General overview for brain connectivity analysis

1. Brain Connectivity Analysis
Andrés Quintero Zea

2. Pipeline

3. Overview
• The use of graph analysis in neuroscience has become essential to
quantify brain dysfunctions in terms of aberrant reconfiguration of
brain networks.
• Despite its evident impact, graph analysis of brain networks is not a
simple toolbox that can be blindly applied to brain signals:
• It requires the know-how of all the methodological steps of the pipeline that
manipulate the input brain signals and extract the network properties.
• Knowledge of the neural phenomenon under study is required to perform
physiologically relevant analysis.

4. Brain Nodes
Voxel-based Sensor-based
Spatial Scale
Spatial filters
Source
reconstructions
Sensor-based
Connectivity
measures
The definition of the nodes for brain
graphs is modality-specific.
Spatial Scale
Single voxels
Voxel
aggregates
Hybrid
Voxel-based
Prior anatomical
knowledge
data-driven
approach

5. Links
Link
definition
Data-driven Model-based
Functional Effective

6. Threshold
Graph
filtering
Fix a thresholdStatistical Topological

7. Metrics

8. Classification
Classification
Statistical
model
Machine
learning

9. Challenges
• Brain graph filtering
• Statistical variability of brain graphs
• Spatio-temporal brain graphs