- Comp-neuro - lists.cnsorg.org

Forecasting responsiveness under propofol - ICASSP 2027 Grand Challenge

by Katja

Dear colleagues, We would like to invite participation in the DOSE-I Challenge, an ICASSP 2027 Signal Processing Grand Challenge on forecasting changes in responsiveness during propofol sedation from frontal EEG. Participants predict future MOAA/S approximately 60 s ahead from pre-index physiological data. The challenge is based on the recently released DOSE-I dataset, the first public large-scale EEG-based multimodal dataset of continuous propofol sedation with temporally dense annotation of sedation depth. Challenge / submissions: https://www.codabench.org/competitions/18100/ Open DOSE-I dataset: https://doi.org/10.5281/zenodo.18483291 == Timeline == • Challenge opens: October 1, 2026 • Final submission deadline: December 1, 2026 • Results and invitations: December 8, 2026 • Invited two-page papers due: January 7, 2027 • ICASSP 2027: May 16-21, 2027, Toronto, Canada Best wishes, K. Seeliger on behalf of the DOSE-I Challenge organizers +++++ academic website: https://seelikat.github.io/

Sept. 29, 2026

Computational Postdoctoral Position: Uncovering the Mathematics of Predictive Pursuit

by jonathan.whitlock＠ntnu.no

About the position We are seeking an enthusiastic and highly motivated Postdoctoral Fellow with a quantitative PhD and background in machine learning, dynamical systems, physics, engineering or related fields for a 3-4 year project investigating the computational principles of Predictive Pursuit in freely moving rodents. This project is an interdisciplinary collaboration between the labs of Jonathan Whitlock at the Kali Institute for Systems Neuroscience (NTNU, Trondheim, Norway and Alex Cayco-Gajic at the Group of Neural Theory in Ecole Normale Supérieure (ENS-PSL, Paris, France). The candidate will be physically based in Trondheim, with extensive opportunities for research visits to Paris. About the project The project aims to uncover how the brain anticipates and reacts to dynamically fleeing agents and to perceptual mismatch. We will use the head and body of freely moving rodents as physical readouts of internal planning, dynamic decision-making and perceptual processing, combining high-resolution motion capture and high-density neural recordings across a range of behavioral conditions. The successful candidate will lead the data-driven modeling effort, developing state-of-the-art statistical models combining machine learning and dynamical systems to infer changes in strategy from high-dimensional behavioral data. The project is highly collaborative, with modeling developed in partnership with the lab of Alex Cayco-Gajic in Paris, while working closely with behavioral neurophysiologists at the Kavli Institute in Trondheim. Duties of the position • Develop machine-learning and dynamical-systems approaches for analyzing high-dimensional behavioral data. • Model postural, movement and performance dynamics to identify behavioral states and pursuit strategies. • Carry out high-quality, independent research within the project framework. • Publish findings in high-impact academic journals and present at international conferences. • Participate actively in collaborations and in the intellectual life of the research group and Required selection criteria • A PhD in a quantitative field, such as physics, computational neuroscience, computer science, or engineering • Strong expertise in machine learning, dynamical systems, computational modeling or quantitative analysis • Demonstrated experience analyzing large, high-dimensional datasets, preferably including behavioral, video or neurophysiological • Publish findings in high-impact academic journals and present at international conferences. • Participate actively in collaborations and in the intellectual life of the research group and institute. • Documented experience with scientific programming, e.g. Python, MATLAB or related languages. • A strong academic record and documented research productivity. • Excellent oral and written communication skills in English. • Ability to work both independently and collaboratively in an interdisciplinary research environment. Interested? Apply through the job ad portal: nettskjema.no/a/655482 Questions? Jonathan Whitlock: jonathan.whitlock(a)ntnu.no | Alex Cayco-Gajic: natasha.cayco.gajic(a)ens.psl.eu Labs: www.whitlocklab.org | www.caycogajiclab.github.io

