“Big Data”and Industrialisation of Neurosciences: a Safe Roadmap for Understanding the Brain?

New technologies in neuroscience generate reams of data increasing at an exponential pace and spur the design of very-large data-mining initiatives. Their development has triggered the emergence of coordinated research of unprecedented scale and constitution of massive databases concerning the structure and function of the Brain. In particular, among recent supranational ventures, the European “The Human Brain Project” (HBP), the US consortia (“B.R.A.I.N.” and “The Human Connectome”), the “MindScope”privately-owned Allen Institute, all participate to this worldwide effort. With the help of the GAFAM giants of the Web industry, all flirt with the possibility to achieve, within the next decade(s), full simulation of the Human Brain. This objective, which was considered, up to now, as out of reach, could soon become reality.

The epistemological question that I address here focuses on the scientific, strategic and societal underpinnings of this runaway enthusiasm for industrial-scale projects of a novel kind and ambition, at the interface between “wet” (Biology) and “hard” (Statistical Physics, Micro-electronics and Computer Science) sciences. Rather than presenting the achievements and hopes fueled by big-data-driven strategies – already covered in depth in special issues of leading journals - I deliberately chose to focus on three major issues:

1) is the industrialization of neuroscience the soundest way to achieve significant progress in Brain knowledge?    
2) do we have a safe “roadmap”, based on consensual scientific grounds and reasonable expectations? and     
3) do these large-scale approaches guarantee reaching a better understanding of the Brain and the relation between neural activity and the emergence of cognition?

This “opinion” paper emphasizes the contrast between the accelerating technological development – amplified by the progresses of artificial intelligence – and the relative lack of progress in conceptual and theoretical understanding of the biological Brain. It underlines the risks of building a “techno-science” bubble – driven by uncertain political and economical promises – at the expense of more incremental approaches in fundamental research based on the parallel exploration of a diversity of roadmaps and theory-driven hypotheses. I conclude to: 1) the necessity of identifying current bottlenecks with appropriate sharpness – before launching any form of neuroscience industrialization – and 2) developing novel interdisciplinary tools and strategies specifically designed to handle the complexity of The Brain and increase our knowledge of the biological foundations of mind processes.