps” demonstrate promise but critical limitations: lack of scientific foundation and evidence of efficacy; missing features and functions; and low to moderate quality. Our interdisciplinary team followed the NIH Stage Model for Behavioral Intervention Development to: 1) establish an evidence-based intervention model for BPSD management (NIH Model Stage 0); 2) apply user- centered design to embed this evidence-based model into Brain CareNotes, a mobile telehealth app (NIH Model Stage IA); and 3) conduct I-CARE, a set-up pilot study that established the feasibility and potential efficacy of Brain CareNotes (NIH Model Stage IB-II). The pilot study demonstrated that at the 6-month endpoint, Brain CareNotes reduced informal caregiver burden and reduced BPSD. Here we propose I-CARE 2, a Stage III randomized clinical trial (RCT), as the next step in the NIH Stage Model. I-CARE 2 will evaluate the real-world efficacy of Brain CareNotes on the primary outcomes of informal caregiver burden and BPSD at 12 months. We plan to enroll N=160 community-dwelling, English-speaking informal caregivers of patients with ADRD, across the state of Indiana. Informal caregivers will be randomized (stratified by sex and race) to 12 months of Brain CareNotes (n=80) or Attention Control education-only app (Dementia Guide Expert) (n=80). Follow-up will occur at 12 months, with additional assessments at 6 months to test for early effects. We will test primary hypotheses that, relative to Attention Control, informal caregivers randomized to Brain CareNotes will have: (H1) lower caregiver burden as measured by the Caregiver Distress sub-score on the Neuropsychiatric Inventory (NPI); and (H2) lower BPSD as measured by the NPI Total Score. Secondary hypotheses will be tested comparing groups on (H3) depressive symptoms as measured by the Patient Health Questionnaire (PHQ)-9 and (H4) acute care utilization as determined by the number of hospital and emergency room visits captured in the statewide regional health information exchange. If successful, this NIH Stage III RCT study will yield evidence of the efficacy of a highly scalable non- pharmacological intervention for BPSD, one of the most burdensome aspects of ADRD care. If our caregiver- facing mobile telehealth app is efficacious in real-world settings, subsequent Stage IV-V effectiveness and implementation research efforts can help relieve the critical public health burden of ADRD.

NIH Research Projects · FY 2024 · 2022-08

PROJECT SUMMARY The complex events of gametogenesis and early embryonic development require tight regulation to ensure proper reproduction and healthy offspring. To achieve this regulation while maintaining the plasticity necessary for embryogenesis, germ cells rely heavily on RNA-level regulation of gene expression. RNA regulation plays a number of important roles in germ cell development and maintenance, including maintenance of germ cell- specific gene programs, protection of the germline genome from foreign or damaging sequences, and translational repression and storage of maternal transcripts necessary for early embryonic development prior to the onset of zygotic transcription. A diverse network of RNA binding proteins and small RNA pathways govern this crucial RNA regulation, many of which have overlapping or redundant roles to ensure proper regulatory fine-tuning. Adenosine DeAminases that act on RNA (ADARs), are RNA binding proteins that can influence the cellular fate of transcripts either by binding to RNA or by catalyzing the deamination of Adenosine to Inosine, known as A-to-I RNA editing. ADARs are present in all animals and have been shown to play important roles in development, innate immunity, and oncogenesis. While the roles of ADARs in germ cells has not been explored, my own preliminary data suggests ADARs are highly expressed in the germline and can influence hundreds of germline transcripts. Additionally, previous work from other labs suggests that ADARs act along with small RNA pathways to perform functions necessary for proper reproduction. As such, I hypothesize that ADARs play a role in the extensive RNA regulation that takes place in the germline. My preliminary experiments investigating the effects of ADARs on germline transcripts suggest that ADARs play a role on regulating ribosome biogenesis. Additionally, I have found that many germline-edited transcripts are known maternal transcripts, which are translationally repressed throughout the germline and stored for loading into the embryo. For these reasons, I hypothesize that ADARs play a role in translational repression that occurs throughout the germline during gametogenesis. To address this hypothesis, I will expand upon my investigation of the effects of ADARs on germline transcripts as well as interactions with other germline RNA regulators (Aim 1). I will assess the impact of ADARs on germline ribosome biogenesis and translational activity (Aim 2). Finally, I will investigate the impact of ADAR editing on maternally loaded transcripts and early embryonic RNA populations (Aim 3). Through these experiments, I will gain an understanding of the effects of ADARs on germline transcripts, and a bigger-picture understanding of their role in germ cell development and maintenance, early embryonic development, and reproduction in general. This work will contribute to our understanding of the complex processes that facilitate successful and healthy reproduction.

