Category Archives: 2022

Visual Reactive Programming – Bonsai 1022

Applications are closed but you can express your interest in the next edition by clicking on the button above and filling in the form.

This is a Cajal NeuroKit course that combines online lectures about fundamentals and advanced neuroscience topics with hands-on and physical experiments.

Researchers can participate from anywhere in the world because the course material is shipped to participants in a kit box that contains all the tools needed to follow the online course.

This course is now at its third edition. It is held at least once a year.

Call for TAs: If you already know how to programme in Bonsai and you would like to run this course locally as a Teaching Assistant with a group of students, please click on the button below to fill in the TA form. Thank you.

Course overview

Modern neuroscience relies on the combination of multiple technologies to record precise measurements of neural activity and behaviour. Commercially available software for sampling and controlling data acquisition is often too expensive, closed to modification and incompatible with this growing complexity, requiring experimenters to constantly patch together diverse pieces of software.

This course will introduce the basics of the Bonsai programming language, a high-performance, easy to use, and flexible visual environment for designing closed-loop neuroscience experiments combining physiology and behaviour data.

This language has allowed scientists with no previous programming experience to quickly develop and scale-up experimental rigs, and can be used to integrate new open-source hardware and software.

Course Teaser

What will you learn?

By the end of the course you will be able to use Bonsai to:

– create data acquisition and processing pipelines for video and visual stimulation.
– control behavioral task states and run your closed-loop experiments.
– collect data from cameras, microphones, Arduino boards, electrophysiology devices, etc.
– achieve precise synchronization of independent data streams.

The online material will be soon found here.


Gonçalo Lopes

Course Director

NeuroGEARS, London, UK​


João Frazão Champalimaud Research, Lisbon, PT

Niccolò Bonacchi – International Brain Laboratory, Lisbon, PT

Nicholas Guilbeault – University of Toronto, CA

André Almeida – NeuroGEARS, London, UK

Bruno Cruz – NeuroGEARS, London, UK

Course sponsors


Day 1 – Introduction to Bonsai

  • Introduction to Bonsai. What is visual reactive programming.

  • How to measure almost anything with Bonsai (from quantities to bytes).

  • How to control almost anything with Bonsai (from bytes to effects).

  • How to measure/control multiple things at the same time with one computer.

  • Demos and applications: a whirlwind tour of Bonsai.

Day 2 – Cameras, tracking, controllers

  • Measuring behavior using a video.

  • Recording real-time video from multiple cameras.

  • Real-time tracking of colored objects, moving objects and contrasting objects.

  • Measuring behavior using voltages and Arduino.

  • Data synchronization. What frame did the light turn on?

Day 3 – Real-time closed-loop assays

  • What can we learn from closed-loop experiments?

  • Conditional effects. Triggering a stimulus based on video activity.

  • Continuous feedback. Modulate stimulus intensity with speed or distance.

  • Feedback stabilization. Record video centered around a moving object.

  • Measuring closed-loop latency.

Day 4 – Operant behavior tasks

  • Modeling trial sequences: states, events, and side-effects.

  • Driving state transitions with external inputs.

  • Choice, timeouts and conditional logic: the basic building blocks of reaction time, Go/No-Go and 2AFC tasks.

  • Combining real-time and non real-time logic for good measure.

  • Student project brainstorming

Day 5 – Visual stimulation and beyond

  • Interactive visual environments using BonVision.

  • Machine learning for markerless pose estimation using DeepLabCut.

  • Multi-animal tracking and body part feature extraction with BonZeb.

  • Student project presentation.

  • Where to next.

The course will be held from 13:00 to 17:00 GMT.


Registration fee: 500€ per person (includes shipping of the course kit, pre-recorded and live lectures before and during the course, full attendance to the course, and course certificate).

The CAJAL programme can offer some stipends (waived partial or full registration fee). Please apply through the course online application form.

Registration fee for a group: 500€ for one person and one course kit + 150€ for any additional person (without the course kit)

Applications are closed but you can express your interest in the next edition by clicking on the button above and filling in the form.

Please note that this is not considered as an application.

To receive more information about this NeuroKit, email


Modern Approaches to Behavioural Analysis

Modern Approaches to Behavioural Analysis is a Cajal NeuroKit. The course will combine online lectures on fundamentals and advanced neuroscience topics with guided data analysis and exercises.

Course overview

The goal of neuroscience is to understand how the nervous system controls behaviour, not only in the simplified environments of the lab, but also in the natural environments for which nervous systems evolved.

In pursuing this goal, neuroscience research is supported by an ever-larger toolbox, ranging from optogenetics to connectomics. However, often these tools are coupled with reductionist approaches for linking nervous systems and behaviour. This course will introduce advanced techniques for measuring and analysing behaviour, as well as three fundamental principles as necessary to understanding biological behaviour: (1) morphology and environment; (2) action-perception closed loops and purpose; and (3) individuality and historical contingencies [1].

[1] Gomez-Marin, A., & Ghazanfar, A. A. (2019). The life of behavior. Neuron, 104(1), 25-36

What will you learn?

This course will emphasize the philosophical and observational skills required to understand behaviour, while also providing training in motion capture technologies and computer vision methods that can assist in the collection and analysis of video recorded behaviour datasets.

Focusing on the tool DeepLabCut, students will analyse either their own original video dataset or datasets of general interest and have the opportunity to practice tracking, pose estimation, action segmentation, kinematic analysis and modeling of behaviour.

By the end of the course, you will:

  • be familiar with modern and historical frameworks for studying the behaviour of living biological systems
  • practice methods for carefully and precisely observing and defining behaviours
  • understand the limits and capabilities of computer vision
  • develop an intuition for how to build experimental setups that can take advantage of tools such as DeepLabCut

Furthermore, this course shares and promotes open source software, and we encourage students to try new ideas, share insights, and connect with the open-source community.

Pre-course for TAs

We are running a pre-course in early November at the EPFL in Geneva (Switzerland) and online, on November 7 – 11, 2022, to train Teaching Assistants. If you would like to help us teach this course locally or online, you can email us at


Alexander Mathis

Course Director EPFL, Switzerland

Danbee Kim

Co-director NeuroGEARS, UK

Keynote speakers

Nicola Clayton (Cambridge University, UK)

Ole Kiehn (Copenhagen University, Denmark)

Elizaveta Kozlova (EPFL)

Guest lecturers

Johanna T Schultz (USC, Australia)

Caleb Weinberg (Harvard Medical School, USA)

Nacho Sanguinetti (Harvard University, USA)

Local training hubs:


Day 1 – What is animal behaviour?

  • Historical and current theoretical frameworks for the study of behaviour in living biological systems

  • Practical exercises for training skills in observing and defining behaviours

Day 2 – Tools for modern-day ethology

  • Fundamentals of video recording, computer vision, and deep learning

  • Introduction to DeepLabCut

  • Creating a tailored DeepLabCut model for your data or data shared by us.

Day 3 – Training computers to see as we see

  • Multi-animal tracking

  • Live tracking

  • Evaluating, utilizing and optimizing your DeepLabCut model from day 2

Day 4 – Analysis by eye and by computer

  • Movement kinematics in living biological systems

  • Action segmentation – when does a behaviour start and end?

  • Analyse original video dataset of behaviour

Day 5 – Working on your data and discussion

  • Advanced DLC topics and potential pitfalls

  • Keep analyzing data and student presentations

The course will be held from 13:00 to 17:00 GMT.


Registration fee: 200€ per person (includes pre-recorded and live lectures before and during the course, tutoring, and course certificate).

Applications closed on 24 October 2022, 23:59 CEST

To receive more information about this NeuroKit course, email