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

Workshop on Clinical Computational Neuroscience at OCNS*2021

by Laure Buhry

Dear all, We would like to announce the Workshop on *“Clinical computational neuroscience: How computational neuroscience can solve problems from the clinic”,* which will be held on *July 7th* during the OCNS annual meeting from 9:30 am to 5:45 am (Paris time) / 3:30 am to 11:45 am (NY time)/ 5:30 pm to 1:45 am (Sydney time). Please keep in mind that for workshop attendance a registration at the main conference (https://www.cnsorg.org/cns-2021-registration-fees) is necessary. More information here: https://xenia-kobeleva.com/CNS2021/ We would love to see you there! Organizing Committee: Laure Buhry (co-chair) Xenia Kobeleva -- Dr Laure Buhry Associate Professor LORIA UMR CNRS 7503 - INRIA - University of Lorraine, France

June 25, 2021

Postdoc position in neuronal network modelling and simulation

by Andrew Davison

Dear colleagues, A postdoc position in neuronal network modelling and simulation is available within the Neuroinformatics research group of the Paris-Saclay Institute of Neuroscience, as part of the Human Brain Project (https://neuropsi.cnrs.fr/en/departments/icn/group-leader-andrew-davison/) The large number of different simulation environments in neuroscience presents both a problem and an opportunity. Since each simulator has its own programming interface and output data format, reproducing, reusing, or combining models written for different simulators typically presents considerable difficulty. On the other hand, since each simulation environment has a different balance between efficiency, flexibility, scalability and user-friendliness, we can choose the most appropriate one for a given problem, or cross-check the results obtained with different tools. Simulator-agnostic model representation languages such as NeuroML and PyNN allow us to preserve the advantages of simulator diversity while reducing or eliminating the disadvantages, thereby making reproducibility and reuse much easier. Such languages let us take a single model description and simulate it in different environments without having to reimplement the model each time. The aim of this project is to expand the scope of PyNN from networks of simplified neuron models, such as integrate-and-fire, to networks consisting of biophysically- and morphologically-detailed neuron models, targeting the NEURON and Arbor simulators, the SpiNNaker and BrainScaleS neuromorphic computing systems, and interoperability with NeuroML and the SONATA format. We offer a flexible and collaborative working environment, including remote working up to two days per week. For more details and to apply, see https://emploi.cnrs.fr/Offres/CDD/UMR9197-ANDDAV-007/Default.aspx?lang=EN Informal enquiries are welcome, contact andrew.davison(a)cnrs.fr Andrew Davison, PhD Group leader, Neuroinformatics Department for Integrative and Computational Neuroscience (ICN) NeuroPSI - Paris-Saclay Institute of Neuroscience CNRS - Université Paris-Saclay 1, avenue de la Terrasse 91198 Gif-sur-Yvette France Tel: +33 1 69 82 34 51 Twitter: @apdavison https://neuropsi.cnrs.fr/en/departments/icn/group-leader-andrew-davison/

June 24, 2021

Tutorial on "Understanding early visual receptive fields from efficient coding principles"

by Zhaoping Li

Understanding principles of efficient coding can enable you to answer questions such as: why should the input contrast response function of a neuron take its particular form? Why do retinal ganglion cells have center-surround receptive fields? How correlated or uncorrelated should the visual responses from different retinal ganglion cells be? Why do receptive fields of retinal ganglion cells increase their sizes in dim light? How could visual coding depend on animal species? Why are color selective V1 neurons less sensitive to visual motion signals? How can one predict the ocular dominance properties of V1 neurons from developmental conditions? How should neurons adapt to changes in visual environment? This tutorial guides you on how to answer such questions. It contains: (1) A list of 45 short video lecture clips (about 10 minutes each on average) on YouTube, see http://www.lizhaoping.org/zhaoping/EfficientVisualCoding_Playlist.html (2) In addition to (1), you can join CNS *2021 (see https://www.cnsorg.org/cns-2021-tutorials#T3 ), which enables social interactions with the lecturer and other students via Discord, and on July 3rd (the tutorial day) for highlights, Q&As, and discussions. best, Li Zhaoping -- Li Zhaoping Ph.D. Prof. of Cognitive Science, University of Tuebingen Head of Dept of Sensory and Sensorimotor Systems, Max Planck Institute of Biological Cybernetics Author of "Understanding vision: theory, models, and data", Oxford University Press, 2014 www.lizhaoping.org

