neuromath final conference of the cost action bm0601

Meditation and brain activity

Klaus B. Bærentsen University of Aarhus, Department of Psychology

NeuroMath Final Conference of the COST Action

BM0601 “Advanced Methods for the Estimation of Human Brain Activity and Connectivity” May 20-21, 2011, ROME, ITALY

Overview

• Meditation as balancing the mind • Theoretical background • FSL Wizard

– MATLAB script – Development process – Program functions – Example results of analyses

• Future ?

2012-01-30 Klaus B. Bærentsen, University of Aarhus, Department of Psychology

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Meditation

• Achieving a balanced state of mind: – ”control of fluctuations of the mind”. – ”still the fluctuations of the mind”. – ”then the mind (the self) abides in itself. Consciousness can abide

in its very nature”. – At other times ”the self (mind, awareness) identifies itself with the

fluctuating patterns of consciousness”. – Patanjali: Yoga Sutras

• Meditation compared to sensori-motor balance (eg skiing, standing, walking, shooting at a target). – Objectively measurable indicator of balance?


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Balance • Investigations of infants learning to sit and walk

– At first uncontrolled variability in posture and movement – Gradual achievement of some stability in posture by constraining degrees

of freedom in limb movements – Later increasing stability in posture by increasing degrees of freedom in

limb movements to compensate for momentary disturbances. • Studies of marksmanship reveal development of synergistic

compensatory limb movements in experts • Measurement of behavioral achievement of stability

– No such measurement in this investigation of meditation – (but see Guo & Pagnoni 2008, Neuroimage).

• Measurement of neural processes – Possible differences between resting and meditating ?


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Theoretical background

• Lundervold’s illustration of the mathematical and scientific roots of emergence etc. – Cyprus Workshop nov. 2009 Nonlinear Biomedical Physics

(2010) 4: supplement – Psychology not mentioned

• Some psychological theories are compatible with dynamical theories in natural sciences – Russian theory of activity and Cultural Historical Psychology – Gibsons Ecological Psychology – Dynamical systems, Synergetics, Complex adaptive systems etc.


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Activity theory An alternative to stimulus-response reflex theory

Subject Stimulus Response

The basic schema of stimulus – response theory:

Stimuli do not ”cause” responses, they may perturb ongoing activity. Ongoing activity usually causes stimulation of sensory organs. (cf Dewey 1896: behaviour is not reflexes, but ”coordinations”)


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Activity theory An alternative to stimulus-response reflex theory

intention

information

experience Subject Activity Object

Execution Modification

Contact Reception

experience

Interpretation of Leont’ev (1974) Soviet Psychology. 13(2):4-33.

Light Sound Smell Touch


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Activity flow of information during interacting with objects in the environment

Interoception (need etc)

metabolism


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Dimensions of mind in activity

• Activity – Motive = need + potentially

need satisfying object

• Action – Goal = intended result of

activity (Sensory parameters of goal state)

• Operation – Form of activity given the

conditions of realisation (external and internal)

Result


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MO ME

Anokhin (1969)

OR: orienting reaction EA: environmental afferentiation ME: memory RF: collaterals of reticular formation AA: activating afferentiation MO: motivation

Functional systems stage 1 Afferent synthesis


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Functional systems stage 2 Execution

MO ME

Anokhin (1969)



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Functional systems stage 3 Achievement or change of goal

MO ME

Anokhin (1969)


Ecological flow/form/time


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Activity theory, cultural historical psychology Functional systems theory

ecological psychology,

Dynamical systems, synergetics, self organisation in complex adaptive systems, etc etc


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Meditation investigated with fMRI

• Goal: Characterisation and visualisation of dynamics of brain activity during: – Meditation.

• On-off • Continuous

– Baseline-resting state. – Fingertapping. – (… and in general).

• Concatenation group analysis with FSL – http://www.fmrib.ox.ac.uk/fsl/

• Assume: Experimental tasks create pertubations of continuously ongoing neural processes (cf. baseline – resting state; default mode).

• Questions: – Extent to which IC’s represent

”Standard” RSN components? – Different temporal

relationsshifts among IC’s during tasks?

– Varying patterns of correlation and causation during tasks?


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Output from ICA with FSL

• Task related sets of individual process components, – anatomical areas in which variations in BOLD signal

follow a common pattern (time series) • during fingertapning, resting, meditation on-off and continuous

meditation.

