- Comp-neuro - lists.cnsorg.org

CNS*2025 Workshop "Brains and AI" - Speaker Lineup and Schedule

by Vassilis Cutsuridis

Dear Colleagues, We are excited to announce the upcoming *CNS*2025 Workshop* *"Brains and AI"*, to be held on *Wednesday, July 9, 2025, in Florence, Italy*. This workshop will explore the intersection of neuroscience and artificial intelligence - bringing together researchers applying AI to brain data and those leveraging insights from neuroscience to build better AI systems. https://users.sussex.ac.uk/~tn41/CNS2025_workshop/ <https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fusers.sus…> Advances in neuroscience techniques have dramatically increased the volume of data we can now collect from animal and human brains. However, this surge in data has introduced new challenges in extracting meaningful insights. Fortunately, these developments have coincided with breakthroughs in artificial intelligence (AI), which holds the potential to transform how we analyze and utilize scientific information. While there is significant potential here, we are just starting to figure out how to apply modern AI models to interpret and process scientific data, and significant challenges remain. The trend of applying AI to better understand the brain concurs with another reviving trend: applying knowledge from neuroscience to developing new AI. Indeed, despite the tremendous progress, the existing generation of AI shows significant limitations, including a lack of continual learning, poor generalization, dependence on enormous amounts of data for training, bias, and safety problems. These are features where the biological brain excels, highlighting the strong need to learn once more from neuroscience how to develop the next generation of AI. The proposed workshop will combine these two complementary trends, bringing experts from the field together to discuss how AI can facilitate new scientific discoveries and how knowledge of the brain can help improve AI. Below is the list of confirmed speakers: - Fleur Zeldenrust - Vassilis Cutsuridis - Spyridon Chavlis - Andreas Tolias *(online)* - Robert Legenstein - Max Garagnani - Martin Trefzer - Julian Göltz - Maxim Bazhenov - Dhireesha Kudithipudi - Thomas Nowotny The workshop will conclude with a panel discussion and open debate. We look forward to your participation in what promises to be a thought-provoking and engaging event. Thomas Nowotny, Vassilis Cutsuridis, Maxim Bazhenov

June 24, 2025

NEURON and NetPyNE tutorial at CNS*2025, July 5, 2025

by McDougal, Robert

Dear colleagues, This July 5th, there will be a “Building mechanistic multiscale models with NEURON and NetPyNE” tutorial at CNS*2025, all day in room 6. To attend, please be sure you have registered for the tutorials at the conference: https://www.cnsorg.org/cns-2025-registration This tutorial will introduce multiscale modeling using NEURON 9.0 and NetPyNE. The tutorial will combine background, examples and hands on exercises covering the implementation of models at four key scales: * single neuron electrophysiology (e.g. action potential propagation), * intracellular dynamics (e.g. calcium buffering, protein interactions), * neurons in extracellular space (e.g. spreading depression), and * networks of neurons. For single cell simulations, we will utilize NEURON through Python, simulating point cells and incorporating realistic morphology information from NeuroMorpho.Org. For network simulations, we will use NetPyNE, a high-level interface to NEURON supporting both programmatic and GUI specification that facilitates the development, parallel simulation, and analysis of biophysically detailed neuronal circuits. We conclude with an example that links intracellular molecular dynamics with network spiking activity and local field potentials. The NetPyNE tutorial will be carried out online using the Open Source Brain web platform (http://v2.opensourcebrain.org) and will include an introduction to NeuroML, a standardized computational neuroscience language to describe detailed models of neurons and neural networks. The tutorial highlights recent substantial developments and new features in both NEURON and NetPyNE. Basic familiarity (e.g. loops, functions, variables, if) with Python is recommended. No advanced programming experience or prior knowledge of NEURON or NetPyNE is required. Speakers will include: Salvador Dura-Bernal, William W Lytton, Robert A McDougal, and Adam JH Newton Preliminary Schedule: 09:00 -0 9:20 Introduction to multiscale modeling (WWL) 09:20 - 10:10 NEURON scripting (RAM) 10:10 - 10:40 Coffee break 10:40 - 12:00 Reaction-diffusion simulations (AJHN) 12:00 - 13:00 Lunch break 13:00 - 14:30 NetPyNE graphical web application (SD) 14:30 - 15:00 Coffee break 15:00 - 16:00 NetPyNE scripting (SD) Best regards, Robert McDougal