June 23, 2021

CNS*2021 Workshop: Computational approaches for studying astrocyte dynamics and astrocyte-neuron communication (July 6-7, Online)

by Marsa Taheri

Dear all, We are pleased to announce a workshop on “*Computational approaches for studying astrocyte dynamics and astrocyte-neuron communication*” at this year’s Annual Computational Neuroscience Meeting (CNS*2021). This workshop will run over 2 half-days: July 6-7 (9 am – 12:30 pm UTC-7). ------------------- *Brief Description*: Exciting experimental studies in the last decade have led to an entirely new body of work on the participation of astrocytes in normal and pathological brain function. However, the development of a solid theoretical framework to support and quantify some of the pathways has been somewhat limited, first, due to the lack of intensive collaboration between experimentalists and theorists, and second, due to a persistent neurocentrist view of brain function. Please join us to hear from an incredible lineup of speakers, bringing together specialists, theorists, and experimentalists in the field of astrocyte-neuron signaling: Yukiko Goda, Riken, Japan Alla Borisyuk, University of Utah, USA Jennifer Shih, MIT, USA Annalisa Scimemi, University of Albany, USA Guoqiang Yu, Virginia Tech, USA Laszlo Heja, Hungarian Academy of Sciences, Hungary Anup Pillai, University of Ottawa, Canada Renaud Jolivet, Université de Genève, Switzerland Max Collard, UCSF, USA Audrey Denizot, Okinawa Institute of Science and Technology, Japan Ron Refaeli, The Hebrew University, Israel Kerstin Lenk, Graz University of Technology, Austria ------------------- More information on the workshop at: https://astrocytenet.org/cns2021-online-workshop/ Register and gain access to all CNS*2021 presentations, tutorials, and workshops at: https://www.cnsorg.org/cns-2021 We look forward to your participation! *On behalf of the workshop organizers:* *Kerstin Lenk*, Institute for Neural Engineering, Graz University of Technology, Graz, Austria *Audrey Denizot*, Okinawa Institute of Science and Technology, Computational Neuroscience Unit, Onna-Son, Japan *Barbara Genocchi*, Faculty of Medicine and Health Technology, BioMediTech, Tampere University, Tampere, Finland *Suhita Nadkarni*, Indian Institute of Science Education and Research Pune (IISER Pune), Pune, India *Marsa Taheri*, Department of Neurobiology, University of California Los Angeles, CA, USA Contact information: cns2021.astro.workshop(a)gmail.com

June 23, 2021

Tutorials on Allen Institute data and tools for computational neuroscience at CNS*2021

by Anton Arkhipov

Dear all, Please join us for pre-CNS*2021 tutorials on June 30 and July 1: “From synapses to behavior – using open data, tools, and models from the Allen Institute in computational neuroscience”. https://www.cnsorg.org/cns-2021-tutorials#SA5 The Allen Institute recently released multiple free resources focusing on the structure and function of brain circuits, including data, associated analysis software, and models integrating the data to enable bio-realistic simulations. We will introduce several of these resources in a series of 1-hour sessions. The resources covered will include characterization of cell types and synapse types, 2-photon calcium imaging and Neuropixels electrophysiology in vivo, a visual behavior dataset, and bio-realistic models and modeling software. Wednesday, June 30, 2021 11:30 am – 11:45 am EST (8:30 am – 8:45 am PST) - Introduction 11:45 am – 12:45 pm EST (8:45 am – 9:45 am PST) - Synaptic Physiology (Luke Campagnola) 12:45 pm – 1:00 pm EST (9:45 am – 10:00 am PST) - Break 1:00 pm – 2:00 pm EST (10:00 am – 11:00 am PST) - Visual Coding 2-photon (Saskia de Vries) 2:00 pm – 3:00 pm EST (11:00 am – 12:00 pm PST) - Visual Coding Neuropixels (Josh Siegle) Thursday, July 1, 2021 11:30 am – 11:45 am EST (8:30 am – 8:45 am PST) - Introduction 11:45 am – 12:45 pm EST (8:45 am – 9:45 am PST) - PatchSeq (Nathan Gouwens) 12:45 pm – 1:00 pm EST (9:45 am – 10:00 am PST) - Break 1:00 pm – 2:00 pm EST (10:00 am – 11:00 am PST) - Visual Behavior (Alex Piet) 2:00 pm – 3:00 pm EST (11:00 am – 12:00 pm PST) - Bio-realistic model of the mouse primary visual cortex (Anton Arkhipov and Kael Dai) Please register for CNS*2021 and join us for the tutorials! https://www.cnsorg.org/cns-2021-quick Best wishes, Anton. Anton Arkhipov Associate Investigator T: 206.548.8414 E: antona(a)alleninstitute.org<mailto:antona@alleninstitute.org> [Text Description automatically generated] alleninstitute.org<https://alleninstitute.org> brain-map.org

