- Comp-neuro - lists.cnsorg.org

CNS 2023 Tutorial on Dynamical Systems Methods
by Richard Gast 06 Jul '23

06 Jul '23

Dear members of the computational neuroscience community, I would like to draw your attention to a tutorial that Hil G.E. Meijer, Bastian Pietras, and I will offer at the first day of CNS 2023: "Applied Dynamical Systems Methods in Neuroscience''. In this tutorial, we will explain basic dynamical systems concepts and analysis methods at the example of single neurons, neural networks, and mean-field equations of neural networks. The main goals of the tutorial are (i) to provide the audience with an intuition of how neural systems can be studied via mathematical models, (ii) to explain how we can analyze parameter dependencies of these mathematical models, and (iii) to provide numerical recipes, and software solutions to carry out these analysis methods. For more details on the tutorial, have a look at our website: https://cns2023.sched.com/event/cbd810bd0ffd6a59869a5f89fbf17b58 If you are planning to participate in the hands-on sessions, I advise you to follow the preparation instructions on that website! See you in Leipzig, Richard Gast

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SUBMIT YOUR WORK TO COMPLEX NETWORKS 2023 BEFORE SEPT. 02, 2023
by Hocine Cherifi 06 Jul '23

06 Jul '23

*12* *th **International Conference on Complex Networks & Their Applications* Menton Riviera <https://www.menton-riviera-merveilles.co.uk/>, France November 28 - 30, 2023 COMPLEX NETWORKS 2023 <https://complexnetworks.org/> You are cordially invited to submit your contribution until *September 02, 2023*. *SPEAKERS* · Michael Bronstein <https://www.cs.ox.ac.uk/people/michael.bronstein/> University of Oxford UK · Kathleen Carley <https://www.cylab.cmu.edu/directory/bios/carley-kathleen.html> Carnegie Mellon University USA · Manlio De Domenico <https://manliodedomenico.com/> University of Padua Italy · Danai Koutra <http://web.eecs.umich.edu/~dkoutra/> University of Michigan USA · Romualdo Pastor-Satorras <http://www.fen.upc.edu/~romu/> Univ. Politècnica de Catalunya Spain · Tao Zhou <https://scholar.google.com/citations?user=MXgWgmEAAAAJ&hl=en> USTC China *TUTORIALS* · Tiago de Paula Peixoto <https://skewed.de/tiago> CEU Vienna Austria · Maria Liakata <https://www.turing.ac.uk/people/researchers/maria-liakata> Queen Mary University of London UK *PUBLICATION* Full papers (not previously published up to 12 pages) and Extended Abstracts (about published or unpublished research up to 4 pages) are welcome. · *Papers *will be included in the conference *proceedings edited by Springer* · *Extended abstracts* will be published in the *Book of Abstracts (with ISBN)* Extended versions will be invited for publication in *special issues of international journals:* o Applied Network Science <https://appliednetsci.springeropen.com/> edited by Springer o Advances in Complex Systems <https://www.worldscientific.com/toc/acs/24/02> edited by World Scientific o Complex Systems <https://www.complex-systems.com/about/> o Entropy <https://www.mdpi.com/journal/entropy> edited by MDPI o PLOS <https://journals.plos.org/plosone/> one <https://journals.plos.org/plosone/> o Social Network Analysis and Mining <https://link.springer.com/journal/13278> edited by Springer *SUBMISSION* https://complexnetworks.org/submission/ *TOPICS* *Topics include, but are not limited to: * o Models of Complex Networks o Structural Network Properties and Analysis o Epidemics o Community Structure o Motifs o Network Mining o Network embedding o Machine learning with graphs o Dynamics and Evolution Patterns of Complex Networks o Link Prediction o Multilayer Networks o Controllability o Synchronization o Visual Representation o Large-scale Graph Analytics o Social Reputation, Influence, and Trust o Information Spreading in Social Media o Rumour and Viral Marketing in Social Networks o Recommendation Systems o Financial and Economic Networks o Mobility o Biological and Technological Networks o Mobile call Networks o Bioinformatics o Earth Sciences Applications o Resilience and Robustness of Complex Networks o Networks for Physical Infrastructures o Networks, Smart Cities and Smart Grids o Political networks o Supply chain networks o Complex networks and information systems o Complex networks and CPS/IoT o Graph signal processing o Cognitive Network Science o Network Medicine o Network Neuroscience o Quantifying success through network analysis o Temporal and spatial networks o Historical Networks o Graph-Based Natural Language Processing *GENERAL CHAIRS* Hocine Cherifi (University of Burgundy, France) Luis M. Rocha (Binghamton University, USA)

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Announcing the fourth Canadian Computational Neuroscience Spotlight!
by Scott Rich 05 Jul '23