June 24, 2025

Fwd: Deadline approaching: PhD student using machine learning to understand high-dimensional visual category learning

by Leni Wei

> Begin forwarded message: > > From: "Caspar M. Schwiedrzik" <Caspar.Schwiedrzik(a)ruhr-uni-bochum.de> > Subject: Deadline approaching: PhD student using machine learning to understand high-dimensional visual category learning > Date: 23 June 2025 at 16:23:18 CEST > To: comp-neuro(a)lists.cnsorg.org, announcements(a)lists.cognitivesciencesociety.org > > We are looking for a highly motivated PhD student using machine learning to understand high-dimensional visual category learning. > > The Department of Cognitive Neurobiology of Caspar Schwiedrzik at > Ruhr-University Bochum is looking for an outstanding PhD student with > expertise in computational cognitive neuroscience and/or deep learning > to join our team to the neural basis of mental flexibility. The > project investigates neural mechanisms of high-dimensional visual > category learning, utilizing computational approaches as well as > neuroimaging and neurophysiology in humans and macaque monkeys, > respectively. It is funded by an ERC Consolidator Grant (Acronym > DimLearn; “Flexible Dimensionality of Representational Spaces in > Category Learning”). The PhD student’s project will focus on > developing deep learning “digital twin” models based on neural and/or > behavioral data to investigate flexible multi-task learning. > > The lab seeks to understand the cortical basis and computational > principles of perception and experience-dependent plasticity in the > brain. To this end, we use a multimodal approach including fMRI-guided > electrophysiological recordings in rodents and non-human primates, and > fMRI and iEEG in humans. See https://doi.org/10.1016/j.cub.2023.01.011 > and https://doi.org/10.1038/s41467-024-51543-y for recent examples of > our work. The PhD student will play a key role in our research efforts > in this area. The lab is located at Ruhr-University Bochum > (https://www.rub.de) and the German Primate Center > (http://www.dpz.eu) At both locations, the lab is embedded into > interdisciplinary research centers with international faculty and > students pursuing cutting-edge research in cognitive and computational > neuroscience. The PhD student will have access to dedicated computing > infrastructure, including high performance computing clusters. The > project will be conducted in close collaboration with the labs of > Fabian Sinz (https://sinzlab.org) Alexander Gail > (https://www.dpz.eu/sensomotorik) and Igor Kagan > (http://igorkagan.org) The main site for this part of the project > will be Bochum. Ruhr-University Bochum provides a vibrant and > stimulating neuroscience community with a strong community in > computational as well as experimental neurosciences. The PhD student > will have the opportunity to join the International Graduate School > for Neuroscience (https://www.ruhr-uni-bochum.de/igsn/index.html) or > the International Graduate School of Biosciences > (https://www.biologie.ruhr-uni-bochum.de/biodek/promotion/index.html.en) > > Please find the official job ad and further information here: > https://jobs.ruhr-uni-bochum.de/jobposting/318eb740a64696cad9cbeb78dfa84802… > > -- > Prof. Dr. Caspar M. Schwiedrzik > > Abteilung Kognitive Neurobiologie > Research Center One Health Ruhr > University Alliance Ruhr > Fakultät für Biologie und Biotechnologie > Ruhr-Universität Bochum > > NDEF 05/348, Fach 59 > Universitätsstraße 150 > 44801 Bochum > > Telefon +49 234 32 15220 > > caspar.schwiedrzik(a)rub.de > www.rub.de/

June 24, 2025

SiNAPSA Neuroscience Conference '25 (17.-19. Sept, Ljubljana) - abstract submission deadline approaching

by Nina Omejc

Dear colleagues, We are delighted to invite you to the Sinapsa Neuroscience Conference ’25 <https://www.sinapsa.org/SNC25>, which will take place from 17 to 19 September 2025 at the Faculty of Medicine, University of Ljubljana, Slovenia. The conference programme <https://www.sinapsa.org/snc25/media/schedule/Schedule-SNC25_v20250610.pdf> includes plenary lectures, thematic symposia, poster presentations, an educational workshop, and a public consultation. The program will offer a comprehensive insight into neuroscience with diverse topics ranging from molecular and cellular mechanisms to systemic, clinical, and cognitive neuroscience. The deadline for abstract submission <https://www.sinapsa.org/SNC25/call-for-abstracts> is 30 June 2025. For more information, please visit the conference website at www.sinapsa.org/snc25 <http://www.sinapsa.org/snc25>. Hope to see you in Ljubljana in September! SiNAPSA Neuroscience Conference ’25 Organizing committee www.sinapsa.org/snc25 <http://www.sinapsa.org/snc25>