Sept. 28, 2026

2nd UK Theoretical Neuroscience Workshop – 18 December 2026, London

by Dimitris Pinotsis

We are pleased to announce the *second UK Theoretical Neuroscience Workshop*, taking place at *City St George’s, University of London*, on *Friday, 18 December 2026*. The workshop will bring together researchers and students working in theoretical, mathematical, and computational neuroscience for a day of invited *talks, poster presentations,* and *discussion*. 📍 *Venue:* City St George’s, University of London 📅 *Date:* Friday, 18 December 2026 🕘 *Time:* 09:00–17:30 💡 *Programme:* Invited talks, poster sessions, discussions, and a *poster award* Invited speakers include researchers from UCL, Oxford, Warwick, Nottingham, Birmingham, and Edinburgh, covering topics across neural dynamics, learning, network modelling, motor control, functional connectomics, temporal inference, and related areas. Further information, including the programme and abstracts, is available Here <https://dpinotsis.wixsite.com/uk-theoretical-neuro> Please feel free to circulate this announcement among interested colleagues and students. Best wishes, UK Theoretical Neuroscience Workshop Organisers Professor Steve Coombes Dr Dimitrios Pinotsis

Sept. 28, 2026

Open PhD and postdoc positions in computational neuroscience/neuroAI

by Roxana Zeraati

Dear all, We are inviting applications for the following collaborative PhD and postdoc positions in computational neuroscience/neuroAI: - PhD (based at TU Dresden, Germany): https://nextcloud.tuebingen.mpg.de/index.php/s/wbpcYQ5pgMjDJos - Postdoc (based at the Max Planck Institute for Biological Cybernetics, Germany): https://nextcloud.tuebingen.mpg.de/index.php/s/wjKjAHRidF5R4M8 We, the Natural Decision Making Group and the Embodied Decision Making Group, are joining forces within the CMC Unit <http://cmclab.org/> to uncover the computational, biological, and ecological principles underlying adaptive decision-making. We combine computational methods from reinforcement learning, dynamical systems, and AI with analyses of neural and behavioral data to investigate how different species adapt their decisions to the dynamics of their natural environments, while accommodating their embodied constraints. We would appreciate it if you could share these calls with anyone who might be interested in your network. Best wishes, Roxana and Shervin

Sept. 26, 2026

postdoc or staff scientist

by Canavier, Carmen C.

Carmen Canavier at LSU Health Sciences Center in New Orleans is recruiting a computational neuroscientist(s) at the postdoctoral or staff scientist level. One project involves modeling the local circuit in the medial entorhinal cortex with respect to theta nested gamma and grid cell activity and the other involves modeling the local circuit in hippocampal area CA1 with respect to cholinergic modulation and place field formation. Please email me at ccanav(a)lsuhsc.edu<mailto:ccanav@lsuhsc.edu> for details.

Sept. 25, 2026

Postdoctoral position: Computational neuroscience, nonlinear dynamics, and control (University of Arizona)

by drew＠arizona.edu

The Maurer laboratory in the Department of Neuroscience at the University of Arizona is recruiting a postdoctoral researcher interested in theoretical and computational approaches to neural dynamics. A central question is how inhibitory circuitry reshapes the states and transitions available to a recurrent neural network: not simply by reducing excitation, but by dynamically restricting, routing, and stabilizing trajectories through neural state space. We are particularly interested in whether relatively low-dimensional inhibitory or feedback signals can reorganize high-dimensional population activity, alter attractor structure and metastability, regulate transitions among network states, and stabilize circuits that would otherwise be unstable or chaotic. The position sits deliberately between theory and experiment. The researcher will have access to large-scale electrophysiological datasets including neuronal spiking, LFP, EEG, behavior, and circuit perturbations. The goal is to develop mechanistic models that generate discriminating predictions and can be tested against experimental interventions, rather than simply fitting models to neural data. We welcome applicants from computational neuroscience as well as control theory, nonlinear dynamical systems, applied mathematics, engineering, physics, computer science, and related quantitative fields. Prior neuroscience experience is not required. The position is full-time at the University of Arizona in Tucson, with salary according to NIH guidelines and full benefits. Applications are open until the position is filled. University of Arizona posting: req27102 Application materials: CV, cover letter, and statement of research interest. For informal questions, please contact: Andrew P. Maurer, PhD Associate Professor, Neuroscience University of Arizona drew(a)arizona.edu

