- Comp-neuro - lists.cnsorg.org

Final call: Spectral analysis in neuroscience course for non-specialists
by Axel Hutt Nov. 9, 2026

Nov. 9, 2026

Final call for registration ============================================================= Course: Spectral analysis of time series in neuroscience: Fundamental methods ============================================================= The 1-day course addresses fundamental aspects of spectral analysis without diving much into theory, just from a practical point of view. The aim is to provide a fundamental understanding of the different techniques out there to avoid mistakes, artefacts and to be able to choose the best technique for the own data. The course is planned like an interactive workshop, where we discuss analysis techniques and clarify open questions and possibly fill gaps of methodology understanding. The course content addresses non-specialists in mathematical analysis, e.g. researchers with education in neurobiology, medicine or psychology, but of course it is also open to theory-oriented researchers who intend to understand the practical side of spectral analysis in neuroscience. Possible topics to be discussed are, e.g. * Sampling theory * Fourier analysis and its possible artefacts, e.g. aliasing, spectral leakage * Time-frequency analysis (Short-Time Fourier Transform, Wavelet Transform, Hilbert Transform and Empirical Mode Decomposition) and its limits in applications * Synchronisation, coherence and Phase-Amplitude Coupling Event information: * Location: Bernstein Center Freiburg im Breisgau, Großer Hörsaal, Hansastr. 9a , 79104 Freiburg, Germany ( [ https://www.bcf.uni-freiburg.de/ | https://www.bcf.uni-freiburg.de ] ) * Date of course and time: Friday, November 27 2026, 9:15-15:45 * Registration : send an email to Axel Hutt (email address: first name.lastname at inria.fr) * Registration deadline: Monday, November 9 2026 * Registration fee: none, free of charge The course is supported by the Neurowissenschaftliche Gesellschaft ( [ https://www.nwg-info.de/ | https://www.nwg-info.de/ ] ). -- Dr. rer. nat. Axel Hutt Directeur de Recherche Equipe NECTARINE - INRIA Nancy Center at University of Lorraine Equipe MLMS - iCube Strasbourg Bâtiment NextMed , 2, rue Marie Hamm 67000 Strasbourg, France Team webpage: https://www.inria.fr/fr/nectarine

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Workshop on sign- and goal-tracking, Potsdam, 20–22 Nov 2026 – online participation open to all
by Daniel Schad Nov. 8, 2026

Nov. 8, 2026

Dear colleagues, We would like to invite you to an international workshop on individual differences in Pavlovian conditioned approach: Sign- and goal-tracking: Human data, computational models, and rodent foundations Potsdam, Germany (near Berlin) – Friday 20 November (15:00) to Sunday 22 November 2026 (14:30) https://danielschad.github.io/workshopSTGT.html Research on sign- and goal-tracking has developed rapidly in several partly overlapping areas: rodent work on the neural and neurochemical mechanisms, computational accounts of why identical cue–reward contingencies produce different conditioned responses across individuals, and a growing body of human research using eye-tracking, physical approach tasks, and neural responses to cues and rewards. Researchers from these areas rarely meet in the same room. The aim of the workshop is to compare the approaches side by side – lever autoshaping, gaze-based and neural measures, physical approach tasks, and formal models – and to discuss not only findings but also the practical and methodological details of how the work is done. Speakers and contributors include Patrick Anselme, François Cinotti, Shelly Flagel (online), Sara Garofalo, Michelle Heck, Robert Honey, Jonathan Morrow, Cristina Orsini, Martin Paulus, Terry Robinson (online), Nicola Sambuco, Benjamin Saunders (online), Francesco Versace, and Reinout Wiers (online). Ralf Engbert and Daniel J. Schad facilitate the workshop. How to take part Online: Participation via Zoom is open to everyone. Email us at stgtworkshop.potsdam(a)gmail.com and we will send you the programme and the access details. On site: A small number of places remain in Potsdam (participation fee €70, covering some food and drinks). If you would like to attend in person, please write to us as soon as possible – on-site places are limited and allocated on a first-come, first-served basis. Posters: A poster session open to researchers at all career stages runs alongside the workshop. If you are attending on site and would like to present, please include a title and a short abstract in your email. Please feel free to forward this invitation to colleagues and students who may be interested. With best wishes, Daniel Schad Prof. Dr. Daniel J. Schad Institute for Mind, Brain & Behavior HMU Health and Medical University, Potsdam, Germany Workshop email: stgtworkshop.potsdam(a)gmail.com

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Hippocampus Atlas: Request for feedback
by Sheetal Jadhav Nov. 8, 2026