June 24, 2025

CNS*2025 Workshop "Enabling synaptic plasticity, structural plasticity, and multi-scale modeling with morphologically detailed neurons using Arbor"

by Jannik Luboeinski

Dear Colleagues, * * we are pleased to announce the workshop "*Enabling synaptic plasticity, structural plasticity, and multi-scale modeling with morphologically detailed neurons using Arbor*", which will take place at *CNS*2025* on *Wednesday, 9 July*, in Florence, Italy. Current computational neuroscience studies are often limited to a single scale or simulator, with many still relying on standalone simulation code due to computational power and technology constraints. Simulations incorporating biophysical properties and neural morphology typically focus on single neurons or small networks, while large-scale neural network simulations often resort to point neurons as a compromise to incorporate plasticity and cell diversity. Whole-brain simulations, on the other hand, frequently sacrifice details at the individual neuron and network composition levels. This workshop introduces recent advances leveraging the next-generation simulator Arbor (https://arbor-sim.org/) designed to overcome these challenges. Arbor enables seamless conversion from the widely used NEURON simulator, facilitates the study of functional and structural plasticity in large neural networks with detailed morphology, and supports multi-scale modeling through co-simulation, integrating microscopic and macroscopic levels of simulation. Arbor is a library optimized for efficient, scalable neural simulations by utilizing both GPU and CPU resources. It supports the simulation of both individual neurons and large-scale networks while maintaining detailed biophysical properties and morphological complexity. The workshop will feature presentations covering three key aspects: * *Effortless transition from NEURON to Arbor:* Beatriz Herrera will introduce the SONATA format, which simplifies the migration process and enables cross-simulator validation, ensuring a smooth transition to Arbor for researchers familiar with NEURON. * *Plasticity simulations with Arbor:* In two talks, Jannik Luboeinski and Felix Wolf will present Arbor’s capabilities in modeling calcium-based functional plasticity as well as calcium-based distance-dependent structural plasticity, providing insights into synaptic and structural changes. * *Multi-scale co-simulation with TVB:* Thanos Manos will demonstrate Arbor’s co-simulation capabilities with The Virtual Brain (TVB) platform, illustrating the study of epilepsy propagation as an example of multi-scale modeling. The workshop will conclude with an *interactive coding session*, offering participants hands-on experience with Arbor and an opportunity to apply the presented concepts. We look forward to meeting you at the workshop, where we expect fruitful exchange and interesting discussions! Best regards, Thorsten Hater, Han Lu, Jannik Luboeinski

June 23, 2025

Full day tutorial on Multiscale Modeling with MOOSE at CNS*2025, July 5, 2025!

