Periodic Reporting for period 1 - NeuArc2Fun (Biological neural networks: from structure to function)
Periodo di rendicontazione: 2016-03-01 al 2018-02-28
The key for a useful formalism is finding the adequate balance between the mathematical tractability and biological realism of the model. To address this trade-off problem, NeuArc2Fun focuses on the mesoscopic level, i.e. scales at which many interacting neural populations can be simultaneously recorded by current state-of-the-art experimental techniques, such as electrode arrays. The advantage of this model-based approach is the ability to make predictions about the role of each component of the model –in particular, its heterogeneous connectivity– in shaping neural activity. A particular focus was on bridging several disciplines in a common comprehensive formalism: dynamic system, graph theory, statistics and information theory.
The primary application of the framework was targeted at electrophysiological data recorded in monkeys from the laboratory of Prof. Thiele in Newcastle University. Modeling such data is particularly challenging because they exhibit a large variability over repeated trials in the same condition, which hinders the extraction of consistent condition-specific information.
On the theoretical side, the proposal planned 2 articles in collaboration with Drs Tauste Campo and Zamora-Lopez from the CNS group (1 article with each), linking dynamic system (my speciality) with statistics and with graph theory respectively. The first one has been published in Network Neuroscience in 2017 (doi.org/10.1162/NETN_a_00019) and the second one has just been accepted by Physical Review E (March 2018; preprint on arxiv: http://arxiv.org/abs/1712.05693). A third paper was published in Biological Cybernetics (http://doi.org/10.1007/s00422-017-0741-y) formally linking network dynamics with information theory.
On the application side, it turned out that electrophysiological data are more difficult to analyze with the developed network model than fMRI data. This explains why 1 publication (same article in Network Neuroscience mentioned above) focuses on electrophysiological data from the lab of Prof. Alex Thiele (Newcastle University), whereas the other application papers concern fMRI data. Using other types data in the network model was in fact mentioned in the proposed risk management. Nonetheless, the application to electrophysiological data is still ongoing work and will lead to another submitted paper about the connectivity between cortical layers, tentatively in 2018.
The 2-year MSCA fellowship also gave me the opportunity to (co)supervise 5 PhD and master students. Among those, 4 led to publications or submitted manuscripts: Katharina
Glomb (2 published in Neuroimage, doi.org/10.1016/j.neuroimage.2017.07.065 and doi.org/10.1016/ j.neuroimage.2017.12.074) Niels Reuter (me as last author, published in Human Brain Mapping,
doi.org/10.1002/hbm.23913) Vicente Pallares (me as last author, minor revisions in Neuroimage, available on biorxiv doi.org/10.1101/201624) and Murat Demirtas (submitted, available on biorxiv doi.org/10.1101/286484). I also gave internal seminars within the CNS group at UPF in the context of the Journal Club (October 2016 and November 2017) to review recent advances in the literature and Group Meeting (September 2016, June and September 2017) where I presented my own work.
The diffusion of gained knowledge and visibility of the work was supported by attending 9 conferences, including 2 oral presentations in plenary sessions for Neural Coding 2016 and
Coupling and Causality in Complex Systems 2017. There was also the organization a workshop on connectivity analysis (extraction of “fingerprint” of brain activity; http://matthieugilson.eu/
events/workshop_CNS2017.html) in CNS 2017 (Antwerp, Belgium) and the co-organization of a workshop in CNS 2016 (Jeju, South Korea; www.fz-juelich.de/inm/inm-6/EN/Aktuelles/Termine/ MAMC_workshop_CNS2016/_node.html including an oral presentation). I also visited laboratories to develop new collaborations (for new types of data, beyond fMRI and electrophysiology), during 4 laboratory visits (including 1 to finish a paper with Niels Reuter in Maastricht). I also took part in a winter school as a tutor (http://education.humanbrainproject.eu/web/5th-school/scientificprogramme- application).