imaging

Neuroinflammation in Cerebral Small Vessel Disease

Project Summary/Abstract Cerebral small vessel disease (cSVD) is a leading cause of vascular contributions to cognitive impairment and dementia (VCID), which is the 2nd leading cause of dementia and a significant contributor to Alzheimer’s disease (AD). Thus far, the underlying pathogenesis of cSVD is poorly understood. Several lines of evidence, including animal models, postmortem human brain pathology, and systemic inflammatory markers, demonstrated the damaging role of chronic neuroinflammation in cSVD. Direct evidence of neuroinflammation at the tissue level in patients with cSVD is still critically needed. The sphingosine-1-phosphate receptor 1 (S1PR1) regulates neuroinflammation through microglial and astrocyte activation and trafficking and has emerged as a promising target for neuroinflammation. In postmortem brains of patients with cSVD, we observed elevated S1PR1 expression and colocalization of S1PR1 with astrocytes and microglia. A novel 11C-CS1P1 PET radiotracer with high affinity and specificity targeting S1PR1 has been recently developed and validated in animal models and post-mortem human specimens. Under an FDA-approved eIND (IND 146548), we have successfully completed the safety and dosimetry study in healthy participants and performed preliminary studies in patients with cSVD. We found that 11C-CS1P1 PET uptake is significantly associated with WMH lesion burden in patients with cSVD after controlling for age, sex, race, vascular risk factors, and amyloid deposition. We hypothesize that 11C-CS1P1 PET uptake is a tissue-level biomarker of neuroinflammation to provide insight into cSVD severity, progression, and prognosis. We will 1) evaluate the relationship between 11C-CS1P1 PET uptake and cSVD neuroimaging abnormalities and cognitive impairment, 2) evaluate the test-retest repeatability and longitudinal evolution, and 3) determine whether 11C-CS1P1 PET uptake at baseline predict cSVD progression. The successful completion of this study will establish 11C-CS1P1 PET as an neuroinflammation imaging biomarker and investigate the role of neuroinflammation in cSVD pathogenesis and progression. It will lay a foundation for developing future therapies in modulating neuroinflammation.

Utilizing integrin-targeted PET imaging and therapeutics to predict and treat radiation-induced pulmonary fibrosis

Project Summary/Abstract. Lung cancer is the leading cause of cancer death in the US, with over 125,000 deaths annually. Radiation therapy (RT) is a critical component of curative lung cancer treatment for many patients. However, radiationinduced pulmonary fibrosis (RIPF) is a common side effect that carries a poor prognosis with limited treatment options. Up to 40% of patients with lung cancer who receive RT may experience RIPF. RIPF is a late effect of RT, typically occurring 3 or more months after treatment. The symptoms of RIPF can include shortness of breath, pleural effusions, decreased lung function, and respiratory failure. Cell surface integrin heterodimers play a key role in the pathogenesis of RIPF. In particular, the integrin αvβ6, which is expressed at a low level in the alveolar epithelium at baseline, is significantly upregulated upon RT damage. The key role of integrin αvβ6 in RIPF is illustrated by studies in which mice lacking integrin αvβ6, or treated with an αvβ6-blocking antibody, do not develop RIPF. Here, we propose to translate this mechanistic understanding of RIPF into novel approaches for monitoring and treating RIPF. We hypothesize that non-invasive αvβ6 PET imaging will be safe and can specifically bind to αvβ6 in patients with RIPF. Additionally, we hypothesize that a novel small-molecule integrin antagonist, IDL2965, can mitigate and treat RIPF in mice. In this project, we are utilizing mice to model RIPF, as mice develop RIPF that mimics human disease. In addition, cellular and in vitro models do not approximate the complex biology leading to the development of RIPF. Our data using [64Cu]Cu-DOTA-αvβ6-BP to detect early RIPF in mice are compelling in both single-fraction high-dose RT and lower dose-larger volume RT models (Lo et. al, IJROBP 2025). However, to progress to clinical trials in patients with cancer, we will obtain data to submit an Investigational New Drug (IND) application to the FDA. Importantly, we propose translating [64Cu]Cu-DOTA-αvβ6-BP PET imaging into patients with lung cancer, allowing us to better identify RIPF and develop a tool to determine the efficacy of IDL-2965 in future clinical studies. The specific aims of the proposal are: (1) Characterize the utility of [64Cu]Cu-DOTA-αvβ6-BP in mice with conventionally fractionated RT and identify circulating biomarkers of RIPF, and determine the in vivo toxicology of [64Cu]Cu-DOTA-αvβ6-BP to prepare and submit an exploratory Investigational New Drug (eIND) application to the FDA, (2) Conduct a first-in-human clinical trial of [64Cu]Cu-DOTA-αvβ6-BP to determine its safety and human dosimetry in patients with evidence of RIPF from computed tomography or in healthy controls, and (3) Determine the effect of integrin antagonism using IDL-2965 on mitigating RIPF in preclinical mouse models. The goals of this proposal are two-fold: (1) demonstrate safety and target specificity for [64Cu]Cu-DOTA-αvβ6-BP so that it can be used in future studies to identify RIPF and evaluate the efficacy of anti-fibrotic therapies, and 2) determine the ability of IDL-2965 to prevent RIPF in preclinical mouse models.

Multimodal computational models for early prediction of peritoneal recurrence in gastric cancer

ABSTRACT Gastric cancer represents a significant disease burden and is a leading cause of cancer-related deaths in the United States and globally. Approximately 80% of gastric cancer patients are diagnosed at an advanced stage, with the peritoneum being the most common site of relapse (peritoneal recurrence) after radical surgery. Nearly 50% of patients with advanced-stage gastric cancer develop peritoneal recurrence post-surgery, resulting in a median survival of only 3–6 months and a markedly reduced quality of life. Early peritoneal recurrence is primarily characterized by micro-metastasis, which traditional imaging techniques struggle to detect due to the small size of metastatic nodules. Predicting the likelihood and timing of peritoneal recurrence is crucial for identifying at- risk patients, enabling timely interventions that could improve survival rates and quality of life. Unfortunately, reliable predictive biomarkers and models for peritoneal recurrence in gastric cancer are lacking in clinical practice, highlighting an urgent need for innovative predictive tools. This proposal aims to develop and validate novel predictive models for early peritoneal recurrence in gastric cancer, leveraging advanced deep learning techniques and multimodal integration of clinical, radiological (CT), and histopathological (hematoxylin and eosin, H&E) data. In Aim 1, we will develop a rational approach for predicting peritoneal recurrence by creating a novel deep learning multimodal method guided by genomics knowledge. Additionally, we will integrate both deep learning-extracted features and traditional hand-crafted radiomics features with clinical data to improve prediction accuracy. Aim 2 focuses on developing a robust prediction model of peritoneal recurrence utilizing a pre-trained foundation model from large-scale H&E image data. Aim 3 will combine CT, H&E, and clinical data to further enhance predictive capabilities, employing an innovative cross-modal collaborative optimization approach for multimodal data integration. All models will be trained and internally validated using a retrospective cohort from Atrium Health Wake Forest Baptist Comprehensive Cancer Center and externally validated in two independent cohorts from additional institutions to ensure robustness across populations and imaging protocols. Additionally, we will compare our models with existing methods, including clinical staging and alternative fusion strategies. If successful, these models will enhance risk stratification and prediction of peritoneal recurrence in gastric cancer patients, significantly improving survival rates and quality of life by identifying those likely to develop peritoneal recurrence post-surgery and facilitating timely intervention. Furthermore, they can help avoid the risk of complications and extra medical costs associated with overtreatment. Since the information is derived from routinely examined CT, H&E and clinical data, they could be seamlessly integrated into current clinical workflows. The AI technology developed through this project has the potential to benefit underserved populations in low- resource settings and reduce healthcare disparities in the U.S.

Urothelial Resurfacing with Irreversible Electroporation for Adjuvant Therapy of Bladder Cancer

PROJECT SUMMARY Over 70% of bladder cancer (BCa) patients are diagnosed with early-stage and localized non-muscle invasive disease (NMIBC), yet achieving durable cancer-free survival remains a significant challenge. Most of these patients will experience local tumor recurrence within five years following standard of care (SoC) transurethral resection of bladder tumor (TURBT) and intravesical adjuvant chemo- or immunotherapy. Recurrence is driven by microscopic tumors and premalignant lesions dispersed within the urothelial layer that survive and escape these treatments. As TURBT effectively treats tumors visible on imaging, current research has predominantly focused on drugs and biologics for improving intravesical adjuvant therapy. In this proposal we pose the provocative question whether a TURBT-like ablative technique can be extended to debulk malignancy in the entire bladder and investigate the synergy with intravesical adjuvant therapy in improving outcomes. Our objective is to address this technology and knowledge gap by developing and validating whole bladder urothelial resurfacing (WBUR) using irreversible electroporation (IRE). During IRE, microsecond-long pulsed electric fields (PEF) are used to induce rapid cell death by catastrophic permeabilization of the cell membrane, without affecting the extracellular matrix (ECM) within the treated tissue. In prior work, we designed devices that utilized this unique mechanism of IRE for performing penetrative ablation in the ureter, bile duct and bronchus of swine while preserving lumen function. Our findings provided strong rationale for IRE being an ideal candidate for WBUR as alternate techniques such as thermal ablation or ionizing radiation must be performed with extreme care in the bladder to avoid perforation or fistula formation. In subsequent preliminary work we developed technology to demonstrate the feasibility and safety of WBUR with IRE in a rat model of BCa and scalability in human-sized swine bladder. In Aim 1, we will investigate the cancer treatment efficacy of combination WBUR and intravesical adjuvant therapy. In Aim 2, validate WBUR derived liquid biopsy for monitoring cancer status. In Aim 3, engineer PEF delivery strategy to enhance the safety and specificity of WBUR. The innovation of our proposed work is defined by developing whole bladder ablation as a debulking strategy and examining its synergy with SOC adjuvant therapy (Aim 1), enabled by new electrode paradigm and PEF delivery strategy (Aim 3), monitoring by an unconventional liquid biopsy approach (Aim 2). Our work can immediately aid the management of NMIBC patients who cannot undergo radical cystectomy, with future application as a cancer prevention strategy in high-risk patients. Success of individual aims will result in major contributions to the topics of IRE, BCa treatment and diagnosis.

Short-wave infrared Cerenkov imaging to better visualize targeted radiotherapy and diagnostic radiotracers

SUMMARY. The problem: Cerenkov luminescence (CL) imaging (CLI) is a new imaging method that utilizes light emitted during decay of radiotracers. CLI merges optical and nuclear imaging by utilizing affordable yet highly sensitive optical cameras with clinical radiotracers. It provides fast and cheap clinical optical imaging to explore radiotracer distribution in patients. While not tomographic, CLI systems have a lower price, smaller footprint and higher resolution than nuclear imaging scanners. Yet, due to the very low signal intensity of CL its versatility remains limited since CLI requires strict exclusion of ambient light with an enclosure. Therefore, CLI requires novel approaches to make clinical imaging more feasible. We hypothesized that we could explore the short-wave infrared (SWIR) part of CL to enable CLI under ambient light without enclosure, providing improved and facile CLI, particularly of isotopes used for therapy that cannot be imaged otherwise. SWIR imaging (900- 1300 nm) has almost no autofluorescence, absorption or scatter but provides significantly higher depth penetration, yielding images with higher contrast and resolution compared to the visible range. Since typical LEDs do not emit light beyond 850 nm, they do not interfere with the SWIR camera. We can therefore perform CLI in the SWIR range (SWIR-CLI) without the limiting light-tight box and under ambient LED light and also achieve better signal penetration and accuracy. We will investigate if SWIR-CLI can be used to monitor distribution of therapeutic isotopes for targeted radiotherapy (TRT), a fast-expanding field as highlighted by Novartis’ acquisition of Lutathera and Pluvicto for the price of $6 bn. These agents are targeting 177Lu as therapy to neuroendocrine and prostate cancers. For TRT α-emitting isotopes are particularly attractive due to the α- particle’s short path length with high linear energy transfer. However, α-emitters are very difficult to image with conventional equipment. The α-emitter could be swapped with an imaging isotope, but this can alter the agent’s biodistribution. The α-particle itself does not have sufficient energy to produce CL but several daughters in the decay chains of most α-emitters produce electrons with sufficient energy to create CL. We have already imaged the α-emitter 223Ra in patients and have recently shown that CLI of α-emitters in the SWIR is possible. SWIR- CLI could therefore provide a facile imaging approach for α-emitters. We will answer with our three independent Aims the following questions: (1) Can we image diagnostic isotopes with SWIR-CLI? (2) Can we image therapeutic emitters with SWIR-CLI? (3) Can we use SWIR-CLI to image patients undergoing PET and/or TRT? Animal studies will employ established mouse cancer models to optimize imaging parameters and validate findings, directly informing the co-clinical Aim 3 trial. By eliminating the requirement for a light-tight enclosure and enabling CLI under ambient light, SWIR-CLI represents a significant shift in the practical deployment of CLI rather than an incremental improvement. Our study will broaden the reach of CLI by enabling imaging under ambient lighting, unlocking innovative new opportunities for CLI (monitoring TRT) in research & clinical settings.