• ”FSL Wizard” postprocessing utilise: – Thresholded maps of component localisation – IC time series for eigenvector and individual subjects – IC Fourier power spectrum for eigenvector – Realignment parameters for individual subjects

FSL Wizard


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FSL Wizard

• MATLAB script running on Linux

• Control FSL analyses – Selecting designs to

analyse – Selecting scans based on

a number of criteria, eg. • Highres. Anatomical scan

available • Subject also involved in

other tasks etc. 2012-01-30 Klaus B. Bærentsen, University of

Aarhus, Department of Psychology 17

FSL Wizard

• FSL analysis • Postprocessing of IC

information • IC time series

correlation analysis • Anatomical

comparison


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FSL Wizard

• Task list – Queue of analyses to

perform – Keeps track of

performed analyses • Unique time stamp

– Easy to repeat (modified) analyses


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FSL Wizard • FSL Analysis and postprocessing

options (checkboxes) – Anatomical identification of IC’s – Correlation of IC time series with

realignment parameters – Correlation of IC’s (real subjects) – Correlation of IC Eigenvectors – Comparison of IC anatomies

(Dist_3d) – IC time series correlation options

• Phase shifting +/- 1-5 phases (scan) • Travelling window (5 phases- n phases) • Level of significance for correlation • No of phases in epochs (eg 13)

– Change order of IC’s in analysis


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FSL Wizard • Anatomical identification of IC’s

– Local maxima – MNI- Talairach space - Talairach daemon

– Total cluster voxels – Talairach daemon

– Conversion from NiFTI via MNI to Talairach space.

• Anatomical comparison across components across scans

– Change order of IC’s according to a predefined functional ordering

– Minimal distance between local maxima

– Comparison of voxels involved in IC’s


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Anatomical comparison

• Functional ordering and comparison across scans – is important for interpretation of

• IC time series correlation comparison across different scans – Ideally components should be identical ? – Or differences may have functional importance ?

• Comparison to standard RSN network components would be preferable – Beckmann et al (2005); Smith et al. (2009)


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Common RSN components


23 Beckmann et al (2005), Smith et al (2009)

a) Primary visual cortex. c) Auditory and higher order cognitive cortex. Temporal, Thalamus. e) Default mode network: Posterior cingulum, vmPFC,, PTO. g) dlPFC, ACC, right parietal cortex (dorsal visual route).

b) Secundary visual cortex. d) Sensory- motor cortex. f) Executive control: ACC, dlPFC h) dlPFC, ACC, left parietal cortex (dorsal visusl route).

RSN reference IC’s


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a) Primary visual cortex. b) Secondary visual cortex. c) Auditory and higher order cognitive (Temporal, Thalamus). d) Sensory- motor cortex.

e) Default mode network: f) Executive control g) Spatial attention; dlPFC, right parietal. h) Spatial attention; dlPFC, left parietal cortex

Anatomical identification of RSN’s Functional reordering


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RSN Anatomical similarity


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The selection of components (IC’s) representing RSN’s based on visual inspection. In general this leads to acceptable results, but for a few instances Table show relative proportion (%) of overlapping voxels in components, as well as average rank of comparisons (all IC’s compared) Selection of components only on the basis of 1. rank calculated overlap is not viable. Visual inspection, or maybe combination with neuroanatomical infomation is necessary.

Anatomical identification of RSN e


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IC time series correlation

• Realignment • IC time series correlation with realignment parameters. • Assessment of the extent to which IC represent movement artefacts or

psychological factors

• Correlation with experimental designs • Indication for task relevance

• Mutual correlation • 5-phase (17.5 sec.) interval

• Improbable that IC’s should remain in constant pattern of correlation during a complete scan

• Time shifted correlations • Indicator for causal relationships


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Example component time series


29 Bærentsen (2011) Psyke & Logos – accepted.

RSN time series correlation with design Eigenvectors


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Correlations are significant at p<0.001 (uncorrected for multiple comparisons). Continuous meditation df= 275; all other tasks, df=75.

Res

ting

stat

e 1

Res

ting

stat

e 2

Med

itatio

n on

-off

1

Med

itatio

n on

-off

2

Con

tinuo

us

med

itatio

n

Res

ting

stat

e 1+

2

Fing

erta

ppin

g

Med

itatio

n

on

-off

1+2

Regressors Epoch

Continuous

Correlations between components Eigenvectors


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Meditation on-off 1 Meditation on-off 2

Resting state 1 Resting state 2 Continuous meditation

Correlations are significant at p<0.001 (uncorrected for multiple comparisons). Continuous meditation df= 275; all other tasks, df=75.

