Computational Neuroscience workshops

This workshop connects mathematical and theoretical neuroscience approaches to the dynamics of densely connected recurrent spiking networks. Mean-field methods link individual-neuron dynamics with population behaviour, while low-dimensional collective dynamics and low-rank connectivity provide complementary descriptions informed by experiments and simulations. Researchers with mathematical and physics backgrounds alternate presentations to compare these perspectives. Public research lectures run from Monday afternoon through Wednesday, followed by doctoral tutorials on Thursday and Friday at the Bernoulli Center, EPFL, Lausanne. Registration begins at 13:30 on 2 November, with the introduction at 13:45 and talks from 14:00. Tuesday and Wednesday lectures and Thursday and Friday tutorials start at 09:00. Times are Europe/Zurich, CET (UTC+01:00). Seats are limited; researchers from outside EPFL pay CHF90 and commit to attending the lecture sessions. Tutorials are restricted to PhD students. Separate registration forms for doctoral students and other researchers are linked on the official workshop page. Preparation assumes mathematics or physics at master’s level and familiarity with computational neuroscience.

This online workshop connects computational neuroscience, machine learning and neuromorphic engineering through research on spiking neural networks. It examines artificial and biologically plausible learning algorithms and how trained spiking circuits can reveal principles of neural processing. Two afternoons combine four invited talks, seven contributed-talk slots, flash presentations and a virtual poster session, with time for discussion. Invited speakers are Susanne Schreiber, Mihai Petrovici, Eugene Izhikevich and Giulia D’Angelo. The programme begins at 14:00 CET on both 4 and 5 November; the first day reaches posters at 17:30, and the second concludes with remarks at 17:25. Attendance is free with registration to receive streaming links. The abstract deadline was 25 September 2026. Ticket sales end on 4 November 2026.

Researchers from neuroscience, engineering and clinical practice will examine technologies for understanding brain function and treating disorders. Three tracks cover emerging neural recording and imaging methods, machine learning and brain-inspired computation, and clinical translation through neuroprosthetics, neuromodulation and brain-computer interfaces. The programme connects multiscale measurement, interpretable models, multimodal data and biomarkers with deployment challenges. Panels consider ethics, standards, clinical needs, careers and funding; posters, live demonstrations, exhibits and an aging-brain symposium support exchange. In-person at the National Housing Center, 1201 15th St NW, Washington, DC 20005, November 11–13. All times are US Eastern (America/New_York): November 11 registration 12:00, activities 13:00; November 12–13 registration 08:00, sessions 08:30; closing events end November 13 at 18:00. Regular fees: IEEE members USD 425, non-members USD 475; students USD 50/75 respectively. Early rates ended October 1. General poster/demo abstracts close October 19. Member and non-member registration is available through the event website.

This four-day workshop combines whole-brain modelling, machine learning and high-order interaction analysis to study human neuroimaging data beyond pairwise descriptions. Through reproducible Python workflows, participants combine theory-driven simulations with multivariate descriptors of collective brain dynamics to capture individual variability, explore brain health and support more mechanistic analyses of M/EEG and fMRI data. Opening lectures by Rodrigo Cofré on whole-brain models and high-order interactions, Kaichao Wu on modelling brain criticality in health and disease, Yonatan Sanz Perl on brain modelling and the physics of cognition, and Joana Cabral on functional connectivity as eigenmode resonance are followed by theory and hands-on tutorials on brain clocks (Carlos Coronel), brain high-order interactions (Marilyn Gatica), propagation of perturbations in brain networks (Xiaoge Bao) and HOI-based digital twins (Rubén Herzog), with poster sessions and flash talks. Lei Zhao gives the closing lecture on cognitive impairments in chronic pain within a brain-ageing framework, and the final day is devoted to developing project proposals in collaborative groups. Sessions run from 10:00 to 18:30 on 17–20 November 2026 at the Complex Balear de Recerca, Parc BIT, Universitat de les Illes Balears, in Palma de Mallorca. The workshop is held in person and in English for 40 participants selected by application, with no registration fee, and targets students and early-career researchers with scientific Python experience; applications closed on 25 September 2026.