June 23, 2021

Software WG satellite tutorials at CNS*2021 on Bash, Git, and Python: June 28, 29 2021

by Ankur Sinha

Dear all, Apologies for the cross-posts. The INCF/OCNS Software Working Group is running three beginner/intermediate level satellite tutorials on Bash, Git, and Python at CNS*2021. These tutorials are on Monday and Tuesday (28/29 June). They are intended for both complete beginners and occasional/regular users who are looking to expand and refresh their skills. More information on these, including topics that we will cover can be seen on our website: https://ocns.github.io/SoftwareWG/2021/06/09/software-wg-tutorials-at-cns-2… - Effective use of Bash (Felix B. Kern): 28 June, 2021 1200 UTC - Effective use of Git (Ankur Sinha): June 28, 2021 1700 UTC - Python for beginners (Joe Graham, Shailesh Appukuttan, Ankur Sinha): 29 June, 2021 1300 UTC One can register for CNS*2021 here to gain access to excellent set of tutorials/workshops/posters and oral presentations that are being organised this year: https://www.cnsorg.org/cns-2021 More information on the Software working group, our work, how you can contact us, and how you can join us (it is open to all) is here: https://ocns.github.io/SoftwareWG/index.html On behalf of the Software WG, -- Thanks, Regards, Ankur Sinha (He / Him / His) Research Fellow at the Silver Lab | http://silverlab.org/ Department of Neuroscience, Physiology, & Pharmacology University College London, London, UK Time zone: Europe/London

June 23, 2021

Post-doc position on machine learning and human motion/physiological data analysis at AIST, Japan

by 平山淳一郎

Dear colleagues, We invite applications for a postdoctoral researcher position on machine learning and human motion/physiological data analysis, available at Mathematical Neuroscience Research Group, Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST) (https://www.aist.go.jp/index_en.html) Japan. The successful candidate will join a collaborative project with ATR, Kyoto University and Hokkaido University on human-AI co-evolution, funded by NEDO (https://www.nedo.go.jp/english/) and conduct research on machine learning modeling and analysis of human motion data and/or related physiological signals from the brain and body, depending on his/her interests. The starting date is negotiable, with a preference for candidates who can start early. The initial appointment will be until March 2022, with the possibility of extension until March 31, 2025. Salary for the postdoctoral fellow will follow the AIST guideline. To apply, please visit https://jrecin.jst.go.jp/seek/SeekJorDetail?fn=3&ln=1&id=D121020014&ln_jor=1 and send the required application documents to junichiro.hirayama(a)aist.go.jp. The deadline of application is August 31, 2021. The deadline may be extended until the position is filled. -- Jun-ichiro Hirayama Senior Researcher Human Informatics and Interaction Research Institute National Institute of Advanced Industrial Science and Technology (AIST) junichiro.hirayama(a)aist.go.jp https://staff.aist.go.jp/junichiro.hirayama

June 23, 2021

Postdoctoral positions in the Geffen lab at the University of Pennsylvania

by Maria Geffen

The Geffen laboratory <http://hosting.med.upenn.edu/hearing> at the University of Pennsylvania <http://www.upenn.edu/> has multiple postdoctoral positions open in systems neuroscience with the broad goal of understanding the neuronal circuits for auditory perception and learning. We are looking for energetic and talented scientists interested in studying the function of the brain. The postdoctoral fellow will have the opportunity to learn and apply a host of systems neuroscience techniques, including two-photon imaging of population activity, optogenetic manipulations, large-scale electrophysiology and behavior in mice. Prior experience with some of these methods is preferred, but not required. Depending on the candidate’s interests, all projects provide an opportunity to learn and apply advanced computational methods, including dynamic systems analysis of neuronal population activity; Bayesian approaches for understanding the relation between neuronal activity and behavior; machine learning methods to understand large-scale neuronal activity. We currently have openings for postdoctoral fellows for three projects: (1) Neuronal mechanisms for predictive coding: Auditory perception relies on predicting statistics of incoming signals, be it identifying the speech of a conversation partner in a crowded room or recognizing the sound of a babbling brook in a forest. The human brain detects statistical regularities in sounds as a fundamental aspect of prediction, evidenced by reduced responses to repeated sound patterns and enhanced responses to unexpected sounds. Multiple studies demonstrate that the neuronal responses to regular signals are reduced through adaptation, which can contribute to prediction. However, adaptation alone is not sufficient to account for prediction and studies at cellular and neuronal population levels in animals thus far lend only partial support to existing theories of predictive coding. The goal of the project is to close this gap in knowledge and to determine the circuits that predict signals and detect statistical regularity and its violation in auditory behavior. Funded by NIH NIDCD. (2) Neuronal circuits for learning-driven changes in auditory perception: Everyday auditory behavior depends critically on learning-driven changes in auditory perception that rely on neuronal plasticity within the auditory pathway. By combining state-of-the-art optogenetic, electrophysiological, behavioral and computational approaches, the project seeks to identify the function of specific circuit elements in auditory learning. Funded by NIH NIDCD. (3) Neuronal mechanisms for hearing under uncertainty: In everyday life, because both sensory signals and neuronal responses are noisy, important cognitive tasks, such as auditory categorization, are based on uncertain information. To overcome this limitation, listeners incorporate other types of signals, such as the statistics of sounds over short and long time scales and signals from other sensory modalities into their categorization decision processes. This project will identify the contribution of specific cell types to categorization and the neuronal mechanisms for how contextual signals bias auditory categorization. In collaboration with Dr. Yale Cohen <https://auditoryresearchlaboratory.weebly.com/> and Dr. Konrad Kording <http://kordinglab.com/>, funded by NIH BRAIN Initiative. Our laboratory is a close community of fun-loving scientists, striving to help each other while exploring the mysteries of the brain. Our trainees have won numerous awards and have been awarded government and private foundation grants. We value diversity and promote equity in the scientific community and beyond <https://hosting.med.upenn.edu/hearing/philosophy/>. The systems neuroscience community at the University of Pennsylvania is top-notch and highly collaborative, and postdoctoral fellows will have opportunities to engage in interdepartmental initiatives, including MindCore <https://mindcore.sas.upenn.edu/>, MINS <https://www.med.upenn.edu/ins/> and CNI <https://www.cni.upenn.edu/>. Penn has a gorgeous campus and offers many cultural activities. Philadelphia is a beautiful city with world-class music, food and entertainment. To apply, please email Dr. Geffen at mgeffen(a)pennmedicine.upenn.edu <mailto:mgeffen@pennmedicine.upenn.edu> : a cover letter (summarize your prior research experience, why you are interested in the position, and your future plans) and your CV. __________________________ Maria N. Geffen, Ph.D. (she/her) Associate Professor Department of Otorhinolaryngology Department of Neuroscience Department of Neurology Stemmler Hall G14 3450 Hamilton Walk Philadelphia PA 19104 (215)898-0782 mgeffen(a)pennmedicine.upenn.edu http://hosting.med.upenn.edu/hearing Twitter: @neimarkgeffen

