Thesis Project Form
Title (tentative): From biological to digital twin: a pipeline for electrical stimulation of human derived neuronal networks| Thesis advisor(s): Frega Monica | E-mail: |
| Address: | Phone: (+39) 010 33 52144 |
Description
Motivation and application domain
Electrical stimulation is an emergent strategy for modulating pathological neuronal network activity. However, understanding which is its cellular target is still a challenge.
Computational models can help linking cellular properties to dynamics, and thus can be used to understand the effect of stimulation on neuronal properties. However, comutational models integrating stimulation and neuronal networks are not present in literature.
Computational models can help linking cellular properties to dynamics, and thus can be used to understand the effect of stimulation on neuronal properties. However, comutational models integrating stimulation and neuronal networks are not present in literature.
General objectives and main activities
The goal is to develop a computational pipeline in which neurons and electrical stimulation are integrated. This will enable to model how neurons or neuronal networks elctrically respond to stimuli.
The activities involve: analysis of activity of neuronal networks plated on Micro electrode arrays derived from healthy subjects and patietns hiPSCs; analysis of the effect of electrical stimulation on the activity of unhealthy neuronal networks; development of computational pipeline which integrates neurons with morphology, geometry of MEA, electrical stimulation, neuronal activation and signal propagation.
The activities involve: analysis of activity of neuronal networks plated on Micro electrode arrays derived from healthy subjects and patietns hiPSCs; analysis of the effect of electrical stimulation on the activity of unhealthy neuronal networks; development of computational pipeline which integrates neurons with morphology, geometry of MEA, electrical stimulation, neuronal activation and signal propagation.
Training Objectives (technical/analytical tools, experimental methodologies)
Data analsysis in vitro
Computational modelling with Neuron
Computational modelling with Neuron
Place(s) where the thesis work will be carried out: Neuroengineering group (DIBRIS)
Additional information
Pre-requisite abilities/skills: Knowledge of MATLAB or Python for data analysis; familiarity with electrophysiology and neuronal network concepts; background in bioengineering, biomedical engineering, or neuroscience.
Maximum number of students: 1
Financial support/scholarship: NO