05 Jul '23

Dear Comp-Neuro mailing list members, We are pleased to announce the fourth edition of the Canadian Computational Neuroscience Spotlight (CCNS) <https://www.crowdcast.io/c/ccnsv4> will take place this fall, October 5 and 6. The meeting will once again take place entirely virtually using the Crowdcast platform, and parlay the savings from this virtual setting into no registration fees for attendees. CCNS was created in the immediate aftermath of the initial COVID-19 lockdowns, which caused the cancellation of multiple conferences within the Canadian neuroscience community. As one of the first brand-new meetings created with the virtual space in mind <https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008…>, CCNS distinguished itself by exploiting the online setting to engage an international audience, increase content accessibility through no registration fees and permanently available replays, and place an added spotlight on trainee contributions. Two successful follow-up editions of the meeting took place in 2021 and 2022. CCNSv4 will highlight three fantastic keynote speakers: Dr. Rick Adams <https://www.ucl.ac.uk/mental-health/mental-health-awareness-week/meet-dr-ri…>, Dr. Jeremie Lefebvre <https://www.uottawa.ca/brain/people/lefebvre-jeremie>, and Dr. Sarah Muldoon <https://www.buffalo.edu/cas/math/people/faculty/muldoon.html>. The keynote talks will be complemented by interactive workshop sessions led by our organizing committee. The remainder of the program will highlight trainee contributions, both through spotlighted talks and parallel sessions. The preliminary program can be seen after registration through the Crowdcast platform <https://www.crowdcast.io/c/ccnsv4>, and further details will be added to our homepage (ccnsmeeting.ca) in the coming weeks. Trainees interested in presenting are encouraged to first register for the conference via Crowdcast (crowdcast.io/c/ccnsv4 <https://www.crowdcast.io/c/ccnsv4>) and then complete this Google Form <https://docs.google.com/forms/d/e/1FAIpQLSeev-EA5ccwKapzRV43xD4NfDYGyDeAiWp…>. Submissions received by 5 p.m. EDT on September 1 will be considered for longer “spotlight” presentations. We anticipate all submissions that reasonably fall under the broad banner of “computational neuroscience” will be accepted unless demand far exceeds our expectations. A final schedule for the meeting, including the schedule of trainee talks, will be made available no later than September 18. Please feel free to reach out to the organizing committee if you have any questions about this meeting, and we look forward to seeing you at CCNSv4! Sincerely, The CCNS Organizing Committee: Scott Rich <http://scottrich.strikingly.com/>, Ph.D. Research Fellow, SickKids Research Institute. Andreea Diaconescu <https://cognemo.com/>, Ph.D. Independent Scientist, Krembil Center for Neuroinformatics at CAMH. John Griffiths <https://t.co/AlUQymEUae?amp=1>, Ph.D. Independent Scientist, Krembil Center for Neuroinformatics at CAMH. Milad Lankarany <https://sites.google.com/view/lnsbsp/home>, Ph.D. Scientist, Krembil Research Institute.

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Invitation for Hands-on Tutorial on PyNN at CNS*2023 Inbox
by CHITARANJAN MAHAPATRA 05 Jul '23

05 Jul '23

*Dear all,* *We are delighted to announce that a half-day tutorial titled "Hands-on Tutorial on PyNN: A Simulator-Independent Language for Building Neuronal Network Models" will be held at the 32nd Annual Computational Neuroscience Meeting (CNS*2023 conference) in Leipzig, Germany. We invite all registered participants to join the tutorial, which will take place on the first day of the meeting, 15 July 2023, just before the main event.* *Computational neuroscientists have developed a diversity of software platforms for simulating neural network models at different scales. However, each simulator has its own programming or configuration language, leading to considerable difficulty in porting models from one simulator to another. A common programming interface to multiple simulators would help to reduce or eliminate the problems of simulator diversity while retaining the benefits. PyNN is such an interface, making it possible to write a simulation script once, using the Python programming language, and run it without modification on any supported simulator (currently including NEURON, NEST, Brian, and the SpiNNaker and BrainScaleS neuromorphic hardware systems).* *Prerequisites:* *Basic familiarity with the Python programming language* *Useful links:* *Main website: https://ebrains.eu/service/pynn/ <https://ebrains.eu/service/pynn/>* *Documentation: http://neuralensemble.org/docs/PyNN/ <http://neuralensemble.org/docs/PyNN/>* *Download: https://pypi.org/project/PyNN/ <https://pypi.org/project/PyNN/>* *Organizers:* *Chitaranjan Mahapatra (Neuroinformatics Group, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, France)* *Shailesh Appukuttan (Neuroinformatics Group, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, France)* *Andrew Davison (Neuroinformatics Group, Paris-Saclay Institute of Neuroscience, CNRS, Paris-Saclay University, France)* *Speakers/Instructors:* *Chitaranjan Mahapatra, Speaker (Paris-Saclay Institute of Neuroscience, France)* *Nitin Anisetty, Instructor (Indian Institute of Technology Bombay, India)* *We also invite all tutorial participants to create a free EBRAINS account using an institutional email address. By doing so, you will gain complete access to EBRAINS tools and services.* *Best regards,* *Chitraranjan* ------------------------------------------------------------------------------------------------- Chitaranjan Mahapatra

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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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