- Comp-neuro - lists.cnsorg.org

Special session in Generative, Foundation Models for Robotics: From Language and Vision to Embodied Action, at WCCI 2026

by Alper Yegenoglu

Dear colleagues, We cordially invite you to submit your paper to the Special Session: "*Generative Foundation Models for Robotics: From Language and Vision to Embodied Action*", to be held at the *2026 IEEE World Congress on Computational Intelligence (WCCI 2026)*. *Website*: https://wccigenai2026.github.io This special session aims to bring together recent advances in generative and foundation models and their applications to robotics. Topics of interest include, but are not limited to: * Diffusion models for robot trajectory planning and control * Generative adversarial networks for robotic applications * Flow matching methods for robotic control * Language-guided robot manipulation and navigation * Meta-learning for adaptive robotic behaviors * Multi-task planning and execution * Transfer learning across robotic domains and environments * Generative imitation learning from human demonstrations * Generative design of robot morphologies * Co-evolution of robot structure and control * Curriculum learning with generative models * Constraint-aware generative planning *Organizers:* Erdal Kayacan (Paderborn University, Germany) Chen Qinyu (Leiden University, The Netherlands) Konstantinos Alexis (Norwegian University of Science and Technology, Norway) Guido de Croon (TU Delft, The Netherlands) Erdi Sayar (Paderborn University, Germany) Van Huyen Dang (Paderborn University, Germany) Alper Yegenoglu (Paderborn University, Germany) Adrian Redder (Paderborn University, Germany) *Paper Submission Deadline*: 31 January, 2026 (UTC-12) Kind regards, Alper -- Dr. *Alper Yegenoglu* Postdoctoral Researcher Automatic Control Group (RAT) University of Paderborn Warburger Str. 100 33098 Paderborn Germany *Office* P1.7.15.4 *Telephone* +49 5251 60-1898 *E-Mail* alper.yegenoglu(a)uni-paderborn.de *Web* https://en.ei.uni-paderborn.de/rat

Jan. 6, 2026

Allen Institute Modeling Software Workshop 2026 - and a brief survey

by Anton Arkhipov

Dear Colleagues, Happy New Year! It is that time of year again when we are asking for your thoughts about modeling and simulation software. Could you please help us understand what the field needs by filling out this brief survey<https://forms.office.com/pages/responsepage.aspx?id=1pxmMn9zOUuL3daVESDT_IQ…>? That will be very helpful to guide our work (and is required by the NIH). Also, consider joining us for the Allen Institute Modeling <https://alleninstitute.org/events/2026-modeling-software-workshop/> Software Workshop<https://alleninstitute.org/events/2026-modeling-software-workshop/> on July 20-22, 2026 at the Allen Institute in Seattle, WA! This hands-on workshop focuses on building and simulating complex and heterogeneous network models grounded in real biological data. Participants will learn to use BMTK, SONATA, VND, our data, and models for simulating brain circuits. Applications<https://alleninstitute.submittable.com/submit/339665/2026-allen-institute-m…> are due March 15th, 2026. Selected applicants will be notified by May 1, 2026. Limited travel funding is available. And another exciting event is happening on January 27 in Singapore: the Neuro for AI & AI for Neuro<https://neuroai-multimodal-workshop.github.io/> workshop at the AAAI 2026 conference<https://aaai.org/conference/aaai/aaai-26/>. Join us for a day of talks, posters, and discussions about cutting-edge research at the intersection of Neuro and AI. We are looking forward to hearing from you. Best regards, Anton. Anton Arkhipov Investigator, Allen Institute antona(a)alleninstitute.org<mailto:antona@alleninstitute.org> alleninstitute.org<https://alleninstitute.org> brain-map.org<https://portal.brain-map.org/>