Correlations between components Real subjects


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Med

i.on-

off 1

Bas

elin

e 1

Med

i.on-

off 2

Con

t.Med

i.

Bas

elin

e 2

a b c d e f g h

Fing

erta

p

Correlations between components Eigenvectors,17. 5 sec. intervals


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Fingertap. Number of 17.5 sec. Intervals with positive correlations between RSN components (p<0.001).

Fingertap. Number of 17.5 sec. Intervals with negative correlations between RSN components (p<0.001).

Correlations between components 17. 5 sec. Intervals


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Continuous meditation


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Participants and support • Experimental participants. • Anne Sophie Jørgensen, Jørgen Høher, Rients Ritskes (meditation teachers). • Colleagues assistants, discussants

– Lektor Hans Stødkilde-Jørgensen (MR Research Center, Aarhus University hospital, Skejby Sygehus).

– Pernille Bruhn, Jakob Erland, Johannes Damsgaard Bruhn, Mark Forsnæs, Anders Chr. Green, Tue Hartmann, Jens Mammen, Cecilie Møller, Bo Sommerlund, Kirstine Sonne Berg, Freya Winther, (PIAU).

– Eva B. Vedel Jensen, Niels Væver Hartvig, Thordis Thorarinsdottir (Department of Statistics).

– Many unmentioned colleagues and students. – COST BM0601 Neuromath

• Økonomisk støtte – Humanistisk forskningsråd (Rococo projektet) – Aarhus Universitets Forskningsfond.

Literature Activity theory, Functional systems, Ecological psychology, Dynamical systems

• Leontyev, A. N. (2009) The Development of Mind. Selected Works of Aleksei Nikolaevich Leontyev. CC-SA (Creative Commons Attribution-Share Alike 3.0) 2009

• Leontyev, A. N. (2009b) Activity, Consciousness and Personality. In: Selected Works of Aleksei Nikolaevich Leontyev. CC-SA (Creative Commons Attribution-Share Alike 3.0) 2009

• Leontyev, A. N. (1977) Activity and Consciousness. CC-SA (Creative Commons Attribution-Share Alike 3.0) 2009 • May be retrieved from: http://www.marxists.org/archive/leontev/

• Anokhin, P. K. (1974) Biology and Neurophysiology of the Conditioned Reflex and its Role in Adaptive Behavior. Pergamon, Oxford etc.

XVIII, 574 p. • Anokhin, P. K. (1969) Cybernetics and the Integrative Activity of the Brain. In: Cole, M. & I. Maltzman (eds.) A Handbook of Contemporary

Soviet Psychology. Basic Books, N. Y. Etc. Pp. 830 - 856. • Alexandrov Yu. I. & M. E. Sams (2005) Emotion and consciousness: Ends of a continuum, Cognitive Brain Research, Vol. 25 (2), Pp. 387-

405. • Bernstein, N. A. (1967) Some Emergent Problems of the Regulation of Motor Acts. In: Bernstein, N. A. The Coordination and Regulation of

Movements. Pergamon Press. Oxford etc. 1967. pp 114-142.

• Turvey, M.T. & C. Carello (1986): The Ecological Approach to Perceiving-Acting: A Pictorial Essay. Acta Psychologica 63:133-155. • Gibson, J. J. (1966): The Senses Considered as Perceptual Systems. Boston. Houghton Mifflin. • Gibson, J. J.: The Ecological Approach to Visual Perception. Hillsdale, N. J. Lawrence Erlbaum, 1986.

• Tschacher W. & H. Haken (2007) Intentionality in non-equilibrium systems? The functional aspects of self-organized pattern formation. New

Ideas in Psychology, Vol. 25(1), p. 1-15. • Edelman, G. M. & G. Tononi (2000): A Universe of Consciousness. How Matter becomes Imagination. Basic Books, New York. (222 p). • Freeman, W. J. (2000): How Brains Make up their Minds. Columbia University Press, N. Y. (157 p).

2012-01-30 Klaus B. Bærentsen, University of

Aarhus, Department of Psychology 36

http://www.marxists.org/archive/leontev/�

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