NIH Research Projects · FY 2026 · 2022-08

PROJECT SUMMARY Social connectedness is critical for promoting healthy aging, including delaying the onset of Alzheimer’s disease (AD). Developing and maintaining social relationships relies on social cognitive function – the process by which people understand, store, and apply information about others. Social cognitive decline is a hallmark feature of healthy aging that has been implicated in exacerbating the onset and progression of AD. Thus, understanding the mechanisms underlying age-related social cognitive deficits is essential for ultimately improving the clinical course of AD. Neuroscience is uniquely suited to identify these mechanisms because the brain regions underlying social behavior have been well-characterized. However, the limited work in this domain has relied on narrowly defined measures of brain activity and impoverished stimuli, which neglect the complex and dynamic nature of brain function and of social interactions. The current proposal thus applies cutting-edge computational methods from the field of network neuroscience to social cognitive aging to examine how age-related changes in brain networks affect dynamic social cognitive processes. Specifically, we focus on the default network – a collection of brain regions disproportionately targeted by AD that also support social cognition. In Aim 1, 50 cognitively healthy older adults (ages 65+) and 50 young adults (ages 18-35) complete the Reading the Mind in the Eyes and the False belief tasks, two well-validated experimental measures of social cognition, while undergoing functional magnetic resonance imaging (fMRI). Using a novel computational approach developed by the research team, we will jointly model brain activity and connectivity dynamics in the default network to discover brain regions and interconnected systems that predict age-related social cognitive deficits. Aim 2 then determines how default network connectivity reorganizes dynamically (network stability) across variable task states to decode complex and dynamic social cognition. Here, 50 healthy older and 50 young adults will undergo fMRI while viewing a film depicting complex social interactions. We will generate connectivity matrices for different task/cognitive states to identify stable/flexible patterns of connectivity within individual default networks as well as across brain networks, ultimately relating them to social cognitive deficits. Finally, Aim 3 uses an independent sample of 50 older adults from the Indiana Alzheimer’s Disease Center who have undergone fMRI. These individuals are high-risk for AD or have been diagnosed with Mild Cognitive Impairment or AD. We will apply the simultaneous neural models and network stability analyses from the prior aims to identify the network properties in the default network that are most strongly associated with disease state. The proposed study combines cutting-edge network neuroscience methods with social cognitive aging to advance our understanding of healthy aging and AD. Ultimately this work will transform our understanding of the mechanisms by which healthy aging and AD disrupt social cognitive function.

NIH Research Projects · FY 2025 · 2022-08

Many agencies within the Department of Health and Human Services, including the Centers for Medicare and Medicaid Service (CMS) and the National Institutes of Health (NIH), have identified (Alzheimer’s Disease and related dementias (ADRD) as a top research priority. This is driven by the high burden of ADRD on patients and society. In 2020, the estimated societal cost of ADRD was more than $300 billion and the projected annual economic cost of ADRD will exceed $1,500 billion by 2050. To address this, the National Institute on Aging calls for the development of short courses on interdisciplinary behavioral and social sciences research on Alzheimer’s Disease and related dementias to improve the skills of the ADRD workforce in treating this disease (RFA-AG-22-010). In response to this call, scientists at Indiana University (IU) propose to launch the Agile Nudge University program. The aims of the program are to establish a network of highly engaged scientists who specialize in treatment and research for Alzheimer’s Disease and related dementias and to develop virtual curriculum to train an ADRD research workforce. The expert team of ADRD scientists at IU have been developing curriculum in the emerging field of Agile Science for the past ten years, equipping researchers and healthcare leaders with tools, adaptive processes, and agile strategies for designing, implementing, and spreading sustainable ADRD solutions that leverage behavior change principles. This has prepared Indiana University to be the Agile Nudge University program’s hub to deliver training for skills development in Agile Innovation, Agile Implementation, and Agile Diffusion of behavioral nudges with the main goal of the program of improving ADRD care. The program will offer comprehensive interdisciplinary mentoring and collaboration opportunities for graduate students, postdoctoral fellows, and early-career, midcareer, and senior faculty interested in ADRD research. It will also provide an online platform, supporting an open-source online library of individual tested nudges and general theory-based nudge strategies, group-based problem-solving sessions. The high costs of treating Alzheimer’s disease and the costs incurred by patients and caregivers, both tangible and intangible, are a major threat to public health and the US economy. Training the ADRD workforce in the effective design and implementation of interventions will bridge the gap between the bookshelf and real-world application within the healthcare system.