Sept. 24, 2026

Upcoming Open Lab Online seminars and workshops

by Nada El Mahmoudi

Dear all, We are happy to share several upcoming Open Lab Online events on open tools, training, and methods in neuroscience and behavior. Open Lab Online is an international initiative that organizes accessible online seminars and workshops around open-source tools, experimental methods, and training across neuroscience and behavior. Animal Training Methods Across Species From Experimental Design to Naturalistic Behavior This seminar series will explore how animals are trained to interact with experimental tasks, touchscreens, vehicles, virtual environments, and naturalistic paradigms. First confirmed speakers include Kelly Lambert, Jennifer Taylor-O’Connor, Rainer Friedrich, Matthew Isaacson, and Marieke Schölvinck & Martha Nari Havenith, with additional seminars to be announced. Dates: 14 October, 4 November, 25 November, 20 January, 10 February Time: 16:00 CEST / 10:00 EDT for 14 October; 16:00 CET / 10:00 EST from November Full program and registration: https://nenckiopenlab.org/animal-training-methods-across-species/ Neural Data Analysis with Open-Source Tools From Raw Signals to Behavior-Linked Activity This hands-on workshop series will introduce an open-source workflow for neural data analysis, taught directly by the developers of the tools. The series will cover: SpikeInterface → Bombcell → Pynapple → NeMoS Part 1: Spike Sorting and Curation 19–20 October, 15:00–18:00 CEST / 09:00–12:00 EDT each day Modules: SpikeInterface + Bombcell Part 2: Behavior-Linked Analysis and Modeling 26–27 October, 14:00–15:30 CET / 09:00–10:30 EDT each day Modules: Pynapple + NeMoS Full program and registration: https://nenckiopenlab.org/neuraldata/ Bonsai Module I Workshops We will also host two Bonsai Module I workshops for participants interested in behavioral experiments, video tracking, closed-loop systems, and real-time data acquisition. 29 September, 16:00 CEST / 10:00 EDT https://nenckiopenlab.org/event/2200/ 13 October, 16:00 CEST / 10:00 EDT https://nenckiopenlab.org/event/bonsai-module-i-2/ Please feel free to share these events with anyone who may be interested. To receive future Open Lab Online announcements, you can subscribe to the mailing list here<https://5584ba20.sibforms.com/serve/MUIFADA4d4FHqdFYLj0P-heCkOQ5zMtIUiggjmg…>. You can also join the Open Lab Online Discord here<https://discord.gg/z7gvyj9yrV>. Best wishes, The Open Lab Online Team Dr. Nada El Mahmoudi Post-doctoral researcher, Peyrache lab The Neuro (Montreal Neurological Institute) McGill University, Canada

Sept. 24, 2026

Announcement: daftar 1.0 — recording what produced each computational result

by Aslan Satary Dizaji

Dear all, I would like to share an open-source tool that may be useful to people running simulations and model fits. The problem. Experiment trackers such as MLflow and Weights & Biases assume an experiment is a training loop with epochs, losses and checkpoints. A Hodgkin–Huxley simulation, a hierarchical fit across participants, or an EEG preprocessing pipeline has none of those. Months later it is often impossible to say which code version, environment and seed produced a given figure. What it does. One decorator or context manager around existing code records the environment, git state, every parameter, every seed, and content hashes of inputs into a plain-JSON manifest. daftar diff then compares two runs and separates fields that could have caused a difference from fields that merely record one — including the case where results differ and nothing that could have caused it does, which is a finding rather than a glitch. Seeds are applied rather than merely recorded, since noting that a run was irreproducible does not help anyone. Ten adapters record framework-specific state a generic tracker cannot infer: the integration method Brian2 auto-selected (it is stored nowhere), which ICA components were excluded in MNE, which confounds were regressed out in Nilearn, whether a NEURON compiled mechanism is stale relative to its .mod sources. No dependencies, no server, no account, no network access. Apache 2.0. Currently in peer review at pyOpenSci. pip install daftar https://github.com/aslansd/daftar One thing that emerged from building it, which may interest this list: four independent frameworks (MNE, cpm, Brian2, sbi) all report only one of the two reasons an optimiser stops. A fit that hit its iteration limit is indistinguishable from one that converged. I would welcome criticism, particularly from anyone who has previously tried a reproducibility tool and stopped using it. Aslan Satary Dizaji https://turan-cybernetics.com/ https://sites.google.com/a/umich.edu/aslansdizaji

