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Thesis topic proposal
 
Balázs Hangya
Neurobiological basis of learning investigated by data analysis, simulation and modeling techniques

THESIS TOPIC PROPOSAL

Institute: Eötvös Loránd University, Budapest
physics
Doctoral School of Physics

Thesis supervisor: Balázs Hangya
Location of studies (in Hungarian): Institute of Experimental Medicine
Abbreviation of location of studies: MTA


Description of the research topic:

A better understanding of the brain function behind cognitive processing is an important challenge for the 21st century. Analyzing and understanding the increasingly available big data is a complex task that requires strong quantitative knowledge. Our goal is to better understand neural mechanisms of cognitive functions such as learning, attention and decision making. We are also investigating pathological conditions focusing on dementia related to Alzheimer's and Parkinson's disease as well as COVID-19 infection. This requires neurophysiological measurements and their analyses with advanced data analysis techniques, including linear statistical and information theory methods, neural modeling and model selection, Bayesian statistics, and the formulation of biophysical models. We plan to publish the results in leading interdisciplinary and neuroscience journals.

Required language skills: English
Number of students who can be accepted: 3

Deadline for application: 2022-05-31


2024. IV. 17.
ODT ülés
Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).

 
All rights reserved © 2007, Hungarian Doctoral Council. Doctoral Council registration number at commissioner for data protection: 02003/0001. Program version: 2.2358 ( 2017. X. 31. )