etudes de connectivités fonctionnelles et effectives

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Etudes de Connectivités fonctionnelles et effectives. Oury Monchi, Ph.D. Unité de Neuroimagerie Fonctionnelle, Centre de Recherche, Institut Universitaire de Gériatrie de Montréal & Université de Montréal. Les analyses que nous avons étudiées jusqu’à mainteant - PowerPoint PPT Presentation


  • Etudes de Connectivits fonctionnelles et effectives

    Oury Monchi, Ph.D.

    Unit de Neuroimagerie Fonctionnelle, Centre de Recherche, Institut Universitaire de Griatrie de Montral & Universit de Montral

  • Les analyses que nous avons tudies jusqu mainteantnous permettent dvaluer si lactivit dune une ou plusieurs rgions du cerveau augmentent de matire significative dansune condition par rapport ou une autre Durant les travaux pratiques vous avez aussi vu commentreconstruire le signal BOLD pour une rgion et unecondition donne Ceci dit ces anlyses ne nous permettent pas davoir dinformation sur les intractions entre diffrentes rgions du cerveau pendant que lon performe une tche

  • tudes de connectivites Analyses de donnes IRMf 1. Connectivite fonctionnelle 2. Connectivite effectiveB. Fusions multimodales 1. TMS/PET 2. TMS/fMRIC. Imagerie par Tenseur de Diffusion Dr. Thomas Jubault (12 Mars)

  • Structure Function Relationships Functional Segregation

    Where are regional responses to experimental input?Univariate analyses of regionally specific effects

    Functional integrationHow does one region influence another (coupling b/w regions)?How is coupling effected by experimental manipulation (e.g. attention)?Multivariate analyses of regional interactions

  • System analyses in functional neuroimagingFunctional integrationAnalyses of inter-regional effects: what are the interactions between the elements of a given neuronal system?Functional connectivity= the temporal correlation between spatially remote neurophysiological eventsEffective connectivity= the influence that the elements of a neuronal system exert over anotherFunctional specialisationAnalyses of regionally specific effects: which areas constitute a neuronal system?MECHANISM-FREEMECHANISTIC MODEL

  • Aims Summarise patterns of correlations among brain systemsFind those spatio-temporal patterns of activity which explain most of the variance in a series of repeated measurements (e.g. several scans in multiple voxels)

    ProcedureSelect those voxels whose activation levels show a significant difference between the conditions of interestCalculate the covariance matrixPrinciple Component Analysis (PCA) is a Singlular Value Decomposition (SVD) of the covariance matrix. This produces Eigenimages

    Functional Connectivity: The Basics

  • Functional connectivity: methodsSeed-voxel correlation analysesEigenimage analysisPrincipal Components Analysis (PCA)Singular Value Decomposition (SVD)Partial Least Squares (PLS)Independent Component Analysis (ICA)

  • Pros & Cons of functional connectivityPros:useful when we have no model of what caused the data (e.g. sleep, hallucinatons, etc.)Cons:no mechanistic insight into the neural system of interestinappropriate for situations where we have a priori knowledge and experimental control about the system of interestmodels of effective connectivity necessary

  • PPI example: attentional modulation of V1V5Friston et al. 1997, NeuroImage 6:218-229Bchel & Friston 1997, Cereb. Cortex 7:768-778 V1 x Att.=Attention

  • PPI: interpretationTwo possible interpretations of the PPI term:V1Modulation of V1V5 by attentionModulation of the impact of attention on V5 by V1.V1

  • Pros & Cons of PPIsPros:given a single source region, we can test for its context-dependent connectivity across the entire brainCons:very simplistic model: only allows to model contributions from a single area ignores time-series properties of datanot easily used with event-related dataoperates at the level of BOLD time serieslimited causal interpretability in neural terms,more powerful models neededDCM!

  • Functional and Effective Connectivity

  • Models of effective connectivity = system models. But what precisely is a system?System = set of elements which interact in a spatially and temporally specific fashion.System dynamics = change of state vector in timeCausal effects in the system:interactions between elementsexternal inputs uSystem parameters : specify the nature of the interactionsgeneral state equation for non-autonomous systemsoverall system state represented by state variableschange of state vector in timechange of state vector in time

  • Practical steps of a DCM study - IConventional SPM analysis (subject-specific)DCMs are fitted separately for each session consider concatenation of sessions or adequate 2nd level analysisDefinition of the model (on paper!)Structure: which areas, connections and inputs?Which parameters represent my hypothesis?How can I demonstrate the specificity of my results?What are the alternative models to test?Defining criteria for inference:single-subject analysis:stat. threshold? contrast?group analysis:which 2nd-level model?

