In 1950, Alan Turing asked "Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child's?" Today, 75 years later, constructing a computer program that can learn like a child and that develops a human-like general intelligence and consciousness is still considered a grand, if not the ultimate, challenge for artificial intelligence (AI). An interdisciplinary community of scientists from AI, Cognitive Science, Psychology, Engineering, and Neuroscience are tackling this grand challenge. In the Developing Minds global lecture series we showcase the progress being made. It is organized by the Developmental AI Task Force of the IEEE Technical Committee on Cognitive and Developmental Systems of the IEEE Computational Intelligence Society. See also: IEEE Int. Conference on Development and Learning (ICDL), IEEE Transactions on Cognitive and Developmental Systems (TCDS).

The ANDA-NI school consists of three modules: Two online courses, ANDA and NI, and the in-person ANDA-NI Retreat for collaborative projects to put the learned material into practice on your own favorite datasets. Each online course is available for standalone enrollment. Participation in the ANDA-NI Retreat requires to take part in both online courses (ANDA and NI).

The AREADNE Conferences have been created to gather global scientific
leaders who work on neural ensembles and establish a touch-point for the
widely disparate and hybrid field. With a beautiful setting on Milos,
the conferences have been carefully planned to foster discussion and
interaction between attendees to encourage the establishment of lasting
professional relationships. The meetings continue our efforts to promote
systems neuroscience in Greece through creating a world-class forum for
cutting-edge research. For 2026, we will be Celebrating Twenty Years of
AREADNE Conferences!

A landmark symposium in computational neuroscience, gathering the field’s foremost experts from around the world to celebrate past achievements, share current breakthroughs, and brainstorm future directions.

The International Conference on Neuromorphic Computing and Engineering brings together a diverse community of researchers, from students to leading experts in academia, startups, and industry, to advance the understanding and engineering of brain-inspired computing technologies. The program spans electrical engineering, neuroscience, IT, materials science, physics, AI, philosophy, and ethics. Building on the success of the first ICNCE (2024), which gathered over 500 participants, this year's event will be held at the Eurogress Aachen, located in the heart of the historic city near RWTH Aachen University and Forschungszentrum Jülich.

Consciousness Commons is a two-day collaborative satellite workshop following ASSC 2026 that brings together early-career researchers to develop new scientific projects using open datasets in consciousness science. Participants work in interdisciplinary teams to formulate hypothesis-driven research questions and develop rigorous analysis plans using openly shared datasets — including the Cogitate Consortium datasets. The workshop combines hands-on exposure to open scientific workflows with structured collaborative project development and guidance on preregistration and reproducible research practices. By the end of the workshop, each team will have produced a preregistered research plan specifying their hypotheses, dataset, and analysis pipeline — and teams will be eligible to compete for $25,000 in seed funding to support their project after the event.

The Pre-FENS Brainhack is a lively event that brings together people who are passionate about open science, open-source tools, and collaboration around computational and systems neuroscience. The hackathon provides an opportunity for people from different institutions to work together on projects of shared interest and learn from each other. The 2026 edition of the Pre-FENS Brainhack will center on reproducibility in interpreting data within systems neuroscience, drawing inspiration from CON²PHYS — CONceptual CONsistency in electroPHYSiology. During the Brainhack, participants will analyze the same electrophysiology dataset and attempt to answer multiple-choice questions that reflect real research challenges. This setup aims to reveal how researchers deal with conceptual ambiguity and how their analytical choices affect outcomes. The event fosters collaboration in teams of 3-4, integrating varied expertise and code practices to enhance reproducibility in analyses. Read more about the concept here. In addition to hands-on work, Research Software Engineers (RSEs) will provide talks about current tools and practices in systems neuroscience, offering insights into making analyses more reproducible through cleaner code, standard data layouts, and effective testing practices.

This Satellite will bring together leading researchers using animal models to study decision making through a combination of behavior, large-scale neuronal recordings, targeted circuit manipulations, and computational modeling. Talks will highlight recent advances in identifying how neural population dynamics in cortical and subcortical circuits give rise to adaptive choice behavior. A strong emphasis will be placed on mechanistic interpretations that link circuit activity to behavior across timescales, from moment-to-moment action selection to longer-term learning and strategy formation. By integrating experimental and theoretical approaches, the symposium aims to define current conceptual frameworks, identify unifying principles in the study of decision making, clarify how different timescales interact within and across brain circuits, and discuss key challenges for future research. The event will be of interest to systems neuroscientists, computational neuroscientists, and trainees seeking a circuit-level understanding of decision making grounded in causal experimentation.

The FENS Forum of neuroscience is the largest international neuroscience meeting in Europe. Taking place in even years, the FENS Forum rotates between different European countries and attracts more than 7,000 international delegates. In 2026, FENS, in collaboration with the Spanish Society of Neuroscience, is excited to welcome scientists from all corners of the world to Barcelona to unite in celebration of neuroscience. This forum will bring together leading experts, researchers, and students from around the world to explore the latest breakthroughs in neuroscience. With an inspiring programme of scientific sessions, thought-provoking talks, and ample networking opportunities, the FENS Forum 2026 is the perfect place to shape the future of neuroscience.