by MOOSE Neuro

Dear all, We are pleased to announce a full-day hands-on tutorial on *Multiscale Modeling with MOOSE *at CNS*2025! *Saturday, July 5, 2025, 09:00 - 16:00 CEST, Belvedere room* The objective of this tutorial is to familiarize participants with MOOSE ( https://mooseneuro.github.io/) a comprehensive simulation platform designed for computational modeling in neuroscience and systems biology. In addition to tutorials on biophysical and biochemical models, we shall showcase new features of MOOSE, including *jardesigner, *a new web-based frontend for multiscale modeling. We will illustrate the use of *jardesigner *and MOOSE to build and run spiking neuron models incorporating chemical signaling for neuromodulation and synaptic plasticity on spines. Prerequisites - Some familiarity with basic Python programming and common system commands to run programs from the command-line is expected. - As most of the topics will be hands-on, participants should bring their laptops. - Participants must have a Python environment installed on their laptops. - Participants are encouraged to create a Python environment as described in MOOSE installation instructions: https://github.com/MooseNeuro/moose-core/blob/development/docs/source/insta… *Speakers:* Dr. Subhasis Ray, Prof. Upinder S. Bhalla, Dr. Bhanu Priya S Tentative Schedule 09:00 - 09:40 Multiple Scales in Neuroscience, Upinder S. Bhalla 09:40 - 10:10 Overview of MOOSE, Subhasis Ray 10:10 - 10:40 Coffee Break 10:40 - 11:25 Setting up the software environment, Bhanu Priya S and Subhasis Ray 11:25 - 12:10 Abstract neuron models, Bhanu Priya S 12:10 - 14:00 Lunch Break 14:00 - 14:45 Biophysical neuron model with ion channels, Subhasis Ray 14:45 - 15:30 Modeling biochemical systems, Upinder S. Bhalla 15:30 - 16:00 Coffee Break 16:00 - 17:00 Multiscale modelling and Jardesigner, Upinder S. Bhalla 17:00 - 17:20 Discussion You can save this schedule to your calendar via CNS*2025 Florence: Multiscale modeling with MOOSE <https://cns2025florence.sched.com/event/25kRo/multiscale-modeling-with-moose> We will also present a poster on "*Developments around MOOSE for modeling in Systems Biology and Neuroscience*" on July 8th, 2025. More details can be found here: CNS*2025 Florence: P252: Developments around MOOSE for mode... <https://cns2025florence.sched.com/event/24uTo/p252-developments-around-moos…> Please feel free to share this announcement with anyone who might be interested. Best regards, Parita Mehta Community Manager for MOOSE *On behalf of the MOOSE Team* GitHub: MooseNeuro <https://github.com/MooseNeuro/> Official website: *https://mooseneuro.github.io/ <https://mooseneuro.github.io/> * LinkedIn: *MOOSE Neuro Simulator | LinkedIn <https://www.linkedin.com/in/moose-neuro-simulator-064088315/>* X: *MOOSE Neuro Simulator (@mooseneurosim) / X <https://x.com/mooseneurosim>* Bluesky Social: MOOSE Neuro Simulator <https://bsky.app/profile/moosesim.bsky.social>

June 23, 2025

Neurobridge CNS*2025 Satellite Symposium 'Neural Population Dynamics and Latent Representations'

by Eleonora Russo

Dear all, We are pleased to invite you to the NEUROBRIDGE CNS*2025 Satellite Symposium on Neural Population Dynamics and Latent Representations. In recent years, the study of neural population dynamics has gained growing traction in systems and computational neuroscience, offering a principled framework to link single-neuron activity with behaviorally relevant computation. During the symposium, we will discuss recent machine learning and theoretical advances for analyzing population-level activity and explore how emergent network properties can reveal mechanistic principles of cognition and behavior, with translational implications for clinical neuroscience. Confirmed speakers: * Lorenzo Gaetano Amato – Sant'Anna School of Advanced Studies, Pisa, IT * Demian Battaglia – University of Strasbourg, FR * Daniel Durstewitz – Central Institute for Mental Health, Mannheim, DE * Tatiana A. Engel – Princeton University, Princeton, USA * Sean Froudist-Walsh – University of Bristol, Bristol, UK * Matthieu Gilson – Institut des Neurosciences, Marseille, FR * Maurizio Mattia – Istituto Superiore di Sanità, Rome, IT * Leonardo Pollina – EPFL, Lausanne, CH * Sara Solla – Northwestern University, Evanston, USA The full-day symposium will take place on July 10th in the 📍 Aula Magna at the Scuola Superiore Sant’Anna, Piazza Martiri della Libertà 33, Pisa. Registration for the symposium is free of charge, but seats are limited! For more information and to register, please visit: 👉 https://neurobridge-tne.github.io/ The event will also be streamed online; the link will be available on the symposium website. Please feel free to share this announcement with anyone who might be interested. Best regards, The organisers, Eleonora Russo, Jacopo Carpaneto, Alberto Mazzoni, Nicolò Meneghetti, Silvestro Micera, Calogero Maria Oddo, Solaiman Shokur. --------------------------------------------------------------------------------------------------------------------- Eleonora Russo, Ph.D. PI of the Brain Dynamics Laboratory TT Assistant Professor at Sant’Anna School of Advanced Studies, The BioRobotics Institute, P.za Martiri della Liberta', 33 56127 Pisa, Italy

