September 2021 - Comp-neuro - lists.cnsorg.org

Online workshop "Towards multipurpose neural network models II: Model testing and model fitting"
by Anton Arkhipov Sept. 14, 2021

Sept. 14, 2021

Dear Colleagues, Registration is now open for the online workshop "Towards multipurpose neural network models II: Model testing and model fitting" organized by Gaute Einevoll (NMBU/University of Oslo) and Anton Arkhipov (Allen Institute, Seattle) and supported by the European Institute for Theoretical Neuroscience (EITN). Please join us for three days of talks about cutting-edge science by fantastic speakers, as well as panel discussions. Dates: September 29 – October 1, 2021 Time: 8AM – 12:15PM US Pacific time / 5PM – 9:15PM Central European Time Daily. Registration: https://cnrs.zoom.us/webinar/register/WN_saMXfg31Roe4tqHbWtTdFg Please see the agenda below and more details at this web page: https://www.eitn.org/index.php/calendar-event/eventdetail/750/-/workshop-on… We hope to see you there! Wednesday, September 29, 2021 Gaute Einevoll (NMBU/U. Oslo) Introduction Jacob Macke (U. Tübingen) Keynote. Simulation-based inference: Bridging the gap between mechanistic models and machine learning. Aaron Milstein (Rutgers U.) Nested parallel simulation and multi-objective optimization of neuronal cell and circuit models Atle Rimehaug (U. Oslo) Enhancing model constraints by utilizing current source densities Kristin Tøndel (NMBU) Facilitating optimization using metamodelling Frances Skinner (Krembil Brain Institute, University Health Network, and University of Toronto) Clarity in model development and goals leads to model linkages and biological insights Panel debate – All participants of the day. Thursday, September 30, 2021 Anton Arkhipov (Allen Institute) Introduction James DiCarlo (MIT) Keynote. Reverse Engineering Visual Intelligence Sharon Crook (Arizona State U.) Testing the Data-driven Model Szabolcs Kali (Institute of Experimental Medicine, Budapest, Hungary) Systematic construction and evaluation of models of rodent hippocampal neurons Peter Jedlicka (U. Giessen) Building consistent and robust models of hippocampal granule cells and CA1 pyramidal cells Stefan Mihalas (Allen Institute) Computing with a mess: How nonstationary, heterogeneous and noisy components help the brain’s computational power Panel debate – All participants of the day. Friday, October 1, 2021 Markus Covert (Stanford) Special lecture. Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation Kanaka Rajan (Mount Sinai) Keynote. Data-constrained neural network models of adaptive learning in the brain Julijana Gjorgjeva (Max Planck Institute and TUM) Biologically plausible learning in developing networks Carsen Stringer (Janelia) Rastermap: Extracting structure from high-dimensional neural data Arvind Kumar (KTH Stockholm) Structure and activity dynamics relationship in biological neuronal networks: Measurements and models Panel debate – All participants of the day.

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PhD position in computational neuroscience/machine learning at UC Santa Barbara
by Michael Beyeler Sept. 14, 2021

Sept. 14, 2021

The Bionic Vision Lab lab at the University of California, Santa Barbara (UCSB) invites applications for a fully funded PhD position to develop computational models of neural activity in mice navigating through real-world and virtual environments. The successful candidate will have a strong quantitative background that includes machine learning, programming experience, and a thorough interest in neuroscience. This is an opportunity to work on an impactful real-world problem within a highly interdisciplinary and collaborative environment. Interested applicants should send a CV and transcript (unofficial is fine) to Michael Beyeler (mbeyeler(a)ucsb.edu) Official applications will have to be submitted through UCSB Grad Admissions before the application deadline indicated below. All genders welcome. Application deadline: December 1, 2021 Start date: Fall 2022 UCSB is a dynamic research institution, particularly in physical sciences and engineering, and was recently rated one of the Top 5 public schools in the United States (US News & World Report). Neuroscience research is well established here, featuring >35 faculty members whose research interests span the range from molecular to theoretical neuroscience.

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Call for community feedback on the endorsement of Neurolucida XML as a standard
by Malin Sandström Sept. 14, 2021

