Assessing direct paths of intracortical causal information flow of oscillatory activity with the isolated effective coherence (iCoh)

Functional connectivity is of central importance in understanding brain function. For this purpose, multiple time series of electric cortical activity can be used for assessing the properties of a network: the strength, directionality, and spectral characteristics (i.e., which oscillations are preferentially transmitted) of the connections. The partial directed coherence (PDC) of Baccala and Sameshima (2001) is a widely used method for this problem. The three aims of this study are: (1) To show that the PDC can misrepresent the frequency response under plausible realistic conditions, thus defeating the main purpose for which the measure was developed; (2) To provide a solution to this problem, namely the “isolated effective coherence” (iCoh), which consists of estimating the partial coherence under a multivariate autoregressive model, followed by setting all irrelevant associations to zero, other than the particular directional association of interest; and (3) To show that adequate iCoh estimators can be obtained from non-invasively computed cortical signals based on exact low resolution electromagnetic tomography (eLORETA) applied to scalp EEG recordings. To illustrate the severity of the problem with the PDC, and the solution achieved by the iCoh, three examples are given, based on: (1) Simulated time series with known dynamics; (2) Simulated cortical sources with known dynamics, used for generating EEG recordings, which are then used for estimating (with eLORETA) the source signals for the final connectivity assessment; and (3) EEG recordings in rats. Lastly, real human recordings are analyzed, where the iCoh between six cortical regions of interest are calculated and compared under eyes open and closed conditions, using 61-channel EEG recordings from 109 subjects. During eyes closed, the posterior cingulate sends alpha activity to all other regions. During eyes open, the anterior cingulate sends theta-alpha activity to other frontal regions.

[1]  Dietrich Lehmann,et al.  Reduced functional connectivity between cortical sources in five meditation traditions detected with lagged coherence using EEG tomography , 2012, NeuroImage.

[2]  Wei Liao,et al.  Nonlinear connectivity by Granger causality , 2011, NeuroImage.

[3]  M. Eichler,et al.  Assessing the strength of directed influences among neural signals using renormalized partial directed coherence , 2009, Journal of Neuroscience Methods.

[4]  Valer Jurcak,et al.  10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems , 2007, NeuroImage.

[5]  Juan C. Jiménez,et al.  Modeling the electroencephalogram by means of spatial spline smoothing and temporal autoregression , 1995, Biological Cybernetics.

[6]  S. Bressler,et al.  Frequency decomposition of conditional Granger causality and application to multivariate neural field potential data , 2006, Journal of Neuroscience Methods.

[7]  Helmut Ltkepohl,et al.  New Introduction to Multiple Time Series Analysis , 2007 .

[8]  Thomas E. Nichols,et al.  Nonparametric permutation tests for functional neuroimaging: A primer with examples , 2002, Human brain mapping.

[9]  D Lehmann,et al.  Isolated effective coherence (iCoh): causal information flow excluding indirect paths , 2014 .

[10]  Sebastian Haufe,et al.  The role of alpha-rhythm states in perceptual learning: insights from experiments and computational models , 2014, Front. Comput. Neurosci..

[11]  Edward T. Bullmore,et al.  Volitional eyes opening perturbs brain dynamics and functional connectivity regardless of light input , 2013, NeuroImage.

[12]  Richard M. Leahy,et al.  Electromagnetic brain mapping , 2001, IEEE Signal Process. Mag..

[13]  Roberto D. Pascual-Marqui,et al.  Discrete, 3D distributed, linear imaging methods of electric neuronal activity. Part 1: exact, zero error localization , 2007, 0710.3341.

[14]  H. Helmholtz Ueber einige Gesetze der Vertheilung elektrischer Ströme in körperlichen Leitern mit Anwendung auf die thierisch‐elektrischen Versuche , 1853 .

[15]  Joseph T. Lizier,et al.  Directed Information Measures in Neuroscience , 2014 .

[16]  F. Vollenweider,et al.  Localization of MDMA‐induced brain activity in healthy volunteers using low resolution brain electromagnetic tomography (LORETA) , 2001, Human brain mapping.

