- Comp-neuro - lists.cnsorg.org

Tutorial "Using open tools to build efficient workflows for data access, management and analysis" at CNS*2023
by Michael Denker 05 Jul '23

05 Jul '23

We would like to take the opportunity to invite you to our hands-on tutorial titled "Using open tools to build efficient workflows for data access, management and analysis" which will be held in the morning tutorial session on July 15, 2023 of this year's CNS*2023 conference in Leipzig, Germany (https://www.cnsorg.org/cns-2023) The tutorial is open to all registered participants, and assumes only basic experience with the Python programming language. Tutorial materials will be made available during the session. In order to interactively follow the tutorials online, we suggest to create a free EBRAINS account (https://www.ebrains.eu/page/sign-up) in advance. Synopsis: Neuroscientists today face challenges in managing the growing volume and complexity of data generated through rapid technological and methodological advancements and sophisticated experimental paradigms. Data management tools and methods provide indispensable solutions for researchers to efficiently handle, organize, and analyze datasets, facilitating model validation, refinement, and simulation, while fostering collaborations. This tutorial presents examples combining multiple tools synergistically into a complete digitized workflow to help researchers manage and control data and analysis processes. - GIN is a platform for version-controlled (git and git-annex) data management and collaboration. It supports any file types and folder structure, provides web and command-line access, provides an option for local installation, and services including format validation and data publication (DOI). - odML is an open, lightweight, and flexible format that provides a common schema (with implementations in XML, JSON, and YAML) to collect, organize and share metadata in a human- and machine-readable way. - NIX is a lean data model and file format for storing fully annotated scientific datasets, i.e., the data together with rich metadata (odML) and their relations in a consistent, comprehensive format. - Neo provides programmatic data objects for working with and representing electrophysiological data and can read data from many proprietary formats. In combination with NIX, Neo makes electrophysiological data interoperable with generic analysis scripts, tools, and services. - Elephant provides a large portfolio of standard and advanced methods for analyzing data from neuronal spike trains or time series data, such as LFPs. The Neo data model makes them easily accessible to scientists and applications. - Alpaca enables simple capture of human-readable provenance of the data processing workflow. Organizers: - Reema Gupta, Faculty of Biology, Ludwig-Maximilians-Universität München - Moritz Kern, Institute of Neuroscience and Medicine (INM-6/10), Jülich Research Centre - Michael Denker, Institute of Neuroscience and Medicine (INM-6/10), Jülich Research Centre - Thomas Wachtler, Faculty of Biology, Ludwig-Maximilians-Universität München

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Fully funded PhD fellowships in computational neurosciences (Benoit Cottereau’s team, Cerco, CNRS UMR 5549 in Toulouse and IPAL IRL 2955 in Singapore) on spatial cognition with spiking neural networks
by COTTEREAU Benoît 05 Jul '23

