January 2023 - Comp-neuro - lists.cnsorg.org

Python Package: SER model
by Fabrizio Damicelli Aug. 8, 2024

Aug. 8, 2024

Dear Computational Neuroscience Community, I would like to point you to a potentially useful Python Package that might be of interest for your research, especially in the realm dynamical models and spreading dynamics on networks. "ser": S(usceptible)E(xcited)R(efractory) model on graphs, a dynamical model of spreading excitations. Code Repository: https://github.com/fabridamicelli/ser As of today, a few people already trust it and the package registers >11K total downloads, ~500/month (pypi.org) and has been used already in a few research projects. A few interesting features: - It is light-weight and fast (`numba` accelerated), i.e. many experiments can be simply run on a laptop - Installation and getting started is easy: `pip install ser` - Example notebooks: https://github.com/fabridamicelli/ser/blob/main/examples The SER model is a classical cellular automaton model used to study all sorts of complex systems, ranging from forest fire dynamics to self-organized criticality in the brain. Despite of the simplicity of its setup, it is capable of generating complex emergent dynamics with absolutely non-trivial higher-order statistical properties. To learn more about the SER model and its applications, you might want to check out these references: - Messe et al. (2018). Toward a theory of coactivation patterns in excitable neural networks. doi.org/10.1371/journal.pcbi.1006084 - Haimovici et al. (2013). Brain Organization into Resting State Networks Emerges at Criticality on a Model of the Human Connectome. doi.org/10.1103/PhysRevLett.110.178101 - Damicelli et al. (2019). Topological reinforcement as a principle of modularity emergence in brain networks. doi.org/10.1162/netn_a_00085 Check it out and any feedback/suggestions/bug reports are more than welcome (simply open an issue: https://github.com/fabridamicelli/ser/issues) All the best, Fabrizio Damicelli

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Call for Visiting Scholars in Theoretical Sciences at OIST (Application by August 15)
by Kenji Doya Oct. 21, 2023

Oct. 21, 2023

We are pleased to announce Visiting Scholars in Theoretical Sciences at OIST for a flexible term of 1 to 12 months as below. ***** As part of an initiative to develop a vibrant program in theoretical sciences, OIST invites applications for Visiting Scholars in the Theoretical Sciences. The Okinawa Institute of Science and Technology (OIST) is a research institution with a Ph.D. program. Outstanding graduate students and faculty are being attracted internationally. OIST is beautifully situated on the tropical island of Okinawa, Japan. Applicants should have a Ph.D. in a relevant field and be independent researchers, i.e., should have an academic standing equivalent to senior postdoc, junior group leader, or faculty member at a research-intensive institution. The position has a flexible term of 1 to 12 months taken continuously starting between October 2021 and March 2022 with a preference for longer-term visitors. The appointment may be taken while on leave or sabbatical from another university and comes with housing, research funds, and moving allowance. Successful candidates will be eligible to apply for support with salary, where this is necessary to facilitate the visit. No teaching duties come with the position. OIST is an institution with no departments, aiming to eliminate barriers between people working in different fields. It provides a family-friendly working environment including the multilingual Child Development Center and has proactive policies designed to promote a culture of diversity. OIST is an equal opportunity, affirmative action educator, and employer. Further details can be found at https://www.oist.jp/. Applicants should submit a CV including a list of publications, a brief description of their research to date and proposed research while visiting OIST, and the desired period of visit. All visits are subject to the availability of funding. Applications received by August 15, 2021, are guaranteed full consideration. If you have any questions, please send inquiries to: tsvp(a)oist.jp To apply, please go to our Interfolio page, http://apply.interfolio.com/88541 ---- Kenji Doya <doya(a)oist.jp> Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University 1919-1 Tancha, Onna, Okinawa 904-0495, Japan Phone: +81-98-966-8594; Fax: +81-98-966-2891 https://groups.oist.jp/ncu

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Faculty position at Cold Spring Harbor Laboratory in computational neuroscience
by Benjamin Cowley Aug. 28, 2023