June 23, 2025

Associate Professor Position in Australia - Monash University

by Elizabeth Zavitz

Dear colleagues, Please find below an advertisement for an Associate Professor position in the Department of Electrical and Computer Systems Engineering at Monash University, Melbourne, Australia. Monash Careers – Associate Professor <https://careers.pageuppeople.com/513/cw/en/job/678997/associate-professor-e…> In this role, you will play a key part in shaping the next generation of engineers. You’ll engage with students through dynamic teaching, mentor future leaders, and collaborate with passionate colleagues to deliver cutting-edge courses. Your expertise will complement our strengths in control systems, wireless technology, signal processing, robotics and AI—driving real-world solutions in electronics, RF, sensors, energy systems, and computing. You’ll also lead impactful research that addresses global challenges, with the support of a collaborative and inclusive research culture. The application deadline is September 14th, 2025, 11:55 pm AEST. Please feel free to share this opportunity with interested colleagues. For any inquiries, do not hesitate to reach out. Liz -- Elizabeth Zavitz, PhD Electrical and Computer Systems Engineering 233 14 Alliance Lane (Bldg 72) Monash University Clayton, VIC 3800 Australia

June 23, 2025

World wide VVTNS series- fifth season closing lecture: Wednesday, June 25, 2025, at 11:00 am EDT| Sebastian Seung , 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 *VTNS Fifth Season Closing Lecture *that will be delivered by Sebastian Seung, Princeton Neuroscience Institute on the topic Insights into vision from interpreting a neuronal wiring diagram The lecture will be held on zoom on Wednesday, June 25, 2025, at *11:00 am EDT * To receive the link: https://www.wwtns.online/register-page *Abstract: *In 2023, the FlyWire Consortium released the neuronal wiring diagram of an adult fly brain. This contains as a corollary the first complete wiring diagram of a visual system, which has been used to identify all 200+ cell types that are intrinsic to the Drosophila optic lobe. About half of these cell types were previously unknown, and less than 20% have ever been recorded by a physiologist. I will argue that plausible functions for many cell types can be guessed by interpreting the wiring diagram. *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

June 22, 2025

Advances in Intelligent Systems, Technologies and Applications

by Barna Iantovics

Call for papersSpecial Issue: Advances in Intelligent Systems, Technologies and ApplicationsJournal: Applied Sciences (ISSN 2076-3417) Impact Factor 2.5Submission https://www.mdpi.com/journal/applsci/special_issues/5IQ6DOHB42 Dear Colleague, You are kindly invited to contribute with a paper to the Special Issue. Intelligence in nature is very diverse; it can be discussed in terms of the intelligence of chimps, dolphins, and many other animals and even the collective intelligence of very simple life forms such as ants. The concept of intelligence is being adopted in many domains of science. From practical and theoretical perspectives, an essential current research direction that is under examination by a very large number of scientists worldwide is the development of artificial systems, also called agent-based systems, which can be either individual agents or cooperative multiagent systems. These systems are embedded in the environment, possess a certain degree of autonomy, and are capable of perceiving the environment and executing actions in it. Intelligence in agent-based systems can emerge through advanced problem-solving abilities. To develop these intelligent systems, techniques such as supervised learning and unsupervised learning play pivotal roles. Supervised learning involves training systems on labeled datasets, enabling them to map inputs to outputs and improve their predictions or classifications over time. These methods are extensively used in applications such as image recognition, natural language processing, and medical diagnosis. On the other hand, unsupervised learning enables systems to 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 enhance intelligent systems, producing highly contextualized and accurate responses or actions. These approaches are instrumental in developing advanced systems for domains such as conversational AI, knowledge management, and decision support. Intelligent agent-based systems have many real-world applications, including the health sciences and industry. The number and diversity of intelligent systems are increasing rapidly. In this context, the great challenge consists of creating increasingly intelligent systems. Another critical challenge, approached by only a few researchers worldwide, is the development of universal metrics, including black-box-based intelligence metrics, to measure the intelligence of these systems. Such advances could allow for the comparison of systems based on their intelligence. In cooperative multiagent systems, intelligence can be assessed at the system level; this is known as collective intelligence. Even in very simple cooperative multiagent systems, agents may interact nonlinearly at various decision points, resulting in emergent complexity and intelligence at the system level. This Special Issue aims to establish a solid foundation for future research through a collection of papers that advance the field by elaborating on theories, designing applications, and presenting surveys regarding the next generation of increasingly intelligent systems. The areas of research covered in these papers could include the study of self-organization, emergence, hybridization, scalability, robustness, measuring machine intelligence, and the integration of advanced paradigms such as supervised learning, unsupervised learning, retrieval-augmented generation, and cache-augmented generation. Kind regards,Guest EditorsProf. Dr. Laszlo Barna IantovicsProf. Dr. László KovácsDr. Attila Biró

June 19, 2025