05 Jul '23

Fully funded PhD fellowships in computational neurosciences (Benoit Cottereau’s team, Cerco, CNRS UMR 5549 in Toulouse and IPAL IRL 2955 in Singapore) on spatial cognition with spiking neural networks Starting date: Second semester of 2023 Supervisors: Benoit Cottereau, research director at CNRS (Contact: benoit.cottereau(a)cnrs.fr<mailto:benoit.cottereau@cnrs.fr>), in close collaboration with Robby Tan, associate professor at National University of Singapore (NUS) Keywords: Computational neurosciences, Spatial cognition, Artificial intelligence (AI), Vision, Spiking neural networks, Event-based cameras. Fully funded PhD fellowships are available to work at the CNRS (Cerco laboratory in Toulouse and also IPAL in Singapore) under the supervision of Benoit Cottereau (CNRS research director), in close collaboration with Robby Tan (assistant professor at NUS, Singapore). The aim of the project is to develop computational models of spatial cognition in humans (e.g., for depth/motion perception or navigation). In order to reproduce the very low energy consumption of visual information processing in biological systems, these models will be based on spiking-neural networks (SNNs) and will process data collected from event-based cameras. These models will be evaluated with respect to biological data (their responses will be compared to those observed in neural recordings and/or in behavioural experiments). The candidates should be willing to work in an international environment which involves Singapore and France, have a good level in English, very good programming skills and be interested in neurobiology. Some knowledge in neurosciences/ cognitive sciences would be a plus. The research will mainly take place in Toulouse, a student city (Toulouse is the second university hub in France) with high quality of life located in the south west of France (close to the Pyrenees, the Mediterranean Sea and the Spanish border). Long stays in Singapore (a multicultural and attractive city of south-east Asia) are also planned. Each of the three positions will be fully funded during the three years of the PhD, with standard French salaries. Applications should be sent to benoit.cottereau(a)cnrs.fr<mailto:benoit.cottereau@cnrs.fr>, including a CV and 2 names of references. **************************************************************************************************** Benoit R. Cottereau, PhD, HDR, CNRS Research director (DR2) at the Brain and Cognition Research Center (CerCo, CNRS, UMR 5549, Toulouse): http://cerco.cnrs.fr/page-benoit-cottereau/ Director of the SV3M team (Spatial Vision in Man, Monkey and Machine): http://cerco.cnrs.fr/en/sv3m-spatial-vision-in-man-monkey-machine/ Supervisor of the Integrative Neurosciences master program of Toulouse III University e-mail: benoit.cottereau(a)cnrs.fr phone: (+33)-5-62744520

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PLOS Complex Systems is coming!
by Hocine Cherifi 04 Jul '23

04 Jul '23

View this email in your browser <https://view.e.plos.org/?qs=dee8047ee42f8224301af96522f8b69a270a53ce74ede07…> [image: PLOS] <https://click.e.plos.org/?qs=e061474313b570c1a547d4ee8221ae589c93c76242c1d0…> *Announcing PLOS Complex Systems* *A new home for complex systems research that transcends disciplines* Dr Cherifi, We’re proud to announce *PLOS Complex Systems*, a forthcoming new journal to complement our existing portfolio and continue our mission to support research communities around the globe. *PLOS Complex Systems* <https://click.e.plos.org/?qs=e061474313b570c1405def8d96d43bf81f83b9b03ed88c…> will publish research of broad significance that untangles the complex systems at the heart of the world we live in. Open Science options at every stage of research communication facilitate new connections that inspire ideas and accelerate progress across disciplines while cross-fertilizing knowledge that enable solutions to fundamental challenges facing our society today. Find out more <https://click.e.plos.org/?qs=e061474313b570c1405def8d96d43bf81f83b9b03ed88c…> [image: Hocine Cherifi] *“I am thrilled to be part of the launch of *PLOS Complex Systems*, a significant step forward in understanding the intricacies of our world. This journal has the power to break down disciplinary boundaries and encourage researchers to approach problems holistically. Together, we have the opportunity to shape the future of complex systems research and make a lasting impact on scientific understanding and societal progress.”* *- Hocine Cherifi, Editor-in-Chief* Want to learn more?Find out more about the scope of *PLOS Complex Systems*, our Editor-in-Chief, and other relevant journal information on our website. Start here <https://click.e.plos.org/?qs=e061474313b570c1405def8d96d43bf81f83b9b03ed88c…>

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Postdoc at NYU
by Grace Lindsay 03 Jul '23

03 Jul '23

The Lindsay Lab is hiring a postdoc! Work in the lab focuses on using artificial neural networks as models of the brain. A potential postdoc should be interested in working on a project that could fit into either of the first two research areas listed here: https://lindsay-lab.github.io/research/ (specifically, modeling attention in artificial neural networks or testing tools of neural analysis on artificial neural networks). To apply, send a CV, half page project proposal & contact info for 3 references to grace.lindsay(a)nyu.edu with subject "Postdoc Application" -- Grace Lindsay Assistant Professor, Psychology & Data Science New York University gracewlindsay.com lindsay-lab.github.io *Models of the Mind: How Physics, Engineering and Mathematics Have Shaped Our Understanding of the Brain* <https://gracewlindsay.com/2021/02/10/models-of-the-mind-how-physics-enginee…>

