2019 School on Brain Connectomics

Course content

Technical description

Connectomics is one of the hottest inter-disciplinary topics today. It links computer science and Engineering with life- and neuro-sciences. Connection networks grow over functional (fMRI, ASL, EEG, MEG) and structural (diffusion weighted MRI) data and the integration of the two in both static and dynamic conditions sheds light on the way our brain actually works. Connectomics also holds a paramount potential for clinical applications through the characterization of the network's modulation in pathologies and the assessment of the treatment. The BRAINCONN 2019 Winter School will address all the steps of the pipeline leading from raw data to connectivity models addressing structural, functional and effective connectivity. The School articulates across five days each focusing on one specific aspect. In particular, days 1 opens with a lecture introducing brain connectomics and illustrating the different aspects that are concerned and sets the basis for diffusion MRI signal reconstruction and modelling as well as for the construction of the structural connectivity matrix; day 2 will face some issues affecting signal acquisition and pre-processing in diffusion MRI including the issue of data harmonization from multi-site acquisitions; day 3 faces advanced topics in microstructure modelling and provides a solid background on tractography methods, illustrates pitfalls and recent advances and provides hints for practical usage of existing algorithms. Day 4 is dedicated to functional imaging with lectures dedicated to functional MRI, EEG and MEG and to the introduction of related connectivity models. Day 5 opens with a wide overview on cortical parcellation strategies enabling region-based connectivity models to prepare for the two last lectures concerning effective connectivity models and graph theory. Days 1, 3, 4 and 5 will also host hands-on sessions on the related topics discussed in the morning sessions covering all the main practical aspects of data processing and connectivity modelling.

Outline on topics to be covered

The School on Brain Connectomics aims at gathering the knowledge in the different fields that are touched by these topics providing the students a comprehensive view of this research area as well as awareness about the cutting-edge methodological, experimental and technical aspects that are involved. As described in the previous Section, the main topics that will be covered are as follows:

  • Signal acquisition and modeling in diffusion MRI
  • Microstructure modeling in diffusion MRI
  • Tractography methods and related issues
  • Data harmonization across different acquisition sites and protocols
  • Acquisition and processing of functional data (functional MRI, EEG, MEG)
  • Connectivity modeling (structural, functional and effective)
  • Graph models

Preliminary program

Day 1 - September 23

Time Topic Title Lecturer
9:00 - 10:00 Opening Lecture Structural and functional connectomics - an overview Jean Philippe Thiran
10:00 - 11:00 Diffusion MRI DWI acquisition strategies for improved reproducibility and inter-scanner harmonization of diffusion MRI Carlo Pierpaoli
11:00 - 11:30 Coffee break
11:30 - 12:30 Diffusion MRI An introduction to modeling in Diffusion MRI: Tensors, Propagators, and Compartments Mauro Zucchelli
12:30 - 14:00 Lunch
14:00 - 17:00 Hands-on Session Mauro Zucchelli

Day 2 - September 24

Time Topic Title Lecturer
9:00 - 10:00 Data acquisition and harmonization Brain Morphometry using diffusion MRI data Carlo Pierpaoli
10:00 - 11:00 Data acquisition and harmonization Diffusion MRI data harmonization: experience from the international MICCAI Challenges and future directions.
Can we learn anything new?
Francesco Grussu
11:00 - 11:30 Coffee break
11:30 - 12:30 Data acquisition and harmonization Overview of data acquisition and pre-processing factors that affect brain diffusion MRI quality Jorge Jovicich
12:30 - 14:00 Lunch

Day 3 - September 25

Time Topic Title Lecturer
9:00 - 10:00 Diffusion MRI: Microstructure and Tractography Diffusion MRI: Microstructure modeling and multidimensional encoding Markus Nilsson
10:00 - 11:00 Diffusion MRI: Microstructure and Tractography What can we learn from the diffusion MRI signal? Donald Tournier
11:00 - 11:30 Coffee break
11:30 - 12:30 Diffusion Computational Methods for Neuroanatomical Bundle Segmentation Paolo Avesani
12:30 - 14:00 Lunch
14:00 - 17:00 Hands-on Session Donald Tournier