NIH Research Projects · FY 2025 · 2022-08

Abstract Text The Mapping Component at Indiana University (MC-IU) will develop and implement at scale a socio-technical infrastructure that combines human expertise and machine learning algorithms to construct, visualize, and use the Human Reference Atlas (HRA). It will continue to lead the construction of ASCT+B tables (expert-curated, connected lists of anatomical structures, cell types, plus biomarkers based on standard ontologies) and associated reference object libraries that together define the evolving Human Reference Atlas. We will collaborate closely with the other mapping component to incorporate cell-by-gene references (e.g., Azimuth) and other cell-by-biomarker references and 3D reference objects as they become available. We will work with the HIVE and other teams to link the atlas to experimental data and scholarly paper evidence. We will work closely with 15 other international consortia to ensure the HRA meets user needs and supports driving use cases that advance biomedical research and clinical practice. In close collaboration with the HIVE and tissue data generating teams in HuBMAP and beyond, we will define and incrementally extend data formats and ontologies for querying, integrating, and sharing HRA data. We will incorporate modern machine learning and human-in-the-loop approaches to accelerate the pace at which raw tissue imaging data is converted into annotated and segmented tissue maps. Advanced spatial management will be used to keep track of millions of cells derived in tissue data, to support spatial registration of new tissue, and to enable efficient spatial queries and exploration in the HRA user interfaces. We will develop a vasculature-based common coordinate system to better capture human diversity and develop computational models of functional tissue units to link anatomical structure to function.

NIH Research Projects · FY 2026 · 2022-05

PROJECT SUMMARY / ABSTRACT Cannabis use continues to be high among adolescents and is increasing in young adults. This is a significant public health issue as heavy cannabis use during this period is linked to an increased risk for developing affective, addictive, or psychotic disorders later in life. Adolescence and early adulthood are also when the prefrontal cortex (PFC), which plays a key role in executive function and working memory, is maturing. Interestingly, psychiatric disorders seen following early cannabis use often involve the PFC and deficits in executive function are common in these disorders. This suggests that adolescent cannabis use disrupts PFC maturation, impairing working memory/executive function and increasing risk for later psychiatric disorders. This hypothesis is supported by functional imaging studies of individuals who heavily used cannabis during adolescence that have identified defects in functional connectivity between PFC and several brain regions. Thus, cannabis use may cause miswiring of PFC circuits, increasing the risk for psychiatric disorders. To better understand the consequences and mechanisms of cannabis use during adolescence and early adulthood, we model this process in rodents by adolescent administration of Δ-9-tetrahydrocannabinol (THC), the primary intoxicating component of cannabis. These studies robustly demonstrate enduring deficits in PFC- mediated behaviors following adolescent THC that are lacking if similar doses of THC are given to adults, emphasizing a specific window of vulnerability. Our preliminary data investigating potential mechanisms have identified three, likely-interrelated processes. The first is that adolescent THC treatment decreases projections from the mediodorsal thalamus to the medial PFC (mPFC). The second is that adolescent THC treatment causes neuroinflammation, including increased IL-6 and activated microglia. The third is that co-treatment with cannabidiol prevents the behavioral and neuroinflammatory effects of adolescent THC. In the proposed studies we will investigate the mechanisms underlying these findings and evaluate mechanism-based potential therapies to reverse the behavioral and cognitive abnormalities caused by adolescent THC. We propose to develop a mechanistic understanding of the consequences of adolescent cannabis use by combining molecular, anatomical, electrophysiological, and behavioral approaches to complete three aims: Aim 1. Test the hypothesis that CB1 receptors are required for the detrimental effects of adolescent THC on working memory and evaluate potential therapies to reverse these deficits. Aim 2. Test the hypothesis that adolescent THC exposure reduces MD thalamus/mPFC connectivity to impair working memory. Aim 3. Test the hypothesis that adolescent THC activates microglia to excessively prune mPFC inputs from the MD thalamus to impair working memory.