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PhD candidate on machine learning for normative modeling of functional brain activity -1 fte 4 years
by Mostafa Kia 03 Jul '23

03 Jul '23

Dear Colleagues, We are excited to announce an excellent opportunity for an enthusiastic Ph.D. candidate to join our team at the computation psychiatry group at the Department of cognitive science and artificial intelligence, Tilburg University. We are currently seeking a candidate to undertake normative modeling on big MEG/EEG data, a captivating research area with vast potential for precision psychiatry. As a Ph.D. candidate in this role, you will have the chance to apply state-of-the-art machine learning techniques on big MEG/EEG data, contributing to the advancement of our understanding of the biological underpinnings of mental disorders. Your research will focus on responsible normative modeling, allowing for valuable insights and potential applications of machine learning for precision psychiatry. We are looking for a candidate who possesses a strong background in machine learning, probabilistic data modeling, and neuroimaging. Proficiency in data analysis techniques, programming skills, and experience with MEG/EEG data will be advantageous. For more information regarding this vacancy, please consult the original call at https://www.academictransfer.com/en/329751/phd-candidate-on-machine-learnin… . Best regards, Seyed Mostafa Kia <https://research.tilburguniversity.edu/en/persons/seyed-mostafa-kia>, PhD Assistant Professor Department of Cognitive Science & Artificial Intelligence <http://www.csai.nl/> Tilburg School of Humanities and Digital Sciences Warandelaan 2, 5037 AB, Tilburg, The Netherlands

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PhD position Bioengineering and Robotics: Early vision function in silico networks of LIF neurons | PSPC Labs Genoa, ITALY
by Silvio P. Sabatini 01 Jul '23

01 Jul '23

Applications are invited for one full-time PhD studentship for a period of 3 years, at the Department of Informatics, Bioengineering, Robotics, and System Engineering (DIBRIS), University of Genoa, Italy. The position will start on Nov 1st, 2023 on the following research project: **Early vision function in silico networks of LIF neurons** One approach to understanding implications of the initial stages of visual processing is ideal observer analysis, which evaluates the information available to support psychophysical discriminations at various stages of the early visual representation. Computational approaches primarily rely on simple generative models, which do not take into account the distinctive properties of individual elementary channels, as well as the active nature of the input sensory pattern. Accordingly, many details remain underrated, as well as their implications on functional vision not fully understood. The project's goal is to develop an “artificial observer” composed of an active event-based camera feeding a neuromorphic multi-layer network of leaky integrate and fire (LIF) neurons. The system should provide the inference engines for relating visual representations to performance on perceptual judgement tasks. Multiple and varying parameters captured under complex, real-life conditions should be comparatively assessed in silicon and human observers. The research will be conducted at the Bioengineering/PSPC labs of DIBRIS. Applicants are expected to: (1) have a Master’s degree in Bioengineering, Computer Science, Physics or related disciplines, (2) have a keen interest in Vision Science and in Artificial Intelligence, (3) have good programming skills in at least one language (MATLAB, C/C++, Python, C#), (4) work well in group problem solving situations, (5) have intermediate communication skills (oral and written in English). Experience in neural modeling is a plus. Prospective students, please contact Silvio P. Sabatini ( silvio.sabatini(a)unige.it) providing your CV and qualifications, the name and contact details of two references, and a description of your research interests. *Online application is possible till *July 10th , 2023 (12:00 a.m. CET)** Full details on the call and the application procedure are available at: https://unige.it/en/students/phd-programmes https://biorob.phd.unige.it/how-to-apply Regards, -- -- --------------------------------------------------------------------- Silvio P. SABATINI, PhD [PSPC Research Group] DIBRIS - University of Genova | e_mail: silvio.sabatini(a)unige.it Via Opera Pia, 13 | phone: +39 010 33 52092 I-16145 Genova (ITALY) | fax: +39 010 33 56533 URL: http://pspc.unige.it --------------------------------------------------------------------- "Imagination is more important than knowledge..." [Albert Einstein]