The Bernstein Network will have an information booth at this event!

Neuromatch Academy teach skills and techniques for computational sciences and research in Neuroscience, Climate Science, and Artificial Intelligence and Machine Learning. It serves thousands of students each year with hundreds of teaching assistants (TA). Students learn by solving problems in small groups and by running group projects; they learn in many languages in an incredibly supportive environment.

Computational Neuroscience and Inference from data are disciplines that extensively use tools from Mathematics and Physics to understand the behavior of model neuronal networks and analyze data from real experiments. Due to its interdisciplinary nature and the complexity of the neuronal networks, the list of techniques that are borrowed from Physics and Mathematics is an extensive one. Although using tools from standard curriculum of Physics, Mathematics and Engineering is common, more advanced research requires methods and techniques that are not usually covered in any single discipline. To fill in this gap, this summer school covers some of the most important methods used in computational neuroscience research through both main lectures and scientific seminars (5-6 main lectures per topic and 1-2 seminars by each invited seminar speaker). The program is primarily intended for PhD students, but advanced Master’s students (who will have defended before July 2026) and first-year postdoctoral researchers are also welcome to apply. There are no registration fees. Accommodation and meals will be covered for all selected participants. Attendance for the full duration of the school is mandatory. Application deadline: March 15, 2026

Applications are invited for a virtual edition of the Systems Vision Science Summer School and Symposium that took place in Max Planck Institute for Biological Cybernetics in Tuebingen, Germany in August 2023 and August 2025 and virtual in 2024. This year, the virtual edition enables students to attend from afar by formal lectures via Zoom and informal and social communications via a Slack channel. Systems Vision Science combines computational, behavioral, and neuroscience methods to discover functions and algorithms for vision in various brain regions and their implementations in neural circuits. This summer school is 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. The Summer School will be followed by a Systems Vision Science Virtual Symposium on July 31st. All admitted summer school students will be invited to attend this symposium and are encouraged to submit for a presentation at the symposium. The symposium will also feature two invited keynote presentations.

Understanding how the brain gives rise to behavior requires computational and theoretical methods. These allow us to formalize the function of neural circuits and to quantify behavior, as well as to analyze and understand complex high-dimensional datasets. Theoretical and experimental approaches work synergistically in modern neuroscience, where computational methods are critical for designing and interpreting experiments. This course teaches concepts, methods, and practices of modern computational neuroscience through a combination of lectures and hands-on project work. During the course’s mornings, distinguished international faculty deliver lectures on topics across the entire breadth of experimental and computational neuroscience. For the remainder of the time, students work on research projects in teams of 2 to 3 people under close supervision of expert tutors and faculty. Research projects are proposed by faculty before the course, and include the modeling of neurons, neural systems, and behavior, the analysis of state-of-the-art neural data (behavioral data, multi-electrode recordings, calcium imaging data, connectomics data, etc.), and the development of theories to explain experimental observations.

CCN is an annual forum for discussion among researchers in cognitive science, neuroscience, and artificial intelligence, dedicated to understanding the computations that underlie complex behavior. The conference began in 2017, with a goal to deepen interactions between these disciplines and to discover ways that the communities can benefit one another and leverage each other’s successes, articulated in this TICS commentary paper. The conference is primarily single-track featuring keynote speakers and oral presentations. Paper submissions are presented as posters with a few additionally selected for oral presentations. Community-proposed programming happens in single-track and parallel sessions, including "GACs", "K&Ts", and other community events. Generative Adversarial Collaborations (GACs), are symposia designed to clarify theoretical debates and scaffold forward progress. Keynote-and-Tutorial presentations (K&Ts) foster science and skill-building, presenting cutting-edge science as a talk, followed by the code and a tutorial of how to execute those methods. Open events are designed to welcome all creative ideas for community building, skill building, science exchange, mentorship and career development. We aspire to have an active, open, and responsive culture to meet the needs of this dynamic growing field. We encourage participation from experimentalists and theoreticians investigating complex brain computations in humans and animals.

he fourth instantiation of this European Summer School will bring together PhD students, early postdocs, and an international list of faculty for an intense training programme in primate cognitive and systems neuroscience. It will provide an outstanding training opportunity for young scientists working with non-human primates. Teaching will focus on cognitive processes in primate sensory and motor systems as well as in social settings and decision making, and will include important and novel results and methodologies. Topics of animal welfare, ethics, and media outreach will also be covered. Each faculty member will teach for about one half-day and furthermore will be available for individual scientific discussions, career planning advice, and scientific networking. Participants are expected to present their ongoing work in a poster presentation.

Animals interact with a complex world, encountering a variety of challenges: They must gather data about the environment, discover useful structures in these data, store and recall information about past events, plan and guide actions, learn the consequences of these actions, etc. These are, in part, computational problems that are solved by networks of neurons, from roughly 100 cells in a small worm to 100 billion in humans. Methods in Computational Neuroscience introduces students to the computational and mathematical techniques that are used to address how the brain solves these problems at levels of neural organization ranging from single membrane channels to operations of the entire brain.