[17]  D. Lehmann,et al.  Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. , 1994, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[18]  J Mazziotta,et al.  A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[19]  H. Akaike On the use of a linear model for the identification of feedback systems , 1968 .

[20]  M. Fuchs,et al.  A standardized boundary element method volume conductor model , 2002, Clinical Neurophysiology.

[21]  K. Müller,et al.  Robustly estimating the flow direction of information in complex physical systems. , 2007, Physical review letters.

[22]  Lester Melie-García,et al.  Estimating brain functional connectivity with sparse multivariate autoregression , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[23]  L.A. Baccald,et al.  Generalized Partial Directed Coherence , 2007, 2007 15th International Conference on Digital Signal Processing.

[24]  D. Brillinger Time series - data analysis and theory , 1981, Classics in applied mathematics.

[25]  Katarzyna J. Blinowska,et al.  A new method of the description of the information flow in the brain structures , 1991, Biological Cybernetics.

[26]  J. Geweke,et al.  Measures of Conditional Linear Dependence and Feedback between Time Series , 1984 .

[27]  R D Pascual-Marqui,et al.  Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. , 2002, Methods and findings in experimental and clinical pharmacology.

[28]  J. Pearl Causality: Models, Reasoning and Inference , 2000 .

[29]  G. Knyazev,et al.  The default mode network and EEG alpha oscillations: An independent component analysis , 2011, Brain Research.

[30]  Jeffrey M. Hausdorff,et al.  Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .

[31]  Laura Astolfi,et al.  The physiological plausibility of time-varying Granger-causal modeling: Normalization and weighting by spectral power , 2014, NeuroImage.

[32]  C. Granger Investigating causal relations by econometric models and cross-spectral methods , 1969 .

[33]  R. Blair,et al.  An exact statistical method for comparing topographic maps, with any number of subjects and electrodes , 2005, Brain Topography.

[34]  N. Birbaumer,et al.  BCI2000: a general-purpose brain-computer interface (BCI) system , 2004, IEEE Transactions on Biomedical Engineering.

[35]  L. Faes,et al.  A framework for assessing frequency domain causality in physiological time series with instantaneous effects , 2013, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[36]  Karl J. Friston,et al.  Effective connectivity: Influence, causality and biophysical modeling , 2011, NeuroImage.

[37]  J.C. Mosher,et al.  Multiple dipole modeling and localization from spatio-temporal MEG data , 1992, IEEE Transactions on Biomedical Engineering.

[38]  Dietrich Lehmann,et al.  Coherence and phase locking in the scalp EEG and between LORETA model sources, and microstates as putative mechanisms of brain temporo-spatial functional organization , 2006, Journal of Physiology-Paris.

[39]  Shennan A. Weiss,et al.  Field effects and ictal synchronization: insights from in homine observations , 2013, Front. Hum. Neurosci..

[40]  J.C. Mosher,et al.  Recursive MUSIC: A framework for EEG and MEG source localization , 1998, IEEE Transactions on Biomedical Engineering.

[41]  H. Akaike A new look at the statistical model identification , 1974 .

[42]  Luiz A. Baccalá,et al.  Partial directed coherence: a new concept in neural structure determination , 2001, Biological Cybernetics.

[43]  Thomas E. Nichols Multiple testing corrections, nonparametric methods, and random field theory , 2012, NeuroImage.

[44]  C. Radhakrishna Rao,et al.  A lemma on G-inverse of a matrix and computation of correlation coefficients in the singular case , 1981 .

[45]  Luiz A. Baccalá,et al.  Studying the Interaction Between Brain Structures via Directed Coherence and Granger Causality , 1998 .

[46]  W. Klimesch Alpha-band oscillations, attention, and controlled access to stored information , 2012, Trends in Cognitive Sciences.

[47]  Rolando J. Biscay-Lirio,et al.  Assessing interactions in the brain with exact low-resolution electromagnetic tomography , 2011, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[48]  Karen O. Egiazarian,et al.  Measuring directional coupling between EEG sources , 2008, NeuroImage.

[49]  J L Lancaster,et al.  Automated Talairach Atlas labels for functional brain mapping , 2000, Human brain mapping.