June 22, 2021

Three Assistant Professor Positions at University of Sussex

by Thomas Nowotny

Dear all, The School of Engineering and Informatics at the University of Sussex is seeking to hire three Assistant Professors (“Lecturers”, permanent position) in Computer Science and AI. One of the positions is particularly focused on a researcher with interests in one or more of the following areas: machine learning, ethical AI, computational Neuroscience, complexity science, consciousness science and bio-inspired AI and robotic control. They should be able to teach general subjects in Computer Science and Artificial Intelligence at Undergraduate and Taught Postgraduate levels. They will work within the Artificial Intelligence Research Group, including opportunities to interact with the robotics group in the Department of Engineering. The AI Research Group at the University of Sussex was created through the merger of the Evolutionary and Adaptive Systems (EASy) and the Data Science groups. We conduct research and teach a wide range of AI related topics, often cross-disciplinary and with a unique Sussex angle. We collaborate internationally and locally with academics, businesses, and public stakeholders, working at the frontiers of knowledge, on solving real-world problems, and in policy and public outreach. Applications should be accompanied by a full CV, and statements of future research plans and ways in which the applicant could contribute to teaching across the School. Please contact Dr Ian Mackie I.Mackie(a)sussex.ac.uk<mailto:I.Mackie@sussex.ac.uk> , Head of the Department of Informatics, for informal enquiries. The full job advert is posted at https://t.co/K0CdIYx6xH?amp=1 including a detailed person specification and details how to apply. Please get in touch if you are interested in these positions and forward to any interested colleagues. Kind regards, Thomas -- Prof Thomas Nowotny Head of the AI Research Group Director of Research and Knowledge Exchange School of Engineering and Informatics University of Sussex Falmer, Brighton BN1 9QJ, UK Phone: +44-1273-678593 FAX: +44-1273-877873

June 22, 2021

Post-doc / research associate position in neural reinforcement learning using causal models (Sheffield, UK, 33 months, deadline 4th July)

by Aditya Gilra

Dear All, We're looking for a post-doc / research associate to work on bio-plausible neural networks that learn causal models of the environment and utilize these to plan and explain actions in reinforcement learning. The position is for 33 months at the University of Sheffield, UK. Read more at: https://www.chistera.eu/projects/causalxrl . Apply via (deadline: 4th July): https://jobs.shef.ac.uk/sap/bc/webdynpro/sap/hrrcf_a_posting_apply?PARAM=cG… Best, Aditya. -- Aditya Gilra, Lecturer (Assistant Professor), Machine Learning Group <https://www.sheffield.ac.uk/dcs/research/groups/machine-learning> & Neuroscience Institute <https://www.sheffield.ac.uk/neuroscience-institute/research/computational-a…> , Department of Computer Science, University of Sheffield, UK. https://www.sheffield.ac.uk/dcs/people/academic/aditya-gilra

June 22, 2021