SUPR
Deep learning analysis of anatomical brain connectivity in Alzheimer's disease and Ageing
Dnr:

NAISS 2024/22-1154

Type:

NAISS Small Compute

Principal Investigator:

Blanca Zufiria

Affiliation:

Karolinska Institutet

Start Date:

2024-09-09

End Date:

2025-09-01

Primary Classification:

30105: Neurosciences

Webpage:

Allocation

Abstract

The aims of this project are the following: 1. Identify the anatomical brain connections that show changes in cognitively normal individiuals. 2. Determine if these changes are comparable or overlap with some of the ones affected in the clinical stages of AD. 3. Establish whether some of the connectivity alterations already occur in the preclinical stages of AD. 4. Identify the mechanisms underlying these changes in brain connectivity both in health and disease. As the operations involved in developing graph neural networks in Tensorflow are computationally intensive, we need a robust server to effectively support our analysis. Additionally, since we are working with medical images that take up more space than other types of data used in conventional machine learning algorithms, having an additional storage resource would be highly beneficial. Finally, the data xthat would be used is properly anonymized.