barriers

Increasing Lung Cancer Screening Uptake Among High-Risk Emergency Department Patients

PROJECT SUMMARY/ABSTRACT Lung cancer is the leading cause of cancer death in the US. Although lung cancer screening (LCS), using low- dose CT scan, decreases lung cancer mortality through early disease identification, fewer than 1 in 6 eligible individuals get screened, with significant differences based on demographic and socio-economic factors. LCS is a process, not just a test. The critical first steps in this process are (1) identification of high-risk individuals who are eligible for LCS, and (2) recruitment of these individuals into an LCS program. The Emergency Department (ED) setting is optimal for an intervention to promote LCS by accomplishing these steps. Individuals at high risk for lung cancer are over-represented in the ED population, including: individuals that smoke, non-White individuals, patients with lower education levels, and the under-insured. In fact, over 2.3 million high-risk people pass through EDs every year who are eligible for LCS but have never been screened. The investigators’ long-term goal is to develop a low-cost, scalable intervention that increases LCS uptake among ED patients and is deployable in any ED with a regionally referrable LCS program. The objective of the proposed randomized clinical trial is to test the efficacies of text messaging and a facilitated referral strategy to promote uptake of LCS in order to achieve this goal. Step 1 of the approach is to identify participants that are eligible for LCS. Step 2 is to randomize eligible participants, using a 2x2 design, among four study arms: (1) basic referral for LCS (i.e. verbal referral with written materials; comprising an enhanced control arm), (2) basic referral plus a subsequent series of text messages, grounded in behavioral change theory, aimed at generating intention and motivation to get screened, (3) facilitated referral for LCS (i.e. submission of a requisition to LCS program by staff), and (4) facilitated referral plus text messages. The investigators’ pilot work demonstrated the feasibility and efficacy of the proposed approach. A total of 1036 individuals eligible for LCS will be recruited from a high-volume urban ED and a low-volume rural ED, randomized among study arms, and followed-up at 120 days to assess interval LCS uptake. The Specific Aims of the proposed project are, (1) Compare LCS program uptake among study arms that receive text messages to study arms that do not, (2) Compare LCS program uptake among study arms with basic referral to study arms with facilitated referral, (3) Investigate the interaction between receipt of text messages (yes/no) and referral type (basic/facilitated), and (4) Evaluate participant feedback on (a) differential barriers to LCS across sub-groups and (b) acceptability and appropriateness of ED-based promotion of LCS. The study team is at the forefront of developing ED-based interventions to promote cancer screening. This project leverages the universal access setting of the ED to identify individuals at greatest risk for lung cancer and get them screened. A scalable ED-based intervention that increases LCS uptake would save lives.

FIRE-PF: Developing and Testing a Trauma-Informed Alcohol Intervention to Enhance Mental Health in Firefighters

PROJECT SUMMARY Alcohol use and hazardous drinking are ubiquitous among firefighters in the United states and is associated with significant physical and mental health risks for this population. Due to the nature of their work, firefighters experience substantially higher rates of trauma exposure and are subsequently at greater risk of developing specific mental health conditions compared to the general population, particularly trauma-related psychopathology (e.g., posttraumatic stress). Hazardous drinking and posttraumatic stress frequently co-occur among firefighters, leading to poorer health outcomes compared to either condition alone. Despite this elevated risk, firefighters often lack access to tailored, empirically supported interventions, and no existing mental health interventions address hazardous drinking in a trauma-informed framework for this at-risk population. Personalized feedback interventions (PFIs) are a promising approach that could address this gap. By delivering brief, patient-centered feedback on drinking behaviors and perceptions within the context of trauma and occupational stress, PFIs aim to reduce problematic drinking behaviors and stigma related to coping-orientated drinking and improve stress management strategies. PFIs can be brief, cost-effective, and easily disseminated in a format accessible to large groups, making them a strong candidate for use with firefighters who face critical barriers to engaging in traditional mental health programs. This innovative study aims to develop a single-session, trauma-informed, online PFI tailored specifically for firefighters, using a comprehensive, three-phase approach to address three primary aims. The Development Phase involves developing, adapting, and enhancing a trauma-informed PFI by gathering qualitative feedback from firefighters (N = 45) and using an iterative, rapid user-centered design approach to ensure the intervention is engaging for firefighters as well as relevant and aligned with fire service culture. The Evaluation Phase will assess the feasibility, acceptability, and preliminary impact of the PFI in a mixed-methods longitudinal open trial with firefighters (N = 50), with a focus on the intervention's usability, delivery, and influence on drinking behaviors. The Implementation Planning Phase will involve qualitative and quantitative assessments with fire service leaders (N = 15) to identify implementation barriers and shape future research testing the implementation process for the intervention and inform future strategies for resource integration and fostering sustainable community partnerships. This proposal will equip Dr. Lebeaut with essential training for an independent research career, including training in (1) qualitative methodologies, (2) user-centered design, (3) developing, adapting, and enhancing trauma-informed alcohol interventions, and (4) developing collaborative relationships with community partners in the fire service. The proposed study will directly inform a future R01 to evaluate the intervention’s efficacy and scalability and support the development of a firefighter-focused research program.

