Abstract

Speaker: Dr Giorgia Baron, Department of Information Engineering, University of Padova, Italy.

Title: Revealing the Spatial Pattern of Brain Hemodynamic Sensitivity to Healthy Aging through Sparse Dynamic Causal Model.

Abstract: Age-related changes in the BOLD response could reflect neurovascular coupling modifications rather than simply impairments in neural functioning. In this study, we propose the use of a sparse dynamic causal model (sDCM) to decouple neuronal and vascular factors in the BOLD signal, with the aim of characterizing the whole-brain spatial pattern of hemodynamic sensitivity to healthy aging, as well as to test the role of hemodynamic features as independent predictors in an age-classification model. sDCM was applied to the resting-state functional magnetic resonance imaging data of a cohort of 126 healthy individuals in a wide age range (31 females), providing reliable estimates of the hemodynamic response function (HRF) for each subject and each region of interest. Then, some features characterizing each HRF curve were extracted and used to fit a multivariate logistic regression model predicting the age class of each individual. Ultimately, we tested the final predictive model on an independent dataset of 338 healthy subjects (173 females) selected from the Human Connectome Project in Aging and Development cohorts. Our results entail the spatial heterogeneity of the age effects on the hemodynamic component, since its impact resulted to be strongly region- and population-specific, discouraging any space-invariant–corrective procedures that attempt to correct for vascular factors when carrying out functional studies involving groups with different ages. Moreover, we demonstrated that a strong interaction exists between certain right-hemisphere hemodynamic features and age, further supporting the essential role of the hemodynamic factor as an independent predictor of biological ageing rather than a simple confounding variable.

See the published paper here: https://doi.org/10.1523/JNEUROSCI.1940-23.2024

Bio: Giorgia Baron earned her master’s degree in Bioengineering in September 2020 from the University of Padua. Her master’s thesis focused on applying a sparse Dynamic Causal Modeling (DCM) algorithm to analyze stroke-induced alterations in whole-brain directed connectivity using resting-state functional magnetic resonance imaging (fMRI) data, which earned her an award from the National Group of Bioengineering in 2021. She later pursued a Ph.D. in Information Engineering, specializing in Bioengineering, at the University of Padua, focusing on the intricate mechanisms of human brain function through dynamic causal modeling of resting-state fMRI data. Currently, as a post-doctoral researcher at the Neuropsychology Laboratory of IRCCS San Camillo, she investigates neuroimaging data from patients with stroke, Parkinson’s disease, and mild cognitive impairment (MCI) to better understand their cognitive correlations.

Venue: MRC CBU West Wing Seminar Room and Zoom https://us02web.zoom.us/j/82385113580?pwd=RmxIUmphQW9Ud1JBby9nTDQzR0NRdz09 (Meeting ID: 823 8511 3580; Passcode: 299077)