Delineating the role of TREM2 in chronic pancreatitis

PROJECT SUMMARY Chronic pancreatitis (CP) is a progressive digestive disorder characterized by persistent inflammation, irreversible fibrosis, and acinar cell damage. However, current treatment options remain limited, underscoring the need for effective, targeted therapeutic strategies through a deeper understanding of the disease microenvironment. Macrophages are pivotal players in the CP microenvironment, exhibiting dual roles in inflammation and tissue remodeling. A defining feature of macrophages is their remarkable phenotypic plasticity, enabling them to transition between pro-inflammatory and anti-inflammatory phenotypes. However, the specific macrophage phenotypes contributing to the immune imbalance in CP and their precise mechanisms of action remain poorly understood. TREM2 (Triggering Receptor Expressed on Myeloid cells 2), a transmembrane receptor of the immunoglobulin superfamily, has emerged as a critical modulator of tissue damage responses in multiple disease settings, though its function in CP remains unexplored. Our preliminary single-cell RNA-seq analyses of human CP tissues reveal an enrichment of inflammatory macrophages alongside a marked downregulation of TREM2 compared to non-diseased controls. This reduction in TREM2 correlates with marked increases in pro-inflammatory mediators, such as IL-1β and NF-κB, suggesting that TREM2 in macrophages contributes to maintaining homeostasis and restraining inflammatory signaling. Accordingly, diminished TREM2 expression appears to skew macrophages toward a pathologically hyper-inflammatory state. We hypothesize that loss of TREM2 disrupts the delicate balance among immune cells, fibroblasts, and acinar cells, fueling a self-reinforcing cycle of inflammation and fibrosis that exacerbates pancreatitis. To test this hypothesis, our R01 will leverage integrative single-cell transcriptomics, spatially resolved imaging, transgenic mouse models, functional organoid co-culture assays, and in vivo experiments to elucidate TREM2’s regulatory mechanisms in CP. This research aims to address two key scientific questions: (1) How does TREM2 suppress pro-inflammatory macrophage phenotypes and restrain IL-1β-induced inflammatory signaling? (2) How does the crosstalk among pro-inflammatory macrophages, fibroblasts, and acinar cells exacerbate the local inflammatory environment, leading to further pancreatic damage? Through this study, we aim to establish TREM2 as a pivotal inhibitory checkpoint in the NF-κB/NLRP3/IL-1β axis, preventing unchecked macrophage-driven inflammation, fibroblast activation, and further acinar cell damage. Successful completion of this project will deepen our mechanistic understanding of CP and identify new therapeutic strategies to mitigate fibrotic progression and preserve pancreatic function. Ultimately, these insights may guide the development of immunomodulatory treatments to attenuate CP severity, thereby transforming the clinical management of this devastating disorder.

Improved Surgical Visibility and Navigation during Endoscopic Treatment of Upper Tract Urothelial Carcinoma

Project Summary The importance of localizing and treating all upper tract urothelial cancer (UTUC) tumors during a renal sparing, endoscopic treatment is emphasized by the high risk of cancer progression from inadequate tumor treatment. Insufficient treatment necessitates kidney and ureteral removal (i.e., nephroureterectomy). Nephroureterectomy permanently compromises renal function, and increases morbidity and mortality, while negatively impacting a patient’s quality of life. In contrast, endoscopic treatment (i.e., using a laser to ablate only the tumors) improves long-term outcomes by sparing healthy kidney tissue. However, endoscopic treatment is underutilized compared to nephroureterectomy because it is difficult to accomplish. Successful endoscopic treatment is dependent on the surgeon’s ability to create a mental 3D map of the branched, intrarenal endoscopic anatomy intraoperatively from preoperative 2D imaging, which is extremely difficult. Since mental mapping relies on hand-eye coordination, memory, and spatial reasoning, it is inherently imprecise and its impact on accuracy and tumor treatment is dependent on the surgeon’s experience. To make matters worse, even when tumors are successfully visualized, the surgeon often cannot accurately assess the location of tumor margins or infer pathologic grade due to the limited field of view and depth of field (10mm and 6mm on average, respectively) of current scopes. The scopes only provide visualization of a small part of the surgical field at any instant. These inherent challenges prevent many surgeons from attempting endoscopic tumor treatment since incomplete treatment leads to a devastating, oncologic outcome. Our overall goal is to create an enhanced visualization and navigational system that makes endoscopic UTUC tumor treatment easier and more accurate for all surgeons, enabling wider utilization. Toward this goal, our specific objective in this proposal is to test the hypothesis that our system can make endoscopic UTUC surgery more accurate and efficient. To test this hypothesis, we propose three Specific Aims: Aim 1 involves the development of an automatic, real-time segmentation and grading system of UTUC tumors during endoscopic treatment. Aim 2 integrates a 3D navigational map of collecting system anatomy, which includes tumor and endoscope location, during endoscopic surgery. Aim 3 evaluates the system in patients, with zero risk to the human subjects. The endpoint of this R01 will be a fully validated enhanced visualization and navigational system for endoscopic UTUC surgery, which would provide the necessary experimental data towards a large-scale, multi-center clinical trial and future FDA approval. As our system would require only software integration to current endoscopic surgical cameras, all existing endoscopic surgical systems could in principle immediately benefit from the results of this project. In this way, we believe the success of our project will facilitate improved UTUC treatment and mitigate progression to a higher risk extirpative surgery.

Factors Driving Wear and Implant Failure in Total Shoulder Arthroplasty

Polyethylene (PE) wear and implant-related failure remain leading causes of revision in total shoulder arthroplasty (TSA), a procedure which now surpasses the growth rate of hip and knee arthroplasty. Both anatomic (aTSA) and reverse (rTSA) TSA outcomes are heavily influenced by complex interactions between rotator cuff function, scapular motion, implant design, and patient-specific loading—factors not adequately captured in current preclinical implant testing standards. Emerging evidence suggests that PE wear progression in TSA is highly dependent on shoulder kinematics, joint loading, implant positioning, and individual patient factors. Nonetheless, data on in vivo motion and load profiles remain sparse, and few tools exist to link these profiles to clinically relevant wear patterns or associated periprosthetic inflammatory tissue responses. Accordingly, the primary objective of this project is to develop validated, patient-specific models that predict PE wear in TSA and identify modifiable surgical, design, and rehabilitation targets to improve implant longevity and restore patient mobility. Additionally, we will establish histopathological hallmarks that indicate TSA failure caused by PE wear debris. Our central hypothesis is that specific shoulder kinematics and joint loading drive distinct PE wear patterns in TSA associated with mechanical failure or inflammatory-mediated osteolysis, depending on implant design and positioning. To achieve the overall objective of this work, shoulder motions and muscle excitations across 25 activities of daily living will be collected at pre-op and post-op (>6 months) in both aTSA and rTSA patients, with long-term follow-up of patient-reported outcomes via validated surveys (5 years). Unsupervised machine learning will categorize patients into movement-based phenotypes, which will then inform a multi-scale modeling framework to estimate in vivo shoulder joint loads and implant wear across the varying movement strategies. Predicted wear patterns will be validated using state-of-the-art preclinical wear simulators. Simultaneously, we will quantify how patient, surgical, and implant factors contribute to wear in retrieved TSA components (>400 samples), correlating imaging-based wear patterns with clinical outcomes, patient-reported function, inflammatory tissue responses, and radiographic indications of loosening. For that purpose, we will establish benchmarks of TSA wear rates and introduce a new histopathological approach augmented by infrared spectroscopic imaging. This work is innovative because we are linking patient-specific movement patterns following TSA with multi-scale computational models to predict PE wear, breaking the current approaches of using generic motions and loads in existing testing standards. This work will produce the first integrated, publicly available database of TSA kinematics, joint loading, and PE wear patterns and rates, along with validated computational tools to inform implant design, surgical planning, rehabilitation strategies, and personalized risk assessment. Ultimately, these advances will improve functional outcomes and long-term success for TSA patients and enable better preclinical testing methods and standards.

Cytoskeletal connectors: Deciphering the fundamental mechanisms of cytoskeletal dynamics and transport

PROJECT SUMMARY The cytoskeleton is a dynamic network of filamentous structures, including microtubules and actin, that regulate essential cellular processes such as cell shape, growth, and signaling. Cytoskeleton also serves as tracks for molecular motors, which transport a variety of cellular cargoes, including organelles, macromolecules, and vesicles. These cargoes are linked to motors by specialized connector proteins. Disruptions in connector proteins are implicated in a range of neurodevelopmental and neurodegenerative diseases, as well as cancers. Despite their importance, these proteins continue to be understudied, primarily due to their perceived role as passive linkers and the technical challenges in working with them. However, recent discoveries suggest that connector proteins may play more active roles, in some cases even have enzymatic functions. This proposal aims to uncover mechanisms of connector protein functions through a detailed investigation of actin-microtubule and motor-cargo interactions. Actin and microtubules are linked by the spectraplakin family of large and evolutionarily conserved proteins, critical for neuronal development and differentiation. Recent discoveries of ATPase domains within these proteins suggest they may haves beyond simply linking cytoskeletal components. One goal of this proposal is to investigate the role of spectraplakin’s ATPase domains via structural, biochemical, and cell biology approaches. Another goal is to explore how dynamic changes in motor-cargo connectors facilitate the transport of diverse cargoes along microtubule tracks. The focus will be on the cytoplasmic dynein-1 (dynein) and the connectors (adaptors) that activate and link dynein to cargo. Dynein is a microtubule minus-end directed motor that plays essential roles in cell division, and transports hundreds of different cellular cargoes. While several motor-cargo connectors have been identified, the regulatory mechanisms enabling cargo transport are not fully understood. We are investigating whether connector proteins work together to activate dynein movement and/or facilitate cargo handoff between different dynein complexes. Using innovative approaches, including time- resolved cryo-EM, complex in-vitro reconstitutions, and live-cell imaging in induced neurons, we are uncovering critical mechanisms that govern cytoskeletal connector proteins, furthering our understanding of how the cytoskeleton regulates essential cellular processes.

Linking Single-Cell Transcriptomic, Morphological, and Temporal Signatures of Vulnerability in Neurodegeneration

Neurodegeneration involves complex cellular phenotypes and molecular changes that vary widely among the cells of the nervous system. Current methodologies permit either detailed molecular profiling (e.g., single-cell transcriptomics) or functional phenotyping (e.g., live imaging of neuronal activity), but not both in the same cells. Thus, it is difficult to directly link a neuron's functional state or fate with its gene expression profile. To address this limitation, we developed an innovative technology, VISTA-FISH (Video Imaging with Spatial- Temporal Analysis by FISH), that couples prospective live-cell imaging with high-resolution spatial transcriptomic profiling of the same cells. This approach enables in situ comparisons of gene expression in neurons that exhibit divergent behaviors or outcomes. Using VISTA-FISH, we will profile iPS-derived human neurons to link single-cell gene expression, morphology, and temporal phenotypes to study molecular pathways driving resilience as well as susceptibility. After exposing neurons carrying TDP43 and C9orf72 mutations to a stimulus inducing TDP43 aggregation, we will jointly record TDP43 localization and neuron activity using live-cell microscopy, then measure single-cell gene expression of the same cells (Aim 1). We will also combine live-cell measurements of TDP43 half-life with CRISPR screening and single-cell gene expression (Aim 2). These rich datasets will enable us to determine transcriptomic changes associated with differences in protein aggregation, protein synthesis, and protein degradation in individual cells, providing an unprecedented molecular perspective on factors responsible for vulnerability and resilience to neurodegeneration.

