How does collective neuronal activity form the basis of functions of the nervous system? Sensing, acting, perceiving… all these functions are emergent properties of complex networks including millions of neurons; the knowledge of the behavior of individual neurons is not enough to understand their collective behavior in a network. We thus need to understand the behavior of neuronal assemblies[1] for understanding their function. This is particularly important in a time when our increasing knowledge in physiology and physiopathology opens immense perspectives for the development of neuro-prosthetics in the growing field of brain machine interfaces (BMI). However, it is still an enormous challenge to mesure, manipulate, analyze and interprete the neuronal activity at the level of networks based on technological and theoretical progress.

Among technological evolutions, we find:

• novel electrodes and implants to record simultaneously from tens or even hundreds of brain sites
• electronic/software interfaces that allow one to follow in real time the activity of entire populations of neurons and to control them in closed loop situations
• imaging techniques (optical imaging, 2 photon imaging, optogenetics)

This progress opens new horizons in terms of scales, resolutions and specificity of measures, but at the same time it generates a huge amount of data whose growing volume, complexity and richness requires new methodologies in signal processing and statistics (non-supervised classification, deconvolution, causality analyses, time-frequency analyses, bayesian analyses, multi-dimensional scaling, higher-order correlations, etc.), and the use of standardized data bases to organize the obtained data.

Finally, the complexity of the observed collective neuronal dynamics requires the development of theoretical models derived from engineering, informatics, physics, and applied mathematics (control theory, statistical physics, dynamical systems, point processes, information theory, etc.).  

The integration of very heterogeneous methodological approaches and the follow-up of innovations within a large scientific area (sensory physiology, motor control, cognition, physiopathology, prosthetics, theoretical neuroscience, etc.) require coordinated interactions and multi-disciplinary collaborations between scientists and engineers coming from different and distant disciplines. The research groups (GDR) of the CNRS constitute a powerful instrument to generate and support the development of such synergies. This is the main « raison d’être » of the GDR NeuralNet.

Structure

The environment of our GDR is identified by an ensemble of teams which are particularly enganged in the following thematical axes:

1. Instrumentation
2. Analysis 
3. Action, Motor control
4. Sensory systems, Perception 
5. Decision, Cognition
6. Brain-Machine Interfaces
7. Theoretical Neurosciences

Objectives

The main objective of our GDR NeuralNet is to support innovative research in integrative neuroscience around the main questions as cited below. It is created as the successor of the GDR 2904 « Multi-electrode systems and signal processing applied to the study of neuronal networks », which started to build a lively community since October 2010. The GDR NeuralNet will strengthen and extend its objectives by the following missions

• to create and support synergies between teams in neurobiology, instrumentation, signal processing and modeling; to help exploiting its existing but fairly scattered potential;
• to provide tools that allow one to develop new types of electrodes, electrode arrays, miniaturized electronic active systems, as well as new software tools for analyzing the new large data sets;
• to provide tools for dissemination of scientific and technical knowledge (technology intelligence), exchange of know-how, for developing interfaces with the international community;
• to facilitate the insertion of young researchers in the national community;
• to train young researchers to avoid the lack of knowledge of techniques or the usage of technological solutions without the necessary theoretical knowledge of the technical problems;
• to sensitize for valorization and transfer of knowledge toward industry.

Actions

• Organization of meetings between national stakeholders, international stakeholders and companies for scientific equipment. These meetings may take place in form of work groups and lectures, but specifically the annual conference which will be organized successively in different french cities.
• Financing of missions such as scientific meetings, visits and exchanges of PhD students and young researchers of different laboratories.
• Organization of an annual school including advanced methodological courses, best practice courses, and the valorization of tools developed within the GDR.
• Use of a web site and mailing lists helping to distribute advertisements (seminars, calls, conferences, internal advertisements of the GDR) and to facilitate the exchange of information.

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[1]         a neuronal assembly is defined as a group of neurons whose temporally coordinated discharge (synchronous or sequential) participates at the emergent function of a network, where a single neuron may participate in different assemblies at different moments in time. An ensemble of neurons is defined as any group of neurons, independent of their functional role, for instance, all neurons recorded simultaneously by a multi-electrode array.