ELFT HÍRADÓ

[Horváth Zsolt Endre <horvath.zsolt.endre AT ek.hun-ren.hu>]

Kedves Kollégák!


2025 március 5-én, szerdán 11 órakor kerül sor a KFKI 26. épület, 1. 
emeleti tanácsteremben
Michelle Cirunay (EK MFA Komplex Rendszerek Labor)



"Modelling connectome structure using avalanched-based models with 
Hebbian learning on hierarchical modular networks"

című előadására.

Abstract:
Brain studies mainly focus on the anatomical wiring of the brain and its 
topological qualities to ascertain the exact relationship between 
anatomical structure and function. In this study, we examine the 
weighted degree distributions of various large connectomes: fruit fly, 
mouse retina, and human connectomes KKI-113 and KKI-18. We find that the 
behavior of the node strength (weighted degree) distribution varies 
according to the scale under consideration. The distributions exhibit 
power-law behavior on a global scale, with an approximately universal 
exponent near 3. However, this tendency deviates at the local level as 
the node strength distributions of the KKI-18 follow a stretched 
exponential, and the fly and mouse retina follow the log-normal 
distribution, respectively,  which are suggestive of underlying random 
multiplicative processes which support non-locality of learning in a 
brain near the critical state. We also attempt to provide analytical and 
numerical explanation on the observed scale-free behavior. Furthermore, 
to gain insight on the dynamics that led to this observed scale-free 
behavior of the global weight distributions of connectomes, we impose an 
avalanche-based model with Hebbian learning over Hierarchical modular 
network (HMN) architecture to simulate the dynamic process of 
reinforcement [weakening] of preferred [unused] pathways.  HMNs recover 
key features of neuronal activity, making them good representative 
baseline structures for modeling cortical activity. Via targeted link 
creation and/or reinforcement for dynamically activated sites in a 
sandpile-like avalanche, and a random weakening and/or pruning during 
stasis times, we recover edge weight distributions that closely resemble 
the empirical connectome edge weight distributions in various neural 
systems.



Minden érdeklődőt szívesen látunk!

Horváth Zsolt Endre
Szeminárium koordinátor

--
Dr. Zsolt E. HORVÁTH
Institute for Technical Physics and Materials Science,
Centre for Energy Research
(EK MFA)
Konkoly Thege Rd. 29-33, 1121 Budapest,
Mail: P.O.Box 49, H-1525 Budapest, Hungary
Phone: +36-1-392-2680, Fax: +36-1-392-2226
e-mail:horvath.zsolt.endre AT ek-cer.hu