BIS’2017 – Full day working session on “Computational methods for the better understanding of human cognition and health” – 9 June 2017

Sutardja Dai Hall (SDH) Building, Meeting room 242

This full day working session brings together -but not only- researchers involved in the Inria@SiliconValley theme “Content & Supporting Learning Technologies“.



With recent advances in information technology, an ever increasing amount of data is being collected to better understand human cognition and health. With the staggering amount and size of the data, new questions arise. How can we adequately analyze these data? How can we summarise millions of time points in a structured and interpretable way? How can we use what we know about the computational brain in other contexts, such as artificial intelligence? How can we build new computational tools for medicine in order to significantly improve patients’ daily life?

Recent advances in the field, such as machine learning applications, present researchers with new opportunities, but come with new limits. In this workshop, we will give an overview of recently developed computational methods for the better understanding of the human brain, both in fundamental research as in profitable applications.  

In the morning, we will present the most recent developments of (neuro) informatics tools by the ongoing Inria@SiliconValley collaborations. These collaborations include the Inria teams Asclepios, Athena, Magnet, Parietal and the californian institutions Berkeley, USC and Stanford. The morning session enables attendees to get a deeper understanding of the current Inria@SiliconValley projects, fostering further discussion and collaboration.

In the afternoon, the discussion will be expanded to the most recent breakthroughs based on ‘brain computing’ in the industrial world (part 1) and in academia (part 2). Leaders in neuroscience both from industry and academia will present their ongoing activities. We will hear from community efforts as well as from start-ups in the Silicon Valley, to grasp how these new technologies help better understanding of the brain.




10:00 Nina Miolane

GeomStats Inria/Stanford,

Consultant for  Bay Labs

Personal website

Exploring the brain anatomy with Geometric Statistics
10:20 Demian Wassermann

LargeBrainNets Inria/ Stanford

Lab website

Anatomo-Functional Structure of the Visual Word Form Area: Combining Functional and Diffusion MRI
10:40 – 11:00 BREAK
11:00 Joke Durnez

MetaMRI Inria/Stanford

Lab website

Neuropowertools: improving statistical power in fMRI neuroimaging studies
11.20 Fei Sha


Personal website

Task transferability via word embedding
11.40 Jean-Baptiste Poline

MetaMRI /Berkeley

Team website

Issues on re-usability of statistical results in fMRI
12:00 – 14:00 LUNCH


Marion Le Borgne, John Naulty







NeuroTechX: the international neurotechnology network
14:30 Eric Oermann

Verily, Google Life Science





Saving brains faster with machine learning – time is brain
15:00 Matthieu Le

Inria, now Arterys





Automating radiologists’ workflows with Deep Learning
15:30 – 16:00 BREAK
16:00 Zarinah Agnew


Personal website

Motor induced sensory suppression in the brain
16:30 Natalia Bilenko

Berkeley, now Bay Labs


Modeling of natural stimulus representation in the human brain using canonical correlation analysis