Laserlab-Europe’s Post

New Paper alert! Now published in Cell Press - @Current Biology 💥 📣 Resulting from a large collaboration between the Donders Institute for Brain, Cognition, and Behaviour, Bangor University, and Institut des Sciences Cognitives Marc Jeannerod, UMR 5229 CNRS !! In a set of experiments we bring evidence that the visual sensitivity to social interactions is supported by activity of a visual occipitotemporal region in the left hemisphere - i.e. the left Extrastriate Body Area (lEBA). We do this bringing converging evidence from multiple neuroscientific methods: via correlational methods (fMRI - functional magnetic resonance imaging) we show that activity of lEBA is associated with the perception of face-to-face human dyads stimuli; via causal methods (TMS - Transcranial magnetic brain stimulation) we crucially show that interfering online with this region reduces behavioural effects (replicated here in this study) indicative of such sensitivity to social interactions. Very proud of this collaboration with Etienne ABASSI Eva Balgova Paul Downing @Liuba Papeo Kami Koldewyn that went through pandemic-related disruptions and that - most importantly - closes the loop between brain activity and behaviour using correlational and causal methods!! Link: https://lnkd.in/dnPeU9fw

BioAmp EXG Pill is now available in pre-soldered version on almost all our online stores. A lot of students were finding it difficult to solder the header pins and JST Ph 2.0 connector on the BioAmp EXG Pill in order to start using it. So finally after a lot of requests we have decided to pre-solder everything before shipping it to the customers. List of all our online stores: https://buff.ly/3ugbl7r What do you think about this decision? Let us know in the comments! About BioAmp EXG Pill: It is a publication grade pill size sensor using which you can record and visualize various biopotential signals from your body be it from eyes (EOG), muscles (EMG), heart (ECG) or even brain (EEG). Students and researchers in more than 50 countries are using it to explore the field of neuroscience by making amazing HCI (Human Computer Interface) and BCI (Brain Computer Interface) projects. #upsidedownlabs #opensource #bci #hci #neuroscience

Math puzzles can trigger stress, but here's a study that leverages EEG signals from our #Enobio to delve into the changes in relative band power during both math tasks and relaxation. And how did the researchers achieve this? 🧮🤔 The EEG data from our Enobio was processed and analyzed, showing changes in #EEG relative band power during both math tasks and relaxation with audio-visual stimuli. 📊 Using Long Short Term Memory (LSTM) deep learning models, they achieved an impressive 86% accuracy in classifying mental states, especially in the beta band. Curious to dive deeper into this fascinating research? 📚 Check out the study here at IEEE: https://lnkd.in/dCvVJbkG Kudos to Rashmi C R and shantala cp from Channabasaveshwara Institute of Technology, Gubbi #research #medtech #Electroceuticals #Technology #Healthtech #Healthcare #Science #Innovation #Study #ResearchArticle #Neuroscience #Neurotechnology #Electroencephalography

Done & Dusted (4/4) 🚀 Excited to share that I've just completed the "Neuroscience and Neuro imaging" Specialization! 🎓 Special thanks to The Johns Hopkins University and instructors Tor Wager University of Colorado Arnold Bakker Martin Lindquist Elizabeth Sweeney Ciprian M. Crainiceanu John Muschelli III. This specialization combines the strength of 4 different neuroscience courses into a cohesive learning experience. Taught by Johns Hopkins University, it begins with fundamental neuroscience concepts for neuroimaging. Neuroimaging methods are used with increasing frequency in clinical practice and basic research. Starting with the neuroanatomy of the brain, it then moves into principles of neuroimaging, including experimental design in neuroimaging, functional connectivity MRI, diffusion tensor imaging and spectroscopy imaging. The specialization then continues with two courses that focus on Functional Magnetic Resonance Imaging, one of the most widely used techniques for investigating the living, functioning human brain as people perform tasks and experience mental states, and a convergence point for multidisciplinary work. To conclude, the specialization moves into implementation of neurohacking using the R programming language, with the associated packages to perform data manipulation, processing, and analysis of neuroimaging data, using publicly available structural MRI. Applied Learning Project Learners will go from fMRI data design, structure and acquisition to using the R programming language and its associated package to perform manipulation, processing, and analysis of neuroimaging data. Specifically, you will learn how to read/write images of the brain in NIfTI format, visualize and explore these images, perform inhomogeneity correction, brain extraction, and image registration (within a subject and to a template). Huge thanks to everyone involved in this amazing learning experience. Ready to apply these new skills and insights to advance our understanding of the brain! 🧠💡 #Neuroscience #fMRI #BrainResearch #ContinuousLearning #MultidisciplinaryScience #PublicHealth #MentalHealth #DataAnalysis #LifelongLearning

Using Raw EEG, researchers are finding ways to understand best how students learn visually by using real-time brain wave data. These neuroscience findings could help advance education research and help tailor education to different learning styles. See more of the research from Soyiba Jawed (Brno University of Technology/ Vysoké učení technické v Brně), Ibrahima Faye (Universiti Teknologi PETRONAS ), and Aamir Saeed Malik (Universiti Teknologi PETRONAS) at IEEE Early Access for TNSRE: https://lnkd.in/enskJPnN #EEG #deeplearning #Neuroscience #brainscience #neurotechnology

