Von Interaktionen zu Interaktionsnetzwerken: Zeitabhängige funktionelle Netzwerke am Beispiel der Epilepsie

Zusammenfassung

Das menschliche Gehirn ist ein komplexes Netzwerk aus interagierenden nichtstationären Subsystemen (Netzwerk von Netzwerken), deren komplizierte räumlich-zeitliche Dynamiken bis heute nur unzureichend verstanden sind. Dabei versprechen aktuelle Entwicklungen im Bereich der Zeitreihenanalyse sowie der Theorie komplexer Netzwerke neue und verbesserte Einblicke in die Dynamiken von Hirnnetzwerken auf verschiedenen räumlich-zeitlichen Skalen. Wir geben einen Überblick über diese Entwicklungen und besprechen am Beispiel zeitabhängiger epileptischer Hirnnetzwerke Fortschritte im Verständnis von Hirndynamiken, die über multiple Skalen hinweg variieren.

Abstract

The human brain is a complex network of interacting non-stationary subsystems (network of networks), and its complicated spatio-temporal dynamics remain poorly understood. Recent developments in the field of time-series analysis and complex network theory promise new and improved insights into the dynamics of brain networks on various spatio-temporal scales. We review these developments and, with the help of evolving epileptic brain networks as an example, discuss recent advances in understanding brain dynamics that vary on multiple scales.

Schlüsselwörter

EEG - Epilepsie - Zeitabhängige Hirnnetzwerke - Zeitreihenanalyse - Hirndynamik - Netzwerktheorie - Netzwerkerkrankung - Interaktionen

Key words

EEG - epilepsy - evolving brain networks - time series analysis - brain dynamics - network theory - network disease - interactions

