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Postdoctoral Research Scientist, Ocean CDR Atlas
The nonprofit research organization [C]Worthy is recruiting a postdoctoral scientist to create a high-resolution Ocean CDR Atlas for the West Coast of North America. The role uses ROMS-MARBL regional models, tracer validation, sensitivity experiments and reproducible data workflows to lower the modeling burden for ocean carbon-removal monitoring and verification.
Trackoscope: A low-cost, open, autonomous tracking microscope for long-term observations of microscale organisms
Cells and microorganisms are motile, yet the stationary nature of conventional microscopes impedes comprehensive, long-term behavioral and biomechanical analysis. The limitations are twofold: a narrow focus permits high-resolution imaging but sacrifices the broader context of organism behavior, while a wider focus compromises microscopic detail. This trade-off is especially problematic when investigating rapidly motile ciliates, which often have to be confined to small volumes between coverslips affecting their natural behavior. To address this challenge, we introduce Trackoscope, an 2-axis autonomous tracking microscope designed to follow swimming organisms ranging from 10μm to 2mm across a 325 square centimeter area for extended durations—ranging from hours to days—at high resolution. Utilizing Trackoscope, we captured a diverse array of behaviors, from the air-water swimming locomotion of Amoeba to bacterial hunting dynamics in Actinosphaerium, walking gait in Tardigrada, and binary fission in motile Blepharisma. Trackoscope is a cost-effective solution well-suited for diverse settings, from high school labs to resource-constrained research environments. Its capability to capture diverse behaviors in larger, more realistic ecosystems extends our understanding of the physics of living systems. The low-cost, open architecture democratizes scientific discovery, offering a dynamic window into the lives of previously inaccessible small aquatic organisms.
Research Data Management in neuroimaging
This set of short webinars will provide neuroscience researchers working in a neuroimaging setting with practical tips on strengthening credibility at different stages of the research project. Each webinar will be hosted by Cassandra Gould Van Praag from the Wellcome Centre for Integrative Neuroimaging.
Data privacy for neuroimaging
This set of short webinars will provide neuroscience researchers working in a neuroimaging setting with practical tips on strengthening credibility at different stages of the research project. Each webinar will be hosted by Cassandra Gould Van Praag from the Wellcome Centre for Integrative Neuroimaging.
Preregistration in neuroimaging
This set of short webinars will provide neuroscience researchers working in a neuroimaging setting with practical tips on strengthening credibility at different stages of the research project. Each webinar will be hosted by Cassandra Gould Van Praag from the Wellcome Centre for Integrative Neuroimaging.
Toward an open science ecosystem for neuroimaging
It is now widely accepted that openness and transparency are keys to improving the reproducibility of scientific research, but many challenges remain to adoption of these practices. I will discuss the growth of an ecosystem for open science within the field of neuroimaging, focusing on platforms for open data sharing and open source tools for reproducible data analysis. I will also discuss the role of the Brain Imaging Data Structure (BIDS), a community standard for data organization, in enabling this open science ecosystem, and will outline the scientific impacts of these resources.
The future of neuropsychology will be open, transdiagnostic, and FAIR - why it matters and how we can get there
Cognitive neuroscience has witnessed great progress since modern neuroimaging embraced an open science framework, with the adoption of shared principles (Wilkinson et al., 2016), standards (Gorgolewski et al., 2016), and ontologies (Poldrack et al., 2011), as well as practices of meta-analysis (Yarkoni et al., 2011; Dockès et al., 2020) and data sharing (Gorgolewski et al., 2015). However, while functional neuroimaging data provide correlational maps between cognitive functions and activated brain regions, its usefulness in determining causal link between specific brain regions and given behaviors or functions is disputed (Weber et al., 2010; Siddiqiet al 2022). On the contrary, neuropsychological data enable causal inference, highlighting critical neural substrates and opening a unique window into the inner workings of the brain (Price, 2018). Unfortunately, the adoption of Open Science practices in clinical settings is hampered by several ethical, technical, economic, and political barriers, and as a result, open platforms enabling access to and sharing clinical (meta)data are scarce (e.g., Larivière et al., 2021). We are working with clinicians, neuroimagers, and software developers to develop an open source platform for the storage, sharing, synthesis and meta-analysis of human clinical data to the service of the clinical and cognitive neuroscience community so that the future of neuropsychology can be transdiagnostic, open, and FAIR. We call it neurocausal (https://neurocausal.github.io).
Sharing data from your in vivo studies
Handling data in your in vivo studies
Preregistering your in vivo studies
How evidence synthesis can boost in vivo credibility
As part of the BNA's ongoing Credibility in Neuroscience work, this series of three short webinars will provide neuroscience researchers working in an in vivo setting with tips on how to improve the credibility of their work. Each webinar will be hosted by Emily Sena, member of the BNA's Credibility Advisory Board, with the opportunity for questions.
