Course overview

This course provides a foundation for new experimental neuroscientists. It is targeted at students beginning a PhD or researchers entering the field from another discipline. It should be considered a “prerequisite” for more advanced training courses in a specialized topic.

The course introduces the essentials of data acquisition/control, data analysis, and machine learning by guiding the students through the hands-on construction of an increasingly capable robot. In parallel, related concepts in neuroscience are introduced as nature’s solution to the challenges students encounter while designing and building their own “intelligent” system.

Course Partners

Voight-Kampff

Course directors

Adam Kampff

Course Director Voight Kampff, London, UK

Elena Dreosti

Co-Director University College London, UK

Instructors

– Peter Vincent (Sainsbury Wellcome Centre, London, UK)

Spenser Wilson (Sainsbury Wellcome Centre, London, UK)

 

Eirinn Mackay (Sainsbury Wellcome Centre)

– Virginia Rutten (The Gatstby Computational Neuroscience Unit)

 

What will you learn?

You will be building a robot without using any black boxes. The robot’s physical layout mimics the basic anatomy of a (vertebrate) brain, and as you gradually open this course’s 21 “boxes” your robot will evolve into an increasingly sophisticated machine. We thus call this robot the No-Black-Box-Bot or NB3.

The course is divided into three sections (following the anatomy of the brain): hindbrain (reflexes), midbrain (behaviour), and forebrain (intelligence?).

The online material can be found here.

Week 1: Measuring and Moving

Aims:

Students build a basic sensory-motor system (a Braitenberg vehicle) that seeks or avoids light and learn about fundamentals of electronics, sensors/actuators, and amplification.

Schedule:

Day 1: “The White Box” Toolkit, Electrons

Day 2: Magnets + Light, Sensors + Motors

Day 3: Semiconductors 

Day 4: Amplifiers

Day 5: Reflexes, NB3 demos

Week 2: Computers and Programming

Aims:

Students extend their robot to make decisions based on sensory input and perform basic computations. With the addition of a microcontroller, the students will learn the fundamentals of computers and programming, and the robots will develop more complex behaviours.

Schedule:

Day 1: Decisions, Logic

Day 2: Data, Memory

Day 3: Computers

Day 4: Control

Day 5: Behaviour, NB3 demos

5N7A9808
Nicole_V_Camera_Mounted

Week 3: Data Analysis and Machine learning

Aims:

Students add a computer and camera to their robot. They then learn how to use modern neural networks to create an “intelligent” visual system for their robot that can identify obstacles, rewards, and much more… 

Schedule

Day 1: Hearing + Speech, Vision

Day 2: Learning, Intelligence?

Day 3: NB3 work, NB3 work

Day 4: NB3 work, NB3 work

Day 5: NB3 work, NB3 demos

Receive information

If you want more information about this NeuroKit, email info@cajal-training.org