The NeuralNet minischool combines theory with practical work on participants’ laptops to develop skills in extracting and interpreting neuronal spikes. Spike-sorting sessions introduce available methods and the SpikeInterface framework, then cover preprocessing, running sorters, postprocessing, automatic and manual curation, and visualization. Participants can bring their own data for supervised analysis. The final morning addresses spike-train methods, including firing rates, population representations, waveform and cell-type analysis, connectivity through cross-correlograms, and decoding, with exercises using an open DANDI dataset. Pierre Yger, Pierre Le Merre and Samuel Garcia teach the programme. In-person sessions take place at the Saint Germain Campus, 45 rue des Saints-Pères, Paris: 23 November 14:00–18:00; 24 November 09:00–12:00 and 14:00–18:00; 25 November 09:00–12:00. Times are Europe/Paris, CET (UTC+01:00). The minischool itself is free, but registration for the paid main NeuralNet meeting is required first. Use the separate minischool registration form linked from the official page; main-meeting registration remains open until capacity is reached.

This practical workshop explains how to establish chronic video-EEG recordings in rodent epilepsy models, from equipment and electrode placement to seizure monitoring and data management. Analysis ranges from spike and seizure quantification to machine learning. A second component introduces Motion Sequencing (MoSeq), an unbiased method for identifying and measuring behavior from video, with workflows for studying seizures, behavioral changes and associated conditions. Participants examine the hardware, software and implementation choices needed to introduce both approaches into their laboratories. Monday 7 December, 10:00–11:30 Mountain Standard Time (America/Denver). Part of the 2026 American Epilepsy Society Annual Meeting. In-person meeting registration and a free myAES account are required. Standard full-meeting rates are USD 800 for member scientists and USD 1,075 for non-member scientists; student rates are USD 250 and USD 360, respectively. Other professional and one-day categories are available. Seating priority goes to registered attendees.

The Patagonian School of Science, Dynamics of Large-Scale Neural Systems, is an 11-day residential school in circuit neuroscience that brings leading neuroscientists together with 20–25 PhD students and postdocs for in-depth discussion of significant questions in the field without time constraints. Co-directed by Inés Samengo (Instituto Balseiro) and Rafael Yuste (Columbia University), it runs from 8 to 19 December 2026 at Peumayen, Brazo Huemul, on the northern shore of Lake Nahuel Huapi near Bariloche, Argentina. Faculty include Susanne Schreiber (Humboldt-Universität zu Berlin), Carina Curto (Penn State University), Valeria Della Maggiore (CONICET, UBA), Soledad Gonzalo Cogno and Edvard Moser (Kavli Institute, Trondheim), Nachum Ulanovsky (Weizmann Institute), Christian Machens (Champalimaud Foundation), Emilio Kropff (Instituto Leloir) and Iván Davidovich, working across scales from single cells to populations and from rodents to bats. The daily schedule combines faculty talks, participant presentations and informal discussion at a site without connectivity, and includes a module on research ethics. Selection gives special consideration to applicants from Argentina and elsewhere in Latin America. Tuition is USD 1,200, covering lodging and meals for the 11 days, with scholarships supported by Fundación Bunge y Born and private funds; applications closed on 25 September 2026 (AoE).

NeurReps, Symmetry and Geometry in Neural Representations, is a NeurIPS workshop that brings together mathematicians, machine learning researchers and neuroscientists working to uncover the geometric principles shared by brains and machines. In neuroscience, mounting evidence suggests that neural circuits encode task and environmental structure through low-dimensional manifolds, conserved symmetries and structured transformations; in deep learning, sparsity, equivariance and compositionality are guiding the development of more generalisable and interpretable models. Following editions from 2022 to 2025, NeurReps 2026 expands into geometric representation steering and geometric mechanistic interpretability and introduces a Findings track to foster collaboration between experimentalists and theorists, alongside an archival proceedings track published in a dedicated PMLR volume. The programme combines invited talks, contributed papers and a panel session on topology, geometry and neuroscience towards a unified framework. The workshop runs from 8:00 to 17:00 AEDT on Friday 11 December 2026 in Hall 4 of the International Convention Centre (ICC) Sydney. It is organised by Francisco Acosta, David Klindt, Louisa Cornelis, Alison Pouplin, Nina Miolane and Fatih Dinc.