Circadian regulation of reperfusion efficacy in acute ischemic stroke

Reperfusion with thrombectomy has changed the clinical landscape for ischemic stroke. Recently, some studies suggest that patients with “large cores” may still benefit from reperfusion. Why? If these “cores” represent dead brain, why should reperfusion help? One logical explanation is that currently used neuroimaging “cores”, do not always identify uniformly dead tissue. Our pilot data suggest that these “cores” include tissue with a wide range of injury, indicated as changes in relative CT Hounsfield Units (rHU). Importantly, circadian mechanisms may be involved. Ischemic tissue with less severe changes in rHU tend to occur in the morning (active phase) when responses to reperfusion are better. In mouse models of stroke, ischemic injury is also less severe when strokes occur during the nighttime (active phase for nocturnal animals). In contrast, more severe ischemic injury during the daytime (inactive phase for mice) is accompanied by dampened vasodilation and CBF response along with increased immunothrombosis and neutrophil extracellular traps (NETosis). Is it possible that understanding these circadian mechanisms may help identify patients who respond best to reperfusion? And is it possible that targeting these circadian mechanisms can help convert non- responders into responders? In this multi-PI project, we use a translational approach (clinical neuroimaging and biomarkers in stroke patients, mouse models of stroke, CT-PET imaging of tissue viability, molecular pharmacology) with three integrated aims that can be pursued in parallel. Aim 1 will use neuroimaging in stroke patients to show that less severe rHU values in reperfusion-responsive “cores” tend to occur in the morning, whereas more severe rHU values in reperfusion-non-responsive “cores” occur later. Aim 2 will use clinical biomarkers to show that more severe rHU “cores” that are not reperfusion-responsive correlate with circadian effects on vasodilation and immunothrombosis. Aim 3 will use mouse stroke models to test whether targeting these circadian mechanisms of vasodilation and immunothrombosis can convert reperfusion-non-responders into reperfusion-responders. Patients cannot choose when they have a stroke. So why should we pay attention to circadian mechanisms? There may be 2 reasons that are addressed by the present project. First, thrombectomy is resource-intensive, and in spite of the very low number-needed-to-treat, only 20% of “large core” patients do well after reperfusion. Our studies may help identify who (when) these responders are. Second, the pathophysiologic mechanisms of cerebral ischemia differ depending on time-of-day. Therefore, understanding and then targeting these circadian mechanisms may allow us to convert reperfusion non-responders into responders.

COCHLEAR SIGNALING MEDIATED BY HENSEN’S CELLS

PROJECT SUMMARY/ABSTRACT The organ of Corti has two types of auditory sensory cells (inner and outer hair cells) surrounded by nearly a dozen different types of supporting cells organized in a very meticulous pattern. Hair cells mediate the mechano-electrical transduction process of the organ of Corti and thus most cochlear auditory research has focused on these sensory cells. In contrast, much less is known about the different types of cochlear supporting cells, even though they likely impact hair cell function. Hensen’s cells are located laterally to the outer hair cell rows and appear to be the only cell type in the cochlear epithelium that expresses TRPA1 channels. These channels are widely known for their role as sensors of tissue damage and inflammation in nociceptive neurons. Not surprisingly, we recently found that Hensen’s cells are main sensors of tissue damage in the cochlear epithelium via the activation of TRPA1 channels (Velez-Ortega et al., Nat Commn, 2023). Additionally, our preliminary data also supports the role of Hensen’s cells in signaling pathways important for the proper innervation of the organ of Corti (aim 1), for the transmission of cochlear damage signals to the brain (aim 2), and for the regulation of hearing sensitivity after acoustic trauma (aim 3). Thus, here we will explore the hypothesis that TRPA1- mediated signaling pathways in the Hensen’s cells are required for the proper innervation and auditory function of the organ of Corti. In Aim 1 we will perform a detailed comparison of the morphology and synapses of afferent cochlear neurons of wild-type and Trpa1-/- mice at several developmental stages (using immunolabeling, confocal microscopy, STED microscopy, and electron microscopy) to assess the role of TRPA1 activity on the postnatal refinement of the cochlear innervation. Aim 2 will evaluate whether the afferent type II spiral ganglion neurons (SGN) can be activated downstream of TRPA1 channel gating in Hensen’s cells by testing responses of neonate and adult type II SGN to TRPA1 agonists (via live-cell time-lapse calcium imaging and patch clamp recordings of type II SGN dendrites). Aim 3 will test the impact of TRPA1 signaling in Hensen’s cells to the operating point of the cochlear transducer (via the recording of cochlear microphonics) and to cochlear tuning (via the recording of ABR tuning curves). This study is significant because it will contribute to our understanding of the cellular (Hensen’s cells plus type II SGN) and molecular (TRPA1 channels) mechanisms of the elusive cochlear nociceptive pathway. In addition, given that the loss of TRPA1 channels does not affect hearing thresholds in mice, we believe that undiagnosed deficits in TRPA1-dependent responses in the human population could represent a hidden susceptibility for cochlear damage after noise exposure or other insults.

Examining the foundations of reading comprehension: a longitudinal study of brain and behavior starting in infancy

SUMMARY Reading comprehension (RC) is one of the most complex skills that we utilize daily and is crucial for functioning in modern society, but despite its significance for academic achievement, employment prospects, and mental health, many children and adults do not exhibit proficient RC abilities. New theoretical models aiming to explain variability in RC suggest a dynamic interplay and co-development among ‘precursor’ foundational and cognitive- linguistic skills, interacting with environmental and socio-ecological factors across the developmental timeline of learning to read. Behavioral and neuroimaging studies in school-age children have demonstrated critical mechanistic support for these multifactorial RC models by identifying the developmental trajectories of precursor skills and further showing that brain areas, tracts, and networks typically underlying language and cognitive skills are also involved in RC. Nevertheless, the precursor skills that support RC start developing in infancy and the brain correlates underlying these precursors begin to develop in utero, which suggests that typical and atypical RC developmental trajectories could diverge long before school age. As such, examining RC development using a multifactorial, longitudinal approach that includes brain and behavior starting in infancy is critical for developing theoretical frameworks that can inform early preventative and intervention strategies. Here, we propose a comprehensive longitudinal study of RC development in which we examine direct and indirect effects on RC from brain, behavioral, familial risk, and environmental data from infancy to adolescence. To achieve this goal, we will combine two existing longitudinal cohorts, one ranging from infancy to late childhood (n = 174) and the other from preschool to early adolescence (n = 137). By applying state-of-the-art pediatric neuroimaging analyses, multiple indicator growth model structural equation models, and an innovative behavior- brain co-development measurement index to this unique, combined dataset, we will be able to identify brain and behavioral measures in infancy that directly and indirectly support subsequent RC development (Aim1). We will further characterize how longitudinal trajectories of behavioral measures as well as brain structure, function, and white matter organization contribute to RC development and how familial risk and environmental factors shape these trajectories (Aim 2). Finally, we will examine how the co-development of brain and behavior, as measured with an innovative co-development index, relates to subsequent RC (Aim 3). If successful, we will contribute the first multifactorial longitudinal model of RC development comprising direct and indirect effects from brain, behavior, brain-behavior co-development, familial risk, and environmental measures beginning in infancy. Understanding RC development using a multifactorial longitudinal lens will be crucial for building theoretical models and developing experimental designs focused on early preventative and intervention approaches long before the start of formal schooling.

Maternal Depression and Antidepressant Effects on Fetal Brain Structure and Function (FABMOMS)

PROJECT ABSTRACT Major depressive disorder (MDD) is one of the most common diseases in childbearing women, with a prevalence of 12.7% in pregnancy and 21.9% the year after birth. Exposure to maternal stress and depressive symptoms alters fetal/infant neurodevelopment, functional brain connectivity, and networks implicated in stress processing. About 5% of pregnant women are prescribed a serotonin selective or serotonin norepinephrine reuptake inhibitor (collectively, SRI). Remission of maternal MDD is crucial to the health and functioning of the mother and family. In observational studies typical of this field, differentiating the effects of drug exposure on offspring from the sequelae of the underlying psychiatric disease, both physiological and psychosocial, is challenging. Substantial progress has been made using sophisticated study designs and analytic approaches with large pregnancy cohorts that reduce the risk of spurious associations. Increased rates of overall and cardiac defects, stillbirth, preterm birth, and fetal growth have been largely explained by confounding by factors associated with both MDD and these outcomes rather than SRI exposure. Assessing the neurobehavioral development of children exposed in utero to SRI is the current research priority in this field. Our team pioneered the development of novel and safe fetal and neonatal quantitative magnetic resonance imaging (qMRI) tools, which will be combined with an evaluation of maternal heart rate variability to explore associations between exposures to stress, psychiatric symptoms and SRI on fetal and neonatal brain structure and function. The overarching goal of this project is to evaluate the separate and interactive effects of exposure to antidepressants in utero and maternal MDD on fetal and infant brain structure and function, with a specific focus on the hippocampus. We will accomplish this by evaluating four groups of pregnant women who have: 1) MDD treated with SRI to remission), 2) MDD treated with SRI (non-remitted, with both depressive symptom and SRI exposure), 3) MDD untreated with antidepressants, and 4) no current MDD or SRI treatment. Maternal assessments will occur at intake and in the early third trimesters and in then newborn period (at the time of fetal/newborn MRI) after birth. Maternal and infant evaluations will continue at 6 and 12 months postpartum. Maternal psychosocial and psychiatric status will provide extensive data on the context in which mothers experience pregnancy and infant care and allow adjustment for factors that will inevitably differ across groups. Lastly, we will explore the effects of maternal choline on MDD and offspring brain development. As these exposures and neurodevelopmental studies are conducted, exploring primary preventive strategies is a public health imperative. We will explore a potential mediator, poor maternal choline intake, a modifiable risk factor for both maternal MDD and altered fetal hippocampal growth and infant neurobehavior.

Response and defense mechanisms of extraintestinal Escherichia coli to reactive oxygen and chlorine species

Members of the Escherichia coli species are remarkably diverse and comprise commensal, probiotic and pathogenic strains. While some pathogenic E. coli cause intestinal diseases, extraintestinal E. coli (ExPEC) can colonize and infect environments outside the gut. For instance, members of this pathotype can inhabit the urinary tract where they are confronted with a multitude of bactericidal host defense strategies, which requires specialized genetic adaption for survival. ExPEC must defend highly toxic antimicrobials such as hypochlorous acid (HOCl), a potent reactive oxygen and chlorine species (RO/CS) generated during neutrophil-mediated phagocytosis and by enzymes in uroepithelial cells to control bacterial colonization. The increasing rate of ExPEC infections in humans due to changing infection dynamics demonstrate the critical need for a better understanding of ExPEC pathogenesis, which is desperately needed to improve approaches for infection prevention and treatment given the rise in antibiotic resistance spreading among E. coli. Our lab has reported that members of the ExPEC pathotype are more resistant to RCS in vitro and to neutrophil-mediated phagocytosis when compared to non-pathogenic and enteropathogenic E. coli. We identified the defense system responsible for these phenotypes and characterized its regulation during RCS stress: the RcrR regulon consisting of the rcrARB genes is controlled by the RCS-sensing transcriptional repressor RcrR, which reversibly loses its repressor activity upon oxidation by RCS, resulting in de-repression of its downstream targets. Induced expression of rcrB contributes significantly to ExPEC’s increased RCS resistance, however, the precise mechanism of RcrB and the role of RcrA (and potentially other defense players) during RCS stress remain enigmatic. Our long-term goal is to increase the efficacy of existing antimicrobial therapies by purposefully and selectively sensitizing ExPEC to clearance by innate immune cells. The overall objective of this application is a comprehensive analysis of ExPEC’s RCS defense with particular focus on the mechanism of the RcrR regulon. We hypothesize that RcrB directly protects cells from HOCl, while RcrA, another member of the RcrR regulon, mediates evasion from HOCl and invasion into host cells. In Aim 1, we will use phenotypic, biochemical, and imaging approaches to investigate the mechanism by which RcrB contributes to ExPEC’s increased RCS resistance. In Aim 2, we will study the role of RcrA for ExPEC motility, biofilm formation, and host cell invasion. In Aim 3, we will use independent unbiased and targeted approaches, including phenotypic characterization of transposon mutants, to fully comprehend ExPEC-specific responses to and defenses against RCS. Identifying, characterizing and targeting ExPEC-specific defense systems has the potential to increase the body’s own capacity to fight UTIs. Overall, we will involve at least four undergraduate students in our research projects, which we believe will provide an excellent training opportunity for the next generation of scientists.