Sept. 14, 2021

Dear all, INCF is seeking community feedback and comments on the review of the MBF neuromorphological file format v 4.0, a format for digital reconstruction & modeling structure for microscopic anatomies, also known as “Neurolucida XML”, which has been submitted to INCF for endorsement as a community standard. If you have experience of using Neurolucida XML, we ask you to read the review report and comment based on your experiences, especially if you share or reuse data in the format, or work on models or tools that use the format. Link to the review: https://f1000research.com/documents/10-712 *Why endorse community standards? * INCF (incf.org) has implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. Our mission is to make neuroscience more open and FAIR, to ensure that research funds and efforts are well invested, and that neuroscientific findings are robust and replicable. Open community review is a very important step in the process. Quality community standards are necessary to make FAIR resources and processes work, but too many neuroscience communities lack robust standards or have competing incompatible standards. The rapid development of new techniques also means that there is a continuous need for new and updated standards, and that old standards need an active developer and user community keeping them up to date. By endorsing standards, INCF wants to make it easy to find the best, most reliable standard appropriate for your research, and ensure recognition for community members investing their time and effort in standards. The review criteria (https://incf.org/incf-standards-review-criteria-v20) include Openness; FAIRness; Design, Testing and Implementation; Governance; Adoption and use; Stability and support; Extensibility; Comparison (similarity to other standards). -- Malin Sandström, PhD Community Engagement Officer malin.sandstrom(a)incf.org ORCID: 0000-0002-8464-2494 International Neuroinformatics Coordinating Facility Karolinska Institutet Nobels väg 15 A SE-171 77 Stockholm Sweden http://www.incf.org

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workshop on Brain Criticality: The Past, the Present and the Future
by Claudius Gros Sept. 14, 2021

Sept. 14, 2021

You are invited to attend the upcoming Bernstein workshop on Brain Criticality: The Past, the Present and the Future https://www.bernstein-network.de/en/bernstein-conference/2021-online/satell… Tuesday, September 21, 2021, 2pm CEST It is free, but you need to register with the Bernstein conference (see link above). Claudius Gros ### ### Prof. Dr. Claudius Gros ### http://itp.uni-frankfurt.de/~gros ### ### Complex and Adaptive Dynamical Systems, A Primer ### A graduate-level textbook, Springer (2008/10/13/15) ### ### Life for barren exoplanets: The Genesis project ### https://link.springer.com/article/10.1007/s10509-016-2911-0 ###

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Bernstein Conference 2021 - abstracts are published
by Anja Dorrn Sept. 13, 2021

Sept. 13, 2021

Each year the Bernstein Network invites the international computational neuroscience community to the annual Bernstein Conference for intensive scientific exchange. It has established itself as one of the most renown conferences worldwide in this field, attracting students, postdocs and PIs from around the world to meet and discuss new scientific discoveries. Due to the ongoing pandemic the Bernstein Conference will be held online. www.bernstein-conference.de ____ IMPORTANT DATES & NEWS * Bernstein Conference: September 21-23, 2021 * Abstracts are published * Registration is open and free of charge * PhD Symposium on September 24, 2021 ____ ABSTRACTS All accepted abstracts are now published online and are citable via Digital Object Identifiers (DOI). Please find them here: https://abstracts.g-node.org/conference/BC21/abstracts#/ ____ REGISTRATION The participation at the online Bernstein Conference 2021 will be free of charge for all participants. Thus the Bernstein Network contributes to keep the scientific exchange alive in the ongoing challenges during the pandemic. Please register here: https://hopin.com/events/bernstein-conference-2021 ____ PHD SYMPOSIUM The Bernstein PhD Symposium on September 24, 2021 is an opportunity for junior researchers to meet their peers, share their experience and make new connections. This year's topic is Gaming meets neuroscience. Please register here: https://hopin.com/events/bernstein-phd-symposium-2021 ____ INVITED SPEAKERS Keynote Timothy Behrens (University of Oxford, UK) Invited Talks Athena Akrami (University College London, UK) Nadine Gogolla (Max Planck Institute for Neurobiology, Martinsried, Germany) Guillaume Hennequin (University of Cambridge, UK) Jennifer Li & Drew Robson (Max Planck Institute for Biological Cybernetics, Tübingen, Germany) Scott Lindermann (Stanford University, USA) Ashok Litwin-Kumar (Columbia University, New York City, USA) Ida Momennejad (Microsoft Research, New York City, USA) Cristina Savin (New York University, USA) Marion Silies (Johannes Gutenberg University, Mainz, Germany) Daniela Vallentin (Max Planck Institute for Ornithology, Seewiesen, Germany) ____ CONFERENCE COMMITTEE Christian Leibold (Conference Chair) Julijana Gjiorgjieva (Program Chair) Christian Machens (Program Vice Chair) Marion Silies (Workshop Chair) Moritz Helias (Workshop Vice Chair) & Matthew Botvinick, Megan Carey, Peter Dayan, Brent Doiron, Rainer Friedrich, Ann Hermundstad, Srdjan Ostojic, Nathalie Rochefort, Nicole Rust, Gasper Tkacik ____ For any further questions, please contact: bernstein.conference(a)fz-juelich.de -- Dr. Anja Dorrn Scientific Coordinator Bernstein Network Computational Neuroscience | Bernstein Coordination Site (BCOS) Branch Office of the Forschungszentrum Jülich at the University of Freiburg Hansastr. 9A | 79104 Freiburg, Germany phone: (+49) 0761 203 9589 web: www.bernstein-network.de<http://www.bernstein-network.de> ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Volker Rieke Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Dr. Astrid Lambrecht, Prof. Dr. Frauke Melchior ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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Biologically plausible models of path planning in humans and rodents
by Jeffrey Krichmar Sept. 10, 2021