  • Stimuli 250 radially moving dots at 4.7 degrees/s

    Pre-Scanning 5 x 30s trials with 5 speed changes (reducing to 1%)Task - detect change in radial velocity

    Scanning (no speed changes)6 normal subjects, 4 x 100 scan sessions;each session comprising 10 scans of 4 different conditions

    F A F N F A F N S .................

    F - fixation point onlyA - motion stimuli with attention (detect changes)N - motion stimuli without attentionS - no motionBchel & Friston 1997, Cereb. CortexBchel et al. 1998, BrainV5+PPCV3AAttention No attentionAttention to motion in the visual system

  • MotionPhoticAttention0.880.480.370.720.420.660.560.55Visual inputs drive V1, activity then spreads to hierarchically arranged visual areas. Motion modulates the strength of the V1V5 forward connection.The intrinsic connection V1V5 is insignificant in the absence of motion (a21=-0.05).Attention increases the backward-connections IFGSPC and SPCV5. A simple DCM of the visual system0.26-0.05Re-analysis of data from Friston et al., NeuroImage 2003

  • V1V5SPCMotionPhoticAttention0.850.57-0.021.360.700.840.23MotionPhoticAttention0.860.56-0.021.420.550.750.89MotionPhoticAttention0.850.57-0.021.360.030.700.85Attention0.23Model 1: attentional modulation of V1V5Model 2: attentional modulation of SPCV5Model 3: attentional modulation of V1V5 and SPCV5Comparison of three simple modelsBayesian model selection:Model 1 better than model 2,model 1 and model 3 equal Decision for model 1: in this experiment, attention primarily modulates V1V5

  • Transcranial Magnetic StimulationTMS involves placing an electromagnetic coil on the subject scalp. High-intensity current is rapidly turned on and off in the coil through the discharge of capacitors.

    The current flowing briefly in the coil generates a changing magnetic field that induces an electric current in the neural tissue, in the opposite direction.

  • Stimulators and CoilsSingle-pulse TMSPaired-pulse TMSRepetitive TMS

  • TMS coilTMS and Functional Imaging (PET) [15O] H2O and [11C]raclopride

  • Frameless StereotaxyTMS and PET Precise localization of the TMS coil relative to the brain is critical for the interpretation of brain-mapping studies

    This is best achieved by acquiring a structural MR image of the subjects brain and using the image to guide positioning of the coil in real time.

    The frameless stereotactic system allows to co-register the subject's MRI with the head's surface and in a second step with the location of the TMS coil on the scalp.

  • 3 ms ISI12 ms ISIt3.03.8t3.63.0Z= 61Z= 48Paired-pulse TMS/ [15O] H2O PET Strafella and Paus, J. Neurophysiol. 2001

  • Reductions in [11C]raclopride BP

    Cortical Control of Dopamine releaseStrafella et al., J. Neurosci. 2001TMS and PET [11C] raclopride

  • Strafella et al., Brain 2003

    Reductions in [11C]raclopride BPTMS and PET [11C] racloprideCortical Control of Dopamine release

  • IRMf et TMS offlineContinuous Theta Burst Stimulation (cTBS)80% active motor thresholdSimilar to slow rTMSSuppresses the cortico-excitabilityHuang et al. Neuron 2005 Long lasting after-effect

    20 sec (300 pulses)

    40 sec (600 pulses)

  • IRMf et TMS online

  • Acknowledgements

    SPM DCM courseDrs. Marcus Gray & Petra VetterDrs. Klaas Enno Stephan &Lee Harrison

    Dr. Randy McInstosh, Dr. Barry Hortwitz

    TMS/PETDr. Antonio P. Strafella, Ji-Hyun Ko

    1- Traditional goal of neuroscience is to understand structure-function relationships within brain.- Attempts to define SFRs can be divided into .fs or fi approaches.Segregation: Lesion studies / today typically answers question where.. Addressed by Univariate..Conventional analyses deal with functional segregation, this is where SPM is based on.

    However, shortcoming is that interactions between regions are disregarded. This is addressed in functional integration. Called coupling. Integration: Asks how does..How is

    - PET / fMRI (EEG MEG)

    Aims of FC are to Summarise patterns of correlationsIdentify spatio-temporal patterns most varianceSo we have a number of scans across multiple voxels.

    Procedure1. Select voxels normal SPM analysis test for main effect ..identify voxels2. Calculate Co-Var3. Perform PCA. This is done by..SVD on Co-Var - produces Eigenimages

    Figure 1. Principle of TMS. Left: the current flowing briefly in the coil generates a changing magnetic field that induces an electric current in the tissue, in the opposite direction.