A novel MRI method for noninvasive imaging of bone quality in type 2 diabetes

ABSTRACT: Type 2 diabetes mellitus (T2DM) affects 500 million of the global population, which is expected to increase to 800 million in 20 years. One of the multiple complications involved with T2DM is the significantly increased bone fracture risk and post-fracture mortality. Dual-energy X-ray absorptiometry (DXA) scans are routinely performed to measure bone mineral density (BMD) and associated fracture risk. However, T2DM patients often show preserved or even elevated BMD despite the significantly increased fracture risk. This mismatch between the BMD measurement and actual fracture risk hampers the accurate assessment of fracture risk and the appropriate treatment of T2DM that considers patient bone health. The lack of an accurate fracture risk assessment tool also confounds the evaluation of the bone health effect of antidiabetic drugs, including recently highlighted glucagon-like peptide-1 receptor agonists (e.g., semaglutide) and sodium-glucose cotransporter-2 inhibitors. Previous studies have suggested that bone quality, rather than bone quantity, as represented by BMD, is a crucial factor contributing to fracture risk in T2DM settings. Collagen crosslinking via advanced glycation end-products (AGEs) in cortical bone has been identified as a distinctive bone quality characteristic of T2DM patients, which explains the increased bone fragility. Although this finding is highly promising for improving the bone health management of T2DM patients, currently, no non-invasive method can monitor collagen crosslinking in the bones. This proposal aims to develop an ultrashort echo time (UTE) MRI-based method for measuring the degree of bone collagen crosslinking by quantifying magnetization transfer between water and collagen in the bone. This method, termed UTE-quantitative magnetization transfer (UTE-qMT) MRI, measures not only the quantity of macromolecules (e.g., collagen) in the bone but also the rates of exchange between water and macromolecular protons, which are related to the degree of collagen crosslinking. The proposal will develop and optimize the accelerated UTE-qMT method for reliably measuring the exchange rate in Aim 1. The optimized technique will be validated by correlating exchange rates with AGE-driven collagen crosslinking and subsequent compromise of bone mechanical properties in Aim 2. Finally, the optimized UTE-qMT MRI method will be translated to animal and human studies to demonstrate its clinical feasibility for investigating the effect of antidiabetic drugs on bone health in patients with T2DM in Aim 3. The successful completion of these aims will enable rapid and accurate assessment of bone fracture risk in patients with T2DM. Furthermore, noninvasively probing bone quality can also accurately assess the effect of antidiabetic drugs on bone health and aid in screening novel T2DM therapeutics for their impact on bone health.

Overcoming Treatment Resistance by Targeting Polyploid Breast Cancer Cells with AI assisted Single-Cell Analysis

Therapy resistance remains a formidable challenge in breast cancer treatment, with emerging evidence identifying polyploid giant cancer cells (PGCCs) as key drivers. These cells, arising through whole-genome doubling (WGD) events, exhibit enhanced resistance to therapies, contributing to disease relapse. PGCCs are characterized by enlarged cell and nuclear sizes, increased DNA content, and greater resilience compared to non-PGCCs. Their prevalence escalates with disease progression and therapeutic stress, underscoring their critical role in treatment resistance. As such, we hypothesize that inhibiting polyploid cancer cells can effectively reduce therapeutic resistance. Despite this, effective strategies targeting PGCCs are limited, hindered by the lack of high-throughput methods to assess PGCC viability and abundance. Traditional screening assays lack the sensitivity to detect the elimination of small populations of PGCCs, while current detection methods, such as visual inspection and flow cytometry, are not suited for high-throughput compound screening. Our preliminary work has established a high-throughput single-cell morphological analysis pipeline capable of quantifying PGCCs, and we successfully screened 2,726 compounds for their efficacy on PGCCs. Based on the preliminary success, we aim to further improve its robustness and accuracy under diverse staining and imaging conditions, ensuring consistent performance across multiple labs for widespread use in PGCC/WGD studies, with deep learning to accelerate the discovery of therapeutic strategies targeting PGCCs. In addition to empirical screening, our scRNA-Seq analysis of PGCCs has revealed altered gene expression, particularly in genes associated with FOXM1, a transcription factor critical in cell cycle regulation and linked to poor outcomes in various cancers. PGCCs also show altered ferroptosis regulators and elevated reactive oxygen species (ROS), indicating susceptibility to ferroptosis. Here, we propose two independent and complementary aims. Aim 1: We will develop and validate a robust deep learning–based single-cell morphological analysis pipeline for accurate PGCC/non-PGCC discrimination across variable staining, imaging, and lab settings. The model will be benchmarked on independent datasets from external labs and released as open-source, version-controlled software with full documentation to support reproducibility and broad adoption in PGCC/WGD research. Aim 2: Leveraging our screen of 2,726 FDA-approved compounds and mechanistic studies of FOXM1 and ferroptosis, we will prioritize and validate therapies that eradicate PGCCs and reduce treatment resistance. Using patient- derived cells, 3D spheroids, and syngeneic/xenograft models, we will rigorously assess top candidates as monotherapy and in combination with standard-of-care agents. Successful completion of this project will accelerate PGCC/WGD research, advance therapeutic strategies to overcome breast cancer resistance, and especially deliver benefits to patients with high PGCC burden. Given the prevalence of WGD across solid tumors and its induction by standard therapies, our approach holds broad clinical relevance and translational impact.

Understanding antiretroviral phosphorylation and dephosphorylation using mass spectrometry imaging-based enzyme histochemistry

PROJECT SUMMARY Our overall goal is to understand the mechanistic differences in the activation and deactivation of two widely used first-line antiretroviral drugs: tenofovir (TFV) and emtricitabine (FTC) in colonic tissues. HIV is a global health problem and roughly 1.3 million people became newly infected with HIV globally in 2022. Pre-exposure prophylaxis (PrEP) is an HIV prevention strategy where HIV-negative individuals use antiretrovirals to reduce the risk of HIV infection. Specifically, oral fixed-dose combinations of two antiretrovirals, namely, TFV (TFV; prescribed as TFV disoproxil fumarate or TFV alafenamide prodrugs) and FTC are FDA-approved for HIV PrEP. The pharmacologically active forms of TFV and FTC are TFV-diphosphate (TFV-DP) and FTC-triphosphate (FTC-TP), respectively, and these phosphorylated metabolites are found in cells. Unfortunately, high variability in the responses of TFV and FTC can lead to poor clinical outcomes, including therapeutic failure. However, the molecular mechanisms responsible for the observed variability in TFV and FTC responses are poorly understood. Although the observed variability in TFV and FTC drug responses is likely to be multifactorial, alterations in drug activation and deactivation can contribute to the observed variability in drug responses. Phosphorylation of TFV is known and recent studies suggest that nucleotidases may involve in the dephosphorylation of TFV metabolites. Although the kinases that phosphorylate FTC in peripheral blood mononuclear cells are known, the kinases that are responsible for the phosphorylation of FTC in putative sites of HIV infection such as colonic tissues are yet to be determined. Notably, unprotected receptive anal intercourse has a 20-fold higher risk of HIV transmission than vaginal intercourse. Thus, understanding the biotransformation of TFV and FTC in colonic tissue is important since it is a susceptible tissue to HIV infection. Recently, we have reported the enzymatic activities of nucleotidases toward the pharmacologically active metabolites of TFV and FTC in vitro. However, the mechanistic details of the biotransformation of the above drugs in HIV susceptible tissues such as colonic tissues are yet to be elucidated. Gaining a mechanistic understanding of the biotransformation of TFV and FTC in putative sites of HIV infection is important to improve their therapeutic efficacy. As such, in this application, we propose an innovative mass spectrometry imaging-based interdisciplinary approach to understand the biotransformation of TFV and FTC in the colon. Aim 1 will establish the role of nucleotide kinases and nucleotidases in regulating TFV and FTC metabolites in colonic cells mechanistically. Aim 2 will characterize the region- and cell-type-specific expression patterns, as well as enzymatic activities of nucleotide kinases and nucleotidases in situ. The proposed project will provide novel understandings of TFV and FTC activating and deactivating mechanisms that can be leveraged to optimize the therapeutic efficacy of the above drugs.

Magnetic resonance true temperature imaging with high spatial and temporal resolution

ABSTRACT The knowledge of temperature and temperature distribution within the brain can be critical to understanding the healthy and diseased brain, its response to acute injury, and in monitoring critically important thermal interventions. There are several temperature sensitive properties such relaxation rates and the proton resonance frequency shift (PRFS) that can be measured with magnetic resonance imaging (MRI) methods but these methods can only measure temperature change. The PRFS method, which provides the most accurate measurement of temperature change can only measure true tissue temperature if the starting true temperature distribution is known. Fortunately, MR spectroscopy (MRS) methods have been developed that show great promise in the measurement of true temperature. These methods rely on the detection of a temperature independent spectral peak of protons bound to carbon atoms in high concentration metabolites, such as N- acetylaspartate (NAA), creatine (Cr) and choline (Cho) which can be used as a reference for the temperature dependent spectral peak of water protons. Both single voxel spectroscopy (SVS) methods and MRS imaging (MRSI) methods have been described but are slow because of the long readout time needed to achieve adequate spectral resolution and the need to perform multiple averages due to the low signal being measured. Echo-planar spectroscopic imaging (EPSI) speeds up MRSI by interleaving an oscillating imaging gradient to spatially encode one of the imaging dimensions simultaneously with spectral readout. Unfortunately, SVS, MRSI, and even EPSI are unsuitable for clinical applications because of the low spatial resolution (voxel size 1 cm3) and temporal resolution (multiple minutes). The goal of this project is to develop an MRI technique that can measure true temperature in the whole brain at spatial and temporal resolutions that enable clinical utility for acutely assessing and longitudinally monitoring healthy and diseased brain tissue, and real time monitoring of thermal interventional therapies. This innovative true temperature measurement technique combines EPSI, for low resolution background field measurements, with PRFS for high spatial and temporal resolution water proton measurements. While conventional EPSI methods interleave volumetric acquisitions with and without water suppression, we propose an innovative modification to take advantage of the very strong water signal to obtain a very high resolution, dynamic method for true temperature measurements. The MRI pulse sequence will be refined, validated (Aim 1), applied to healthy subjects and post-surgery patients at risk for infections (Aim 2), and applied to essential tremor (ET) patients during the required delay between repeated focused ultrasound sonications (Aim 3). Successful completion of the aims of this study will result in a clinically practical method to obtain true temperature measurements in the brain with a spatial and temporal resolution sufficiently high to meet the needs of monitoring focal thermal therapy treatments as well as to provide true temperature measurements over the entire brain for assessment of the state of the brain with disease, infection, and injury.

Primary cilia protein IFT88 governs smooth muscle phenotype and vascular remodeling

Project Summary/Abstract Cardiovascular disease remains the leading cause of death in the United States, accounting for nearly 1 million deaths in 2022. Vascular diseases such as atherosclerosis, aneurysm, and coronary artery disease are regulated largely by smooth muscle cells (SMCs) residing in the blood vessel wall. The central dogma of vascular SMC biology is that differentiated cells can de-differentiate and give rise to a spectrum of alternative phenotypes promoting invasion, proliferation, fibrosis, and inflammation, but the mechanisms regulating SMC phenotypic transitions are poorly understood. Intraflagellar transport 88 (IFT88) is an essential protein for the formation of primary cilia, centriole-associated plasma membrane organelles that project into the extracellular milieu and regulate cell cycle reentry and responses to stimuli like growth factors and mechanical strain. Non- ciliary functions of IFT88 also include progression of the cell cycle checkpoint and polarized motility, both of which are functionally critical for SMC-mediated vascular remodeling. Little is known about the functional role of the primary cilia in SMCs and the role of the essential cilia protein IFT88 in regulating SMC phenotype. To address this gap in knowledge, my postdoctoral studies focus on the role of IFT88 in the context of intimal hyperplasia (K99). During the independent phase (R00), I will apply these findings to arteriovenous fistula (AVF) maturation, a surgical intervention often required for dialysis individuals with polycystic kidney disease (PKD), an IFT88 loss-of-function disease. I will test my central hypothesis that cilia are key regulators of SMC phenotype in three Specific Aims: 1) determine the role of IFT88-dependent SMC primary cilia in mechanotransduction of extracellular matrix (ECM) stiffness (K99), 2) determine the role of IFT88 in pathological intimal hyperplasia (K99), and 3) test whether SMC IFT88 expression is required for adaptive remodeling of grafted veins following AVF placement (R00). Overall, we propose that IFT88+ ciliated SMC represent an unidentified subclass of the SMC phenotype spectrum that is primarily responsible for vascular remodeling and is an attractive potential target for treatment of vascular diseases. Building on strong existing collaborations, we have formed a research and mentoring team with expertise in SMC pathophysiology, primary cilia biology, mechanobiology, AVF surgery, and PKD to complete the proposed aims. The additional training in cell-ECM interactions (Aim 1, K99), in vivo murine ligation injury and in vivo cilia imaging (Aim 2, K99), and AVF surgery and PKD pathology (Aim 3, R00) will be indispensable for preparing the PI, Dr. O’Brien, for his career as an independent investigator. Completion of the proposed aims will also contribute directly to an understanding of the function of IFT88-dependent primary cilia in SMCs and may likely identify novel therapeutic targets for treatment of vascular diseases.