𝗛𝗼𝘄 𝘀𝘁𝗮𝗿-𝘀𝗵𝗮𝗽𝗲𝗱 𝗰𝗲𝗹𝗹𝘀 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗲 𝗳𝗹𝗲𝘅𝗶𝗯𝗹𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴: Star-shaped glial cells, so-called astrocytes, are more than just a supporting cell of the brain. They are actively involved in learning processes and interact with the nerve cells. But what exactly is it that astrocytes do? Researchers at the University Hospital Bonn (UKB) and the University of Bonn are using a biophysical model to clarify how astrocytes interact with nerve cells to regulate rapid adaptation to new information. The results of the study have now been published in the journal "Nature Communications Biology". 𝗥𝗲𝗮𝗱 𝗺𝗼𝗿𝗲: https://lnkd.in/eQEFtuhv Rheinische Friedrich-Wilhelms-Universität Bonn, Tatjana Tchumatchenko, Lorenzo Squadrani, Kirsten Bohmbach, Prof. Christian Henneberger

Wired to learn and remember New research unveils how spinal cord nerve cells can learn and remember—completely independent of the brain The role of the spinal cord is often simplified to that of a simple relay station, carrying messages between the brain and the body. However, the spinal cord can actually learn and remember movements on its own. A team of researchers at the Leuven-based Neuro-Electronics Research Flanders (NERF) details how two different neuronal populations enable the spinal cord to adapt and recall learned behavior in a way that is completely independent of the brain. These remarkable findings, published today in Science, shed new light on how spinal circuits might contribute to mastering and automating movement. The insights could prove relevant in the rehabilitation of people with spinal injuries.  https://lnkd.in/dw5sr8yd

A recent study titled "MindEye2: Shared-Subject Models Enable fMRI-To-Image With 1 Hour of Data," published on arXiv, has marked a significant milestone in the field of neuroscience and brain-computer interfaces. Led by Paul S. Scotti alongside a team of distinguished researchers, this innovative work introduces a revolutionary approach to reconstructing visual perception from brain activity. 🔍 Key Highlights: - Revolutionizing Efficiency: The MindEye2 model drastically reduces the need for extensive fMRI data collection, achieving high-quality visual reconstructions from just one hour of training data per subject. - Innovative Methodology: The research introduces a cutting-edge functional alignment procedure that maps brain data to a shared-subject latent space, then transitions through CLIP image space, and finally into pixel space, utilizing Stable Diffusion XL for the process. - Benchmark Setting Results: The study not only enhances generalization across subjects with limited data but also establishes new standards in image retrieval and reconstruction metrics. 🌐 Broader Impact and Accessibility: This study demonstrates the feasibility of accurate perception reconstructions from a single MRI session, potentially transforming the landscape of brain-computer interface research. Furthermore, the research team has made all related code publicly available on GitHub, encouraging further advancements in the field. 🔗 Explore the full study here: https://lnkd.in/dKqj6_ub This achievement represents a significant leap forward in our understanding and capability within brain-computer interfaces and neuroscience. Congratulations to Paul S. Scotti and the entire research team for their groundbreaking work and contribution to the future of technology and science. #BrainComputerInterface #Neuroscience #fMRI #VisualPerception

3D reconstruction of a piece of human brain to date, which is about half the size of a rice grain. What a breakthrough in Neuroscience! Excellent work done by #Harvard University and #Google 👨🔬 Scientists from Harvard University and Google teamed up to make a big leap in understanding the brain. They created a super detailed 3D map of a tiny piece of a human brain. This might sound small, but that tiny piece contains a ton of information - like 57,000 cells, 230 millimeters of blood vessels and 150 million synapses (connections), all amounting to 1,400 terabytes of data. This is the most detailed map of a human brain ever made. 🧠 A Harvard team led by Jeff Lichtman, the Jeremy R. Knowles Professor of Molecular and Cellular Biology and newly appointed dean of science, has co-created with Google researchers. These scientists have been working together for almost 10 years. They've used special microscopes and computer programs to image the brain and figure out how all the parts are connected. Their ultimate goal is to map an entire mouse brain, which would be much bigger and even more complex. Even though this map is from a tiny piece of brain, it shows some surprising things:- For example, they found some extra strong connections between cells and some unusual loops made by other brain parts. They're not sure if these are normal or because the brain came from someone with #epilepsy. This kind of research, called #connectomics, is like making a complete catalog of all the parts in your brain and how they're connected. By understanding the brain better, scientists hope to learn more about how we think and what goes wrong in brain diseases. A significant step forward in brain mapping! Researchers are now closer to creating a complete map of a mouse brain. #Neuroscience #BrainResearch #3DReconstruction #Breakthrough #Connectomics #Synapses #HarvardUniversity #GoogleResearch #Collaboration Thank you Harvard University and Google 🙏

Researchers at the Center for the Study of Movement, Cognition, and Mobility in the Neurological Institute at the Tel Aviv Medical Center carried out a Kaggle machine learning contest to improve the automated detection of freezing of gait (FOG). FOG occurs in many, but not all people who have Parkinson’s disease. People who have FOG report that their feet are “glued” to the ground. This negatively impairs their mobility and independence and often leads to falls and, eventually, confines the person to a wheelchair. The results of the contest were recently published in Nature Communications. The lead authors were Amit Salomon, Eran Gazit, and Jeff Hausdorff. The open-access paper is found here: https://lnkd.in/dTXiRD7a The paper includes a link to the Python code of the winners.  The work was funded by the Michael J Fox Foundation for Parkinson’s Research and Kaggle. Prof. Ronni Gamzu Eli Sprecher Jeff Hausdorff Amit Salomon Eran Gazit Galit Cohen Benjamin Soffer Haleli Sharir Rozin Ram #ParkinsonsDiseaseResearch #FreezeOfGait #MachineLearning #Neuroscience #MobilityImpairment