Using Structural Connectivity to Reconstruct Brain Activation and Effective Connectivity

HAL Id: hal-02945690

https://hal.inria.fr/hal-02945690

Submitted on 22 Sep 2020

HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Using Structural Connectivity to Reconstruct Brain

Activation and Effective Connectivity

Brahim Belaoucha, Théodore Papadopoulo

To cite this version:

Brahim Belaoucha, Théodore Papadopoulo. Using Structural Connectivity to Reconstruct Brain Activation and Effective Connectivity. Organization for Human Brain Mapping annual Meeting, Jun 2020, Montreal, Canada. 2020. �hal-02945690�

1

Main ideas

4

Contribu�ons and Conclusion

Brahim Belaoucha, Théodore Papadopoulo

Contact: Theodore.Papadopoulo@inria.fr

2020 OHBM

l

ti

J

23 J l 3

3

https://team.inria.fr/athena/

3

_{Experiments and results}

ATHENA UCA INRIA FRANCE

Using Structural Connec�vity to Reconstruct Brain Ac�va�on

and Effec�ve Connec�vity

Université Côte d’Azur, Inria Sophia Antipolis-Méditerranée, Athena Project-Team, France

2

Processing pipeline

Data (MEG/EEG)

Reconstruction

iSDR

Forward problem

Parcella� on[3]

Source network

Source ac� va� ons

Eff ec� ve connec� vity

S 2 S 3 S 1 S 3   Time S 2   Time S 1 Time

T1 Weighted image

diff usion MRI

Tractogram (connec� vity profi le)

FSL

Registra� on

FSL

Brain surfaces extrac� on

FreeSurfer

OpenMEEG

itera�ve Source and Dynamics

Reconstruc�on (iSDR)

S-step

A-step

Ini�aliza�on

0

20

40

60

80

100

%

0

20

40

60

80

100

NR

NR

%

p=1

p=2

p=3

p=4

Fig 1 : Mean and standard deviation of the relative number of active regions

discovered by our method for different MAR orders, compared to MxNE.

The horizontal axis refers to the relative value of the regularization

parameter, while the vertical axis refers to the ratio of the number of

regions recovered by the two methods.

Fig 3 : Effective connectivity between the cortical regions recovered by iSDR

with p=4 from EEG (left) and MEG (right) data, computed as the weighted

average of absolute MAR weights, over subjects and $A_i$'s.