Facilitating the Advancement of Research and Education for Undergraduate Students by Incorporating Laser Scanning Confocal Microscopy (FAREUS-LSCM)

PROJECT SUMMARY/ABSTRACT The University of Puerto Rico at Aguadilla (UPR-Aguadilla) requests funding to acquire a Nikon AX Galvo Confocal Laser Scanning Microscope (LSCM) with a TI2-E inverted platform and a four- laser configuration (405/488/561/640 nm) to establish transformative imaging capabilities at our resource-limited institution serving 96% Pell Grant recipients. This state-of-the-art instrument addresses a critical infrastructure gap, enabling high-resolution fluorescence imaging, live-cell microscopy, and quantitative analysis essential for competitive biomedical research and undergraduate education. The LSCM will directly support four active research projects spanning parasitology (monogenean host-specificity studies), plant pathology (coffee biocontrol development), environmental chemistry (metalloprotein biomarkers), and neuroscience (astrocyte dysfunction in diabetic epilepsy) while integrating into core laboratory courses including Immunology (BIOL 4009) and Undergraduate research courses (BIOL 3108 and QUIM 4999). Our multidisciplinary faculty, in partnership with the Neuroimaging and Electrophysiology Facility (NIEF) Excellence Imaging Center, offers expertise in confocal microscopy, encompassing advanced imaging and specialized sample preparation techniques. This collaboration ensures effective implementation of the technology, sustained technical support, and high-quality training programs that will enhance research productivity and broaden educational impact. The broad, long-term objective is to transform UPR-Aguadilla from a primarily teaching institution into a research-active campus capable of producing graduate-school-ready students equipped with cutting-edge technical skills. Access to advanced confocal microscopy will stimulate new research collaborations, enhance faculty productivity, and provide 30-40 students annually with hands-on experience in modern imaging technologies currently absent from our curriculum. The instrument will strengthen our partnership with the emerging Natural History Museum of Puerto Rico for specimen digitization and support comprehensive outreach programs targeting 25-50 high school students annually through "Seeing Science Up Close" workshops. Expected outcomes include 1- 2 peer-reviewed publications within three years, establishment of 1-2 new institutional collaborations, and measurable enhancement of biomedical research capacity. This investment will significantly advance STEM education and research opportunities at UPR-Aguadilla while expanding access to cutting-edge scientific instrumentation for students pursuing biomedical careers and contributing to the development of skilled researchers in the biomedical sciences.

Adventures in Spin Labeling: Clinical Perfusion Imaging and the Path to Technical Innovation

Arterial spin labeling (ASL) MRI has become a vital tool in clinical neuroimaging, enabling noninvasive assessment of cerebral perfusion across a range of conditions including stroke, vascular malformations, and brain tumors. With broader clinical adoption, its practical strengths — as well as important limitations — have become increasingly clear.

Consciousness at the edge of chaos

Over the last 20 years, neuroimaging and electrophysiology techniques have become central to understanding the mechanisms that accompany loss and recovery of consciousness. Much of this research is performed in the context of healthy individuals with neurotypical brain dynamics. Yet, a true understanding of how consciousness emerges from the joint action of neurons has to account for how severely pathological brains, often showing phenotypes typical of unconsciousness, can nonetheless generate a subjective viewpoint. In this presentation, I will start from the context of Disorders of Consciousness and will discuss recent work aimed at finding generalizable signatures of consciousness that are reliable across a spectrum of brain electrophysiological phenotypes focusing in particular on the notion of edge-of-chaos criticality.

Convergent large-scale network and local vulnerabilities underlie brain atrophy across Parkinson’s disease stages

Spike train structure of cortical transcriptomic populations in vivo

The cortex comprises many neuronal types, which can be distinguished by their transcriptomes: the sets of genes they express. Little is known about the in vivo activity of these cell types, particularly as regards the structure of their spike trains, which might provide clues to cortical circuit function. To address this question, we used Neuropixels electrodes to record layer 5 excitatory populations in mouse V1, then transcriptomically identified the recorded cell types. To do so, we performed a subsequent recording of the same cells using 2-photon (2p) calcium imaging, identifying neurons between the two recording modalities by fingerprinting their responses to a “zebra noise” stimulus and estimating the path of the electrode through the 2p stack with a probabilistic method. We then cut brain slices and performed in situ transcriptomics to localize ~300 genes using coppaFISH3d, a new open source method, and aligned the transcriptomic data to the 2p stack. Analysis of the data is ongoing, and suggests substantial differences in spike time coordination between ET and IT neurons, as well as between transcriptomic subtypes of both these excitatory types.

Non-invasive human neuroimaging studies of motor plasticity have predominantly focused on the cerebral cortex due to low signal-to-noise ration of blood oxygen level-dependent (BOLD) signals in subcortical structures and the small effect sizes typically observed in plasticity paradigms. Precision functional mapping can help overcome these challenges and has revealed significant and reversible functional alterations in the cortico-subcortical motor circuit during arm immobilization

Functional Imaging of the Human Brain: A Window into the Organization of the Human Mind

Neural circuits underlying sleep structure and functions

Sleep is an active state critical for processing emotional memories encoded during waking in both humans and animals. There is a remarkable overlap between the brain structures and circuits active during sleep, particularly rapid eye-movement (REM) sleep, and the those encoding emotions. Accordingly, disruptions in sleep quality or quantity, including REM sleep, are often associated with, and precede the onset of, nearly all affective psychiatric and mood disorders. In this context, a major biomedical challenge is to better understand the underlying mechanisms of the relationship between (REM) sleep and emotion encoding to improve treatments for mental health. This lecture will summarize our investigation of the cellular and circuit mechanisms underlying sleep architecture, sleep oscillations, and local brain dynamics across sleep-wake states using electrophysiological recordings combined with single-cell calcium imaging or optogenetics. The presentation will detail the discovery of a 'somato-dendritic decoupling'in prefrontal cortex pyramidal neurons underlying REM sleep-dependent stabilization of optimal emotional memory traces. This decoupling reflects a tonic inhibition at the somas of pyramidal cells, occurring simultaneously with a selective disinhibition of their dendritic arbors selectively during REM sleep. Recent findings on REM sleep-dependent subcortical inputs and neuromodulation of this decoupling will be discussed in the context of synaptic plasticity and the optimization of emotional responses in the maintenance of mental health.

Restoring Sight to the Blind: Effects of Structural and Functional Plasticity

Visual restoration after decades of blindness is now becoming possible by means of retinal and cortical prostheses, as well as emerging stem cell and gene therapeutic approaches. After restoring visual perception, however, a key question remains. Are there optimal means and methods for retraining the visual cortex to process visual inputs, and for learning or relearning to “see”? Up to this point, it has been largely assumed that if the sensory loss is visual, then the rehabilitation focus should also be primarily visual. However, the other senses play a key role in visual rehabilitation due to the plastic repurposing of visual cortex during blindness by audition and somatosensation, and also to the reintegration of restored vision with the other senses. I will present multisensory neuroimaging results, cortical thickness changes, as well as behavioral outcomes for patients with Retinitis Pigmentosa (RP), which causes blindness by destroying photoreceptors in the retina. These patients have had their vision partially restored by the implantation of a retinal prosthesis, which electrically stimulates still viable retinal ganglion cells in the eye. Our multisensory and structural neuroimaging and behavioral results suggest a new, holistic concept of visual rehabilitation that leverages rather than neglects audition, somatosensation, and other sensory modalities.

Functional Plasticity in the Language Network – evidence from Neuroimaging and Neurostimulation

Efficient cognition requires flexible interactions between distributed neural networks in the human brain. These networks adapt to challenges by flexibly recruiting different regions and connections. In this talk, I will discuss how we study functional network plasticity and reorganization with combined neurostimulation and neuroimaging across the adult life span. I will argue that short-term plasticity enables flexible adaptation to challenges, via functional reorganization. My key hypothesis is that disruption of higher-level cognitive functions such as language can be compensated for by the recruitment of domain-general networks in our brain. Examples from healthy young brains illustrate how neurostimulation can be used to temporarily interfere with efficient processing, probing short-term network plasticity at the systems level. Examples from people with dyslexia help to better understand network disorders in the language domain and outline the potential of facilitatory neurostimulation for treatment. I will also discuss examples from aging brains where plasticity helps to compensate for loss of function. Finally, examples from lesioned brains after stroke provide insight into the brain’s potential for long-term reorganization and recovery of function. Collectively, these results challenge the view of a modular organization of the human brain and argue for a flexible redistribution of function via systems plasticity.

Recent views on pre-registration

A discussion on some recent perspectives on pre-registration, which has become a growing trend in the past few years. This is not just limited to neuroimaging, and it applies to most scientific fields. We will start with this overview editorial by Simmons et al. (2021): https://faculty.wharton.upenn.edu/wp-content/uploads/2016/11/34-Simmons-Nelson-Simonsohn-2021a.pdf, and also talk about a more critical perspective by Pham & Oh (2021): https://www.researchgate.net/profile/Michel-Pham/publication/349545600_Preregistration_Is_Neither_Sufficient_nor_Necessary_for_Good_Science/links/60fb311e2bf3553b29096aa7/Preregistration-Is-Neither-Sufficient-nor-Necessary-for-Good-Science.pdf. I would like us to discuss the pros and cons of pre-registration, and if we have time, I may do a demonstration of how to perform a pre-registration through the Open Science Framework.

Maladaptive Neuroplasticity in Cortico-limbic Structures: Insights from Surgical Pain Relief in Chronic Neuropathic Facial Pain

Spatio-temporal Regulation of Gene Expression in Neurons: Insights from Imaging mRNAs Live in Action

Structural & Functional Neuroplasticity in Children with Hemiplegia

About 30% of children with cerebral palsy have congenital hemiplegia, resulting from periventricular white matter injury, which impairs the use of one hand and disrupts bimanual co-ordination. Congenital hemiplegia has a profound effect on each child's life and, thus, is of great importance to the public health. Changes in brain organization (neuroplasticity) often occur following periventricular white matter injury. These changes vary widely depending on the timing, location, and extent of the injury, as well as the functional system involved. Currently, we have limited knowledge of neuroplasticity in children with congenital hemiplegia. As a result, we provide rehabilitation treatment to these children almost blindly based exclusively on behavioral data. In this talk, I will present recent research evidence of my team on understanding neuroplasticity in children with congenital hemiplegia by using a multimodal neuroimaging approach that combines data from structural and functional neuroimaging methods. I will further present preliminary data regarding functional improvements of upper extremities motor and sensory functions as a result of rehabilitation with a robotic system that involves active participation of the child in a video-game setup. Our research is essential for the development of novel or improved neurological rehabilitation strategies for children with congenital hemiplegia.

Circuit Mechanisms of Remote Memory

Memories of emotionally-salient events are long-lasting, guiding behavior from minutes to years after learning. The prelimbic cortex (PL) is required for fear memory retrieval across time and is densely interconnected with many subcortical and cortical areas involved in recent and remote memory recall, including the temporal association area (TeA). While the behavioral expression of a memory may remain constant over time, the neural activity mediating memory-guided behavior is dynamic. In PL, different neurons underlie recent and remote memory retrieval and remote memory-encoding neurons have preferential functional connectivity with cortical association areas, including TeA. TeA plays a preferential role in remote compared to recent memory retrieval, yet how TeA circuits drive remote memory retrieval remains poorly understood. Here we used a combination of activity-dependent neuronal tagging, viral circuit mapping and miniscope imaging to investigate the role of the PL-TeA circuit in fear memory retrieval across time in mice. We show that PL memory ensembles recruit PL-TeA neurons across time, and that PL-TeA neurons have enhanced encoding of salient cues and behaviors at remote timepoints. This recruitment depends upon ongoing synaptic activity in the learning-activated PL ensemble. Our results reveal a novel circuit encoding remote memory and provide insight into the principles of memory circuit reorganization across time.

Analyzing Network-Level Brain Processing and Plasticity Using Molecular Neuroimaging

Behavior and cognition depend on the integrated action of neural structures and populations distributed throughout the brain. We recently developed a set of molecular imaging tools that enable multiregional processing and plasticity in neural networks to be studied at a brain-wide scale in rodents and nonhuman primates. Here we will describe how a novel genetically encoded activity reporter enables information flow in virally labeled neural circuitry to be monitored by fMRI. Using the reporter to perform functional imaging of synaptically defined neural populations in the rat somatosensory system, we show how activity is transformed within brain regions to yield characteristics specific to distinct output projections. We also show how this approach enables regional activity to be modeled in terms of inputs, in a paradigm that we are extending to address circuit-level origins of functional specialization in marmoset brains. In the second part of the talk, we will discuss how another genetic tool for MRI enables systematic studies of the relationship between anatomical and functional connectivity in the mouse brain. We show that variations in physical and functional connectivity can be dissociated both across individual subjects and over experience. We also use the tool to examine brain-wide relationships between plasticity and activity during an opioid treatment. This work demonstrates the possibility of studying diverse brain-wide processing phenomena using molecular neuroimaging.