NeuroASCENT- Advancing Science through Career Enhancement and Neuroscience Training

The NeuroASCENT- Advancing Science through Career Enhancement and Neuroscience Training program will support neuroscience‑focused PhD students across multiple graduate programs by providing comprehensive scientific, professional, and research‑development training during their doctoral education. Strengthening the national neuroscience workforce requires ensuring that trainees have access to high‑quality research preparation, strong mentoring, and structured opportunities that enhance their scientific growth and career readiness. Recent analyses of U.S. doctoral recipients indicate that many talented trainees encounter barriers that limit full participation in research careers, underscoring the need for intentional support mechanisms that promote successful advancement. Over the last five years, CU Anschutz PhD programs have seen a substantial increase in students entering from a broad range of academic backgrounds. NeuroASCENT is designed to help these trainees progress efficiently by 1) promoting research excellence, 2) fostering leadership skills, 3) facilitating career development, and 4) providing individualized guidance. To achieve these goals, the program will provide career‑focused workshops, structured research externship opportunities, enhanced mentoring frameworks, and coordinated access to campus resources that extend beyond those offered by individual graduate programs. In partnership with the Office of Research Education, NeuroASCENT will complement and enhance the scientific training provided across biomedical PhD programs while offering added value to the broader CU Anschutz graduate community. Program Directors Dr. Quillinan and Dr. Hughes will oversee training activities, mentor matching, evaluation, program operations, and dissemination. An Institutional Advisory Board composed of research leaders will guide program oversight, and an External Advisory Board of graduate‑education experts will provide additional evaluation and strategic input. NeuroASCENT scholars will also serve on an Executive Advisory Board to develop leadership experience and contribute directly to program refinement. Trainees will typically enter the program after their second year of graduate training and will participate in activities focused on building a supportive peer/mentor network, strengthening scientific confidence and competence, and preparing for careers in academia, government, industry, or non‑profit research organizations.

From Evidence to Scale: Implementation Science and Simulation Modeling to Transform HIV-Hypertension Care Integration

Project Summary As HIV programs mature, cardiovascular disease (CVD) is becoming a leading contributor to morbidity and mortality. Integration of HIV and CVD prevention, with a focus on hypertension–the most prevalent and impactful modifiable CVD risk factor, presents an opportunity to build more robust primary health systems that improve health outcomes and advance health system sustainability–a key priority for the U.S. PEPFAR program. Using an expanded version of the HIV Synthesis microsimulation model—which incorporates hypertension and CVD outcomes—and data from the NHLBI-funded HLB-SIMPLe consortium’s cluster randomized trials in six African countries, we will evaluate the health effects, cost-effectiveness, and scalability of implementation strategies to promote HIV-hypertension integration to improve health outcomes for people with and without HIV under a range of health system constraints. Our first aim is to develop and validate an additional layer to HIV Synthesis model that accounts for health system constraints and implementation strategies for integration of HIV and hypertension care. This will include parameterization using data from the WHO Health System Building Blocks framework and empiric data from trials in the HLB-SIMPLe consortium. Our second aim is to evaluate the health effects and cost-effectiveness of implementation strategies for HIV-hypertension integration to identify the most effective and scalable approaches for settings with varying health system constraints representative of conditions in west, east, and southern Africa. Analyses will include scenarios targeting people with HIV and scaling up to the broader population. Our third aim focuses on engaging policymakers and program managers to promote uptake of findings through dissemination workshops and interactive modeling tools, with tailored model outputs to specific health system contexts. Using qualitative interviews with policymakers, we will use the Weiss schema for conceptualizing research utilization to assess model impact on decision-making. We will use the Translational Science Benefits Model, to capture, classify and conceptualize the clinical, policy, economic, and operational impacts and identify barriers and facilitators to use in country programs focused on HIV, hypertension, and related NCDs. The overarching project goal is to inform evidence-based, cost-effective implementation strategies for integrating NCD care into HIV platforms, improving population health outcomes in Africa and advancing implementation science through generalizable knowledge about the intersection of implementation strategies, health system strength, and service integration.