Nov. 8, 2026

*Hippocampus Atlas*, a free, open-source interactive atlas of the hippocampal formation. It covers cell types, circuits, rhythms, plasticity, theory and disease, and most views are live simulations that run in the browser. It’s an ongoing project, and I’m hoping to get feedback from the community to improve it. - Live atlas: https://sheetal-jadhav.github.io/hippocampus-atlas/ - Code: https://github.com/sheetal-jadhav/hippocampus-atlas The author would welcome corrections and suggestions from researchers and educators. *Feedback (5 min)*: https://forms.gle/aqvg2gDaaSfD4eA16 Best, Sheetal Jadhav (she/her) <https://sheetal-jadhav.github.io/> Computational Neuroscience Researcher

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Fwd: World wide VVTNS series (7th season): November 11, 2026 | Dynamical stability in biologically plausible attractor neural networks | Uri Cohen, The Weizmann Institute of Science
by David Hansel Nov. 8, 2026

Nov. 8, 2026

[image: VVTNS.png] https://www.wwtns.online <https://streaklinks.com/A9c7PbbpKY7PxB6PaAJWGD3-/https%3A%2F%2Fwww.wwtns.on…> - on twitter: wwtns@TheoreticalWide You are cordially invited to the lecture Uri Cohen Weizmann Institute for Science on the topic of Dynamical stability in biologically plausible attractor neural networks The lecture will be held on Zoom on November 11, 2026 at *11:00 am ET * To receive the link: https://www.wwtns.online/register-page *Abstract: * Recurrent neural networks are canonical models of biological memory, but previous theoretical approaches to auto-associative memory have studied only highly restrictive conditions that do not readily apply to biological neural circuits. Those approaches ensured memory stability by engineering the model dynamics (e.g., to follow the gradient of a Lyapunov function), so they do not apply to more general classes of dynamical systems. We present an alternative approach that uses a general dynamical system where memory stability is not guaranteed but emerges for certain parameter choices. We develop a theory of the local stability of discrete fixed points in a broad class of networks with graded neural activities and in the presence of noise. Using methods from random matrix theory, we analyze the bulk and outliers of the eigenvalue spectra of the Jacobians that characterize network dynamics around fixed points. We find that either all fixed points are stable or all are unstable, depending on whether their number is below a “critical load for stability”, which differs from the classical “critical capacity”, which measures the maximal number of achievable fixed points regardless of stability. By analyzing how this critical load for stability depends on experimentally measurable quantities that characterize memory-pattern statistics and neuronal activation functions, our analysis highlights the computational benefits of sparse-like patterns and threshold-linear activation functions and offers testable predictions for neural circuits supporting memory. Focusing on hippocampal area CA3, a neural circuit previously suggested to implement auto-associative memory, we partner with experimental collaborators to test the prediction that CA3 pyramidal neurons should use threshold-linear activation. Curating a large dataset of in vivo patch-clamp results for CA3 pyramidal neurons from behaving mice, we provide initial support for this prediction. *About VVTNS: VVTNS is a weekly digital seminar on Zoom targeting the theoretical neuroscience community. Created as the World Wide Neuroscience Seminar (WWTNS) in November 2020 and renamed in homage to Carl van Vreeswijk in Memoriam (April 20, 2022), its aim is to be a platform to exchange ideas among theoreticians. Speakers have the occasion to talk about theoretical aspects of their work which cannot be discussed in a setting where the majority of the audience consists of experimentalists. The seminars are 45 min long followed by a discussion and are held on Wednesdays at 11 am ET. The talks are recorded with authorization of the speaker and are available to everybody on our YouTube channel.* ᐧ

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Fellowships in the Center for Studies in Physics and Biology at Rockefeller University
by jzavatoneveth＠rockefeller.edu Nov. 6, 2026

Nov. 6, 2026

Dear colleagues, The Center for Studies in Physics and Biology expects to have a small number of postdoctoral fellowships available for appointments in September 2027. We are seeking theoretical physicists, mathematicians and computer scientists with a demonstrable interest in the interface between their discipline and biology. The Fellows are to be at that stage of career as to function as independent members of the Center, free to work alone or in collaboration with any members of The Rockefeller University faculty. The appointment is nominally for two years, with a third year implicit, but based on mutual satisfaction. Applicants should submit curriculum vitae, including a list of publications, a 3-page (maximum) research statement and three letters of recommendation by November 30, 2026. The contents of all letters should be addressed to: Director, Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Avenue, Box 75, New York, NY 10065-6399. Applications should be submitted here: https://cspbfellow.rockefeller.edu Consideration will be given to late received applications. Best regards, Jacob Jacob Zavatone-Veth Assistant Professor and Head of Laboratory Laboratory of Theoretical Neuroscience The Rockefeller University

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Summer school in Brazil March 2027
by Kalel Rossi Nov. 6, 2026