Decomposing motivation into value and salience

Humans and other animals approach reward and avoid punishment and pay attention to cues predicting these events. Such motivated behavior thus appears to be guided by value, which directs behavior towards or away from positively or negatively valenced outcomes. Moreover, it is facilitated by (top-down) salience, which enhances attention to behaviorally relevant learned cues predicting the occurrence of valenced outcomes. Using human neuroimaging, we recently separated value (ventral striatum, posterior ventromedial prefrontal cortex) from salience (anterior ventromedial cortex, occipital cortex) in the domain of liquid reward and punishment. Moreover, we investigated potential drivers of learned salience: the probability and uncertainty with which valenced and non-valenced outcomes occur. We find that the brain dissociates valenced from non-valenced probability and uncertainty, which indicates that reinforcement matters for the brain, in addition to information provided by probability and uncertainty alone, regardless of valence. Finally, we assessed learning signals (unsigned prediction errors) that may underpin the acquisition of salience. Particularly the insula appears to be central for this function, encoding a subjective salience prediction error, similarly at the time of positively and negatively valenced outcomes. However, it appears to employ domain-specific time constants, leading to stronger salience signals in the aversive than the appetitive domain at the time of cues. These findings explain why previous research associated the insula with both valence-independent salience processing and with preferential encoding of the aversive domain. More generally, the distinction of value and salience appears to provide a useful framework for capturing the neural basis of motivated behavior.

Localisation of Seizure Onset Zone in Epilepsy Using Time Series Analysis of Intracranial Data

There are over 30 million people with drug-resistant epilepsy worldwide. When neuroimaging and non-invasive neural recordings fail to localise seizure onset zones (SOZ), intracranial recordings become the best chance for localisation and seizure-freedom in those patients. However, intracranial neural activities remain hard to visually discriminate across recording channels, which limits the success of intracranial visual investigations. In this presentation, I present methods which quantify intracranial neural time series and combine them with explainable machine learning algorithms to localise the SOZ in the epileptic brain. I present the potentials and limitations of our methods in the localisation of SOZ in epilepsy providing insights for future research in this area.

How the brain barriers ensure CNSimmune privilege”

Britta Engelhard’s research is devoted to understanding thefunction of the different brain barriers in regulating CNS immunesurveillance and how their impaired function contributes toneuroinflammatory diseases such as Multiple Sclerosis (MS) orAlzheimer’s disease (AD). Her laboratory combines expertise invascular biology, neuroimmunology and live cell imaging and hasdeveloped sophisticated in vitro and in vivo approaches to studyimmune cell interactions with the brain barriers in health andneuroinflammation.

Probing neural population dynamics with recurrent neural networks

Large-scale recordings of neural activity are providing new opportunities to study network-level dynamics with unprecedented detail. However, the sheer volume of data and its dynamical complexity are major barriers to uncovering and interpreting these dynamics. I will present latent factor analysis via dynamical systems, a sequential autoencoding approach that enables inference of dynamics from neuronal population spiking activity on single trials and millisecond timescales. I will also discuss recent adaptations of the method to uncover dynamics from neural activity recorded via 2P Calcium imaging. Finally, time permitting, I will mention recent efforts to improve the interpretability of deep-learning based dynamical systems models.

Trends in NeuroAI - Brain-like topography in transformers (Topoformer)

Dr. Nicholas Blauch will present on his work "Topoformer: Brain-like topographic organization in transformer language models through spatial querying and reweighting". Dr. Blauch is a postdoctoral fellow in the Harvard Vision Lab advised by Talia Konkle and George Alvarez. Paper link: https://openreview.net/pdf?id=3pLMzgoZSA Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri | https://groups.google.com/g/medarc-fmri).

Navigating semantic spaces: recycling the brain GPS for higher-level cognition

Humans share with other animals a complex neuronal machinery that evolved to support navigation in the physical space and that supports wayfinding and path integration. In my talk I will present a series of recent neuroimaging studies in humans performed in my Lab aimed at investigating the idea that this same neural navigation system (the “brain GPS”) is also used to organize and navigate concepts and memories, and that abstract and spatial representations rely on a common neural fabric. I will argue that this might represent a novel example of “cortical recycling”, where the neuronal machinery that primarily evolved, in lower level animals, to represent relationships between spatial locations and navigate space, in humans are reused to encode relationships between concepts in an internal abstract representational space of meaning.

Characterizing the causal role of large-scale network interactions in supporting complex cognition

Neuroimaging has greatly extended our capacity to study the workings of the human brain. Despite the wealth of knowledge this tool has generated however, there are still critical gaps in our understanding. While tremendous progress has been made in mapping areas of the brain that are specialized for particular stimuli, or cognitive processes, we still know very little about how large-scale interactions between different cortical networks facilitate the integration of information and the execution of complex tasks. Yet even the simplest behavioral tasks are complex, requiring integration over multiple cognitive domains. Our knowledge falls short not only in understanding how this integration takes place, but also in what drives the profound variation in behavior that can be observed on almost every task, even within the typically developing (TD) population. The search for the neural underpinnings of individual differences is important not only philosophically, but also in the service of precision medicine. We approach these questions using a three-pronged approach. First, we create a battery of behavioral tasks from which we can calculate objective measures for different aspects of the behaviors of interest, with sufficient variance across the TD population. Second, using these individual differences in behavior, we identify the neural variance which explains the behavioral variance at the network level. Finally, using covert neurofeedback, we perturb the networks hypothesized to correspond to each of these components, thus directly testing their casual contribution. I will discuss our overall approach, as well as a few of the new directions we are currently pursuing.

Combined electrophysiological and optical recording of multi-scale neural circuit dynamics

This webinar will showcase new approaches for electrophysiological recordings using our silicon neural probes and surface arrays combined with diverse optical methods such as wide-field or 2-photon imaging, fiber photometry, and optogenetic perturbations in awake, behaving mice. Multi-modal recording of single units and local field potentials across cortex, hippocampus and thalamus alongside calcium activity via GCaMP6F in cortical neurons in triple-transgenic animals or in hippocampal astrocytes via viral transduction are brought to bear to reveal hitherto inaccessible and under-appreciated aspects of coordinated dynamics in the brain.

Evolution of convulsive therapy from electroconvulsive therapy to Magnetic Seizure Therapy; Interventional Neuropsychiatry

In April, we will host Nolan Williams and Mustafa Husain. Be prepared to embark on a journey from early brain stimulation with ECT to state-of-the art TMS protocols and magnetic seizure therapy! The talks will be held on Thursday, April 25th at noon ET / 6PM CET. Nolan Williams, MD, is an associate professor of Psychiatry and Behavioral Science at Stanford University. He developed the SAINT protocol, which is the first FDA-cleared non-invasive, rapid-acting neuromodulation treatment for treatment-resistant depression. Mustafa Husain, MD, is an adjunct professor of Psychiatry and Behavioral Sciences at Duke University and a professor of Psychiatry and Neurology at UT Southwestern Medical Center, Dallas. He will tell us about “Evolution of convulsive therapy from electroconvulsive therapy to Magnetic Seizure Therapy”. As always, we will also get a glimpse at the “Person behind the science”. Please register va talks.stimulatingbrains.org to receive the (free) Zoom link, subscribe to our newsletter, or follow us on Twitter/X for further updates!

Currents of Hope: how noninvasive brain stimulation is reshaping modern psychiatric care; Adapting to diversity: Integrating variability in brain structure and function into personalized / closed-loop non-invasive brain stimulation for substance use disorders

In March we will focus on TMS and host Ghazaleh Soleimani and Colleen Hanlon. The talks will talk place on Thursday, March 28th at noon ET – please be aware that this means 5PM CET since Boston already switched to summer time! Ghazaleh Soleimani, PhD, is a postdoctoral fellow in Dr Hamed Ekhtiari’s lab at the University of Minnesota. She is also the executive director of the International Network of tES/TMS for Addiction Medicine (INTAM). She will discuss “Adapting to diversity: Integrating variability in brain structure and function into personalized / closed-loop non-invasive brain stimulation for substance use disorders”. Colleen Hanlon, PhD, currently serves as a Vice President of Medical Affairs for BrainsWay, a company specializing in medical devices for mental health, including TMS. Colleen previously worked at the Medical University of South Carolina and Wake Forest School of Medicine. She received the International Brain Stimulation Early Career Award in 2023. She will discuss “Currents of Hope: how noninvasive brain stimulation is reshaping modern psychiatric care”. As always, we will also get a glimpse at the “Person behind the science”. Please register va talks.stimulatingbrains.org to receive the (free) Zoom link, subscribe to our newsletter, or follow us on Twitter/X for further updates!

Epileptic micronetworks and their clinical relevance

A core aspect of clinical epileptology revolves around relating epileptic field potentials to underlying neural sources (e.g. an “epileptogenic focus”). Yet still, how neural population activity relates to epileptic field potentials and ultimately clinical phenomenology, remains far from being understood. After a brief overview on this topic, this seminar will focus on unpublished work, with an emphasis on seizure-related focal spreading depression. The presented results will include hippocampal and neocortical chronic in vivo two-photon population imaging and local field potential recordings of epileptic micronetworks in mice, in the context of viral encephalitis or optogenetic stimulation. The findings are corroborated by invasive depth electrode recordings (macroelectrodes and BF microwires) in epilepsy patients during pre-surgical evaluation. The presented work carries general implications for clinical epileptology, and basic epilepsy research.

Learning produces a hippocampal cognitive map in the form of an orthogonalized state machine

Cognitive maps confer animals with flexible intelligence by representing spatial, temporal, and abstract relationships that can be used to shape thought, planning, and behavior. Cognitive maps have been observed in the hippocampus, but their algorithmic form and the processes by which they are learned remain obscure. Here, we employed large-scale, longitudinal two-photon calcium imaging to record activity from thousands of neurons in the CA1 region of the hippocampus while mice learned to efficiently collect rewards from two subtly different versions of linear tracks in virtual reality. The results provide a detailed view of the formation of a cognitive map in the hippocampus. Throughout learning, both the animal behavior and hippocampal neural activity progressed through multiple intermediate stages, gradually revealing improved task representation that mirrored improved behavioral efficiency. The learning process led to progressive decorrelations in initially similar hippocampal neural activity within and across tracks, ultimately resulting in orthogonalized representations resembling a state machine capturing the inherent struture of the task. We show that a Hidden Markov Model (HMM) and a biologically plausible recurrent neural network trained using Hebbian learning can both capture core aspects of the learning dynamics and the orthogonalized representational structure in neural activity. In contrast, we show that gradient-based learning of sequence models such as Long Short-Term Memory networks (LSTMs) and Transformers do not naturally produce such orthogonalized representations. We further demonstrate that mice exhibited adaptive behavior in novel task settings, with neural activity reflecting flexible deployment of the state machine. These findings shed light on the mathematical form of cognitive maps, the learning rules that sculpt them, and the algorithms that promote adaptive behavior in animals. The work thus charts a course toward a deeper understanding of biological intelligence and offers insights toward developing more robust learning algorithms in artificial intelligence.

Novel approaches to non-invasive neuromodulation for neuropsychiatric disorders; Effects of deep brain stimulation on brain function in obsessive-compulsive disorder

On Thursday, February 29th, we will host Damiaan Denys and Andrada Neacsiu. The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!

Blood-brain barrier dysfunction in epilepsy: Time for translation

The neurovascular unit (NVU) consists of cerebral blood vessels, neurons, astrocytes, microglia, and pericytes. It plays a vital role in regulating blood flow and ensuring the proper functioning of neural circuits. Among other, this is made possible by the blood-brain barrier (BBB), which acts as both a physical and functional barrier. Previous studies have shown that dysfunction of the BBB is common in most neurological disorders and is associated with neural dysfunction. Our studies have demonstrated that BBB dysfunction results in the transformation of astrocytes through transforming growth factor beta (TGFβ) signaling. This leads to activation of the innate neuroinflammatory system, changes in the extracellular matrix, and pathological plasticity. These changes ultimately result in dysfunction of the cortical circuit, lower seizure threshold, and spontaneous seizures. Blocking TGFβ signaling and its associated pro-inflammatory pathway can prevent this cascade of events, reduces neuroinflammation, repairs BBB dysfunction, and prevents post-injury epilepsy, as shown in experimental rodents. To further understand and assess BBB integrity in human epilepsy, we developed a novel imaging technique that quantitatively measures BBB permeability. Our findings have confirmed that BBB dysfunction is common in patients with drug-resistant epilepsy and can assist in identifying the ictal-onset zone prior to surgery. Current clinical studies are ongoing to explore the potential of targeting BBB dysfunction as a novel treatment approach and investigate its role in drug resistance, the spread of seizures, and comorbidities associated with epilepsy.