Aug. 28, 2023

Hi all, Cold Spring Harbor Laboratory has an open search for a faculty position in computational/theoretical neuroscience. Applications are due Nov. 15, 2022. https://www.cshl.edu/about-us/careers/faculty-positions/ Here is the job description: Cold Spring Harbor Laboratory (CSHL) is seeking to fill a faculty position in the area of COMPUTATIONAL/THEORETICAL NEUROSCIENCE. Of particular interest to this search are candidates with expertise in computational and theoretical neuroscience, machine learning, and artificial intelligence. The successful candidate will have an outstanding record of research achievement and an innovative research program. They will join a highly interactive and collaborative neuroscience group working on neural circuits, neural development, neurogenetics, theoretical and computational neuroscience, artificial intelligence, synaptic function, brain disorders, rodent cognition, perception, and social behavior. Preference will be given to applicants at the Assistant Professor level, but outstanding candidates at all career stages will be considered. Cold Spring Harbor Laboratory is a world-renowned research and educational institution with programs in cancer, neuroscience, plant biology, genomics, and quantitative biology. Located on the North Shore of Long Island 30 miles from New York City, the Laboratory has a rich and successful research environment rooted in interdisciplinary collaboration as well as an innovative graduate school that attracts talented students each year. CSHL is committed to fostering a diverse work environment that values best practices in mentorship, equity, and inclusion. Successful candidates will be expected to establish productive research programs while mentoring diverse groups of students and postdocs. Applications are strongly encouraged from groups historically underrepresented in science, including women and U.S. racial/ethnic minority populations. To apply, please submit a cover letter, CV, description of research accomplishments, statement of future research plans, and a statement of diversity & mentoring to: https://cshl.peopleadmin.com/postings/20153 Position ID 03299-R; letters of reference will be requested separately. The statement of diversity & mentoring should describe a candidate’s mentoring philosophy, contributions to equity and inclusion in science, and prior training (as applicable) in mentoring, academic management/leadership, and antidiscrimination/antiracism. We will begin considering applications on a rolling basis on October 5, 2022, and applications will be considered until *November 15*. Inquiries regarding the search should be directed to: CSHLfacultyjobs(a)cshl.edu

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Funded PhD Scholarship in Developmental Neurorobotics at Sheffield Hallam University (UK)
by Di Nuovo, Alessandro Feb. 16, 2023

