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120. Alterations in Dynamic Spontaneous Network Microstates in Mild Traumatic Brain Injury: A MEG Beamformed Dynamic Connectivity Analysis

Author

Antonakakis, Marios, Dimitriadis, Stavros I., Zervakis, Michalis, Papanicolaou, Andrew C., and Zouridakis, George

Subjects
Complexity index, Combinatorics, Degree (graph theory), Traumatic brain injury, medicine, Graph (abstract data type), Beta (finance), medicine.disease, Transition rate matrix, Default mode network, Mathematics, Dynamic functional connectivity
Abstract

Dynamic functional connectivity (DFC) analysis has attracted interest in the last years for the characterization of brain electrophysiological activity at rest. In this work, we investigated changes in mild Traumatic Brain Injury (mTBI) patients using magnetoencephalographic (MEG) resting-state recordings and a DFC approach. The activity of several well-known brain rhythms was first beamformed using linearly constrained minimum norm variance of the MEG data to determine ninety anatomical brain regions of interest. A DFC graph was formulated using the imaginary part of phase lag value which were obtained from 30 mTBI patients and 50 normal controls. Filtering each quasi-static graph statistically and topologically, we estimated a normalized Laplacian transformation of every single quasistatic graph based on the degree of each node. Then, the related eigenvalues of the synchronization of each node were computed by incorporating the complete topology. Using the neural-gas algorithm, we modelled the evolution of the eigenvalues for each group, resulting in distinct FC microstates (FCμstates). Using the so-called chronnectomics (transition rate, occupancy time of FCμstate, and Dwell time) and complexity index over the evolution of the FCμstates, we evaluated the level of discrimination and derived statistical differences between the two groups. In both groups, we detected equal number of FCμstates with statistically significant transitions in the δ, α, β, and γlow frequency bands. The discrimination rate between the two groups was very high in the θ and γlow bands, followed by a statistically significant difference between the two groups in all the chronnectomics and the complexity index. Statistically significant differences in the degree of several anatomical subnetworks (BAN – brain anatomical networks: default mode network; frontoparietal; occipital; cingulo-opercular; and sensorimotor) were revealed in most FCμstates for the θ, α, β, and γlow brain rhythms, indicating a higher level of communication within and between the BAN in the mTBI group. In our previous studies, we focused on intra- and inter-frequency couplings of static FC. Our current study summarizes a complete set of frequency-dependent connectomic markers of mTBI-caused alterations in brain connectivity that potentially could also serve as markers to assess the return of an injured subject back to normality.

Published
2019

124. Computational aspects of finite element modeling in EEG source localization

Author

Awada, Kassem A., Jackson, David R., Williams, Jeffrey T., Wilton, Donald R., Baumann, Stephen B., and Papanicolaou, Andrew C.

Subjects
Electroencephalography -- Research, Finite element method -- Usage, Magnetic resonance imaging -- Research, Biological sciences, Business, Computers, Health care industry
Abstract

A comparison is made of two different implementations of the finite element method (FEM) for calculating the potential due to dipole sources in electroencephalography (EEG). In one formulation (the direct method) the total potential is the unknown that is solved for and the dipole source is directly incorporated into the model. In the second formulation (the subtraction method) the unknown is the difference between the total potential and the potential due to the same dipole in an infinite region of homogeneous conductivity, corresponding to the region where the dipole is located. Both methods have the same FEM system matrix. However, the subtraction method requires an additional calculation of flux integrations along the edges of the elements in the computation of the right-hand side (RHS) vector. It is shown that the subtraction method is usually more accurate in the forward modeling, provided the flux integrations are computed accurately. Errors in calculating the flux integrations may result in large errors in the forward solution due to the ill-conditioned nature of the FEM system matrix caused by the Neumann boundary condition. To minimize the errors, closed-form expressions for the flux integrations are used for both linear and quadratic triangular elements. It is also found that FEM forward modeling errors may cause false extrema in the least-square objective function obtained from the boundary potential, near boundaries between media of differing conductivity. Multiple initial guesses help eliminate the possibility of the solution getting trapped in these false extrema. Index Terms - electroencephalography, finite element method, inverse problems, imaging, numerical methods.