Day 4 - September 26

Time Topic Title Lecturer
9:00 - 10:00 Connectivity models and Graphs Seeding connectivity - cortical parcellations Olivier Coulon
10:00 - 11:00 Functional neuroimaging Decoding the brain activity: functional neuroimaging and connectivity Ilaria Boscolo Galazzo
11:00 - 11:30 Coffee break
11:30 - 12:30 Functional neuroimaging Part 1: Forward and inverse problems in EEG and MEG Maureen Clerc
12:30 - 13:30 Functional neuroimaging Part 2: Machine Learning for Brain Computer Interfaces Maureen Clerc
13:30 - 14:30 Lunch
14:30 - 17:30 Hands-on Session Ilaria Boscolo Galazzo

Day 5 - September 27

Time Topic Title Lecturer
9:00 - 10:00 Connectivity models and Graphs What functional connectivity is good for? A theory of the function of spontaneous activity Maurizio Corbetta
10:00 - 11:00 Connectivity models and Graphs Brain functional connectivity inference: models, definitions, perspectives and pitfalls Laura Astolfi
11:00 - 11:30 Coffee break
11:30 - 12:30 Connectivity models and Graphs Graph theoretical applications to structural and functional connectivity Martjin Van den Heuvel
12:30 - 14:00 Lunch
14:00 - 17:00 Hands-on Session: Brain Connectivity and Graphs Siemon de Lange


Jean Philippe Thiran

EPFL, Switzerland


Carlo Pierpaoli



Mauro Zucchelli

INRIA, Sophia Antipolis, France


Francesco Grussu



Jorge Jovicich

University of Trento


Markus Nilsson

Lund University, Sweden


Donald Tournier

King's College, London, UK


Paolo Avesani

FBK, Trento

Maurizio Corbetta

University of Padova


Ilaria Boscolo Galazzo

University of Verona


Maureen Clerc

INRIA, Sophia Antipolis, France


Olivier Coulon

Institute de Neurosciences de la Timone


Laura Astolfi

La Sapienza, University of Rome


Martijn Van den Heuvel

VU Amsterdam, The Netherland


Siemon De Lange

VU Amsterdam, The Netherland



The school will be held at the Dept. of Computer Science of the University of Verona (Verona, Italy). Facilities will be made available for hands-on laboratory sessions where the students will learn and experiment software tools for data processing (pre-processing, analysis, modeling).


Organizing Committee:


Registration fees:

  • SPS member, student (lowest rate) - € 350 for the whole event
  • Non-SPS member, student - € 400 for the whole event
  • SPS member, non-student - € 500 for the whole event
  • Non-SPS member, non-student - € 550 for the whole event

The number of participants is limited to 40.

Priority will be given to Ph.D. students. If you are a post-doc or a researcher, please contact the organizers (info[at]brainconnectomics [dot] org). Admission to the school is possible if there are positions available.

Application requirements:

  1. The applicant's curriculum vitae
  2. A signed motivation letter from the applicant that includes a statement indicating how this School may benefit the applicant's current or future research or training
  3. If the applicant is a PhD student, a signed letter from the applicant's supervisor confirming her/his enrollment in a PhD course

Applicants should send the necessary documentation via email at the following address: info[at]brainconnectomics [dot] org

Deadline for applications: July 3, 2019
Notification of acceptance will be by July 10.

Applications after the deadline will be accepted until the maximum number of attendants will be reached.

AFTER the notification of acceptance, payments can be made via credit card at the following link: http://www.di.univr.it/;jsessionid=abcBxk96r8RwJdSucCmPw?ent=vendita&codice=BRAIN19&lang=en