1. Graphs and the brain: from social network measures to predicting recovery from coma Iulia Maria Comșa Department of Clinical Neurosciences Supervisor: Dr. Srivas Chennu

2. Patient P2: the fine line Traumatic brain injury after a plane crash Induced coma to allow the brain to recover Coma scores No chances of recovery initially given by doctors Went on to fully recover after two months Can we provide a tool that can predict recovery in similar patients? Wijdicks et al. (2005)

3. It’s a small world Stanley Milgram’s experiment (1967) Average chain length? What is the structure of a network where this is possible? 5 persons! Target person Stock broker, Washington Librarian, New York Painter, New York Starting person Secretary, Boston

4. Small-world networks High clustering Short path length

5. Small-world networks The World Wide Web Source: Martin Spernau; TouchGraph LLC The human brain Source: Bullmore & Sporns (2007) Online social networks Source: Wolphram|Alpha

6. Turning the brain into a network The human brain Source: Bullmore & Sporns (2007) By anatomy

7. Turning the brain into a network By anatomy The human brain Source: Bullmore & Sporns (2007)

8. Turning the brain into a network The human brain Source: Bullmore & Sporns (2007) By function

9. Turning the brain into a network By function The human brain Source: Bullmore & Sporns (2007)

10. EEG recordings Electroencephalography (EEG) records electrical activity from the scalp very good temporal resolution comfortable and cost-efficient Source: www.biosemi.com

11. What can we see in the EEG? Preprocessing Removing artifacts: eye blinks, sudden movements Frequency analyses Oscillations

12. EEG oscillations and consciousness Oscillation frequency varies with consciousness wakefulness awareness Dement & Kleitman (1957)

13. Disorders of consciousness Coma no wakefulness or awareness Vegetative state wakefulness but no awareness Minimally conscious state transient signs of awareness

14. Building spectral connectivity networks from EEG data

16. Connectivity networks in chronic disorders of consciousness Lower frequency networks Re-emergence of healthy patterns in the topology of alpha band networks (8 to 13 Hz) Example: two patients with the same coma score (CRS-R) Tennis playing task to assess covert consciousness: No Yes

17. What about P2’s EEG? Auditory processing task P2 could hear and attend to sounds before showing visible improvement in responsiveness. Can we see this in his connectivity networks? How do graph measures evolve in patients recovering from coma?

18. The aim: A better clinical assessment tool EEG-based Non-invasive Real-time Complementary to current assessment tools Giving a voice to patients like P2!

19. Thank you.