Feb. 16, 2023

About the Project This scholarship will support the PhD candidate to carry out frontier research in Developmental Neurorobotics, a combination of Neuromorphic Computing and Cognitive Developmental Robotics. The PhD candidate will work with the Professor Alessandro Di Nuovo and his team, who have been awarded funding by the EPSRC for his research in the field. We are looking for an outstanding student to work with the team of a new EPSRC project. The research will pioneer the new developmental neuromorphic paradigm, which will be a synergic combination that will go beyond the limitations of the individual paradigms: neuromorphic computing will provide efficient brain-like resources able to process a more accurate representation of the real world, meanwhile developmental robotics will deliver the missing learning mechanisms for complex applications of neuromorphic spiking neural networks. The short-term objective is to demonstrate feasibility and lay the foundation of a biologically plausible framework to simulate the human-like learning process of numerical and abstract cognition, a fundamental characteristic of human intelligence. The team long-term goal is to create an artificial mind for robots that 'grows up' like a child's brain. This will be underpinned by neuromorphic computing which emulates the deep-lying architecture of the brain and will allow it to interpret and adapt to situations. As well as enabling the creation of robots with a human-like ability to reason, behave and interact the creation of an artificial mind will boost research in life sciences disciplines such as neuroscience by allowing researchers to run biologically realistic simulations to test theories. By simulating information on the inner workings of the brain that could not otherwise be detected, it could enhance our understanding of neurodevelopmental and learning disorders and lead to new treatments. Eligibility Information on entry requirements can be found here<https://www.findaphd.com/common/clickCount.aspx?theid=147190&type=184&DID=6…> The ideal candidate should have a Masters degree in Neuromorphic Computing, Computational Neuroscience, Machine Learning, or closely related disciplines in AI and Robotics, excellent programming skills and experience in interdisciplinary research. How to apply Your application should be emailed to industry-innovation-admissions(a)shu.ac.uk<javascript:void(0)> Any interested candidates must contact the lead academic, Prof. Alessandro Di Nuovo, a.dinuovo(a)shu.ac.uk<javascript:void(0)>, to discuss your application. The application should explain how the candidate knowledge, skills and experience are relevant to the project short and long-term objectives. For information on how to apply please visit https://www.shu.ac.uk/research/degrees<https://www.findaphd.com/common/clickCount.aspx?theid=147190&type=184&DID=6…> ________________________________ Funding Notes The PhD studentship provides tuition fees at UK level and a maintenance bursary at the UK Research Councils' national minimum doctoral stipend rate (£17,668 for 2022/23). The scholarship is available for three years of full-time. ________________________________ References Di Nuovo, A., McClelland (2019). Developing the knowledge of number digits in a child-like robot. Nature Machine Intelligence, 1(12), 594-605. Di Nuovo, A., & Jay, T. (2019). Development of numerical cognition in children and artificial systems: a review of the current knowledge and proposals for multi-disciplinary research. Cognitive Computation and Systems, 1(1), 2-11. Di Nuovo, A., & Cangelosi, A. (2021). Abstract Concept Learning in Cognitive Robots. Current Robotics Reports, 2(1), 1-8. Roy, Jaiswal, Panda, (2019). Towards spike-based machine intelligence with neuromorphic computing. Nature, 575(7784), 607-617. Krichmar (2018). Neurorobotics-A Thriving Community and a Promising Pathway Toward Intelligent Cognitive Robots. Frontiers in Neurorobotics, Vol. 12, p. 42. Furber (2016). Large-scale neuromorphic computing systems. Journal of Neural Engineering, 13(5), 51001. Sengupta, et al. (2019). Going deeper in spiking neural networks: VGG and residual architectures. Frontiers in Neuroscience, 13, 95. Quax, D'Asaro,van Gerven, (2020). Adaptive time scales in recurrent neural networks. Scientific Reports, 10(1), 11360.

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Postdoctoral fellowship at the Gatsby Unit
by Lin, I-Chun Jan. 31, 2023

Jan. 31, 2023

The Gatsby Computational Neuroscience Unit invites applications for a postdoctoral Training Fellowship under the guidance of Professor Maneesh Sahani and Professor Jennifer Linden (UCL Ear Institute). You will focus on an investigation of the computational principles that underlie the formation of perceptual representations. The goal is to apply state-of-the-art unsupervised inferential approaches to learn models of acoustic environments, and evaluate the fidelity with which they reproduce neural recordings in the auditory cortex from animals raised in either routine or altered acoustic settings. Deadline: 28 February 2023. For detailed information on the role and how to apply, visit www.ucl.ac.uk/gatsby/vacancies About the Gatsby Unit Established in 1998 through a generous grant from the Gatsby Charitable Foundation, the Gatsby Unit has been a pioneering centre for research in theoretical neuroscience and machine learning. The Unit provides a unique multidisciplinary research environment with strong links to the Sainsbury Wellcome Centre for Neural Circuits and Behaviour, the ELLIS Unit at UCL, and other neuroscience and machine learning groups at UCL and beyond. -- I-Chun Lin, PhD Scientific Programme Manager Gatsby Computational Neuroscience Unit, UCL

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Postdoc/Engineering position at the Cleveland Clinic in Brain-Machine Interfacing/Neural Interfacing
by Dawn Taylor Jan. 31, 2023