Trends in NeuroAI - Unified Scalable Neural Decoding (POYO)

Lead author Mehdi Azabou will present on his work "POYO-1: A Unified, Scalable Framework for Neural Population Decoding" (https://poyo-brain.github.io/). Mehdi is an ML PhD student at Georgia Tech advised by Dr. Eva Dyer. Paper link: https://arxiv.org/abs/2310.16046 Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri | https://groups.google.com/g/medarc-fmri).

Closed-loop deep brain stimulation as a neuroprosthetic of dopaminergic circuits – Current evidence and future opportunities; Spatial filtering to enhance signal processing in invasive neurophysiology

On Thursday February 15th, we will host Victoria Peterson and Julian Neumann. Victoria will tell us about “Spatial filtering to enhance signal processing in invasive neurophysiology”. Besides his scientific presentation on “Closed-loop deep brain stimulation as a neuroprosthetic of dopaminergic circuits – Current evidence and future opportunities”, Julian will give us a glimpse at the person behind the science. The talks will be followed by a shared discussion. Note: The talks will exceptionally be held at 10 ET / 4PM CET. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!

Neurovascular Interactions: Mechanisms, Imaging, Therapeutics

Trends in NeuroAI - Meta's MEG-to-image reconstruction

Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri). Title: Brain-optimized inference improves reconstructions of fMRI brain activity Abstract: The release of large datasets and developments in AI have led to dramatic improvements in decoding methods that reconstruct seen images from human brain activity. We evaluate the prospect of further improving recent decoding methods by optimizing for consistency between reconstructions and brain activity during inference. We sample seed reconstructions from a base decoding method, then iteratively refine these reconstructions using a brain-optimized encoding model that maps images to brain activity. At each iteration, we sample a small library of images from an image distribution (a diffusion model) conditioned on a seed reconstruction from the previous iteration. We select those that best approximate the measured brain activity when passed through our encoding model, and use these images for structural guidance during the generation of the small library in the next iteration. We reduce the stochasticity of the image distribution at each iteration, and stop when a criterion on the "width" of the image distribution is met. We show that when this process is applied to recent decoding methods, it outperforms the base decoding method as measured by human raters, a variety of image feature metrics, and alignment to brain activity. These results demonstrate that reconstruction quality can be significantly improved by explicitly aligning decoding distributions to brain activity distributions, even when the seed reconstruction is output from a state-of-the-art decoding algorithm. Interestingly, the rate of refinement varies systematically across visual cortex, with earlier visual areas generally converging more slowly and preferring narrower image distributions, relative to higher-level brain areas. Brain-optimized inference thus offers a succinct and novel method for improving reconstructions and exploring the diversity of representations across visual brain areas. Speaker: Reese Kneeland is a Ph.D. student at the University of Minnesota working in the Naselaris lab. Paper link: https://arxiv.org/abs/2312.07705

Imaging the subcortex; Microstructural and connectivity correlates of outcome variability in functional neurosurgery for movement disorders

We are very much looking forward to host Francisca Ferreira and Birte Forstmann on December 14th, 2023, at noon ET / 6PM CET. Francisca Ferreira is a PhD student and Neurosurgery trainee at the University College of London Queen Square Institute of Neurology and a Royal College of Surgeons “Emerging Leaders” program laureate. Her presentation title will be: “Microstructural and connectivity correlates of outcome variability in functional neurosurgery for movement disorders”. Birte Forstmann, PhD, is the Director of the Amsterdam Brain and Cognition Center, a Professor of Cognitive Neuroscience at the University of Amsterdam, and a Professor by Special Appointment of Neuroscientific Testing of Psychological Models at the University of Leiden. Besides her scientific presentation (“Imaging the human subcortex”), she will give us a glimpse at the “Person behind the science”. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!

Astrocyte reprogramming / activation and brain homeostasis

Astrocytes are multifunctional glial cells, implicated in neurogenesis and synaptogenesis, supporting and fine-tuning neuronal activity and maintaining brain homeostasis by controlling blood-brain barrier permeability. During the last years a number of studies have shown that astrocytes can also be converted into neurons if they force-express neurogenic transcription factors or miRNAs. Direct astrocytic reprogramming to induced-neurons (iNs) is a powerful approach for manipulating cell fate, as it takes advantage of the intrinsic neural stem cell (NSC) potential of brain resident reactive astrocytes. To this end, astrocytic cell fate conversion to iNs has been well-established in vitro and in vivo using combinations of transcription factors (TFs) or chemical cocktails. Challenging the expression of lineage-specific TFs is accompanied by changes in the expression of miRNAs, that post-transcriptionally modulate high numbers of neurogenesis-promoting factors and have therefore been introduced, supplementary or alternatively to TFs, to instruct direct neuronal reprogramming. The neurogenic miRNA miR-124 has been employed in direct reprogramming protocols supplementary to neurogenic TFs and other miRNAs to enhance direct neurogenic conversion by suppressing multiple non-neuronal targets. In our group we aimed to investigate whether miR-124 is sufficient to drive direct reprogramming of astrocytes to induced-neurons (iNs) on its own both in vitro and in vivo and elucidate its independent mechanism of reprogramming action. Our in vitro data indicate that miR-124 is a potent driver of the reprogramming switch of astrocytes towards an immature neuronal fate. Elucidation of the molecular pathways being triggered by miR-124 by RNA-seq analysis revealed that miR-124 is sufficient to instruct reprogramming of cortical astrocytes to immature induced-neurons (iNs) in vitro by down-regulating genes with important regulatory roles in astrocytic function. Among these, the RNA binding protein Zfp36l1, implicated in ARE-mediated mRNA decay, was found to be a direct target of miR-124, that be its turn targets neuronal-specific proteins participating in cortical development, which get de-repressed in miR-124-iNs. Furthermore, miR-124 is potent to guide direct neuronal reprogramming of reactive astrocytes to iNs of cortical identity following cortical trauma, a novel finding confirming its robust reprogramming action within the cortical microenvironment under neuroinflammatory conditions. In parallel to their reprogramming properties, astrocytes also participate in the maintenance of blood-brain barrier integrity, which ensures the physiological functioning of the central nervous system and gets affected contributing to the pathology of several neurodegenerative diseases. To study in real time the dynamic physical interactions of astrocytes with brain vasculature under homeostatic and pathological conditions, we performed 2-photon brain intravital imaging in a mouse model of systemic neuroinflammation, known to trigger astrogliosis and microgliosis and to evoke changes in astrocytic contact with brain vasculature. Our in vivo findings indicate that following neuroinflammation the endfeet of activated perivascular astrocytes lose their close proximity and physiological cross-talk with vasculature, however this event is at compensated by the cross-talk of astrocytes with activated microglia, safeguarding blood vessel coverage and maintenance of blood-brain integrity.

Trends in NeuroAI - Meta's MEG-to-image reconstruction

Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri). This will be an informal journal club presentation, we do not have an author of the paper joining us. Title: Brain decoding: toward real-time reconstruction of visual perception Abstract: In the past five years, the use of generative and foundational AI systems has greatly improved the decoding of brain activity. Visual perception, in particular, can now be decoded from functional Magnetic Resonance Imaging (fMRI) with remarkable fidelity. This neuroimaging technique, however, suffers from a limited temporal resolution (≈0.5 Hz) and thus fundamentally constrains its real-time usage. Here, we propose an alternative approach based on magnetoencephalography (MEG), a neuroimaging device capable of measuring brain activity with high temporal resolution (≈5,000 Hz). For this, we develop an MEG decoding model trained with both contrastive and regression objectives and consisting of three modules: i) pretrained embeddings obtained from the image, ii) an MEG module trained end-to-end and iii) a pretrained image generator. Our results are threefold: Firstly, our MEG decoder shows a 7X improvement of image-retrieval over classic linear decoders. Second, late brain responses to images are best decoded with DINOv2, a recent foundational image model. Third, image retrievals and generations both suggest that MEG signals primarily contain high-level visual features, whereas the same approach applied to 7T fMRI also recovers low-level features. Overall, these results provide an important step towards the decoding - in real time - of the visual processes continuously unfolding within the human brain. Speaker: Dr. Paul Scotti (Stability AI, MedARC) Paper link: https://arxiv.org/abs/2310.19812

Current and future trends in neuroimaging

With the advent of several different fMRI analysis tools and packages outside of the established ones (i.e., SPM, AFNI, and FSL), today's researcher may wonder what the best practices are for fMRI analysis. This talk will discuss some of the recent trends in neuroimaging, including design optimization and power analysis, standardized analysis pipelines such as fMRIPrep, and an overview of current recommendations for how to present neuroimaging results. Along the way we will discuss the balance between Type I and Type II errors with different correction mechanisms (e.g., Threshold-Free Cluster Enhancement and Equitable Thresholding and Clustering), as well as considerations for working with large open-access databases.

Inducing short to medium neuroplastic effects with Transcranial Ultrasound Stimulation

Sound waves can be used to modify brain activity safely and transiently with unprecedented precision even deep in the brain - unlike traditional brain stimulation methods. In a series of studies in humans and non-human primates, I will show that Transcranial Ultrasound Stimulation (TUS) can have medium- to long-lasting effects. Multiple read-outs allow us to conclude that TUS can perturb neuronal tissues up to 2h after intervention, including changes in local and distributed brain network configurations, behavioural changes, task-related neuronal changes and chemical changes in the sonicated focal volume. Combined with multiple neuroimaging techniques (resting state functional Magnetic Resonance Imaging [rsfMRI], Spectroscopy [MRS] and task-related fMRI changes), this talk will focus on recent human TUS studies.

Neural Mechanisms of Subsecond Temporal Encoding in Primary Visual Cortex

Subsecond timing underlies nearly all sensory and motor activities across species and is critical to survival. While subsecond temporal information has been found across cortical and subcortical regions, it is unclear if it is generated locally and intrinsically or if it is a read out of a centralized clock-like mechanism. Indeed, mechanisms of subsecond timing at the circuit level are largely obscure. Primary sensory areas are well-suited to address these question as they have early access to sensory information and provide minimal processing to it: if temporal information is found in these regions, it is likely to be generated intrinsically and locally. We test this hypothesis by training mice to perform an audio-visual temporal pattern sensory discrimination task as we use 2-photon calcium imaging, a technique capable of recording population level activity at single cell resolution, to record activity in primary visual cortex (V1). We have found significant changes in network dynamics through mice’s learning of the task from naive to middle to expert levels. Changes in network dynamics and behavioral performance are well accounted for by an intrinsic model of timing in which the trajectory of q network through high dimensional state space represents temporal sensory information. Conversely, while we found evidence of other temporal encoding models, such as oscillatory activity, we did not find that they accounted for increased performance but were in fact correlated with the intrinsic model itself. These results provide insight into how subsecond temporal information is encoded mechanistically at the circuit level.