Jan. 5, 2026

Postdoctoral positions in Brain Dynamics / Computational Neuroscience (Chile–Spain)

by Wael El Deredy

Help Shape the Future of Stroke Rehabilitation and Brain Stimulation We invite applications to join the Brain Dynamics Lab—an interdisciplinary research team at the interface of dynamical systems theory, brain network modelling, and neurostimulation-based rehabilitation. Our mission is to uncover and exploit the mechanisms of brain plasticity following stroke and neuromodulation, by combining cutting-edge modelling with real-world neurotechnology. We regard recovery not as anatomical repair, but as a problem of restoring network-level brain dynamics through non-invasive electrical stimulation (tDCS/tACS). We model the brain as a dynamical system perturbed by lesion, reconfigurable via stimulation-dependent plasticity. Paid positions according to the academic level Location: Valencia, Spain Chile [Valparaiso, Santiago, Talca, Concepción, flexible within collaborating institutions] Positions Available: • PhD studentships [2 years] • Postdoctoral research fellows • Research assistants (MSc-level support roles) Fields: Physics, Biomedical Engineering, Electronics/Telecom/Control/Informatics Engineering, Applied Mathematics, Computer Science, Computational Neuroscience What You’ll Work On Successful applicants will join a growing team working on projects including: • Whole-brain network modelling (Kuramoto, Wilson-Cowan, neural mass models) to simulate post-stroke disruption and plastic recovery • Computational modelling of plasticity mechanisms (Hebbian, homeostatic, STDP, resonance-tuned) across varying brain states • Control theory in brain networks, including stimulation as control input to re-establish metastability and synchrony • Analysis of electrophysiological and imaging data (EEG, TMS, lesion mapping) from healthy and clinical populations • Development of simulation-guided protocols for individualized, state-dependent stimulation These positions will support Masters or PhD theses, contribute to postdoctoral innovation, and underpin a translational pipeline from virtual lesion modelling in healthy participants to patient-specific neurorehabilitation strategies. We are looking for: We welcome candidates from a broad range of backgrounds, including: • Physicists with expertise in nonlinear dynamics or network theory • Electrical or Telecom Engineers with skills in signal processing, control theory, modelling, or brain–computer interfaces • Biomedical Engineers experienced in neuroimaging, neurorehabilitation, or neural interfaces • Applied Mathematicians or Computer Scientists with interests in simulation, control or computational neuroscience We value curiosity, collaboration, and a commitment to translational science. Programming skills in Python, Matlab or C++ are required. Prior experience with neural modelling (e.g., Kuramoto, neural masses), data analysis (EEG/fMRI), high performance computing (HPC), or brain stimulation (tDCS/tACS/TMS) is a strong plus but not required. Why join us now This is an exciting moment in the field. Advances in connectome-informed modelling, network control theory, and neuromodulation are converging to make precision neurostimulation a clinical reality. As part of our team, you’ll be at the frontier of: • Designing next-generation rehabilitation tools • Validating models with real-world clinical and experimental data • Publishing in top-tier journals (e.g., Network Neuroscience, Neuroimage, PLOS Comp Biol) • Collaborating with international partners in Spain, Portugal, Chile, and the UK How to apply Send academic CV and one page letter of motivation describing your research interests, and fit with the Brain Dynamics Lab to: Chile Alejandro.Weinstein(a)USM.cl<mailto:Alejandro.Weinstein@USM.cl> Spain Wael.Deredy(a)ValgrAI.EU<mailto:Wael.Deredy@ValgrAI.EU> Selected group publications https://arxiv.org/abs/2511.14065 https://www.biorxiv.org/content/10.1101/2025.04.30.651283v2.abstract https://www.nature.com/articles/s41598-025-27606-5 https://www.nature.com/articles/s41598-025-14299-z https://ieeexplore.ieee.org/abstract/document/10937758/ https://doi.org/10.1098/rstb.2023.0093 https://link.springer.com/article/10.1007/s11571-024-10093-1

Jan. 5, 2026

ICPRAI 2026: Special Session on Frontiers of Artificial Intelligence for Medical Applications: Models, Reasoning, Perception, and Interaction