Jan. 31, 2023

*Postdoctoral/Engineering Position in* *Brain-Machine Interfacing / Neural Interfacing* *at The Cleveland Clinic* We are seeking outstanding postdoctoral candidates and/or engineers for research in brain-machine interfacing and restoration of sensorimotor function via electrical stimulation of the nervous system. We have multiple ongoing projects applicants could get involved with spanning BMI-controlled neuroprosthetics, deep brain stimulation, peripheral nerve stimulation, and intracortical microstimulation. Our primary project is an NIH R01-funded project that is part of a larger government funded clinical trial (ReHAB: *Re*connecting the *H*and and *A*rm to the *B*rain) to restore arm function to paralyzed individuals by using their intracortical brain signals to control peripheral nerve stimulators that reanimate their paralyzed muscles. The specific focus of this five-year NIH-funded project (PIs: *Drs. Dawn Taylor* and *Bolu Ajiboye*) is to improve brain-controlled limb movements by more effectively modulating limb stiffness (i.e. degree of co-contraction of antagonist muscle) to improve limb stability while also minimizing muscle fatigue. Additionally, we have new funding for restoring proprioception via intracortical microstimulation in area 3a in animal models. We also are conducting research into improving deep brain stimulation and alternative peripheral neurostimulation therapies for Parkinson’s’ disease. Research activities include working with animal models and humans as well as neural and biomechanical simulations. Ideal candidates will have experience/familiarity in some or all of the following: intracortical recordings in animals, non-human primates and/or humans; cortical and/or peripheral nerve stimulation for restoration of movement and sensation; real-time neural signal processing; writing custom programs to control multiple pieces of hardware and control objects in a virtual environment (matlab skills preferred); computational or biomechanical modeling. An advanced degree in Biomedical Engineering, Computer Engineering, or Neurosciences is preferred but other applicants will be considered. This is a great opportunity to work with our large interdisciplinary team of researchers, engineers and clinicians to gain a wide range of skills beneficial for your future neural or rehab-related career. Interested candidates should submit their curriculum vitae to Dawn Taylor, PhD ( dawn.taylor(a)case.edu) The Cleveland Clinic is an equal opportunity employer, and we encourage applications from a diverse range of candidates. -- Dawn M. Taylor, Ph.D. Associate Staff, Dept. of Neuroscience, Cleveland Clinic Research Scientist, Cleveland VA Medical Center, Functional Electrical Stimulation Center Associate Professor of Biomedical Engineering & of Molecular Medicine, Case Western Reserve University The Cleveland Clinic Lerner Research Institute 9500 Euclid Ave. / NC30 Cleveland, OH 44195 email: dxt42(a)case.edu or taylord8(a)ccf.org Phone: (216) 636-0140 Fax: (216) 444-7927

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PhD or PostDoc in Computational Neuroscience - Max Planck Institute, Göttingen, Germany
by Viola Priesemann Jan. 30, 2023

Jan. 30, 2023

*Unsupervised Local Learning and Efficient Coding * Our group investigates learning and self-regulation in neural and social networks. By putting both side-by-side, we carve out the principles of self-regulation in living networks. The PhD / PostDoc projects are open topic. If you are interested to understand the principles or implementation of learning in living systems in the context of *efficient coding and its implementation via (unsupervised) local learning rules,* in the context of our ongoing work (e.g. [1-5]), we welcome your application. In our group, we combine approaches from statistical physics, data science, control theory, and information theory to carve out how local, unsupervised learning shapes network function. Potential collaborations with our colleagues from theory and experiment e.g. in Göttingen, Bonn, Tübingen, or Oxford are possible and encouraged. *Deadline*: February 10, 2023 (first position) and April 30, 2023 (second position). It should not matter, which application deadline you choose. *Further Details: * https://www.viola-priesemann.de/open-positions-2/ or https://www.nature.com/naturecareers/job/two-phd-mfx-or-postdoc-positions-m… Please note also our complementary open position on self-organization in social networks. *References: *[1]Zierenberg, Wilting & Priesemann, PRX 2018 <https://journals.aps.org/prx/abstract/10.1103/PhysRevX.8.031018> [2] Mikulasch, Rudelt & Priesemann, <https://www.pnas.org/doi/full/10.1073/pnas.2021925118>PNAS 2021 <https://www.pnas.org/doi/full/10.1073/pnas.2021925118> [3] Jaehne et al., Cell Reports, 2021 <https://www.sciencedirect.com/science/article/pii/S2211124721001558> [4] Rowland et al., biorxiv, 2021 <https://www.biorxiv.org/content/10.1101/2021.12.28.474343v1.abstract> [5] Mikulasch, Rudelt, Wibral & Priesemann, TINS 2022 <https://www.sciencedirect.com/science/article/pii/S0166223622001862> -- Summer school on infodemics and pandemics:https://summerschool.infodemics.info/ Prof. Dr. Viola Priesemann Max-Planck-Institute for Dynamics and Self-Organization & Georg-August-University Göttingen Am Fassberg 17, 37077 Göttingen https://priesemann-group.github.io www.viola-priesemann.de viola.priesemann(a)ds.mpg.de

