- Seminars
- Bridging Scales in Neuro-Oncology: Ex Vivo Neuronal Electrophysiology of the Peritumoral Microcircuits as a Prior for Multiscale Brain Models
Bridging Scales in Neuro-Oncology: Ex Vivo Neuronal Electrophysiology of the Peritumoral Microcircuits as a Prior for Multiscale Brain Models
Speaker
Prof. Michele Giugliano - Università di Modena e Reggio Emilia - Unimore
Date
Jul 17, 2026 - Time:
11:00
Sala Verde – Cà Vignal
Abstract
Glioblastoma recurrence is increasingly understood not merely as a consequence of residual tumor mass, but as the outcome of a pathological integration between glioma cells and the surrounding neuronal circuitry. While most predictive frameworks for recurrence rely on macroscale neuroimaging and structural
or functional connectivity derived from MRI, these approaches largely treat the tumor as a passive lesion embedded in an otherwise normal network, without directly probing the cellular and microcircuit-level processes that may drive connectivity disruption at its source.
During this presentation, I will brainstorm about the activities carried out at UNIMORE that might become extremely precious for a a multiscale computational project on glioblastoma recurrence, focusing on the acquisition and electrophysiological characterization of fresh, glioma-infiltrated human cortical tissue obtained from standard-of-care neurosurgical resections. Using patch-clamp recordings and high-density microelectrode arrays, along the lines of what we do for tissue obtained in drug-resistant epilepsy surgery, we plan to quantify the intrinsic excitability, synaptic integration, and functional connectivity of neurons and glioma cells within the peritumoral microenvironment, generating biophysical parameters that are otherwise inaccessible to imaging-based approaches.
I will finally discuss how these cellular- and microcircuit-level measurements might represent empirical priors for biophysically-informed computational models, providing a mechanistic, bottom-up complement to the macroscale connectivity analyses, and how this integration may ultimately support more biologically
grounded predictions of recurrence location and dynamics.
- Data pubblicazione
- Jul 13, 2026
- Department
- Department of Engineering for Innovation Medicine
ATTACHMENTS
- Locandina_17.07.2026