Nov. 6, 2026

Dear comp-neuro members, The ICTP South American Institute for Fundamental Research (ICTP-SAIFR) is offering a summer school in Brazil on Brain Dynamics <https://www.ictp-saifr.org/sbd2027/> in March 2027. The school will introduce concepts and methods from nonlinear dynamics with applications to neuroscience, with lectures headed by Aneta Koseska, Bard Ermentrout, Elif Koksal, Mauro Copelli, Rubén Moreno Bote and Xiao-Jing Wang. The school will take place in Sao Paulo, at ICTP-SAIFR <https://www.ictp-saifr.org/2027-activities/>, from 15-26 March 2027. *Registration* is free and open until 3 December 2026. Link to the registration is available at https://www.ictp-saifr.org/sbd2027/. For further inquiries, please do not hesitate to contact kalel.rossi(a)mpinb.mpg.de or bruna(a)ictp-saifr.org. Best On behalf of the school’s organizing committee Kalel Rossi, PhD

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Postdoc & PhD student positions
by Haefner, Ralf Nov. 6, 2026

Nov. 6, 2026

Postdoctoral and graduate student positions available How does the brain infer causal relationships in the world? How do beliefs about the causal structure of a scene influence motion perception? How can the underlying computations be modeled using Bayesian inference, and how can these computations be tested using neurophysiological experiments? For this collaborative project between the computational neuroscience lab of Dr. Ralf Haefner, and the neurophysiology lab of Dr. Gregory DeAngelis, both at the Department of Brain & Cognitive Sciences at the University of Rochester, we are looking to recruit two postdoctoral fellows and PhD students. This project is highly collaborative with all researchers being involved in most aspects of the project from experimental design to data collection to data analysis & theory development. The project is based on our prior collaborative work [1,2] and we will have two related posters at the upcoming SfN meeting [3,4]. For the theoretical/computational efforts, candidates are expected to have a background in a quantitative field like computational neuroscience, machine learning, math & psychology, etc.. For the experimental efforts, candidates are expected to have a background in neuroscience, experimental psychology, biomedical engineering, or a related field, and previous research experience in systems neuroscience is highly beneficial. If interested, please submit your CV, a statement of research interests, and the names and contact information for three references to ralf.haefner(a)rochester.edu or gdeangelis(a)ur.rochester.edu. Ralf will also be at SfN to answer any questions. The UR/BCS department is at the center of a vibrant and supportive scientific community. It has particularly strong ties to the Center of Visual Science, the Department for Neuroscience, the Department for Computer Science, the Department for Linguistics, and the Data Science Institute. Rochester in upstate NY is family-friendly and affords a high quality of life with access to a world-class symphony, museums, and a wide range of outdoor activities: several parks within cycling distance, 20min by car to sandy beaches on Lake Ontario, 1h to Finger Lakes / wine country / skiing, 3h to great hiking in the Adirondacks. We also have a balanced 4 season climate with weather for every occasion: Lilac Festival in the spring, beautiful sunny summers (<10 days above 90 degrees), gorgeous fall foliage, and guaranteed snow in the winter. More info here: https://www.visitrochester.com. [1] Shivkumar, S., DeAngelis, G. C., & Haefner, R. M. (2025). Hierarchical motion perception as causal inference. Nature Communications, 16(1), 3868. [2] Lengyel, G., Shivkumar, S., DeAngelis, G. C., & Haefner, R. M. (2026). Bayesian causal inference unifies perceptual and neuronal processing of center-surround motion in area MT. eLife. https://doi.org/10.7554/eLife.110621.1 [3] Dong et al. (2026). Neural correlates of speed-dependent relative motion perception in area MT. SfN Poster# PSTR184.01 / AA2, WCC Halls A-C, Nov 16, 1-5pm [4] Yuan et al. (2026). Motion perception as causal inference: testing the causality assumption. SfN Poster# PSTR184.02 / AA3, WCC Halls A-C, Nov 16, 1-5pm

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Computational Neuroscience job search at University of Maryland (College Park)
by Daniel A. Butts Nov. 5, 2026