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Konstanz School of Collective Behavior 2023
by Ahmed El Hady Jan. 30, 2023

Jan. 30, 2023

*Konstanz School of Collective Behavior 2023* *Konstanz, Germany * *Deadline to apply: March 30th, 2023* The Konstanz School of Collective Behavior (KSCB) will take place between /31 July 2023 – 12 August 2023/ at the cluster of excellence Centre for the Advanced Study of Collective Behaviour (CASCB) at the University of Konstanz <https://www.uni-konstanz.de/en/>. Uni Konstanz is an elite University of Excellence and ranked #1 young university in Germany with “Collective Behaviour" <https://www.exc.uni-konstanz.de/collective-behaviour/> as one of five research foci. Konstanz <https://www.konstanz.de/start> is a vibrant, small city located on the border between Germany and Switzerland, on the shores of the Bodensee (Lake Constance). Over two weeks, students will delve deeply into the topic of collective behaviour with lectures, hands-on tutorials, and projects, making it a unique and unforgettable experience. The school faculty will cover collective behaviors across a variety of species from worms ,drosophila, fish to non – human primates and human. A set of tutorials delving into state-of-the-art quantitative methods used to study collective behavior will complement the lectures. At the end of the school, students will work on independent projects guided by our resident faculty. Accommodation will be provided and paid by the organizers. A limited number of travel awards will be provided and a registration fee will be due (300 euros) once the student is admitted to the Konstanz School of Collective Behaviour. The registration fee will be waived to those coming from underrepresented minorities and those in need of financial support. For further information and application, visit our website: _https://www.exc.uni-konstanz.de/kscb/application-procedure/ <https://www.exc.uni-konstanz.de/kscb/application-procedure/> _ __ *KSCB 2023 faculty (still more to come ) : *Orit Peleg , Kevin Lala, Einat Couzin, Liang Li, Jake Graving, Armin Bahl, Katrin Vogt, Wataru Toyokawa, Serena Ding, Heiko Hamann *Contact us at: **ahmed.el-hady(a)uni-konstanz.de <mailto:ahmed.el-hady@uni-konstanz.de> * ** *All the best regards,* ** Ahmed El Hady On behalf of the KSCB organizational committee

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Postdoc position in Computational Neuroscience
by andrea.alamia＠cnrs.fr Jan. 30, 2023