UniReps asks when, how and why different neural models learn the same representations. Findings in neuroscience and artificial intelligence show that biological brains and artificial models often form similar representations when exposed to similar stimuli. The workshop brings machine learning, neuroscience and cognitive science together to discuss theoretical findings, empirical evidence and practical applications of this phenomenon: learning dynamics in neuroscience, identifiability in the functional and parameter spaces of artificial networks, representation alignment for model merging, stitching and reuse and for multimodal settings, and the invariances that emerge across learning processes, with the aim of unifying internal representations across distinct neural models. The 2026 workshop takes place in Paris on 12 December 2026, coinciding with NeurIPS in Paris. Invited speakers are Marco Baroni (Pompeu Fabra University), Alex Cayco-Gajic (École Normale Supérieure), Sophia Koepke (TUM/University of Tübingen), Joao Sacramento (Google) and Greta Tuckute (Harvard University). Technical paper submissions were due on 10 October 2026 (AoE).

Foundation Models for the Brain and Body is the second edition of a NeurIPS workshop on large-scale pretrained AI models of neural and physiological signals. Advances in brain interfacing and wearable technologies, including EEG, intracortical electrophysiology, EMG, MEG and ECG, now yield large and diverse biosignal datasets collected across real-world contexts, but these timeseries are noisy, heterogeneous and recorded under variable conditions across subjects, devices and environments. The workshop brings together neuroscientists, biomedical engineers, wearable-technology researchers and machine learning experts to develop foundation models that generalise across applications from brain-computer interfacing to health monitoring. This edition broadens the scope to embodied intelligence, with foundation models for movement, motor control and closed-loop interaction between brain, body and machine, and adds a panel discussion on benchmarking that compares evaluation practices across modalities. Invited speakers and panelists are Giulia Lioi (IMT Atlantique), Simon Dahan (Meta), Chethan Pandarinath (Emory, Georgia Tech), A. Ali Heydari (Google), Hubert J. Banville (Meta), Konstantinos Kontras (KU Leuven, MIT) and Sergey D. Stavisky (UC Davis). The workshop runs from 8:00 to 17:00 AEDT on Saturday 12 December 2026 in Hall 1 at NeurIPS 2026 in Sydney. Papers and travel-award applications were due on 5 September 2026 and demos on 19 September 2026.

The second UK Theoretical Neuroscience Workshop is a one-day meeting of talks and posters on mathematical and computational approaches to brain function, organised by Stephen Coombes (University of Nottingham) and Dimitrios Pinotsis (City St George's, University of London). Talks include Peter Latham (UCL) on time and task management in complex environments; Magnus Richardson (University of Warwick) on spatiotemporal coarse-graining of activity within neurons and across networks; Rafal Bogacz (University of Oxford) on predictive dendrites as a foundation for biological learning; Arnd Roth (UCL) on brain-wide dendritic signals that exhibit circuit-specific behavioural modulation; Mark Humphries (University of Nottingham) on cortical control of rhythmic and discrete arm movements; Vladimir Litvak (UCL) on why the low effective dimensionality of the human functional connectome does not invalidate lesion network mapping; and Massimiliano Di Luca (University of Birmingham) on temporal inference in perception and coordinated action. Angus Chadwick (University of Edinburgh) and Eirini Mavritsaki (Birmingham City University) also speak. The workshop runs from 09:00 to 18:10 on Friday 18 December 2026 at City St George's, University of London, with talks in the Northampton Suite (B411) and posters in The Pavilion of the University Building, Northampton Square. Attendance is free but registration is mandatory. Poster abstracts are due on 20 November 2026, and a poster award will be given.

