Oscillations and effective connectivity in human corticothalamic networks

Transcription

1 Oscillations and effective connectivity in human corticothalamic networks Mario Rosanova, MD, PhD Department of clinical sciences «Luigi Sacco» University of Milan, Milan, Italy

2 -Characterize EEG oscillations triggered by TMS in healthy, awake subjects -Measuring cortical effective connectivity in different models of unconsciousness

3 -Characterize EEG oscillations triggered by TMS in healthy, awake subjects -Measuring cortical effective connectivity in different models of unconsciousness

4 -Characterize EEG oscillations triggered by TMS in healthy, awake subjects -Measuring cortical effective connectivity in different models of unconsciousness

5 Bedside assessment of consciousness by evaluating the patient s ability to interact with the external environment

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7 Vegetative State: the patient recovers sleep/wake cycles, yet there is no functional communication with the external world

8 Minimally Conscious State: the patient shows inconsistent signs of interaction with the external world, yet no functional communication

9 Locked-In Syndrome: the patient is fully conscious, yet her/he cannot functionally communicate due to lesions of the motor pathways

10 INTRACORTICAL COMMUNICATION Dehaene and Changeux Tononi and Koch Alkire

11 INTRACORTICAL COMMUNICATION Dynamical Causal Modelling

12 INTRACORTICAL COMMUNICATION EEG 2 EEG 3 TMS/EEG and Source modeling EEG 1 EEG 4 EEG 5

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14 Wakefulness Sleep TMS TMS Massimini et al., Science 2005

15 Wakefulness Sleep TMS Massimini et al., Science 2005

16 Wakefulness Sleep Massimini et al., Science 2005

17 Massimini et al., Cogn. Neurosci, 2010

18 Ferrarelli et al., PNAS 2009 Wakefulness Anaesthesia (Midazolam)

19 At the patient s bedside Transcranial Magnetic Stimulation combined with EEG and source modelling in non-communicating brain-injured patients: Vegetative State (VS) and Minimally Conscious State (MCS) Locked-In Syndrome (LIS)

20 Vegetative State (vigilance without awareness)

21 EEG Trace recorded at the electrode under he stimulator TMS Rosanova, Gosseries et al., Brain 2012

22 GMFP calculated over the 60 EEG channels Significance Threshold p<0.01 (Bootstrap) TMS 4 sources 10 sources 10 sources 7 sources 31 sources Source Modelling was computed by means of Minimum Norm Estimate (MNE)

23 31 sources

24 TMS Rosanova, Gosseries et al., Brain 2012

25 Rosanova, Gosseries et al., Brain 2012

26 TMS Rosanova, Gosseries et al., Brain 2012

27 Rosanova, Gosseries et al., Brain 2012

28 TMS Rosanova, Gosseries et al., Brain 2012

29 Awake, unconscious Awake, minimal signs of consciousness Awake, fully conscious Rosanova et al., sumbitted Rosanova, Gosseries et al., Brain 2012

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31 Longitudinal measurements in acute patients Rosanova, Gosseries et al., Brain 2012

32 Rosanova, Gosseries et al., Brain 2012

33 Rosanova, Gosseries et al., Brain 2012

34 Longitudinal measurements in the three patients who recovered consciousness Rosanova, Gosseries et al., Brain 2012

35 Longitudinal measurements in the two patients who did not recover consciousness Rosanova, Gosseries et al., Brain 2012

36 Effective connectivity values for all patients in sessions where left parietal cortex was stimulated Rosanova, Gosseries et al., Brain 2012

37 Effective connectivity values for all patients and in all sessions (also right parietal and frontal areas) Rosanova, Gosseries et al., Brain 2012

38 Perturbational Complexity non-parametric statistics at the source level TMS t 1

39 Perturbational Complexity non-parametric statistics at the source level TMS t 1 t 2

40 Perturbational Complexity non-parametric statistics at the source level TMS t 1 t 2 t 3

41 Perturbational Complexity non-parametric statistics at the source level TMS t 1 t 2 t 3 t

42 Perturbational Complexity non-parametric statistics at the source level TMS t 1 t 2 t 3 t binary matrix of significant activation sources time

43 Perturbational Complexity non-parametric statistics at the source level TMS t 1 t 2 t 3 t binary matrix of significant activation sources time BITS (Lempel-Ziv-Welch Complexity)

44 Perturbational Complexity

45 Perturbational Complexity

46 Perturbational Complexity Casali et al., in preparation

47 Perturbational Complexity Casali et al., in preparation

48 Shah and Schiff, Eur J Neurosci 2010

49 Thanks! MILAN: Silvia Casarotto Andrea Pigorini Adenauer Casali Matteo Fecchio Simone Sarasso Marcello Massimini MADISON: Fabio Ferrarelli Michael Murphy Michael Peterson Brady Riedner Giulio Tononi LIEGE: Melanie Boly Olivia Grosserie Marie-Aurelie Bruno Pierre Boveroux Steven Laureys Fundings: EU-grant PredictAD STSM COST 2009 Pur 2009 (Univ Milan) Prin 2008 (Italian Gov)