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DPG - Bad Honnef Physics School on "Physics of Viruses" this September
by Viola Priesemann 28 Jun '23

28 Jun '23

Dear all, we are organizing a Bad Honnef Physics School on "Physics of Viruses" from September 10th till 15th 2023. - This school will cover all aspects of the physics of viruses, from their molecular architecture and assembly through to virus transmission, spread and evolution. We have put together a diverse program with world-renowned speakers, which also includes tutorials and time for discussions and networking. The physics center in Bad Honnef is a fantastic venue for such events and participation fees are very affordable (200 EUR, 100 EUR for DPG-members, covering board and lodging for one week at the Physikzentrum at Bad Honnef, which is close to Bonn and beautifully located at the Rhine). We very much look forward to interacting with interested master students, PhD-students, postdocs and even more senior researchers! You may also bring a poster on your own work and/or contribute a short presentation. More information and the schedule for the school can be found here : https://www.dpg-physik.de/veranstaltungen/2023/physics_of_viruses?set_langu…. Space is limited, so please secure your spot at the school as soon as possible. We very much look forward to welcoming you in Bad Honnef! Best regards, Ulrich Schwarz and Sarah Köster PS: PIs, please forward this email to your group members! https://www.dpg-physik.de/veranstaltungen/2023/physics_of_viruses?set_langu… ---------------------- Tel. +49 (2224) 9232-0 Fax +49 (2224) 9232-50 E-Mail: dpg(a)dpg-physik.de www.dpg-physik.de www.linkedin.com/company/dpgphysik www.facebook.com/DPGPhysik www.instagram.com/DPGPhysik www.youtube.com/DPGPhysikTV Deutsche Physikalische Gesellschaft e. V. Geschäftsstelle, Hauptstraße 5, 53604 Bad Honnef Hauptgeschäftsführer: Dr. Bernhard Nunner Eingetragen beim Vereinsregister des Amtsgerichts Siegburg unter Registernummer VR 90474

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NEURON, NetPyne, and TREES at OCNS 2023 in Leipzig
by McDougal, Robert 27 Jun '23

27 Jun '23

Join us at CNS 2023 in Leipzig on July 15th for the tutorial T01: Building mechanistic multiscale models with NEURON, NetPyNE, and TREES. NEURON is a simulator for neurons and networks of neurons with strong support for morphologically detailed models. TREES is a toolbox for working with morphologies, and NetPyNE is an abstraction layer on top of NEURON to facilitate the specification of large network models. We will talk about both basic and new features. This tutorial will be highly interactive, focusing on cloud-based examples for the NEURON and NetPyNE portions. Registration for the tutorials at CNS 2023 is required and can be done at: https://ocns.memberclicks.net/cns-2023-registration Speakers include: Bill Lytton, Robert McDougal, Thomas Künzel, Hermann Cuntz, Adam Newton, and Salvador Dura-Bernal. Full details are available at: https://cns2023.sched.com/event/150df23f7af1dcca6e55694eba15bf83 Hope to see you there!

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Apply now for the Computational Neuroscience Imbizo 2024 - form closes 11th July
by Christopher Currin 27 Jun '23