The seventh Latin-American Summer School in Computational Neuroscience (LACONEU) runs from 11 to 29 January 2027 at CIAE, Universidad de Valparaíso, in Valparaíso, Chile, bringing together students, researchers and experts from Latin America, North America and Europe. The school seeks to advance computational neuroscience in Latin America by combining mathematical and computational tools with applications in biomedical research and clinical practice. Its three modules cover neural models and artificial intelligence, reviewing approaches to modelling neural systems from single neurons and microcircuits to large-scale brain networks and behaviour; machine learning for the analysis of neural data, the simulation of brain processes and the intersection of AI and neuroscience; and diffusion MRI tractography, from the biophysical basis of diffusion MRI to preprocessing and fibre reconstruction for studying structural brain connectivity. Morning lectures by national and international faculty are complemented by hands-on tutorials, problem solving and data analysis, tutored research projects in the afternoons and evenings, and evening seminars open to all audiences. The school especially encourages applicants from Latin America, women and members of historically underrepresented groups in science.

GoEMMI (GOettingen EMergent Minds) is a three-week winter school on learning and computation in brains and machines, held from 15 February to 6 March 2027 at the Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, Göttingen. The programme is organised around three blocks: the theory of emergence and computation, covering conceptual and mathematical frameworks for emergent macrovariables, dynamical autonomy, compositionality and information-theoretic approaches to computation and causality; learning in brains and machines, covering learning objectives, representation formation, neural world models, data-driven discovery of dynamical systems and connections between biological and artificial learning; and computation from local interactions, covering neural dynamics, synaptic plasticity, local learning rules and network mechanisms through which microscopic interactions support coherent computation at larger scales. Lectures and tutorials are complemented by a hackathon, lab tours, a poster session and a dedicated lecture on the philosophy and ethics of artificial intelligence. Speakers include Larissa Albantakis, Nicolas Brunel, Spyridon Chavlis, Adrienne Fairhall, Wulfram Gerstner, Anna Levina, Sarah Marzen, Francesca Mastrogiuseppe, Wiktor Młynarski, Vincent C. Müller, Gonzalo Polavieja, Fernando Rosas, Karoline Wiesner and David Wolpert, together with researchers from Göttingen. There are no registration fees; applications for the 20 student places were open until 1 October 2026.

The second NeuroAI workshop at AAAI connects biological computation with adaptive multimodal AI. It examines how cortical organization, inhibitory–excitatory balance, sparse representations and context-sensitive plasticity can inform efficient learning and reduce forgetting. The reverse direction uses AI to study neural and behavioural data, circuit dynamics and biologically realistic models, with shared benchmarks connecting neuroscience and machine learning. Submissions are due 20 November 2026, with decisions on 5 December. Double-blind review follows AAAI-27 instructions. Short papers allow four non-archival pages and long papers eight archival pages, excluding references. Early registration ends 15 December; the standard rate ends 10 January, followed by late registration.

The NeuroData AI Summer School, formerly NeuroDataReHack, is a one-week residential school on reanalysing open neurophysiology data and applying AI methods to neural data, held from 19 to 24 July 2027 at HHMI's Janelia Research Campus in Ashburn, Virginia. Foundations sessions cover how NWB files are organised, how to find and stream data from the DANDI Archive, and analysis tools built on the standard such as SpikeInterface, Pynapple and Neurosift, using large public datasets. AI-methods sessions cover foundation models for neural activity, coding with large language models and AI agents, decoding and dimensionality reduction, and how to check whether a method developed on one lab's recordings works on another lab's data. Mornings are lectures and afternoons are team projects formed around shared datasets, and lectures are recorded and published. The school is intended for PhD students, postdoctoral researchers and principal investigators with basic Python or MATLAB programming and neurophysiology research experience; preference goes to applicants with a specific project reanalysing existing NWB data, and past NeuroDataReHack participants are not eligible. It is in person only for about 35 participants, with no registration or application fee, on-campus lodging and meals provided, and up to $550 of travel costs reimbursed. Applications close on 29 January 2027 and are reviewed on a rolling basis, with every applicant hearing back by the end of February 2027. The school is supported by NINDS award R25NS149357.

