Workshop on Brain Analysis using COnnectivity Networks


17th October 2016 - Athenaeum CCI

Satellite event of MICCAI 2016

BACON 2016 is the first international workshop on Brain Analysis using COnnectivity Networks offered on the 17th of October 2016 (AM), in Athens, Greece.



Understanding brain connectivity in a network-theoretic context has shown much promise in recent years. This type of analysis identifies brain organisational principles, bringing a new perspective to neuroscience. At the same time, large public databases of connectomic data are now available. However, connectome analysis is still an emerging field and there is a crucial need for robust computational methods to fully unravel its potential. This workshop provides a platform to discuss the development of new analytic techniques; methods for evaluating and validating commonly used approaches; as well as the effects of variations in pre-processing steps.


The academic objective of the workshop is to bring together researchers in medical imaging and neuroscience to discuss the challenges and development of new techniques in brain connectivity analysis (connectomics), as well as their benefits for clinical applications. MICCAI-BACON 2016 will feature two keynote speakers with a focus on both application and methodology, technical paper presentations, poster sessions and demonstrations of state-of-the art techniques and concepts that can be applied in connectomics.


Topics of interest include, but are not limited to:

  • Data processing for network construction (e.g. fMRI preprocessing, brain parcellation/cortical segmentation, quantifying anatomical/functional/effective connectivity, spatio/temporal models)
  • Multimodal processing (e.g. Building joint networks, multimodal parcellation, modelling the interaction between modalities, manifold alignment for connectivity networks )
  • Network-based classification and biomarker identification
  • Analysis for disease detection
  • Longitudinal analysis (developing/ageing connectome)
  • Evaluation/model validation (e.g. Constructing synthetic data, quantitative evaluation measures)
  • Visualisation

Contact: bacon.miccai (at)