27 Jun '23

Dear all, The DEADLINE for the next IMBIZO is approaching very quickly. Don’t let this opportunity slip by if you are hoping to join the most diverse neuroscience summer school at the most beautiful beach in the world! If you know anyone who would benefit from an extraordinary computational neuroscience summer school, please distribute this information as widely as you can: IBRO-SIMONS COMPUTATIONAL NEUROSCIENCE IMBIZO #Imbizo2024 7 January - 28 January 2024, Noordhoek Beach, Cape Town, South Africa http://imbizo.africa/ Application deadline: 11th July 2023 The #Imbizo2024 is a southern hemisphere summer school aiming to promote computational neuroscience in Africa. It will bring together international and local students under the tutelage of the world's leading experts in the field. Like its international sister courses, this four-week summer school aims to teach central ideas, methods, and practices of modern computational neuroscience through a combination of lectures and hands-on project work. Mornings will be devoted to lectures on topics across the breadth of computational neuroscience, including experimental underpinnings and machine learning analogues. The rest of the day will be spent working on research projects under the close supervision of expert tutors and faculty. Individual research projects will focus on the modelling of neurons, neural systems, behaviour, the analysis of state-of-the-art neural data, and the development of theories to explain experimental observations. It also includes a week focused on neuroscience-inspired machine learning! Who should apply? This course is aimed at Masters and early-PhD level students though Honours or advanced undergraduates may also apply. Postdoctoral students who can motivate why the course would benefit them are also encouraged to apply, Students should have sufficient quantitative skills, (e.g. a background in mathematics, physics, computer science, statistics, engineering or related field). Some knowledge of neural biology will be useful but not essential. Experimental neuroscience students are encouraged to apply, but should ensure that they have a reasonable level of quantitative proficiency (i.e. at least second-year level mathematics or statistics and have done at least one course in computer programming). Essential details * Fee (which covers tuition, lodging, and meals): 1350 EUR Thanks to our generous sponsors, significant financial assistance is available to reduce and waiver fees for students, particularly for African applicants. We also hope to provide some travel bursaries for international students. If you are in need of financial assistance to attend the Imbizo, please state so clearly in the relevant section of your application. The Imbizo is planned to be hosted in person, with everyone following our COVID policy <https://imbizo.africa/covid-policy/>. If it is unsafe to hold the summer school, we will follow up with further information at the appropriate time. * Application deadline: 11th July 2023 * References submitted: 14th July 2023 * Notification of results: August 2023 Information and application https://imbizo.africa/ Questions? isicn.imbizo(a)gmail.com What is an Imbizo? \ɪmˈbiːzɒ\ | Xhosa - Zulu A gathering of the people to share knowledge. Incl. past FACULTY and TAs such as... Adrienne Fairhall - Washington University Alex Pouget - University of Geneva Anne-Marie Oswald - University of Pittsburgh Annik Carson - AI Redefined Arif Hamid - University of Minnesota Medical School Aza Allsop - Yale University Bard Ermentrout - University of Pittsburgh Bianca Jones Marlin - Columbia University Blake Richards - McGill University Brent Doiron - University of Chicago Cengiz Pehlevan - Harvard University Christopher Currin - Institute of Science and Technology Austria & IndabaX South Africa Daniela Vallentin - Max Planck Institute for Biological Intelligence David Sussillo - Google Demba Ba - Harvard University Dongyan Lin - MILA Evan Schaffer - Columbia University Franck Kalume - University of Washington Grace Lindsay - New York University Guillaume Lajoie - University of Montreal & MILA Henning Sprekeler - Technical University of Berlin Ilenna Jones - Harvard University Joseph Raimondo - University of Cape Town Mackenzie Mathis - EPFL Lausanne Marjorie Xie - Columbia University Mohamed Abdelhack - Krembil Centre for Neuroinformatics Nina Kudryashova- University of Edinburgh Peter Latham - University College London Rachael Dangarembizi - University of Cape Town Roy Eyono - MILA Spiros Chavlis - IMBB-FORTH SueYeon Chung - New York University Thomas Tagoe - University of Ghana Tim Vogels - Institute of Science and Technology Austria Timothy Lillicrap - DeepMind Xaq Pitkow - Baylor College of Medicine ORGANISERS Demba Ba (Harvard University) Christopher Currin (Institute of Science and Technology Austria & IndabaX South Africa <https://indabax.co.za>) Peter Latham (Gatsby Unit for Computational Neuroscience) Joseph Raimondo (University of Cape Town) Emma Vaughan (Imbizo Logistics) Tim Vogels (Institute of Science and Technology Austria) Sponsors The Imbizo is made possible by the generous support from the Simons Foundation <https://www.simonsfoundation.org/>, the International Brain Research Organisation (IBRO) <https://ibro.org/> as well as the Wellcome Trust, Google Deep Mind and others. Organizational Affiliates University of Cape Town, University College London, Institute of Science and Technology Austria, TReND in Africa <http://trendinafrica.org/>, Neuroscience Institute <http://www.neuroscience.uct.ac.za/>, Gatsby Foundation <http://www.gatsby.org.uk/>, IBRO African Center for Advanced Training in Neurosciences at UCT