Implementing a New Paradigm for Antifungal Drug Development

About 30% of the drugs currently in clinical use function through covalent modification of their target. Yet, until recently, none of these covalent drugs were specifically designed to utilize this irreversible mode of action. It is our hypothesis that the production of a new class of covalent inactivators, designed to selectively modify new drug targets, will lead to novel agents with efficacy against both native and drug-resistant pathogenic fungal species. Because of their novelty these agents will also offer a greater opportunity to bypass the existing mechanisms of drug resistance. Pathogenic fungal infections remain among the leading causes of human mortality, and this threat is rising due to the increasing prevalence of drug- resistance strains and the paucity of effective antifungal drugs against the more virulent fungal species. Our proposed new drug target is an enzyme that plays a critical role in a uniquely microbial pathway that is essential for the survival of fungal organisms. To test our hypothesis and achieve the goals of this project we plan to complete the following specific aims during the initial R21 phase of this project: (1) Optimization of the potency of novel enzyme inactivators. Our goals here are to use our strong preliminary results to address critical barriers that must be overcome to convert potent enzyme inactivators into advanced drug candidates, thereby achieving higher target selectivity and increasing compound reactivity once bound to the target; (2) Enhance the antifungal capability of these enzyme inactivators. Our strategy for this aim is focused on the incorporation of conjugate partners into this new class of covalent inactivators, enabling them to potentially utilize the existing nutrient uptake systems to achieve toxic levels in Candida species; (3) Examine the target selectivity of our new antifungal agents. Results from fungal growth inhibition and fungal killing assays will be used to evaluate and rank the efficacy of our compounds against both wild-type and drug-resistant Candida strains. Specific milestones are presented to evaluate our achievement of these initial aims. Once accomplished we will immediately proceed to the R33 phase of this project, with the aims of: (4) Pharmacological evaluation of lead candidates, though ranking the drug candidates based on their ADME, pharmacokinetic and toxicity properties; and then (5) Evaluate the efficacy of our candidates against pathogenic fungal infections. A systematic infection animal model will be utilized for candidate screening to identify the best agents against disseminated fungal infections, followed by further efficacy screening in an oral infection model. Completion of these aims will produce, refine and evaluate a new class of antifungal agents with a novel mode of action against an unexplored but essential fungal target. The agents with the most promising drug profiles will then be moved into advanced preclinical trials used to select the most effective new antifungal agents.

RECONJOINT: A Preference Elicitation Tool to Improve Shared Decision Making for Breast Reconstruction Surgery

PROJECT SUMMARY/ABSTRACT Breast reconstruction is a critical component of comprehensive breast cancer care, offering physical and emotional restoration after mastectomy. However, 40% of women undergoing breast reconstruction report dissatisfaction and decisional regret due to low involvement with treatment decisions and poor alignment between treatment preferences and the chosen reconstructive technique. Current approaches to shared decision-making (SDM) often fail to elicit and integrate individual-level preferences into treatment planning. This serves as a barrier to effective SDM and patient-centered care. To address this gap, we developed a web- based decision tool that uses adaptive choice–based conjoint (ACBC) analysis to elicit patient-level preferences for breast reconstruction. Preliminary studies indicate that the decision tool is acceptable and usable; patients wanted to view their results and use the tool in clinic, which we could not accommodate at the time because the decision tool currently lacks a structured method for clinical integration. We propose to develop an implementation toolkit for the decision tool to facilitate clinical integration and then test the feasibility, acceptability, and implementation of the intervention, RECONJOINT (decision tool and toolkit). In Aim 1, we will design an implementation toolkit informed by focus groups and developed with input from key partners, including patients, providers, and patient advocates. Candidate elements for the implementation toolkit include components developed for site-level implementation: treatment preferences report, video introducing the tool and existing evidence, and recommendations for patients and providers to incorporate preferences into SDM. In Aim 2, we will evaluate the feasibility, acceptability, and preliminary efficacy of the intervention in a pilot cluster-randomized hybrid type 1 trial conducted at two cancer centers (Memorial Sloan Kettering and Duke University). Our primary outcome of interest is the feasibility of the intervention. Secondary outcomes include acceptability and preliminary efficacy. Using a hybrid design, we will simultaneously evaluate facilitators, barriers, and strategies to implementation and how these factors influence the feasibility and acceptability of the intervention. The Consolidated Framework for Implementation Research and the Theoretical Domains Framework will serve as conceptual frameworks. This study is innovative as it leverages ACBC analysis to elicit patient preferences, designs an intervention with multilevel input from clinical and community partners, and uses a hybrid trial design to simultaneously evaluate feasibility, acceptability, preliminary efficacy, and implementation. By addressing critical barriers to SDM and enhancing patient–provider communication, this research aligns with the goals of PA-25-253 and the National Cancer Plan to deliver high quality, patient-centered cancer care. Findings from this study will inform a full-scale multi-site trial to evaluate the efficacy of the intervention and implementation outcomes (e.g., reach).

