CNS*2020 Online has ended
Welcome to the Sched instance for CNS*2020 Online! Please read the instruction document on detailed information on CNS*2020.
Back To Schedule
Sunday, July 19 • 8:00pm - 9:00pm
P221: Visualization of pathways of potential neurostructures in neurorehabilitation period based on MRI data processing

Log in to save this to your schedule, view media, leave feedback and see who's attending!

Feedback form is now closed.
Margarita Zaleshina, Alexander Zaleshin

Poster Link: https://drive.google.com/file/d/11B-s0cmb8kIyTHi9r3LK4IGdsLSl_9bs/view?usp=sharing
Session Link: https://meet.google.com/iki-sgvg-how

Growth, formation and movement of biological structures are determined by characteristics of the environment and requirements for obtaining external resources. Likewise, the topological organization of the brain, consisting of a set of neurostructures, has a direct effect on the brain's ability to perceive or process data. Additionally, localized damage to a small part of the brain will result in specific disturbances of isolated mental facilities, such as perception or movement [1]. Many researchers are currently studying regeneration and formation of a new spatial filling of tissue at the sites of damage. The individual variability of the anatomy and connectivity of the brain affects the formation of its structure [2]. Studies of both tissue features and the distribution and orientation of individual components are widely used to visualize the microstructures of individual brain regions or to determine the locations of biomarkers [3]. At the same time, it can be shown that neurorehabilitation depends not only on the characteristics of the whole brain, but also on the particular features of the distinct area where growth and recovery occur directly.

In this work, we study cases of regeneration of cortical neurostructures, when the damaged area is filled with new elements for a long period of time. The analysis compares the calculated growth directions of neurostructures, the calculated trajectories of their growth, taking into account the existing environment, and the real growth paths identified on the basis of MRI data.

Our study takes into account that the ways of formation of neural structures during neurorehabilitation have two main characteristics that differ in scale and in details. The first characteristic is the average direction of the formation of new neurostructures. Such a direction, as a whole, is caused by an increase in the “favorableness” of the environment in which growth occurs. The second characteristic is a detailed following of external elements in the existing biological environment, that is, on the one hand, rounding obstacles, and on the other hand, the use of convenient “corridors” for growth and advancement (Fig. 1).

Data packages (fMRI) are collected from Human Connectome Project (https://www.humanconnectome.org/data/). These fMRI could be converted to diffusion-weighted images (dMRI), which are used for tractography analysis and for investigate the heterogeneity of microstructural features.

The study uses spatial data analysis, which calculates the main corridors and growth directions, taking into account the available cortical volume filling. Data at the boundaries of tissue are excluded from analysis to minimize the impact of partial volume averaging with surrounding tissues.


1\. Eickhoff SB, Constable RT, Yeo BTT: Topographic organization of the cerebral cortex and brain cartography. Neuroimage 2018, 170: 332–347.

2\. Maier-Hein L, Eisenmann M, Reinke A, Onogur S, Stankovic M, Scholz P, et al: Why rankings of biomedical image analysis competitions should be interpreted with care. Nat. Commun. 2018, 9(1): 5217.

3\. Fick RHJ, Wassermann D, Deriche R: The Dmipy Toolbox: Diffusion MRI Multi- Compartment Modeling and Microstructure Recovery Made Easy. Front. Neuroinform. 2019, 13: 64.

avatar for Margarita Zaleshina

Margarita Zaleshina

Moscow Institute of Physics and Technology

Sunday July 19, 2020 8:00pm - 9:00pm CEST
Slot 09