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Open research training: Open Seeds mentoring & training program is open for application until July 2023
by Mayya Sundukova 26 Jun '23

26 Jun '23

Dear all, The next cohort of Open Seeds OLS-8 is open for application! Open Seeds is a Mentoring & Training Programme run by OLS, designed for people interested in applying open principles in their work and becoming Open Science ambassadors in their communities. The program is free but requires registration in OpenReview and an application with a project where you would like to apply open skills. More information: https://openlifesci.org/ The deadline to apply is on July 7th, with a decision made in August and the cohort starting in mid-September 2023. On the 28th of June OLS will run an open webinar “Application Clinic (Q&A)” where interested participants can ask the OLS team any questions about their applications to the program. If you have not thought about a project and application, this can be an excellent opportunity to learn more about the program and get inspired https://www.eventbrite.co.uk/e/application-clinic-call-qa-tickets-660976427… . Help us share about the Open Seeds OLS-8 call in your network. More about Open Seeds Purpose: Training for individuals and teams interested in furthering their Open Science skills in any area of research and community projects. Process: Online 16-week with online cohort calls and mentor-based individual support to help participants in integrating open science practices in their work and in the long term become Open Science ambassadors in their community. Open leaders from Open Seeds OLS programme are - taught essential knowledge required to create, lead, and sustain an Open Science project. - connected with members across different communities, backgrounds, and identities by creating space in this program for them to share their experiences and expertise. - empowered to become effective Open Science ambassadors in their communities. *Examples of projects you can bring:* Please see our previous cohorts for a full list of projects that have been developed in OLS: OLS1 <https://openlifesci.org/ols-1/projects-participants/>, OLS-2 <https://openlifesci.org/ols-2/projects-participants/>, OLS-3 <https://openlifesci.org/ols-3/projects-participants/>, OLS-4 <https://openlifesci.org/ols-4/projects-participants/>, OLS-5 <https://openlifesci.org/ols-5/projects-participants/>, OLS-6 <https://openlifesci.org/ols-6/projects-participants/> and OLS-7 <https://openlifesci.org/ols-7/projects-participants/> - Researchers and data scientists: applying open, reproducible and FAIR principles to their current research, data management plan, collaborative workflow design, tooling and roadmapping, the publication of research outcome, a side project they are working on, an app they are building for social good, a prototype they want to further enhance etc. - Business team members: collaborative projects with the researcher, public engagement, dissemination of research output, community engagement, survey and feedback collection, infrastructure design, resource hosting services etc. - Support staff members: data management, reproducible workflow, FAIRification of research components (training, data, web source etc.), support documents for their colleagues, participatory & citizen science - Community/project managers: community-building skills, community development project, collaborative research, training and education opportunity etc. To learn more about the program and process of application, you can check the recording of the application launch call from the previous cohorts on the OLS YouTube channel: https://youtu.be/shM2mVyLjxU For additional details, feel free to reach out to the Open Life Science team at: team(a)openlifesci.org. We are also on social media: - Twitter: https://twitter.com/openlifesci - Linkedin: https://www.linkedin.com/company/openlifesci/ - Youtube channel with open educational resources: https://www.youtube.com/@OpenLifeSci <https://www.youtube.com/@OpenLifeSc>. We look forward to welcoming you in the next cohort. Best wishes, OLS Team

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