Jan. 30, 2023

We are looking for a post-doc to work with us at the Centre de Recherche de Cerveau et Cognition (CerCo) in Toulouse, France. The project will be led by Andrea Alamia and funded by the European Research Council (ERC). Work environment The successful applicant will join the Centre de Recherche de Cerveau et Cognition (CerCo) in a lively research institute in Toulouse, a thriving Southern France city. CerCo is a research center created by the National Center for Scientific Research (CNRS) and the University Paul Sabatier, composed of over 30 research scientists and around 40 doctoral and post-doctoral students. The applicant will join the NeuroAI team, with a strong focus on computational neuroscience and artificial intelligence. The team has access to different experimental facilities, such as EEG, TMS, and fMRI, as well as computational resources (clusters and local GPUs). The project The project is part of an ERC starting grant investigating the role of oscillatory traveling waves in cognitive functions. Our primary goal is to study neural oscillations within and between cortical regions, as well as cortical-thalamic interactions. Our approach's novelty consists of framing the model in the light of Predictive Coding principles, using a computational approach based on spiking and deep neural networks. We'll compare the results of the simulations against experimental recordings of human participants (mostly EEG) to validate and assess the model's predictions. Requirements • Applicants should hold a PhD in computational neuroscience, computer science, engineering, cognitive science, or similar. • Ability to work independently, developing ideas and interests within the project's scope. • A solid mathematical background and excellent computing skills, including programming (e.g., MATLAB, Python). Experience with system theory, models of cortical circuits, and knowledge of neural oscillations are not strictly necessary but highly appreciated. • Fluent in English in both speaking and writing. No knowledge of French is required. The position will run for one year and is renewable for up to 3 years; its starting date is flexible (between March and October 2023). Salary depends on experience and will be determined following CNRS guidelines. To apply, please send a CV, including the name of two potential references, and a summary of research interests to Andrea Alamia (andrea.alamia at cnrs.fr). Review of applications will remain ongoing until the position is filled.

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Software WG: Software Highlight: Dendrify, a framework for incorporating dendrites to spiking neural networks
by Ankur Sinha Jan. 30, 2023

Jan. 30, 2023

Dear all, Apologies for the cross-posts. Please join us for the INCF/OCNS Software Working Group's next Software Highlight session: https://ocns.github.io/SoftwareWG/2023/01/27/dev-session-michalis-pagkalos-… Michalis Pagkalos will introduce and discuss Dendrify, a framework for incorporating dendrites to spiking neural networks, in this session. - Date: February 7, 1600 UTC (Click here to see your local time[1]) (Add to calendar[2]). - Zoom: https://ucl.zoom.us/j/91907842769?pwd=bnEzTU9Eem9SRmthSjJIRElFZ0xwUT09 The abstract for the talk is below: Current SNNs studies frequently ignore dendrites, the thin membranous extensions of biological neurons that receive and preprocess nearly all synaptic inputs in the brain. However, decades of experimental and theoretical research suggest that dendrites possess compelling computational capabilities that greatly influence neuronal and circuit functions. Notably, standard point-neuron networks cannot adequately capture most hallmark dendritic properties. Meanwhile, biophysically detailed neuron models can be suboptimal for practical applications due to their complexity, and high computational cost. For this reason, we introduce Dendrify, a new theoretical framework combined with an open-source Python package (compatible with Brian2) that facilitates the development of bioinspired SNNs. Dendrify allows the creation of reduced compartmental neuron models with simplified yet biologically relevant dendritic and synaptic integrative properties. Such models strike a good balance between flexibility, performance, and biological accuracy, allowing us to explore dendritic contributions to network-level functions while paving the way for developing more realistic neuromorphic systems. - Manuscript: Introducing the Dendrify framework for incorporating dendrites to spiking neural networks | Nature Communications [3] - Source code: Poirazi-Lab/dendrify: Introducing dendrites to spiking neural networks. Designed for the Brian 2 simulator [4]. - Documentation: https://dendrify.readthedocs.io/en/latest/ [1] https://www.timeanddate.com/worldclock/fixedtime.html?msg=Software+Highligh… [2] https://ocns.github.io/SoftwareWG/extras/ics/20230207-dendrify.ics [3] https://www.nature.com/articles/s41467-022-35747-8 [4] https://github.com/Poirazi-Lab/dendrify Please subscribe to the working group's mailing list for reminders, more updates, and to contact us: https://ocns.github.io/SoftwareWG/pages/contact.html On behalf of the working group, -- Thanks, Regards, Ankur Sinha (He / Him / His) | https://ankursinha.in Research Fellow at the Silver Lab, University College London | http://silverlab.org/ Free/Open source community volunteer at the NeuroFedora project | https://neuro.fedoraproject.org Time zone: Europe/London

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