One of the goals of CSN is to engage leading scientists in the field of biomimetics and Neurotechnology to develop a number of standard courses and course materials that will be made available to the broader community through the CSN supported workshops and the CSN portal.
To comply with this goal CSN has started the “CSN book series”. This series is a developing teaching material tool that will include tutorials as well as other volumes describing core concepts, methods and technologies in the field of biomimetics and neurotechnology.

DAC Distributed Adaptive Control : Theory and Practice 

The Distributed Adaptive Control architecture is one of the very few examples of biomimetic architecture of perception cognition and action that has been applied to a range of artificial behaving systems i.e. robots, while having a strong grounding in the pertinent neuroscience of both invertebrate and vertebrate systems.  see [P. Verschure, 2012. Distributed Adaptive Control: A theory of the Mind, Brain, Body Nexus. Biologically Inspired Cognitive Architectures 1, 55-72]

As a subject for teaching material DAC will introduce the students to key concepts of minds and brains both at the functional level and at the level of how the physiology and the anatomy of brains realize these functions.

Original illustration of the DAC book cover by Sytse Wierenga and Anna Mura.      -->   download HERE

iqr Simulator for large scale neural systems  

This book is configured as an educational tutorial to provide not only contextual information on the relevance of simulators of large scale neural datasets but also to teach the knowhow of this type of tools with practical exercises and application in research. The book has 2 main authors, “series editors”, while each chapter has its own authors. As a whole, the book has been written by 6 authors.

The book is self-published by the CSN consortium and it is meant to be free and accessible to a large audience of students, and researchers in general.  

   -->  download HERE

The relevance of the CSN teaching material

The approaches adopted so far in this domain lack a clear conceptualization of the employment of robots in biological sciences. One of the key properties of “biorobotics approach” is that it circumvents the problem of the low degree of generalizability of models developed in simulation only. Support for real-world systems and the convergent validation method is the first cornerstone design philosophy behind iqr.

If we want to build systems able to generate a meaningful behaviour in the real world, they have to be complete in the sense that they must spawn from sensory processing to the behavioural output. Systems compliant with this requirement will inevitably be of a large-scale, where the overall architecture is of critical importance.
iqr is a tool for creating and running simulations of large-scale neural networks that provides sophisticated methods to:
• define connectivity, i.e. open architecture for writing own neuron, synapse types, and interfaces to   hardware
• perform high-speed simulations of large neuronal systems that allow the control real-world devices – robots in the broader sense – in real-time,
• interface to a broad range of hardware devices, i.e. predefined interfaces to robots, cameras, and other hardware;
As a simulation tool, iqr fits in between high-level, general-purpose simulation tools such as Matlab® and highly specific, low-level, neuronal systems simulators such as NEURON. The advantages over a general purpose tool are on the one hand the predefined building blocks that allow the easy and fast creation of complex systems and on the other hand, the constraints that guide the construction of biologically realistic models. The second point is especially important in education, where the introduction into a biological “language” is highly desirable.