NIH Research Projects · FY 2025 · 2022-04

Many current recommendations for dietary intake (DI) and physical activity (PA) to maintain optimal health and minimize risks for chronic health conditions, such as obesity and type 2 diabetes (T2D), are based on statistical analyses of data prone to measurement error, including those collected from self-reported questionnaires and wearable devices. Self-reported measures based on food frequency questionnaires are often used in DI assessments, however, they are prone to recall bias. Wearable devices enable the continuous monitoring of PA but generate complex functional data with poorly characterized systematic errors. Our work and that of others established that failure to account for measurement errors associated with scalar-valued covariates can lead to severely biased estimates, the impacts of function-valued covariates prone to complex heteroscedastic errors or mixtures of error-prone functional and scalar covariates are not well understood. Most work on functional data views the data as smooth, latent curves obtained at discrete time intervals with some random noise that is often regarded as a random process with mean zero and constant variance. By viewing this noise as homoscedastic and independent, potential serial correlations are ignored. However, our preliminary studies indicate that failure to account for these serial correlations in error-prone function-valued covariates can severely bias estimations. Additionally, while classification methods of PA patterns using device-based PA data have been proposed, there is limited work to correct for heteroscedastic measurement errors when classifying error- prone function-valued covariates, such as device-based PA data. With the increased availability of complex, massive high-dimensional function- and scalar-valued biomedical data, the need to correct for measurement error biases within these datasets to permit their accurate evaluation in various regression settings is critical. This project will address these current data limitations by developing novel statistical methods that correct for the complex mixtures of measurement errors associated with device-based PA and self-reported measures of DI applied to obesity and T2D research. Our primary objective is to investigate health outcome-related complex covariate relationships in various U.S. subpopulations by designing and applying statistical models that correct for error-prone DI and PA data biases. Aim 1: Identify latent groups of PA patterns based on device-based functional curves prone to heteroscedastic measurement errors and determine the association between identified PA patterns and T2D status, adjusting for PA biomarkers, age, sex, and race. Aim 2: Assess impacts of measurement error in DI and PA data on the quantile functions of FMI and BMI, adjusting T2D status, age, race, and sex. Aim 3: Construct generalized functional linear regression models with error-prone function- and scalar-valued covariates to evaluate the influence of PA and DI on T2D status. This project will overcome current analytic barriers to accurately evaluating the effects of DI and PA on obesity-related health outcomes.

NIH Research Projects · FY 2025 · 2022-04

PROJECT SUMMARY / ABSTRACT Urgent expansion of telehealth due to the COVID-19 pandemic may have consequences for evidence based primary care, including worsening disparities in cardiovascular disease (CVD) prevention. Implementing evidence based guidelines to reverse CVD risk would prevent more than 50% of annual deaths in middle-aged US adults but is already uneven. Guideline adherence can be improved by tailoring strategies to local barriers as in Dr. Ramly’s prior work that increased follow up on blood pressure and smoking with higher gains among Black patients. Yet tailoring is too expensive and burdensome to be used in practice and is even less feasible with the rapid telehealth expansion. There is a critical need for an alternative to tailoring to enable primary care clinics to rapidly adapt how they implement CVD guidelines after telehealth expansion to avoid worsening disparities. In engineering, configurable solutions make menus of options available to avoid expensive individual tailoring. This approach could enable clinics to use known strategies to address local barriers without engaging in an expert-led individual tailoring process. Preliminary qualitative work found many barriers to optimal care with telehealth that are modifiable with known strategies. Yet configurable solutions using known strategies have not been applied in health care despite the potential to reduce cost and reduce disparities by addressing local needs. Applying this approach will require multi-stakeholder design of a configurable toolkit informed by large clinical data and tested by a pragmatic clinical trial. Dr. Ramly’s long-term goal is to become a clinical investigator in primary care leading an independent research program to improve rapid implementation of evidence based care for chronic conditions. This 5-year K01 will fill his clinical investigation training gaps with mentored research and training in large clinical data, mixed methods, and pragmatic clinical trials. As a systems engineer faculty in a clinical department, Dr. Ramly is well prepared for a successful K01 to transition from engineer collaborator to independent clinical investigator. The overall objective of this proposal is to develop and pilot a configurable toolkit for CVD prevention. Four CVD quality metrics will be targeted: blood pressure control for patients with hypertension, and aspirin, statins, and smoking cessation for patients with coronary artery disease. The specific aims are to: 1) characterize barriers to implementation of CVD guidelines in primary care after telehealth expansion, 2) develop a configurable toolkit of strategies to address local barriers, and 3) pilot test the toolkit to assess reach, effectiveness, adoption, implementation, and maintenance, including subgroup differences. Expected outcomes are an intervention addressing a critical gap in evidence based care after telehealth expansion, with preliminary data for an AHRQ R18 trial. Dr. Ramly will become an independent clinical investigator building on prior expertise in engineering and implementation science. His current and future research aims will advance AHRQ’s mission by focusing on AHRQ-relevant priority populations (chronic conditions, older adults), problem (heart health) and emphasis (primary care).