Sept. 10, 2021

Dear Colleagues, We recently published two papers on biologically plausible models of path planning that simulate and analyze navigation strategies in rodents and humans. Some of the ideas presented in these papers may be applicable to autonomous systems. If you are interested, please see: Krichmar, J.L., and He, C. (2021). Importance of Path Planning Variability: A Simulation Study. Topics in Cognitive Science. https://onlinelibrary.wiley.com/doi/10.1111/tops.12568 Individuals vary in the way they navigate through space. Some take novel shortcuts, while others rely on known routes to find their way around. We wondered how and why there is so much variation in the population. To address this, we first compared the trajectories of 368 human subjects navigating a virtual maze with simulated trajectories. The simulated trajectories were generated by strategy-based path planning algorithms from robotics. Based on the similarities between human trajectories and different strategy-based simulated trajectories, we found that there is a variation in the type of strategy individuals apply to navigate space, as well as variation within individuals on a trial-by-trial basis. Moreover, we observed variation within a trial when subjects occasionally switched the navigation strategies halfway through a trajectory. In these cases, subjects started with a route strategy, in which they followed a familiar path, and then switched to a survey strategy, in which they took shortcuts by considering the layout of the environment. Then we simulated a second set of trajectories using five different but comparable artificial maps. These trajectories produced the similar pattern of strategy variation within and between trials. Furthermore, we varied the relative cost, that is, the assumed mental effort or required timesteps to choose a learned route over alternative paths. When the learned route was relatively costly, the simulated agents tended to take shortcuts. Conversely, when the learned route was less costly, the simulated agents showed preference toward a route strategy. We suggest that cost or assumed mental effort may be the reason why in previous studies, subjects used survey knowledge when instructed to take the shortest path. We suggest that this variation we observe in humans may be beneficial for robotic swarms or collections of autonomous agents during information gathering. Krichmar, J.L., Ketz, N.A., Pilly, P.K., and Soltoggio, A. (2021). Flexible Path Planning through Vicarious Trial and Error. bioRxiv, 2021.2009.2008.459317. https://www.biorxiv.org/node/2148912.abstract Flexible planning is necessary for reaching goals and adapting when conditions change. We introduce a biologically plausible path planning model that learns its environment, rapidly adapts to change, and plans efficient routes to goals. Unlike prior models of hippocamapl replay, our model addresses the decision-making process when faced with uncertainty. We tested the model in simulations of human and rodent navigation in mazes. Like the human and rat, the model was able to generate novel shortcuts, and take detours when familiar routes were blocked. Similar to rodent hippocampus recordings, the neural activity of the model resembles neural correlates of Vicarious Trial and Error (VTE) during early learning or during uncertain conditions. Similar to rodent studies, after learning, the neural activity resembles forward replay or preplay predicting a future route, and VTE activity decreases. We suggest that VTE, in addition to weighing possible outcomes, is a way in which an organism may gather information for future use. Best regards, Jeff Krichmar Department of Cognitive Sciences 2328 Social & Behavioral Sciences Gateway University of California, Irvine Irvine, CA 92697-5100 jkrichma(a)uci.edu http://www.socsci.uci.edu/~jkrichma

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Postdoctoral position available
by Sara A. Solla Sept. 10, 2021

Sept. 10, 2021

*Integrating Human and Machine Learning for Enabling Co-Adaptive * *Body-Machine Interfaces* * Sandro Mussa-Ivaldi and Sara A. Solla PI’s * *Northwestern University* We are seeking postdoctoral applicants with interests and experience in computational methods, machine learning, and human-machine interactions to participate in an NSF-funded project. The goal of the project is customizing human-machine interfaces through a collaborative interaction between human and machine learning. This has relevance to the recovery of function after injury to the spinal cord. The same goals apply also to non-clinical domains. Common to the different domains is the necessity to learn novel movement skills. The project will consider how this challenge is met through the interaction with an adaptive interface, the body-machine interface, that maps body motions onto commands to external devices. The working hypotheses are H1) that through a dynamical process of learning the human operators form an internal model of the interface and connected device, and H2) that the human machine interface can be adapted to its users by an update rule that tracks the learning process of the human operator. The success of the research project will lead to a new family of intelligent human machine interfaces capable of customizing themselves to the evolving ability of their users. Applications, including a brief statement, a bio sketch, and the names of two references, should be sent to bomiproject2021(a)gmail.com