Trends in NeuroAI - SwiFT: Swin 4D fMRI Transformer

Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri). Title: SwiFT: Swin 4D fMRI Transformer Abstract: Modeling spatiotemporal brain dynamics from high-dimensional data, such as functional Magnetic Resonance Imaging (fMRI), is a formidable task in neuroscience. Existing approaches for fMRI analysis utilize hand-crafted features, but the process of feature extraction risks losing essential information in fMRI scans. To address this challenge, we present SwiFT (Swin 4D fMRI Transformer), a Swin Transformer architecture that can learn brain dynamics directly from fMRI volumes in a memory and computation-efficient manner. SwiFT achieves this by implementing a 4D window multi-head self-attention mechanism and absolute positional embeddings. We evaluate SwiFT using multiple large-scale resting-state fMRI datasets, including the Human Connectome Project (HCP), Adolescent Brain Cognitive Development (ABCD), and UK Biobank (UKB) datasets, to predict sex, age, and cognitive intelligence. Our experimental outcomes reveal that SwiFT consistently outperforms recent state-of-the-art models. Furthermore, by leveraging its end-to-end learning capability, we show that contrastive loss-based self-supervised pre-training of SwiFT can enhance performance on downstream tasks. Additionally, we employ an explainable AI method to identify the brain regions associated with sex classification. To our knowledge, SwiFT is the first Swin Transformer architecture to process dimensional spatiotemporal brain functional data in an end-to-end fashion. Our work holds substantial potential in facilitating scalable learning of functional brain imaging in neuroscience research by reducing the hurdles associated with applying Transformer models to high-dimensional fMRI. Speaker: Junbeom Kwon is a research associate working in Prof. Jiook Cha’s lab at Seoul National University. Paper link: https://arxiv.org/abs/2307.05916

Prefrontal mechanisms involved in learning distractor-resistant working memory in a dual task

Working memory (WM) is a cognitive function that allows the short-term maintenance and manipulation of information when no longer accessible to the senses. It relies on temporarily storing stimulus features in the activity of neuronal populations. To preserve these dynamics from distraction it has been proposed that pre and post-distraction population activity decomposes into orthogonal subspaces. If orthogonalization is necessary to avoid WM distraction, it should emerge as performance in the task improves. We sought evidence of WM orthogonalization learning and the underlying mechanisms by analyzing calcium imaging data from the prelimbic (PrL) and anterior cingulate (ACC) cortices of mice as they learned to perform an olfactory dual task. The dual task combines an outer Delayed Paired-Association task (DPA) with an inner Go-NoGo task. We examined how neuronal activity reflected the process of protecting the DPA sample information against Go/NoGo distractors. As mice learned the task, we measured the overlap between the neural activity onto the low-dimensional subspaces that encode sample or distractor odors. Early in the training, pre-distraction activity overlapped with both sample and distractor subspaces. Later in the training, pre-distraction activity was strictly confined to the sample subspace, resulting in a more robust sample code. To gain mechanistic insight into how these low-dimensional WM representations evolve with learning we built a recurrent spiking network model of excitatory and inhibitory neurons with low-rank connections. The model links learning to (1) the orthogonalization of sample and distractor WM subspaces and (2) the orthogonalization of each subspace with irrelevant inputs. We validated (1) by measuring the angular distance between the sample and distractor subspaces through learning in the data. Prediction (2) was validated in PrL through the photoinhibition of ACC to PrL inputs, which induced early-training neural dynamics in well-trained animals. In the model, learning drives the network from a double-well attractor toward a more continuous ring attractor regime. We tested signatures for this dynamical evolution in the experimental data by estimating the energy landscape of the dynamics on a one-dimensional ring. In sum, our study defines network dynamics underlying the process of learning to shield WM representations from distracting tasks.

A synergistic core for human brain evolution and cognition

Virtual Brain Twins for Brain Medicine and Epilepsy

Over the past decade we have demonstrated that the fusion of subject-specific structural information of the human brain with mathematical dynamic models allows building biologically realistic brain network models, which have a predictive value, beyond the explanatory power of each approach independently. The network nodes hold neural population models, which are derived using mean field techniques from statistical physics expressing ensemble activity via collective variables. Our hybrid approach fuses data-driven with forward-modeling-based techniques and has been successfully applied to explain healthy brain function and clinical translation including aging, stroke and epilepsy. Here we illustrate the workflow along the example of epilepsy: we reconstruct personalized connectivity matrices of human epileptic patients using Diffusion Tensor weighted Imaging (DTI). Subsets of brain regions generating seizures in patients with refractory partial epilepsy are referred to as the epileptogenic zone (EZ). During a seizure, paroxysmal activity is not restricted to the EZ, but may recruit other healthy brain regions and propagate activity through large brain networks. The identification of the EZ is crucial for the success of neurosurgery and presents one of the historically difficult questions in clinical neuroscience. The application of latest techniques in Bayesian inference and model inversion, in particular Hamiltonian Monte Carlo, allows the estimation of the EZ, including estimates of confidence and diagnostics of performance of the inference. The example of epilepsy nicely underwrites the predictive value of personalized large-scale brain network models. The workflow of end-to-end modeling is an integral part of the European neuroinformatics platform EBRAINS and enables neuroscientists worldwide to build and estimate personalized virtual brains.

The melanopsin mosaic: exploring the diversity of non-image forming retinal ganglion cells

In this talk, I will focus on recent work that has uncovered the diversity of intrinsically photosensitive retinal ganglion cells (ipRGCs). These are a unique type of retinal ganglion cell that contains the photopigment melanopsin. ipRGCs are the retinal neurons responsible for driving non-imaging forming behaviors and reflexes, such as circadian entrainment and pupil constriction, amongst many others. My lab has recently focused on uncovering the diversity of ipRGCs, their distribution throughout the mammalian retina, and their axon projections in the brain.

From primate anatomy to human neuroimaging: insights into the circuits underlying psychiatric disease and neuromodulation; Large-scale imaging of neural circuits: towards a microscopic human connectome

On Thursday, October 26th, we will host Anastasia Yendiki and Suzanne Haber. Anastasia Yendiki, PhD, is an Associate Professor in Radiology at the Harvard Medical School and an Associate Investigator at the Massachusetts General Hospital and Athinoula A. Martinos Center. Suzanne Haber, PhD, is a Professor at the University of Rochester and runs a lab at McLean hospital at Harvard Medical School in Boston. She has received numerous awards for her work on neuroanatomy. Beside her scientific presentation, she will give us a glimpse at the “Person behind the science”. The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!

The role of CNS microglia in health and disease

Microglia are the resident CNS macrophages of the brain parenchyma. They have many and opposing roles in health and disease, ranging from inflammatory to anti-inflammatory and protective functions, depending on the developmental stage and the disease context. In Multiple Sclerosis, microglia are involved to important hallmarks of the disease, such as inflammation, demyelination, axonal damage and remyelination, however the exact mechanisms controlling their transformation towards a protective or devastating phenotype during the disease progression remains largely unknown until now. We wish to understand how brain microglia respond to demyelinating insults and how their behaviour changes in recovery. To do so we developed a novel histopathological analysis approach in 3D and a cell-based analysis tool that when applied in the cuprizone model of demyelination revealed region- and disease- dependent changes in microglial dynamics in the brain grey matter during demyelination and remyelination. We now use similar approaches with the aim to unravel sensitive changes in microglial dynamics during neuroinflammation in the EAE model. Furthermore, we employ constitutive knockout and tamoxifen-inducible gene-targeting approaches, immunological techniques, genetics and bioinformatics and currently seek to clarify the specific role of the brain resident microglial NF-κB molecular pathway versus other tissue macrophages in EAE.

Use of brain imaging data to improve prescriptions of psychotropic drugs - Examples of ketamine in depression and antipsychotics in schizophrenia

The use of molecular imaging, particularly PET and SPECT, has significantly transformed the treatment of schizophrenia with antipsychotic drugs since the late 1980s. It has offered insights into the links between drug target engagement, clinical effects, and side effects. A therapeutic window for receptor occupancy is established for antipsychotics, yet there is a divergence of opinions regarding the importance of blood levels, with many downplaying their significance. As a result, the role of therapeutic drug monitoring (TDM) as a personalized therapy tool is often underrated. Since molecular imaging of antipsychotics has focused almost entirely on D2-like dopamine receptors and their potential to control positive symptoms, negative symptoms and cognitive deficits are hardly or not at all investigated. Alternative methods have been introduced, i.e. to investigate the correlation between approximated receptor occupancies from blood levels and cognitive measures. Within the domain of antidepressants, and specifically regarding ketamine's efficacy in depression treatment, there is limited comprehension of the association between plasma concentrations and target engagement. The measurement of AMPA receptors in the human brain has added a new level of comprehension regarding ketamine's antidepressant effects. To ensure precise prescription of psychotropic drugs, it is vital to have a nuanced understanding of how molecular and clinical effects interact. Clinician scientists are assigned with the task of integrating these indispensable pharmacological insights into practice, thereby ensuring a rational and effective approach to the treatment of mental health disorders, signaling a new era of personalized drug therapy mechanisms that promote neuronal plasticity not only under pathological conditions, but also in the healthy aging brain.

Learning with multimodal enrichment

BrainLM Journal Club

Connor Lane will lead a journal club on the recent BrainLM preprint, a foundation model for fMRI trained using self-supervised masked autoencoder training. Preprint: https://www.biorxiv.org/content/10.1101/2023.09.12.557460v1 Tweeprint: https://twitter.com/david_van_dijk/status/1702336882301112631?t=Q2-U92-BpJUBh9C35iUbUA&s=19

Quality of life after DBS; Non-motor effects of DBS and quality of life

It’s our pleasure to announce that we will host Haidar Dafsari and Günther Deuschl on September 28th at noon ET / 6PM CET. Haidar Dafsari, MD, is a researcher and lecturer at the University Hospital Cologne. Günther Deuschl, MD, PhD, is a professor at Kiel University. He was president of the International Movement Disorders Society (MDS) from 2011-2013, Editor in Chief of the journal Movement Disorders and has been awarded numerous high-class awards. Beside his scientific presentation, he will give us a glimpse at the “Person behind the science”.The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!

Controlled sampling of non-equilibrium brain dynamics: modeling and estimation from neuroimaging signals

Bernstein Conference 2024

Equal contribution of place cells and non-place cells to the position decoding from one-photon imaging calcium transients

Bernstein Conference 2024

Towards predicting Stroke Etiology from MRI and CT Imaging Data of Ischemic Stroke Patients

Bernstein Conference 2024

Automated processing of calcium imaging videos for densely labeled dendritic and somatic ROIs

COSYNE 2022

A latent model of calcium activity outperforms alternatives at removing behavioral artifacts in two-channel calcium imaging

COSYNE 2022

A latent model of calcium activity outperforms alternatives at removing behavioral artifacts in two-channel calcium imaging

COSYNE 2022

Calcium imaging-based brain-computer interface for investigating long-term neuronal code dynamics

COSYNE 2023

Improved estimation of latent variable models from calcium imaging data

COSYNE 2023

maskNMF: a denoise-sparsen-detect pipeline for demixing dense imaging data faster than real time

COSYNE 2023

On-line SEUDO for real-time cell recognition in Calcium Imaging

COSYNE 2023

Computation Within and Beyond the Brain - Uncovering Brain-Body-Wide Communication Networks through Imaging Cellular Activity of All Cells in a Vertebrate

COSYNE 2025

3D-imaging reveals conserved cerebrospinal fluid drainage via meningeal lymphatic vasculature in mice and humans

The 6-zone track: A novel spatial memory test for awake head-fixed Ca2+ imaging

Activity alterations of various brain regions in Alcohol intoxicated drivers: a systematic review and Meta analysis of functional magnetic resonance imaging studies

Ante-mortem magnetic resonance imaging grey-white matter contrast regional signatures of Alzheimer’s disease neuropathology

A Calcium Imaging Based Brain-Machine Interface for Virtual Navigation

Calcium imaging to determine the pathogenic effects of NMDAR antibodies in autoimmune encephalitis

Capturing dynamics of inhibitory synaptic connectivity underlying learning using in vivo two-photon optical imaging of hippocampal CA1

Characterisation of the neural correlates of central sensitisation induced by the high frequency stimulation (HFS) model in healthy humans using functional magnetic resonance imaging (fMRI)

Characterisation of seizure-spreading depolarisation interactions in awake-headfixed mice using multisite graphene solution-gated field effect transistor arrays combined with Ca2+ imaging

Characterization of brain networks using functional ultrasound imaging

Characterizing patterns of dendritic activity in awake behaving mice using Arboreal Scanning, a multiscale 3D imaging approach

Chronic functional ultrasound imaging combined with behavior tracking on freely moving rats performing spatial exploration

CITE-On: Cell Identification and Trace Extraction Online in functional two-photon calcium imaging

Combining high-resolution functional Ultrasound (fUS)- and fMRI-imaging in the same human subject

Comparing clearing methods and imaging procedures in light sheet microscopy

Cortical deficit in discrimination between communication sounds in a mouse lacking two-pore channels: a calcium imaging and electrophysiological study

Cost function masking artificially inflates group level differences in processing of magnetic resonance imaging data for pathological patient populations

A custom cranial window implant for long-term whole-brain functional ultrasound imaging in behaving mice

Deciphering neuronal and synaptic architecture using new methods for labeling, imaging and segmenting neuronal cells via Standard and Super Resolution Microscopy

Deep brain imaging of axon initial segment dynamics during associative fear learning

Detection of cerebral aneurysm and intracranial vertebral dissection using non-enhanced magnetic resonance imaging in emergency setting: emphasis on magnitude image of susceptibility-weighted image

Dual color imaging in freely-behaving rodents using head-mountable one photon miniscope

Elucidating the neuronal population code of sound location at the inferior colliculus of awake mice using a fast volumetric calcium imaging approach

Encoding of spatial long term memories in a neural network: understanding fear generalization with miniscope calcium imaging

Evaluation of repetitive mild traumatic brain injury by fluorescence and FDG PET imaging

Examining dendritic plasticity of the barrel cortex layer 4 neurons via in vivo high spatiotemporal-resolution imaging

Fiber photometry imaging of locus coeruleus norepinephrine activities for studying neuromodulatory spatiotemporal dynamics across sleep and wakefulness

A flexible two-photon endoscope for fast activity imaging and cell-precise optogenetic photo-stimulation of neurons in freely moving animals

Calcium imaging-based brain-computer interface in freely behaving mice

Bernstein Conference 2024