Methods in Computational Neuroscience (MCN) is a four-week Marine Biological Laboratory course that introduces the computational and mathematical techniques used to address how the brain solves problems at levels of neural organisation ranging from single membrane channels to operations of the entire brain. In each of the first three weeks the course moves up a level of complexity, from molecular and cellular to network to cognitive and behavioural, asking whether biologically plausible mechanisms can explain how nervous systems solve specific computational problems, how such problems can be decomposed, and how those decompositions relate to observable properties of neurons and circuits and their molecular building blocks. Core presentations are given jointly by theorists and experimentalists who have worked on the same problems, with optional first-week tutorials on dynamical systems, information theory, dimensionality reduction, neural network modelling and simulation in Python and MATLAB. Laboratory exercises combine quantitative analysis of experimental data with analytic and numerical exploration of models, often in teams mixing theoretical and experimental backgrounds, and the fourth week is reserved for student projects with resident faculty. The 2027 course, directed by Stefano Fusi (Columbia University) and Roozbeh Kiani (New York University), runs from 24 July to 21 August 2027 and is limited to 24 graduate students, postdocs and faculty from fields ranging from zoology and neurobiology to physics, engineering and mathematics. Applications are due on 10 March 2027, and financial aid is offered.

The School on Analytical Connectionism is a two-week summer course on analytical tools, including methods from statistical physics and probability theory, for probing neural network models of higher-level cognition, bringing together neuroscience, psychology and machine-learning communities. The 2027 school, held in Boston from 2 to 13 August 2027, focuses on interpretability in reasoning and mathematical cognition: how children or artificial systems use and acquire mathematical concepts, how mathematical intuition and expertise develop and interact, and how studying the heuristics and abstractions that AI systems develop may deepen understanding of human mathematical cognition. The first week offers core lectures on mathematical methods for neural network analysis and on key connectionist models linked to experimental observations; the second week offers frontiers lectures. Participants also join tutorials, poster sessions and contributed talks, work in teams on research projects that they pitch in week one and present at the end, and co-author peer-reviewed lecture notes collected into a special issue. The school is directed by Erin Grant (University of Alberta & Amii) and Stefano Sarao Mannelli (Chalmers University of Technology & University of Gothenburg), with SueYeon Chung (Harvard University & Flatiron Institute) and Andrew Saxe (University College London) as advisors. Applications open on 1 February 2027 and close on 1 April 2027 (AoE); first-round outcomes are communicated on 17 May 2027.

Applications are invited for our fifth edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 25-27, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2027. All summer school participants are invited to attend, and welcome to submit contributions to the symposium. Please find the application procedure here https://summerschool.lizhaoping.org/application and apply by March 31, 2027. Check out our webpage https://summerschool.lizhaoping.org to find more out about the program, our invited lecturers/speakers, and other details. Please direct inquiries to svs.summerschool@tue.mpg.de

The Simons Computational Neuroscience Imbizo is a three-week school in Noordhoek, Cape Town, South Africa, that gives African and international students intensive training in research techniques in computational and theoretical neuroscience; imbizo is an isiXhosa and isiZulu word for a gathering to share knowledge. The 2027 school runs from 27 August to 17 September 2027 in three cycles of six working days, each focused on one theme: Molecules to Behavior, on biophysical mechanisms in individual cells and how they become building blocks of neural networks; Cells to Circuits to Behavior, on systems-level functions including sensory processing, birdsong, motor control and decision-making; and NeuroAI, on guiding principles for intelligent systems, how biological principles can inform machine learning and how machine learning can help us understand brains. Days combine morning lectures with further lectures or practical tutorials in simulation and data analysis, and students complete a mini research project under a tutor's supervision. Faculty include Adrienne Fairhall (University of Washington), Eva Dyer (Georgia Tech), Joseph Raimondo (University of Cape Town) and Thomas Tagoe (University of Ghana). The school is designed for students completing master's degrees or starting doctoral studies, with highly motivated advanced undergraduates and postdocs also encouraged, and all students stay in the student accommodation. The fee is €1,650, with fee reductions, waivers and travel bursaries offered according to need and merit; African students are particularly encouraged to apply. Applications open on 5 January 2027 and close on 1 March 2027 at 23:59 SAST, with decisions in April 2027.

Biological mechanisms often have to be reconstructed from indirect measurements such as microscopy images, gene activity and cellular time series. This workshop examines inverse problems in living systems, where noise, complexity and diversity challenge existing mathematical approaches. Mathematicians, physicists, computer scientists and biologists will explore methods including deep learning and models informed by physical constraints to infer hidden cellular, genetic and neural mechanisms from experimental data.