OpenNeuro FitLins GLM: An Accessible, Semi-Automated Pipeline for OpenNeuro Task fMRI Analysis

In this talk, I will discuss the OpenNeuro Fitlins GLM package and provide an illustration of the analytic workflow. OpenNeuro FitLins GLM is a semi-automated pipeline that reduces barriers to analyzing task-based fMRI data from OpenNeuro's 600+ task datasets. Created for psychology, psychiatry and cognitive neuroscience researchers without extensive computational expertise, this tool automates what is largely a manual process and compilation of in-house scripts for data retrieval, validation, quality control, statistical modeling and reporting that, in some cases, may require weeks of effort. The workflow abides by open-science practices, enhancing reproducibility and incorporates community feedback for model improvement. The pipeline integrates BIDS-compliant datasets and fMRIPrep preprocessed derivatives, and dynamically creates BIDS Statistical Model specifications (with Fitlins) to perform common mass univariate [GLM] analyses. To enhance and standardize reporting, it generates comprehensive reports which includes design matrices, statistical maps and COBIDAS-aligned reporting that is fully reproducible from the model specifications and derivatives. OpenNeuro Fitlins GLM has been tested on over 30 datasets spanning 50+ unique fMRI tasks (e.g., working memory, social processing, emotion regulation, decision-making, motor paradigms), reducing analysis times from weeks to hours when using high-performance computers, thereby enabling researchers to conduct robust single-study, meta- and mega-analyses of task fMRI data with significantly improved accessibility, standardized reporting and reproducibility.

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.

Walk the talk: concrete actions to promote diversity in neuroscience in Latin America

Building upon the webinar "What are the main barriers to succeed in brain sciences in Latin America?" (February 2021) and the paper "Addressing the opportunity gap in the Latin American neuroscience community" (Silva, A., Iyer, K., Cirulli, F. et al. Nat Neurosci August 2022), this ALBA-IBRO Webinar is the next chapter in our journey towards fostering inclusivity and diversity in neuroscience in Latin America. The webinar is designed to go beyond theoretical discussions and provide tangible solutions. We will showcase 3-4 best practice case studies, shining a spotlight on real-life actions and campaigns implemented at the institutional level, be it within government bodies, universities, or other organisations. Our goal is to empower neuroscientists across Latin America by equipping them with practical knowledge they can apply in their own institutions and countries.

Integrating theory-guided and data-driven approaches for measuring consciousness

Clinical assessment of consciousness is a significant issue, with recent research suggesting some brain-damaged patients who are assessed as unconscious are in fact conscious. Misdiagnosis of consciousness can also be detrimental when it comes to general anaesthesia, causing numerous psychological problems, including post-traumatic stress disorder. Avoiding awareness with overdose of anaesthetics, however, can also lead to cognitive impairment. Currently available objective assessment of consciousness is limited in accuracy or requires expensive equipment with major barriers to translation. In this talk, we will outline our recent theory-guided and data-driven approaches to develop new, optimized consciousness measures that will be robustly evaluated on an unprecedented breadth of high-quality neural data, recorded from the fly model system. We will overcome the subjective-choice problem in data-driven and theory-guided approaches with a comprehensive data analytic framework, which has never been applied to consciousness detection, integrating previously disconnected streams of research in consciousness detection to accelerate the translation of objective consciousness measures into clinical settings.