Scientists spend a significant amount of time writing, maintaining and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. They end up being overwhelmed by the coding challenges they face and keep re-inventing the wheel. In the hope to free more time for research they increasingly rely on generative AI, which may produce runnable code without the need to fully understand it. Such code can neither be reused nor trusted to work correctly and, as a result, scientists are hesitant to share it and publish it. In this course we will present a selection of advanced programming techniques and best practices which are standard in the industry, but especially tailored to the needs of a programming scientist. Lectures are interactive and allow participants to acquire direct hands-on experience with the topics. Participants will work in pairs throughout the school and will team up to practice the newly learned skills in a real programming project — an entertaining computer game. We use the Python programming language for the entire course. This school is targeted at PhD students, postdocs and more senior researchers from all fields, who do a lot of programming in their academic life, but were never taught how to do so properly. Competence in programming and basic knowledge of Python and git is assumed. Participants are required to work through the proposed introductory material before.

The primary goal of the Human-Inspired Computer Vision (HCV) workshop is to bridge the gap between machine perception and biological systems by integrating findings from neuroscience, psychology, and cognitive science. Although modern computer vision achieves impressive results in many tasks, it still lacks the robustness and contextual flexibility inherent to human vision, and the relationship between artificial and human vision remains unclear. Investigating such a relationship is timely and important for two reasons:

The Summer School in Computational Biology was founded in 2015 by the Computational Biology Network at the University of Coimbra as a means to facilitate access to the Computational Biology field by students and researchers with either biological or exact sciences backgrounds. In the first two weeks of September each year we receive 20–30 international students who wish to acquire skills in Computational Biology. The course is intensive and targeted to students from the M.Sc. to post-doctoral levels with limited or no previous exposure to the field, although applications from B.Sc. students with outstanding CVs/skills are also considered.

The planned workshops will bring together autism researchers and experts in quantitative behavior analysis, both in animal models and in humans. Workshop participants will plan strategies to define and quantify motor and other visible phenotypes from video footage in individuals with autism. The workshops will also address analysis of associated audio data, as individuals with autism often exhibit differences in speech, language, prosody and conversational skills. This work will build off learnings from an initial workshop in behavioral phenotyping held in January of this year.

Please note: Five places are reserved for Bernstein Network members. Apply by August 24 to secure your spot!

This two-day workshop introduces modern approaches to Bayesian and simulation-based inference in the life sciences. On the first day, participants will learn the fundamentals of Bayesian inference and gain hands-on experience using PyMC for real-world data analysis. The second day focuses on simulation-based inference with neural density estimators, including applications to spiking neural network models and brain recordings. Practical exercises throughout the workshop provide opportunities to apply these methods to research questions from neuroscience and beyond.

Evolution in mammal brains has formed basic building blocks that might superficially look similar, but are organized in different structures and are obviously specialized for distinct computations. Accumulating evidence indicates that, while rodents are close evolutionary relatives to our own primate lineage, fundamental changes on all levels of brain organization occurred at the primate-rodent-split. In addition, subsequent primate evolution appears to be marked by apparently qualitative grade shifts. Recent progress across distinct disciplines provides a springboard to take a fresh perspective on what makes primate brains special. This workshop aims to enhance this comparative cognition perspective by contributions on avians and machines, which, despite having very different “brain” structures, perform functions that are surprisingly similar to those of mammals.

Each year the Bernstein Network invites the international computational neuroscience community to the annual Bernstein Conference for intensive scientific exchange. It has established itself as one of the most renowned conferences worldwide in this field, attracting students, postdocs and PIs from around the world to meet and discuss new scientific discoveries.

The objective of this interdisciplinary conference is to bring together researchers in computer science, artificial intelligence, artificial life, control, robotics, neurosciences, ethology, evolutionary biology and related fields in order to further our understanding of the behaviors and underlying mechanisms that allow natural and artificial animals to adapt and survive in uncertain environments. The conference will focus on models of adaptive behavior and its underlying mechanisms, and on experiments grounded on well-defined models including robot, computer simulation and mathematical models designed to help characterize and compare various principles or architectures underlying adaptive behavior in real animals and in synthetic agents, the “animats”. Selected papers will be invited to a special issue in the journal Adaptive Behavior and will be published with Springer Nature.

Each year, scientists from around the world congregate to discover new ideas, share their research, and experience the best the field has to offer. Attend so you can: present research, network with scientists, attend session and events, and browse the exhibit hall. Join the nearly half a million neuroscientists from around the world who have propelled their careers by presenting an abstract at an SfN annual meeting — the premier global neuroscience event.

The Bernstein Network will have an information booth at this event!

This winter school brings together researchers from neuroscience, machine learning, information theory, and applied mathematics to study learning, computation, and representation in complex systems. Topics range from neural dynamics and synaptic plasticity to data-driven discovery of dynamical models, biologically inspired machine learning, information-theoretic approaches to causality, and experimental and data-analytic perspectives. The goal is to foster a shared understanding of how brains and machines learn, represent structure in the world, and give rise to coherent computation across scales.