Nov. 5, 2026

The Department of Biology at the University of Maryland, College Park (UMD), invites applications from individuals using computational approaches to study fundamental questions in neuroscience for a tenure-track or tenured position at the rank of Assistant or Associate Professor. Computational neuroscience is defined broadly; research areas of interest include: biophysical and statistical modeling, computational neurogenetics, neural population codes, and the intersection of biological intelligence and AI ("NeuroAI"). Preference will be given to applicants with computational research programs that integrate experimental data (including multi-modal data) to address important issues in basic and translational neuroscience. This position is intended for applicants with research programs that have minimal or no wet lab components. The successful candidate will be expected to: Establish and sustain a vigorous, externally funded, independent research program in computational neuroscience. Teach undergraduate and graduate courses in neuroscience and/or quantitative biology and contribute to larger campus initiatives in neuroscience, quantitative biology, and/or NeuroAI. Participate in departmental, college, and university service and contribute to a collaborative academic environment. This position is part of a new Quantitative Biology Initiative in the Department of Biology supporting postdoctoral fellows and supports a new Predictive Biology Hub for Human and Environmental Health dedicated to fostering collaborative research and new educational programs in Quantitative Biology. Members of the Department work with colleagues across UMD, including in the Artificial Intelligence Interdisciplinary Institute at Maryland (AIM), the Brain and Behavior Institute (BBI), the UMD Institute for Advanced Computer Studies (UMIACS), and the Institute for Systems Research (ISR). Faculty participate in a number of relevant graduate programs, including Neuroscience and Computational Science (NACS), Biological Sciences (BISI), Biophysics, and Applied Mathematics & Statistics, and Scientific Computation (AMSC). The Department also supports undergraduate programs in Biological Sciences (BSCI) and Neuroscience (NEUR). UMD is located in the Washington, D.C. metropolitan area, which is home to major national institutions and medical centers (e.g., the National Institutes of Health) and proximate to the Rockville Biotech corridor. Details and information on applying: https://umd.wd1.myworkdayjobs.com/UMCP/job/University-of-Maryland-College-P…

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Recruiting Ph.D students in computational cognitive neuroscience
by Stefano Anzellotti Nov. 5, 2026

Nov. 5, 2026

I am looking for a Ph.D student interested in using computational approaches, behavioral methods and/or neuroimaging to study one or more of the following areas: 1. Recognition of objects, actions and events 2. Multi-task learning 3. Agent understanding 4. Individual variation in autism and other psychiatric disorders The laboratory collaborates with Computer Science and Physics PIs, offering opportunities for interdisciplinary training. The position starts in Fall 2027, the deadline for applications is December 15, 2026. For inquiries please contact anzellos(a)bc.edu sending a CV and a brief statement of skills and research interests. Stefano Anzellotti (he/him) Associate Professor, Department of Psychology and Neuroscience Chair, Research Computing Committee Boston College https://sccnlab.bc.edu/

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[COMPLEX NETWORKS 2026] Program Announced – Join Us in Granada!
by Hocine Cherifi Nov. 4, 2026

Nov. 4, 2026

Dear colleagues, 🌐 *The scientific program of COMPLEX NETWORKS 2026 is now available!* Join us in *Granada, Spain, December 2–4, 2026*, for the *15th International Conference on Complex Networks and Their Applications*. 🎙️ *Five distinguished keynote speakers* Alexandra Brintrup · Nitesh Chawla · Kimmo Kaski · Bruno Lepri · Eckehard Schöll 📚 *A rich interdisciplinary program* 27 thematic oral sessions, 3 spotlight sessions, and 5 poster sessions covering network science, graph learning, complex systems, computational social science, and applications across disciplines. 🎓 *Tutorials — December 1* Fariba Karimi · Huijuan Wang 🤝 *More than a conference* COMPLEX NETWORKS is a unique meeting place where researchers from diverse backgrounds exchange ideas, engage in stimulating discussions, and build new collaborations. *Whether presenting or simply attending, everyone is welcome!* 📋 *Explore the program:* https://complexnetworks.org/program/ 🎟️ *Register:* https://complexnetworks.org/registration/ We look forward to welcoming you in Granada for this special 15th edition! Please share this invitation with colleagues and students who may be interested. Best regards, Hocine Cherifi General Co-Chair, COMPLEX NETWORKS 2026 Join us at COMPLEX NETWORKS 2026 <https://www.complexnetworks.org/> *-------------------------* Hocine CHERIFI Laboratoire* I*nterdisciplinaire *C*arnot de *B*ourgogne - ICB UMR 6303 CNRS Université Bourgogne Europe Editor in Chief Plos Complex Systems <https://plos.org/complex-systems-research-journal/#:~:text=PLOS%20Complex%2….> Founding & Adisory Editor Applied Network Science <https://appliednetsci.springeropen.com/> Editorial Board member IEEE ACCESS <https://ieeeaccess.ieee.org/?http%3A%2F%2Fieeeaccess_ieee_org%2F>, Scientific Reports <https://www.nature.com/srep/>, Journal of Imaging <https://www.mdpi.com/journal/jimaging>, Quality and Quantity <https://www.springer.com/journal/11135/>, Computational Social Networks <https://computationalsocialnetworks.springeropen.com/>, Complex Systems <https://www.complex-systems.com/> Evolutionary Intelligence <https://link.springer.com/journal/12065>

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