Adaptive Deep Brain Stimulation: Investigational System Development at the Edge of Clinical Brain Computer Interfacing

Over the last few decades, the use of deep brain stimulation (DBS) to improve the treatment of those with neurological movement disorders represents a critical success story in the development of invasive neurotechnology and the promise of brain-computer interfaces (BCI) to improve the lives of those suffering from incurable neurological disorders. In the last decade, investigational devices capable of recording and streaming neural activity from chronically implanted therapeutic electrodes has supercharged research into clinical applications of BCI, enabling in-human studies investigating the use of adaptive stimulation algorithms to further enhance therapeutic outcomes and improve future device performance. In this talk, Dr. Herron will review ongoing clinical research efforts in the field of adaptive DBS systems and algorithms. This will include an overview of DBS in current clinical practice, the development of bidirectional clinical-use research platforms, ongoing algorithm evaluation efforts, a discussion of current adoption barriers to be addressed in future work.

NMC4 Keynote: Latent variable modeling of neural population dynamics - where do we go from here?

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 machine learning frameworks that enable inference of dynamics from neuronal population spiking activity on single trials and millisecond timescales, from diverse brain areas, and without regard to behavior. I will then demonstrate extensions that allow recovery of dynamics from two-photon calcium imaging data with surprising precision. Finally, I will discuss our efforts to facilitate comparisons within our field by curating datasets and standardizing model evaluation, including a currently active modeling challenge, the 2021 Neural Latents Benchmark [neurallatents.github.io].

NMC4 Panel: NMC Around the Globe

For the first time, we are holding a NMC around the globe session, a panel of computational neuroscientists working in different continents who are willing to discuss their challenges and milestones in doing science and training researchers in their home country. We hope that our panelists can share their barriers, what they define as accomplishments and how they would like the future of computational neuroscience to evolve locally and internationally with our diverse NMC audience.

NeurotechEU Summit

Our first NeurotechEU Summit will be fully digital and will take place on November 22th from 09:00 to 17:00 (CET). The final programme can be downloaded here. Hosted by the Karolinska Institutet, the summit will provide you an overview of our actions and achievements from the last year and introduce the priorities for the next year. You will also have the opportunity to attend the finals of the 3 minute thesis competition (3MT) organized by the Synapses Student Society, the student charter of NeurotechEU. Good luck to all the finalists: Lynn Le, Robin Noordhof, Adriana Gea González, Juan Carranza Valencia, Lea van Husen, Guoming (Tony) Man, Lilly Pitshaporn Leelaarporn, Cemre Su, Kaya Keleş, Ramazan Tarık Türksoy, Cristiana Tisca, Sara Bandiera, Irina Maria Vlad, Iulia Vadan, Borbála László, and David Papp! Don’t miss our keynote lecture, success stories and interactive discussions with Ms Vanessa Debiais Sainton (Head of Higher Education Unit, European Commission), Prof. Staffan Holmin (Karolinska Institutet), Dr Mohsen Kaboli (BMW Group, member of the NeurotechEU Associates Advisory Committee), and Prof. Peter Hagoort (Max Planck Institute for Psycholinguistics, Donders Institute). Would you like to use this opportunity to network? Please join our informal breakout sessions on Wonder.me at 11:40 CET. You will be able to move from one discussion group to another within 3 sessions: NeurotechEU ecosystem - The Associates Advisory Committee: Synergies in cross-sectoral initiatives Education next: Trans-European education and the European Universities Initiatives - Lessons learned thus far. Equality, diversity and inclusion at NeurotechEU: removing access barriers to education and developing a working, learning, and social environment where everyone is respected and valued. You can register for this free event at www.crowdcast.io/e/neurotecheu-summit