NIH Research Projects · FY 2025 · 2022-03

Project Abstract Sport-related concussion (SRC) is a significant public health problem resulting in over 200,000 annual trips to the Emergency Department (ED) in the United States with as many as 3.8 million SRCs occurring annually. From a biomechanical standpoint, the concussion mechanism includes head impact resulting in high magnitude head rotational accelerations. Human studies measuring the accelerations associated with concussive head impacts developed injury risk curves that can be extremely useful from the clinical and safety perspectives. However, recent literature has shown that acceleration magnitudes associated with concussive impacts are extremely variable and not necessarily distinct from the routinely sustained head impact magnitudes. Mounting evidence from human studies has demonstrated that repetitive head impact exposure (HIE) may contribute to decreased SRC tolerance in contact sport athletes. Studies focused on quantifying the relationship between the HIE and incident concussion have been underpowered, as there were limited number of concussions occurring during the observation period. We will utilize the data from the NCAA-DoD Concussion Assessment, Research and Education Consortium (CARE) Head Impact Measurement Core, the largest and most comprehensive study of SRC and repetitive HIE to date, and data from Project Head-to-Head 2 (PHTH2), a large-scale study of SRC and HIE in both collegiate and high school athletes to: (1) determine the association of HIE to SRC occurrence and post-SRC recovery based on the frequency, number, recency, and severity of head impacts sustained in football activities; and (2) build a dynamic predictive algorithm of the SRC risk based on the HIE time series data obtained from the HIT System and other factors, including demographics, concussion history, impact characteristics, and network measures.

NIH Research Projects · FY 2026 · 2022-01

PROJECT SUMMARY/ABSTRACT Training: My research over the past eight years has focused primarily on elephant endocrinology, health, and aging. The work has shown that there are many similarities between elephants and humans (e.g., morbidities, life history, socialness, emotional complexity), and that leveraging information gathered by studying elephants may improve human health and aging. The proposed K01 career development training plan builds on that experience but identifies three areas that require additional training: (1) develop expertise in psychobiology and behavior, (2) enhance skills in aging science and methods, and (3) build skills in designing and implementing randomized experiments. Accordingly, we propose intensive topical mentorship, focused coursework, and contextual learning through the proposed research. This K01 will provide protected time to receive the needed training to enhance my expertise in these three areas and will propel me to becoming an independent research scientist focusing on healthy aging. Research: People who have endured adverse childhood experiences (ACEs) have increased risk of developing physical and psychological diseases later in life. They are 1.6 to 2.4 times more likely to develop obesity, cancer, heart disease, stroke, and diabetes as adults, and life expectancy is reduced by up to 20 years. Understanding how ACEs lead to disease in adulthood is important for developing interventions to interrupt disease progression. The proposed K01 attempts to address this need through the following objectives: to demonstrate the value of using the elephant as a model for human aging, and elucidating how early-life trauma influences an individual’s biological and social trajectory. Like humans, calves are highly reliant and bonded to their mother, and can suffer post-traumatic stress disorder after witnessing her killing. The poaching of random elephants for their tusks has provided a natural experiment to compare highly traumatized orphaned elephants with non-orphaned elephants in regard to their allostatic load, biological age, cognition, and disease susceptibility. This will be the first study that we are aware of that uses the elephant to understand the implications of early-life trauma, while also implementing a randomized experiment. The proposed K01 will not only demonstrate the value of the elephant to further understand human aging, but it will elucidate how early-life trauma influences an individual’s biological and social trajectory. Summary: Findings from this study will inform an R01 grant application to expand the study of early-life trauma and aging using the elephant. This K01 will develop my new expertise in psychobiology, aging, and randomized experiments. At the end of this award, I will be a leading independent scientist conducing innovative research in the field of aging.

