Lead Scientists Programme
The lead scientist programme further strengthens the HBP’s openness measures by attracting leading scientists in the broader field of neuroscience to join the Project.
This scheme was introduced to drive research collaboration in the field of neuroscience, to help high-profile external researchers to achieve their ambitious research aims, and to allow the EBRAINS research infrastructure to benefit from such challenging use cases.
The lead scientists have a high reach and visibility within the communities and are pioneers in their fields. The lead scientists set up a collaborative research project within the HBP and will receive support from the HBP’s High Level Support Team to ensure that methodical and technological developments are being embedded in EBRAINS.
“We hope to leverage the microstructural information of the HBP’s Human Brain Atlas to constrain the imaging data in order to predict dopaminergic drug effects.”
Roshan Cools, HBP Lead Scientist, Radboud University, The Netherlands
Building a prediction model of dopamine drug effects on human cognition
We are working to develop a biologically constrained prediction model of basal dopamine levels. This prediction model will consist of an optimal combination of (behavioural and physiological) proxy-measures of dopamine that captures much of the variance in dopamine drug effects on brain and cognition. The ensuing multivariate dopamine prediction model will offer a pragmatic tool that can be enormously beneficial to the international clinical research community, because it will allow stratification of who will benefit and who will be impaired by dopamine drugs without recourse to expensive and invasive tools like dopamine PET. We will leverage, and share with the HBP, our unique human dopamine dataset.
Lead scientist: Roshan Cools, Radboud University Nijmegen Medical Centre and Donders Centre for Cognitive Neuroimaging, The Netherlands
“I see a great potential for the facilities that the Human Brain Project—and in particular its EBRAINS infrastructure—has to offer.”
Karl Friston, HBP Lead Scientist, University College London, UK
Dysconnection syndromes and dynamic causal modelling
We are addressing the challenge of linking patient data with computational models. Specifically, we will integrate multimodal brain recordings to develop patient-specific models of epileptic brain dysfunction. With such models, one can do in silico lesion experiments and in silico psychopharmacology without endangering a patient through experimental intervention. We will develop a modelling pipeline for implementation in The Virtual Brain on EBRAINS so that the community will directly benefit from our work. This work will advance epilepsy research and also provide a grounding for developing patient-specific computational models of other brain disorders.
Lead scientist: Karl Friston, University College London, UK
Additional PIs working on the project: Richard Rosch UCL
“The HBP has offered new opportunities for me to efficiently link molecular biology of receptors and computational sciences and to develop original models of their function with considerable importance for drug design.”
Prof. Jean-Pierre Changeux, Institut Pasteur, France
Project: Allosteric Modulation of pentameric ligand-gated ion channels: relevance to COVID-19
The project focuses on the allosteric modulation of pentameric ligand-gated ion channels and its relevance to COVID-19, including atomistic models of the nACh-Receptor in its physiologically relevant states (i.e. active, resting, and desensitised), an atomistic description of the conformational dynamics of the modulatory sites during gating, and a database of known allosteric modulators with a structural annotation of their binding site on the receptor will be made publicly available via EBRAINS.
Additional PIs working on the project: Marco Cecchini UNISTRA Strasbourg and Hervé Bourhy Institut Pasteur Paris
“The HBP opened an exciting window or opportunities to interact with leading European scientists from various disciplines in neuroscience including neuroimaging, neurocomputing, robotics and statistics. HBP and particularly the access to the EBRAINS infrastructure exposed my lab to an unprecedented wealth of methods and platforms, expanding our research capabilities beyond the current state of the art. Finally, the HBP provides a unique environment for interdisciplinary discussions across scales (cellular regional and whole brain) models (animal, human and computational), which is almost impossible to achieve in the common disciplined practice in neuroscience.”
Prof. Talma Hendler, Tel Aviv University, Israel
Project: Multi-scale Neural Depiction of Learning from Failure in Humans
The project aims to unveil the intriguing relation between motivation and memory through the lens of reinforcement learning models in humans. We plan to use multiscale brain mapping techniques (simultaneous EEG/fMRI intracranial recordings) along with machine learning analytics in naturalistic set-ups of (e.g., Virtual/Augmented Reality and social robots) and self-neuromodulation (i.e. Brain Computer Interface).
Additional PIs working on the project:
Rainer Goebel, Maastricht University,the Netherlands
Gal Raz, Tel Aviv University, Israel
Leor Wolf Tel Aviv University, Israel
Prof. Stanislas Dehaene, Collége de France, CEA
Project: Singularity of the human brain
The acquisition of large amounts of data in a small number of individuals has proven very useful to better describe fine-scale organisation of cortical structures. In this project, we inquire whether these deep phenotypes can help better understand human-specific cortical areas (language, high-cognition, consciousness) by comparing human and primate individuals.
In particular, we will address whether (i) large quantities of functional contrasts enable us to univocaly identify cortical areas at an individual scale and (ii) if they help match comparable areas of other individuals of the same species (iii) before trying to expand these results to individuals of different species.
We will try to address these questions using various types of data, such as task fMRI - using a wide range of existing protocols - naturalistic stimuli - such as movie watching - but also topographical data - such as cortical thickness or myelin distribution. Finally, we aim at making these results available through intuitive and interactive visualisation supports, enabling experts as well as new-comers to dive into the underlying datasets.
Lead scientist: Prof. Stanislas Dehaene, Collége de France, CEA