by Ghazaleh Khodabandelou

Frontiers of Artificial Intelligence for Medical Applications: Models, Reasoning, Perception, and Interaction ICPRAI 2026, Montréal, Québec, Canada, June, 2026 https://icprai2026.com/ Scope Artificial intelligence has seen remarkable progress in digital healthcare across areas such as learning algorithms, knowledge representation, perception, and interaction. From deep learning advances in vision and language, to reinforcement learning for control, to symbolic and neuro-symbolic hybrids for robust reasoning, modern AI systems are increasingly capable of understanding complex data, adapting to new tasks, and interacting with humans and environments. This Special Session invites original contributions that explore foundational models, architectures, and applications spanning the AI spectrum, including but not limited to learning and representation; planning and decision-making; perception and multimodal understanding; human-AI collaboration; and trustworthy, explainable, and ethical AI. We welcome theoretical analyses, novel algorithms, system implementations, and domain-specific studies that illustrate state-of-the-art techniques and future directions in AI, with special encouragement for work in large language models, multimodal vision-language modeling, and impactful applications in healthcare and medical domains such as medical imaging, autism detection, neurodegenerative disorders (e.g., Alzheimer’s and Parkinson’s), and diabetes management. Topics of Interest Topics of interest include, but are not limited to: • Large Language Models (LLMs) and foundation models • Embeddings, representation learning, and transfer learning • Generative modeling: GANs, VAEs, diffusion and beyond • Multimodal integration: vision-language, audio-visual, sensor fusion • Symbolic, neuro-symbolic, and hybrid reasoning systems • Automated planning, scheduling, and decision-theoretic frameworks • Reinforcement learning, multi-agent systems, and control • Human-AI collaboration, mixed-initiative interfaces, and personalization • Explainability, interpretability, causal analysis, and fairness • Robustness, safety, trustworthiness, and privacy-preserving AI • Healthcare and medical AI applications: imaging, diagnostics, chronic care 1 Important Dates • Full paper submission deadline: January 15, 2026 • Notification of acceptance: March 7, 2026 • Camera-ready deadline: March 13, 2026 • Early Registration deadline: until April 30, 2026 • Special Session at ICPRAI: June 15-18, 2026 Submission Guidelines Please follow the standard ICPRAI submission instructions at the conference website. When up loading your paper, select “Frontiers of Artificial Intelligence for Medical Applications: Models, Reasoning, Perception, and Interaction ” as the target session. Organizers • Prof. Ghazaleh Khodabandelou, University Paris-Est, France ghazaleh.khodabandelou(a)u-pec.fr<mailto:ghazaleh.khodabandelou@u-pec.fr> • Prof. Mounîm A. El Yacoubi, Institut Polytechnique de Paris, France mounim.el_yacoubi(a)telecom-sudparis.eu<mailto:mounim.el_yacoubi@telecom-sudparis.eu> Direct submission link (EasyChair): https://easychair.org/conferences2/submissions?a=35638543 (Please select the Special Session when submitting.)

Jan. 4, 2026

Project Research Scientist Position at IIT Ropar.

by Sukrit Gupta

Dear all, we are hiring a Project Research Scientist (Non Medical) at IIT Ropar for an ICMR project. Our lab does work with clinicians at multiple public hospitals in North India and this project is in collaboration with clinicians at PGIMER, Chandigarh. The project is funded for five years. Would prefer someone who has a computer science or AI background. Detailed advertisement at https://www.iitrpr.ac.in/downloads/sites/default/files/December/AD-01.pdf The selected candidate will be expected to enroll for a PhD at IIT Ropar. If you're interested you can drop me an email at sukrit.gupta(a)iitrpr.ac.in Deadline for application is: 10 January, 2026. Regards, Sukrit ________________ Sukrit Gupta, BEng (CS, PEC, India), PhD (CS, NTU, Singapore) Assistant Professor, Department of Biomedical Engineering, and School of Artificial Intelligence and Data Engineering, Indian Institute of Technology, Ropar, Punjab, India. Office: Room No. BM 28, Super Academic Block, IIT Ropar. Phone: +91 1881 232170, E: sukrit.gupta(a)iitrpr.ac.in, W: https://sites.google.com/site/sukritsite *God, grant me the serenity to accept the things I cannot change, the courage to change the things I can, and the wisdom to know the difference.*

Jan. 4, 2026

What can you do with 1000 neurons? Task 3

by Nicolas P. Rougier (inria)

Dear all, The second task (cued decision) is still unsolved but the the challenge is still running with a new task (valued decision) as well as a new agenda. You'll find instructions at https://github.com/rougier/braincraft and the rules for the new task. Reminder: you have have 1000 neurons (leaky rate models), 100 seconds of training time and 10 runs for evaluation. The difficulty comes from the imposed constraints. Best, Nicolas Rougier. -- Nicolas P. Rougier —— www.labri.fr/perso/nrougier Institute of Neurodegenerative Diseases, Bordeaux