Sept. 24, 2026

30 RTAIM Online Seminar - "Assessing the Ethical Risks of AI-Based Tools for Causal Inference from Real-World Evidence (RWE) in Medicines Evaluation"

by steven gouveia

[??] 30 RTAIM Online Seminar [??] 24 September | 14:00 (Porto) [??] Online via Microsoft Teams Tamas Soroncz-Szabo Physician, epidemiologist, visiting lecturer in clinical research methods, and medical project expert for the European Health and Digital Executive Agency (HaDEA). [???] Assessing the Ethical Risks of AI-Based Tools for Causal Inference from Real-World Evidence (RWE) in Medicines Evaluation The talk will examine how AI is increasingly used to analyse real-world health data for medicines evaluation — and the ethical and regulatory risks that arise when AI-supported conclusions can influence efficacy, patient safety, and healthcare decisions. [??] Join: https://teams.microsoft.com/meet/389914877372834...<https://teams.microsoft.com/meet/389914877372834?p=2VyrR9YvPfgVE9glG6&fbcli…> Meeting ID: 389 914 877 372 834 Passcode: Vn95Mb6h More info: https://ifilosofia.up.pt/activities/seminar-30-rtaim

Sept. 23, 2026

New PhD & Postdoc Opportunities in Computational Neuroscience & Computational Psychiatry

by Nadja R. Ging Jehli

Dear colleagues, We are building a new computational modeling hub at the University of Arizona - join us and grow with us! Ari Kahn and I are joining forces to build a closely connected computational community across two complementary labs at the intersection of decision science, cognitive neuroscience, and computational psychiatry. Together, the Kahn Lab and the NAIADEL Lab are recruiting multiple PhD students for Fall 2027 as well as postdoctoral researchers. Our groups tackle some shared questions from complementary angles: The Kahn Lab studies how people build predictive models of complex environments, use them to plan, and select among planning strategies. This work draws on reinforcement learning, successor representations, network science, control theory, and neuroimaging. Learn more here: www.kahnlab.org<https://www.linkedin.com/safety/go/?url=http%3A%2F%2Fwww%2Ekahnlab%2Eorg&ur…> The NAIADEL Lab studies how humans and artificial agents infer whether their actions matter, adapt when control shifts, and decide whether to persist, switch, or disengage after setbacks. This work draws on reinforcement learning, sequential sampling models, neural networks, and economic theory. Learn more here: www.naiadel.com<https://www.linkedin.com/safety/go/?url=http%3A%2F%2Fwww%2Enaiadel%2Ecom&ur…> Where we converge: We are especially excited about the intersection of meta-learning and meta-control. How do adaptive agents, biological or artificial, select among strategies? How do they recognize when a strategy is failing? And how do they revise their internal models under uncertainty and partial control? Trainees will be based primarily in one lab while benefiting from joint research meetings, shared computational infrastructure, and opportunities for cross-lab collaboration and co-mentorship. How to get involved: Prospective PhD students: Drop us a line with your CV and research interests. The Fall 2027 Psychology PhD application window opens October 15: Ph.D. Cognition and Neural Systems | Psychology<https://psychology.arizona.edu/cns> Postdoctoral candidates and other inquiries: Reach out directly with your CV and a brief statement of your research interests. arikahn(a)arizona.edu<mailto:arikahn@arizona.edu> nadjaging(a)arizona.edu<mailto:nadjaging@arizona.edu> We are very grateful for anyone who shares this within their broader network. Best, Nadja Nadja R. Ging-Jehli, PhD Assistant Professor Neurocomputation, Adaptive Intelligence, Agency Dynamics, & Embodied Learning (NAIADEL Lab) | www.naiadel.com<http://www.naiadel.com/> Cognition and Neuroscience Systems, Department of Psychology University of Arizona (614) 736-7755 | nadjaging(a)arizona.edu<mailto:nadjaging@arizona.edu> | nadja(a)gingjehli.com<mailto:nadja@gingjehli.com> | gingjehli.com<https://www.gingjehli.com/> [A button with "Hear my name" text for name playback in email signature]<https://www.name-coach.com/nadja-gingjehli>

Sept. 23, 2026