NIH Research Projects · FY 2025 · 2021-09

Project Summary/Abstract: In the first year after birth, human sensitivity develops markedly to the fundamental features on which all higher- level vision depends: contrast, spatial scale, edge orientations, chromatic content. It is well known that this development is highly dependent on visual experience because disruptions in experience have significant and, in some cases, permanent consequences for vision from sensation to cognition. The field does not have, however, an empirical characterization of the low-level feature statistics of typical infant visual experience. This gap is critical because emerging studies of higher-level content indicate these statistical properties change with development and are dependent on the infant’s own changing internal visual biases and behaviors (eye movements, head movements, other body movements). These factors play a direct role in selecting and organizing the spatial structure of images projected to the eye. This project will collect and analyze the first- person visual experiences of 200 infants (50 each) at 2-3, 5-6, 8-9, and 11-12 months of age, plus a sample of 20 infants tested at all of those ages. The core hypothesis is that the statistics change systematically in a developmentally consistent sequence in the everyday lives of infants. The experiences are collected by infant head cameras worn for hours in the home and precision measures of eye and head movements in the laboratory. Analyses will quantify the spatial organization of fundamental low-level features in the collected images as a function of age, posture, activity, and specific contents. The project will also characterize the influence of refractive error and front-end visual immaturities on the images. The research will determine how infants’ behaviors influence the spatial organization of visual features in the input by analyzing the motion patterns in the at-home head-camera images and through direct measures of eye and head motion patterns in the laboratory. The research will provide the first characterization of the natural visual statistics of infant experience in the first year after birth and is expected to reveal specific developmental risk-points in those expected visual statistics.

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY Human visual object recognition is remarkable in its ability to recognize individual objects in challenging circumstances and to rapidly recognize even novel instances of tens of thousands of everyday categories. Although a great deal is known about these processes at maturity, very little is known about their development especially with respect to common everyday objects and the experiences that support robust object recognition and categorization. This gap is critical because object recognition and categorization support early word learning, physical problem solving, and the later learning of orthographies and mathematical symbols. This research projects focuses on visual object learning in 1 year old toddlers, a developmental period that at the front end of marked advances in visual object recognition and a period in which children with multiple risk factors begin to fall behind the normative developmental trajectory. The approach focuses on the properties of real- world visual experiences that support learning to recognize individual objects in challenging visual contexts and generalizing that learning to same category members. The method uses head-mounted eye-trackers to capture field-of-view images from 100 infants 17 to 22 months of age as they spontaneously interact and play with objects. Through active interactions with objects infants generates their own packets of visual data for learning. Multiple visual properties relevant to object perception will be algorithmically measured and quantified. Toddlers’ recognition of the actively-engaged object and a novel object from the same category will be measured in challenging benchmark contexts including clutter, occlusion, and different views. Category generalization will be measured in a name generalization task. Advanced statistics and machine learning will determine the visual properties of self-generated experiences that support infants object recognition and categorization. The research will provide the first characterization of the natural visual statistics of toddlers’ active interactions with objects and potentially transformative evidence that the developmental foundation for human prowess in visual object categorization lies not in experiences with many different instances of a single category, the standard assumption, but in active visual experiences with individual objects. Moreover, infants at risk for Developmental Language Delay and Autism show disruptions in early object name learning that have been recently linked to disruptions in visual learning about objects. The project includes preliminary analyses of infants at risk in preparation for the next step in the long-term research program.