Jan. 4, 2026

Special Issue: Bio-Inspired Computation Based on Mathematical Modeling—Theories and Applications in Health Sciences

by Barna Iantovics

Call for papersSpecial Issue: Bio-Inspired Computation Based onMathematical Modeling—Theories and Applications in Health SciencesJournal: Mathematics (ISSN 2227-7390) Impact Factor 2.2Submission https://www.mdpi.com/journal/mathematics/special_issues/9B5062KZ98 Dear Colleague, You are kindly invited to contribute with a paper to theSpecial Issue. It is estimated that biological life that has evolved overmillions of years will be a fruitful source of inspiration for the developmentof novel computational mathematical methods in the years to come, representingimportant research directions on mathematical modeling in the field ofartificial intelligence. Diverse problems in health sciences are computationally hardand cannot be solved efficiently via actual methods. Mathematical modelingbased on bio-inspired computing applied to solve computationally hard problemsin health sciences domains is an emerging field in this area. Bio-inspiredcomputing has been proven successful for solving a large variety of problems indomains of science where other methods have not been so effective. In this context, this Special Issue invites researchers tocontribute original works regarding the development of bio-inspiredcomputational and hybrid methods for solving difficult problems in healthsciences that represent significant scientific advancements. Kind regards,Guest EditorsProf. Dr. Laszlo Barna IantovicsProf. Dr. Matthias DehmerProf. Dr. Francesco FlamminiProf. Dr. Frank Emmert-Streib

Jan. 4, 2026

Call for papers - Special Issue: Advances in Intelligent Systems, Technologies and Applications

by Barna Iantovics

Call for papersSpecial Issue: Advances inIntelligent Systems, Technologies and ApplicationsJournal: Applied Sciences (ISSN2076-3417) Impact Factor 2.5Submission https://www.mdpi.com/journal/applsci/special_issues/5IQ6DOHB42 Dear Colleague, You are kindly invited tocontribute with a paper to the Special Issue. Intelligence in nature is verydiverse; it can be discussed in terms of the intelligence of chimps, dolphins,and many other animals and even the collective intelligence of very simple lifeforms such as ants. The concept of intelligence is being adopted in manydomains of science. From practical and theoreticalperspectives, an essential current research direction that is under examinationby a very large number of scientists worldwide is the development of artificialsystems, also called agent-based systems, which can be either individual agentsor cooperative multiagent systems. These systems are embedded in theenvironment, possess a certain degree of autonomy, and are capable ofperceiving the environment and executing actions in it. Intelligence inagent-based systems can emerge through advanced problem-solving abilities. Todevelop these intelligent systems, techniques such as supervised learning andunsupervised learning play pivotal roles. Supervised learning involves trainingsystems on labeled datasets, enabling them to map inputs to outputs and improvetheir predictions or classifications over time. These methods are extensivelyused in applications such as image recognition, natural language processing,and medical diagnosis. On the other hand, unsupervised learning enables systemsto identify patterns and structures in unlabeled data, facilitating clustering,anomaly detection, and exploratory data analysis. A more recent paradigm,retrieval-augmented generation (RAG) and cache-augmented generation (CAG),combines retrieval- and cache-based methods with generative models to enhanceintelligent systems, producing highly contextualized and accurate responses oractions. These approaches are instrumental in developing advanced systems fordomains such as conversational AI, knowledge management, and decision support.Intelligent agent-based systems have many real-world applications, includingthe health sciences and industry. The number and diversity of intelligentsystems are increasing rapidly. In this context, the great challenge consistsof creating increasingly intelligent systems. Another critical challenge,approached by only a few researchers worldwide, is the development of universalmetrics, including black-box-based intelligence metrics, to measure theintelligence of these systems. Such advances could allow for the comparison ofsystems based on their intelligence. In cooperative multiagent systems,intelligence can be assessed at the system level; this is known as collectiveintelligence. Even in very simple cooperative multiagent systems, agents mayinteract nonlinearly at various decision points, resulting in emergentcomplexity and intelligence at the system level. This Special Issue aims toestablish a solid foundation for future research through a collection of papersthat advance the field by elaborating on theories, designing applications, andpresenting surveys regarding the next generation of increasingly intelligentsystems. The areas of research covered in these papers could include the studyof self-organization, emergence, hybridization, scalability, robustness,measuring machine intelligence, and the integration of advanced paradigms suchas supervised learning, unsupervised learning, retrieval-augmented generation,and cache-augmented generation. Kind regards,Guest EditorsProf. Dr. Laszlo Barna IantovicsProf. Dr. László KovácsDr. Attila Biró