Understanding Perceptual Priors with Massive Online Experiments

One of the most important questions in psychology and neuroscience is understanding how the outside world maps to internal representations. Classical psychophysics approaches to this problem have a number of limitations: they mostly study low dimensional perpetual spaces, and are constrained in the number and diversity of participants and experiments. As ecologically valid perception is rich, high dimensional, contextual, and culturally dependent, these impediments severely bias our understanding of perceptual representations. Recent technological advances—the emergence of so-called “Virtual Labs”— can significantly contribute toward overcoming these barriers. Here I present a number of specific strategies that my group has developed in order to probe representations across a number of dimensions. 1) Massive online experiments can increase significantly the amount of participants and experiments that can be carried out in a single study, while also significantly diversifying the participant pool. We have developed a platform, PsyNet, that enables “experiments as code,” whereby the orchestration of computer servers, recruiting, compensation of participants, and data management is fully automated and every experiment can be fully replicated with one command line. I will demonstrate how PsyNet allows us to recruit thousands of participants for each study with a large number of control experimental conditions, significantly increasing our understanding of auditory perception. 2) Virtual lab methods also enable us to run experiments that are nearly impossible in a traditional lab setting. I will demonstrate our development of adaptive sampling, a set of behavioural methods that combine machine learning sampling techniques (Monte Carlo Markov Chains) with human interactions and allow us to create high-dimensional maps of perceptual representations with unprecedented resolution. 3) Finally, I will demonstrate how the aforementioned methods can be applied to the study of perceptual priors in both audition and vision, with a focus on our work in cross-cultural research, which studies how perceptual priors are influenced by experience and culture in diverse samples of participants from around the world.

Inclusive Human Participant Research

Human participant research is somehow both antithetical and complementary to science. On the one hand, working with human participants provides incredibly rich and complex data with ‘real-world’ ecological validity. On the other, this richness is due to the incredible number of variables which uncontrollably become intertwined with your research interest, potentially limiting the conclusions you can draw from your work. Historical over-representation of white men as research participants, coupled with often overly-stringent exclusion criteria has led to a diversity crisis in human participant research. For our research to be truly inclusive, representative and generalisable to the rest of the population, our data must be collected from diverse individuals. This session will explore common barriers to diversity in studies with human participants, and will provide guidance on how to make sure your own research is accessible and inclusive.

Analysis and manipulation of facilitators and barriers of cell identity reprogramming

ALBA Webinar in Latin America: What are the main barriers to succeed in brain sciences in Latin America?

ALBA is launching a webinar series focusing on region-specific issues linked to diversity and faced by underrepresented groups in brain research around the world. In this first webinar, ALBA focus on issues linked to diversity and faced by underrepresented groups in brain research in Latin America.

Emergence of long time scales in data-driven network models of zebrafish activity

How can neural networks exhibit persistent activity on time scales much larger than allowed by cellular properties? We address this question in the context of larval zebrafish, a model vertebrate that is accessible to brain-scale neuronal recording and high-throughput behavioral studies. We study in particular the dynamics of a bilaterally distributed circuit, the so-called ARTR, including hundreds neurons. ARTR exhibits slow antiphasic alternations between its left and right subpopulations, which can be modulated by the water temperature, and drive the coordinated orientation of swim bouts, thus organizing the fish spatial exploration. To elucidate the mechanism leading to the slow self-oscillation, we train a network graphical model (Ising) on neural recordings. Sampling the inferred model allows us to generate synthetic oscillatory activity, whose features correctly capture the observed dynamics. A mean-field analysis of the inferred model reveals the existence several phases; activated crossing of the barriers in between those phases controls the long time scales present in the network oscillations. We show in particular how the barrier heights and the nature of the phases vary with the water temperature.

Neuro-immune interactions in pain and host defense

The Chiu laboratory focuses on neuro-immune interactions in pain, itch, and tissue inflammation. Dr. Chiu’s research has uncovered molecular interactions between the nervous system, the immune system and microbes that modulates host defense. He has found that sensory neurons can directly detect bacterial pathogens and their toxins to produce pain. Neurons in turn release neuropeptides that modulate immune cells in host defense. These interactions occur at major tissue barriers in the body including the gut, skin and lungs. In this talk, he will discuss these major neuro-immune interactions and how understanding them could lead to novel approaches to treat pain or inflammation.

Open Neuroscience: Challenging scientific barriers with Open Source & Open Science tools

The Open Science movement advocates for more transparent, equitable and reliable science. It focusses on improving existing infrastructures and spans all aspects of the scientific process, from implementing systems that reward pre-registering studies and guarantee their publication, all the way to making research data citable and freely available. In this context, open source tools (and the development ethos supporting them) are becoming more and more present in academic labs, as researchers are realizing that they can improve the quality of their work, while cutting costs. In this talk an overview of OS tools for neuroscience will be given, with a focus on software and hardware, and how their use can bring scientific independence and make research evolve faster.