Embracing variation to boost reproducibility
As part of the BNA's ongoing Credibility in Neuroscience work, this series of three short webinars will provide neuroscience researchers working in an in vivo setting with tips on how to improve the credibility of their work. Each webinar will be hosted by Emily Sena, member of the BNA's Credibility Advisory Board, with the opportunity for questions.
Improving reliability through design and reporting
As part of the BNA's ongoing Credibility in Neuroscience work, this series of three short webinars will provide neuroscience researchers working in an in vivo setting with tips on how to improve the credibility of their work. Each webinar will be hosted by Emily Sena, member of the BNA's Credibility Advisory Board, with the opportunity for questions.
How we can make 3D models more reproducible
The recent history of the replication crisis in psychology & how Open Science can be part of the solution
In recent years, more and more evidence has accumulated showing that many studies in psychological research cannot be replicated, effects are often overestimated, and little is publicly known about unsuccessful studies. What are the mechanisms behind this crisis? In this talk, I will explain how we got there and why it is still difficult to break free from the current system. I will further explain which role Open Science plays within the replication crisis and how it can help to improve science. This might sound like a pessimistic, negative talk, but I will end it on a positive note, I promise!
An open-source experimental framework for automation of cell biology experiments
Modern biological methods often require a large number of experiments to be conducted. For example, dissecting molecular pathways involved in a variety of biological processes in neurons and non-excitable cells requires high-throughput compound library or RNAi screens. Another example requiring large datasets - modern data analysis methods such as deep learning. These have been successfully applied to a number of biological and medical questions. In this talk we will describe an open-source platform allowing such experiments to be automated. The platform consists of an XY stage, perfusion system and an epifluorescent microscope with autofocusing. It is extremely easy to build and can be used for different experimental paradigms, ranging from immunolabeling and routine characterisation of large numbers of cell lines to high-throughput imaging of fluorescent reporters.
The problem of power in single-case neuropsychology
Case-control comparisons are a gold standard method for diagnosing and researching neuropsychological deficits and dissociations at the single-case level. These statistical tests, developed by John Crawford and collaborators, provide quantitative criteria for the classical concepts of deficit, dissociation and double-dissociation. Much attention has been given to the control of Type I (false positive) errors for these tests, but far less to the avoidance of Type II (false negative) errors; that is, to statistical power. I will describe the origins and limits of statistical power for case-control comparisons, showing that there are hard upper limits on power, which have important implications for the design and interpretation of single-case studies. My aim is to stimulate discussion of the inferential status of single-case neuropsychological evidence, particularly with respect to contemporary ideals of open science and study preregistration.
Reproducible EEG from raw data to publication figures
In this talk I will present recent developments in data sharing, organization, and analyses that allow to build fully reproducible workflows. First, I will present the Brain Imaging Data structure and discuss how this allows to build workflows, showing some new tools to read/import/create studies from EEG data structured that way. Second, I will present several newly developed tools for reproducible pre-processing and statistical analyses. Although it does take some extra effort, I will argue that it largely feasible to make most EEG data analysis fully reproducible.
The 3 Cs: Collaborating to Crack Consciousness
Every day when we fall asleep we lose consciousness, we are not there. And then, every morning, when we wake up, we regain it. What mechanisms give rise to consciousness, and how can we explain consciousness in the realm of the physical world of atoms and matter? For centuries, philosophers and scientists have aimed to crack this mystery. Much progress has been made in the past decades to understand how consciousness is instantiated in the brain, yet critical questions remain: can we develop a consciousness meter? Are computers conscious? What about other animals and babies? We have embarked in a large-scale, multicenter project to test, in the context of an open science, adversarial collaboration, two of the most prominent theories: Integrated information theory (IIT) and Global Neuronal Workspace (GNW) theory. We are collecting over 500 datasets including invasive and non-invasive recordings of the human brain, i.e.. fMRI, MEG and ECoG. We hope this project will enable theory-driven discoveries and further explorations that will help us better understand how consciousness fits inside the human brain.
Panel discussion: Practical advice for reproducibility in neuroscience
This virtual, interactive panel on reproducibility in neuroscience will focus on practical advice that researchers at all career stages could implement to improve the reproducibility of their work, from power analyses and pre-registering reports to selecting statistical tests and data sharing. The event will comprise introductions of our speakers and how they came to be advocates for reproducibility in science, followed by a 25-minute discussion on reproducibility, including practical advice for researchers on how to improve their data collection, analysis, and reporting, and then 25 minutes of audience Q&A. In total, the event will last one hour and 15 minutes. Afterwards, some of the speakers will join us for an informal chat and Q&A reserved only for students/postdocs.
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.