Jan. 4, 2026

Fwd: [seminar.wwtns] World wide VVTNS series (6th season): Wednesday, January 7, 2025, at 11:00 am ET - Carlos Brody, Princeton Neuroscience Institute

by David Hansel

[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 VVTNS 2026 opening lecture Carlos Brody Princeton Neuroscience Institute on the topic of *Towards using large-scale, cross-brain neuronal recordings * *to identify the brain’s internal signals* to identify the brain’s internal signals The lecture will be held on zoom on January 7, 2026, at *11:00 am ET * > To receive the link: https://www.wwtns.online/register-page > *Abstract: *Neural activity is often analyzed with respect to external referents, such as the onset of a sensory stimulus or an overt motor action. Simultaneous recordings allow referencing neurons’ activity to each other and thus detecting signals that are internal to the organism. Further, multi-region simultaneous recordings allow observing how these internal signals are coordinated across the brain. Following this logic in rats performing a perceptual decision-making task, we recorded simultaneously from thousands of neurons across up to 20 brain regions at once. Here we report two internal signals which we found to profoundly shape decision-related neural dynamics and brain states. First, we decoded the continuously evolving decision state separately from each region, and found surprisingly large magnitude co-fluctuations in these measures. Dimensionality analysis showed these to be dominated by a single state variable, suggesting that only a single decision-making computation, not multiple parallel computations, are being carried out during the analyzed period. Second, we found that the precise time the subject commits to a decision – a covert event that we decoded from large-scale neural activity in primary motor cortex – was accompanied by a coordinated change, across the brain, from a decision formation to a post-commitment state. The two states differ substantially in their choice-predictive neural dynamics and in their inter-region correlations. Therefore, knowing the time of this state change on single trials is needed to correctly parse fundamentally different phases of decision-making. Overall, our data suggest that internally-referenced signals and state changes, not timelocked to external events but detectable through simultaneous recordings, are major features of neural activity during cognition. *About VVTNS : Launched as the World Wide Theoretical Neuroscience Seminar (WWTNS) in November 2020 and renamed in homage to Carl van Vreeswijk in Memoriam (April 20, 2022), 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, **held on Wednesdays at 11 am ET,** are 45-50 min long followed by a discussion. The talks are recorded with authorization of the speaker and are available to everybody on our YouTube channel.* ᐧ

Jan. 4, 2026

Postdoctoral position in Development and Egocentric Vision.

by Bonnen, Kathryn

Postdoctoral position in Development and Egocentric Vision. The Training Program in Integrative Developmental Processes at Indiana University invites applications for a T32-funded postdoctoral fellowship in Bloomington, Indiana. We seek highly motivated individuals interested in research at the intersection of development, vision science, and computer vision. The postdoctoral fellow will join a collaborative research environment dedicated to understanding developmental processes through egocentric vision in natural tasks, using advanced computational methods and multimodal datasets to advance developmental theory. Indiana University offers a highly interdisciplinary training environment with exceptional career development and mentoring opportunities. The position will be jointly mentored by Dr. Rowan Candy, whose research integrates behavioral, optical, and neuroscientific approaches to study typical and atypical visual development; and Dr. Kathryn Bonnen, a computational neuroscientist specializing in visuomotor coordination in natural tasks. The broader research community includes faculty from Computer Science (Dr. David Crandall, Dr. Zoran Tiganj), Informatics (Dr. Justin Wood, Dr. Samantha Wood), and Psychological and Brain Sciences (Dr. Linda Smith, Dr. Joshua W. Brown, Dr. Ehren Newman). Applicants should have strong computational skills and a background in one or more of the following areas: developmental science, vision science, neuroscience, motor control, computer science, psychology, or related fields. Eligibility: U.S. citizens or permanent residents who currently hold a doctoral degree or will have met all doctoral program requirements before enrolling. Applicants should send a cover letter describing their motivation for applying and a curriculum vitae to: Dr. Rowan Candy (rcandy(a)iu.edu) Dr. Kathryn Bonnen (kbonnen(a)iu.edu) Position is available immediately and will remain open until filled. -- Kathryn Bonnen Assistant Professor, School of Optometry Indiana University kbonnen(a)iu.edu<mailto:kbonnen@iu.edu> https://bonnenlab.github.io

Jan. 3, 2026