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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.
Norse: A library for gradient-based learning in Spiking Neural Networks
We introduce Norse: An open-source library for gradient-based training of spiking neural networks. In contrast to neuron simulators which mainly target computational neuroscientists, our library seamlessly integrates with the existing PyTorch ecosystem using abstractions familiar to the machine learning community. This has immediate benefits in that it provides a familiar interface, hardware accelerator support and, most importantly, the ability to use gradient-based optimization. While many parallel efforts in this direction exist, Norse emphasizes flexibility and usability in three ways. Users can conveniently specify feed-forward (convolutional) architectures, as well as arbitrarily connected recurrent networks. We strictly adhere to a functional and class-based API such that neuron primitives and, for example, plasticity rules composes. Finally, the functional core API ensures compatibility with the PyTorch JIT and ONNX infrastructure. We have made progress to support network execution on the SpiNNaker platform and plan to support other neuromorphic architectures in the future. While the library is useful in its present state, it also has limitations we will address in ongoing work. In particular, we aim to implement event-based gradient computation, using the EventProp algorithm, which will allow us to support sparse event-based data efficiently, as well as work towards support of more complex neuron models. With this library, we hope to contribute to a joint future of computational neuroscience and neuromorphic computing.
Blood phosphorylated tau as biomarkers for Alzheimer’s disease
Alzheimer's disease (AD) is the most common cause of dementia, and its health and socioeconomic burdens are of major concern. Presently, a definite diagnosis of AD is established by examining brain tissue after death. These examinations focus on two major pathological hallmarks of AD in the brain: (i) amyloid plaques consisting of aggregated amyloid beta (Aβ) peptides and (ii) neurofibrillary tangles made of abnormally phosphorylated tau protein. In living individuals, AD diagnosis relies on two main approaches: (i) brain imaging of tau tangles and Aβ plaques using a technique called positron emission tomography (PET) and (ii) measuring biochemical changes in tau (including phosphorylated tau at threonine-181 [p-tau181]) and the Aβ42 peptide metabolized into CSF. Unlike Aβ42, CSF p-tau181 is highly specific for AD but its usability is restricted by the need of a lumbar puncture. Moreover, PET imaging is expensive and only available in specialised medical centres. Due to these shortcomings, a simple blood test that can detect disease-related changes in the brain is a high priority for AD research, clinical care and therapy testing. In this webinar, I will discuss the discovery of p-tau biomarkers in blood and the biochemistry of how these markers differ from those found in CSF. Furthermore, I will critically review the performance of blood p-tau biomarkers across the AD pathological process and how they associate with and predict Aβ and tau pathophysiological and neuropathological changes. Furthermore, I will evaluate the potential advantages, challenges and context of use of blood p-tau in clinical practice, therapeutic trials and population screening.
An interdisciplinary perspective on motor augmentation from neuroscience and design
By studying the neural correlates of hand augmentation, we are exploring the boundaries of neuroplasticity seeing how it can be harnessed to improve the usability and control of prosthetic devices. Tamar Makin and Dani Clode each discuss their research and perspectives within the field of prosthetics that has led to this unique collaboration and exploration of motor augmentation and the brain.
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