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Postdoc position on neural mechanisms of flexible behavior
by Luca Mazzucato Sept. 5, 2021

Sept. 5, 2021

Dear colleagues, We are looking for a computational neuroscience postdoc to lead a project on the neural mechanisms of flexible behavior. The theory position will be co-supervised by Luca Mazzucato and David McCormick and funded by the NIH BRAIN Initiative collaboration between the McCormick, Niell, Jaramillo and Mazzucato labs at University of Oregon. The project aims at elucidating the whole-brain dynamics enabling flexible modality switching in an audiovisual decision-making task. A successful candidate will use state-space models and multi-area recurrent network models to elucidate the activity and functional connectivity of cortical circuits from large datasets in behaving mice (2-photon mesoscope with ~10k neurons; multiple neuropixel probes). Experience with deep learning is recommended for integrating behavioral analyses with task performance and neural activity. The postdoc will be part of the vibrant neuroscience and machine learning community at the University of Oregon including the Institute of Neuroscience <https://ion.uoregon.edu/> and the Knight Campus <https://accelerate.uoregon.edu/> for Accelerating Science. The University is located in beautiful Eugene, the country's leader in the "20-minute friendly <https://tinyurl.com/y8jd8pmr>" bike commute movement, at close range between the Cascades ski areas and the Pacific Ocean. Successful candidates will have a PhD in Physics, Neuroscience, Mathematics, Computer Science, Statistics or a related discipline and, preferably, experience in theoretical neuroscience and statistical analysis of large neuroscience datasets. For inquiries please contact Luca Mazzucato or David McCormick.

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8th Baltic-Nordic Summer School on Neuroscience and Neuroinformatics (BNNI 2021)
by Pawel Herman Sept. 5, 2021

Sept. 5, 2021

Dear Fellow Neuroscientists and Students We would like to invite you to the 8th Baltic-Nordic Summer School on Neuroscience and Neuroinformatics, which will be organised as a virtual event on 21-25 September, 2021. The 8th Baltic-Nordic Summer School on Neuroscience and Neuroinformatics 2021 “Learning in the Brain and NeuroRobots – from Molecules to Behaviour” offers interdisciplinary course and covers modelling at different levels of organization of the brain, from single neurons to microcircuits, neural networks and neurorobotics. The course offers lectures on the latest achievements in understanding learning, neural and network dynamics and function in health and disease, neurorobotic theory and applications, and hands-on tutorials on the EBRAINS services and tools. The summer school targets advanced master students, doctoral students and postdoctoral researchers in biomedical and technology sciences, ranging from medicine, biology, psychology, to mathematics, informatics, information technology, physics and chemistry, who would like to get an introduction to neuroinformatics and computational neuroscience and especially the EBRAINS Infrastructure<http://ebrains.eu/> (ebrains.eu<http://ebrains.eu>). Further information and registration: https://www.humanbrainproject.eu/en/education/BNNI2021/ Best regards Pawel Herman on behalf of the organising committee ------------------------------------ Paweł Herman Associate Professor, PhD, Docent KTH Royal Institute of Technology School of Electrical Engineering and Computer Science (EECS) Division of Computational Science and Technology (CST) Lindstedtsvägen 5 114 28 Stockholm, Sweden room 4442 (4th floor, D-building) tel. +46 8 790 6513

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DEADLINE EXTENDED: Summer School on Network and Control Sciences for Psychiatry
by Jasper Bischofberger Sept. 2, 2021

Sept. 2, 2021

Dear all, We are happy to announce a Summer School on “Current and Future Applications of Network and Control Sciences for Psychiatry” Host Institution: *University of Tübingen, Germany* Location: *Online event* Dates: *September 29th – October 1st 2021* Abstract deadline: *September 10th, 2021* Registration fees: *free* *Focus* This Summer School gives an opportunity to students and young researchers to get acquainted with and exchange within a range of current topics in network and control sciences and its applications in Psychiatry. ____ *Keynotes* Danielle S. Bassett (University of Pennsylvania, USA) Peter Dayan (MPI Tübingen, Germany) John Medaglia (Drexel University, USA) For the full list of speakers visit: https://www.medizin.uni-tuebingen.de/de/summer-school-controlpsychiatry/spe… ____ *Registration* The summer school is free of charge for all participants, but to get all important information please register online via: https://www.medizin.uni-tuebingen.de/de/summer-school-controlpsychiatry ____ *Poster Submission* Participants can present their latest research results as a poster. Some of the most relevant submissions will have the possibility to present their work in a dedicated oral session and receive an official certificate. Please submit your abstract (limited to 250 words) latest by September 10th to: controlpsychiatry(a)med.uni-tuebingen.de ____ Questions? Please contact: controlpsychiatry(a)med.uni-tuebingen.de We are excited to see you soon! Best wishes, The organizing committee

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