Published
1997

137. Contributors

Author

Aboitiz, Francisco, primary, Basile, Luis F.H., additional, Frank Benson, D., additional, Blomert, Leo, additional, Cappa, Stefano F., additional, Caramelli, Paulo, additional, Cardebat, Dominique, additional, Chantraine, Yves, additional, Cherrier, Monique M., additional, Chevalier, Hélène, additional, Cohen, Henri, additional, Cohe, Laurent, additional, Corina, David, additional, Crosson, Bruce, additional, Cummings, Jeffrey L., additional, Dehaene, Stanislas, additional, Démonet, Jean-François, additional, Denes, Gianfranco, additional, Dronkers, Nina F., additional, Eviatar, Zohar, additional, Fields, Julie A., additional, Gahl, Brigitta, additional, Gainotti, Guido, additional, Gandour, Jackson T., additional, Goodglass, Harold, additional, Hagoort, Peter, additional, Happé, Francesca, additional, Harris, Anthony E., additional, Hellige, Joseph B., additional, Hild, Manfred, additional, Hiscock, Merrill, additional, Andrés, Ide, additional, Gonia, Jarema, additional, Joanette, Yves, additional, Katz, Richard C., additional, Kinsbourne, Marcel, additional, Kolk, Herman, additional, Lacher, Sieglinde, additional, Lecours, André-Roch, additional, Mansur, Leticia Lessa, additional, Ludy, Carl A., additional, Luu, Phan, additional, MacWhinney, Brian, additional, Martin, Nadine, additional, McDonald, Skye, additional, Mendez, Mario F., additional, Molfese, Dennis L., additional, Nadeau, Stephen E., additional, Neils-Strunjaš, Jean, additional, Nitrini, Ricardo, additional, Pachana, Nancy A., additional, Papanicolaou, Andrew C., additional, Paradis, Michel, additional, Poncelet, Martine, additional, Roth, Volkbert M., additional, Sarkari, Shirin, additional, Segalowitz, Sidney J., additional, Seymou, Philip H.K., additional, Simos, Panagiotis G., additional, Simard, Martine, additional, Small, Steven L., additional, Stemmer, Brigitte, additional, Tan, Arlene A., additional, Tracy, Joseph I., additional, Tröster, Alexander I., additional, Tucker, Don M., additional, Van der Linden, Martial, additional, Van Lancker, Diana, additional, Westbury, Chris, additional, Whitaker Professor, Harry A., additional, Willmes, Klaus, additional, and Zaidel, Eran, additional

Published
1998
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141. Localization of auditory response sources using magnetoencephalography and magnetic resonance imaging

Author

Papanicolaou, Andrew C., Baumann, Stephen, Rogers, Robert L., Saydjari, Christy, Amparo, Eugenio G., and Eisenberg, Howard M.

Subjects
Magnetoencephalography -- Usage, Evoked potentials (Electrophysiology) -- Evaluation, Magnetic resonance imaging -- Usage, Brain -- Localization of functions, Health
Abstract

Brain activity may be observed noninvasively using magnetoencephalography (MEG), which measures the magnetic fields outside the head generated by the brain activity within. However, the magnetic fields may be altered by factors unrelated to brain activity, such as the size and shape of the patient's head. In order to determine if physical variations may reduce the validity of information obtained from MEG, the technique was used to identify the sources of auditory responses in eight normal subjects. Both same-side and opposite-side responses to sound were examined, and they were found to be located in slightly different places for each patient. The important feature of the data is that the localizations were similar for each patient, suggesting that the influence of variations is small, and that MEG may serve as a useful adjunct to other procedures for localizing brain function. (Consumer Summary produced by Reliance Medical Information, Inc.)

Published
1990

148. A functional analysis approach to the static replication of European options.

Author

Bossu, Sébastien, Carr, Peter, and Papanicolaou, Andrew

Subjects
FUNCTIONAL analysis, OPTIONS (Finance), INTEGRAL equations, CHARACTERISTIC functions, DERIVATIVE securities, CAPITAL assets pricing model
Abstract

The replication of any European contingent claim by a static portfolio of calls and puts with strikes forming a continuum, formally proven by Carr and Madan [Towards a theory of volatility trading. In Volatility: New Estimation Techniques for Pricing Derivatives, edited by R.A. Jarrow, Vol. 29, pp. 417–427, 1998 (Risk books)], is part of the more general theory of integral equations. We use spectral decomposition techniques to show that exact payoff replication may be achieved with a discrete portfolio of special options. We discuss applications for fast pricing of vanilla options that may be suitable for large option books or high frequency option trading, and for model pricing when the characteristic function of the underlying asset price is known. [ABSTRACT FROM AUTHOR]

Published
2021
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