Publication History

Article published online:
29 September 2020

• Literatur

• 1 Hutcheon B, Yarom Y. Resonance, oscillation and the intrinsic frequency preferences of neurons. Trends Neurosci 2000; 23: 216-222
• 2 Salinas E, Sejnowski TJ. Correlated neuronal activity and the flow of neural information. Nat Rev Neurosci 2001; 2: 539-550
• 3 Makeig S, Debener S, Onton J. et al. Mining event-related brain dynamics. Trends Cogn Sci 2004; 8: 204-210
• 4 Bressler SL, Menon V. Large-scale brain networks in cognition: emerging methods and principles. Trends Cogn Sci 2010; 14: 277-290
• 5 Fell J, Axmacher N. The role of phase synchronization in memory processes. Nat Rev Neurosci 2011; 12: 105-118
• 6 Siegel M, Donner TH, Engel AK. Spectral fingerprints of large-scale neuronal interactions. Nat Rev Neurosci 2012; 13: 121-134
• 7 Engel AK, Gerloff C, Hilgetag CC. et al. Intrinsic coupling modes: Multiscale interactions in ongoing brain activity. Neuron 2013; 80: 867-886
• 8 Lee HW, Arora J, Papademetris X. et al. Altered functional connectivity in seizure onset zones revealed by fMRI intrinsic connectivity. Neurology 2014; 83: 2269-2277
• 9 Uhlhaas PJ, Singer W. Neural synchrony in brain disorders: relevance for cognitive dysfunctions and pathophysiology. Neuron 2006; 52: 155-168
• 10 Engel AK, Moll CKE, Fried I. et al. Invasive recordings from the human brain: clinical insights and beyond. Nat Rev Neurosci 2005; 6: 35-47
• 11 Niediek J, Boström J, Elger CE. et al. Reliable analysis of single-unit recordings from the human brain under noisy conditions: tracking neurons over hours. PLoS One 2016; 11: e0166598
• 12 Marom S. Neural timescales or lack thereof. Prog Neurobiol 2010; 90: 16-28
• 13 He BJ. Scale-free brain activity: past, present, and future. Trends Cogn Sci 2014; 18: 480-487
• 14 Breakspear M. Dynamic models of large-scale brain activity. Nat Neurosci 2017; 20: 340
• 15 Schreiber T, Schmitz A. Surrogate time series. Physica D 2000; 142: 346-382
• 16 Andrzejak RG, Lehnertz K, Mormann F. et al. Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state. Phys Rev E 2001; 64: 61907
• 17 Andrzejak RG, Mormann F, Widmann G. et al. Improved spatial characterization of the epileptic brain by focusing on nonlinearity. Epilepsy Res 2006; 69: 30-44
• 18 Rizzi M, Weissberg I, Milikovsky DZ. et al. Following a potential epileptogenic insult, prolonged high rates of nonlinear dynamical regimes of intermittency type is the hallmark of epileptogenesis. Sci Rep 2016; 6: 31129
• 19 Robertson LC. Binding, spatial attention and perceptual awareness. Nat Rev Neurosci 2003; 4: 93-102
• 20 Pikovsky AS, Rosenblum MG, Kurths J. Synchronization: A universal concept in nonlinear sciences. Cambridge, UK: Cambridge University Press; 2001
• 21 Pritchard WS, Duke DW. Measuring chaos in the brain - a tutorial review of EEG dimension estimation. Brain Cogn 1995; 27: 353-397
• 22 Di Ieva A, Grizzi F, Jelinek H. et al. Fractals in the neurosciences, part I: general principles and basic neurosciences. Neuroscientist 2014; 20: 403-417
• 23 Di Ieva A, Esteban FJ, Grizzi F. et al. Fractals in the neurosciences, part II: clinical applications and future perspectives. Neuroscientist 2015; 21: 30-43
• 24 Dikanev T, Smirnov D, Wennberg R. et al. EEG nonstationarity during intracranially recorded seizures: statistical and dynamical analysis. Clin Neurophysiol 2005; 116: 1796-1807
• 25 Martini M, Kranz TA, Wagner T. et al. Inferring directional interactions from transient signals with symbolic transfer entropy. Phys Rev E 2011; 83: 11919
• 26 Friston KJ. Functional and effective connectivity: a review. Brain Connect 2011; 1: 13-36
• 27 Pereda E, Quian Quiroga R, Bhattacharya J. Nonlinear multivariate analysis of neurophysiological signals. Prog Neurobiol 2005; 77: 1-37
• 28 Lehnertz K, Dickten H. Assessing directionality and strength of coupling through symbolic analysis: an application to epilepsy patients. Phil Trans R Soc A 2015; 373: 20140094
• 29 Porz S, Kiel M, Lehnertz K. Can spurious indications for phase synchronization due to superimposed signals be avoided?. Chaos 2014; 24: 33112
• 30 Colclough GL, Woolrich MW, Tewarie PK. et al. How reliable are MEG resting-state connectivity metrics?. Neuroimage 2016; 138: 284-293
• 31 Bullmore E, Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 2009; 10: 186-198
• 32 Reijneveld JC, Ponten SC, Berendse HW. et al. The application of graph theoretical analysis to complex networks in the brain. Clin Neurophysiol 2007; 118: 2317-2331
• 33 Rubinov M, Sporns O. Complex network measures of brain connectivity: Uses and interpretations. Neuroimage 2010; 52: 1059-1069
• 34 Papo D, Zanin M, Martinez JH. et al. Beware of the small-world neuroscientist!. Front Hum Neurosci 2016; 10: 96
• 35 Bröhl T, Lehnertz K. Centrality-based identification of important edges in complex networks. Chaos 2019; 29: 33115
• 36 Stahn K, Lehnertz K. Surrogate-assisted identification of influences of network construction on evolving weighted functional networks. Chaos 2017; 27: 123106
• 37 Ansmann G, Lehnertz K. Surrogate-assisted analysis of weighted functional brain networks. J Neurosci Methods 2012; 208: 165-172
• 38 Cook MJ, O’Brien TJ, Berkovic SF. et al. Prediction of seizure likelihood with a long-term, implanted seizure advisory system in patients with drug-resistant epilepsy: a first-in-man study. Lancet Neurol 2013; 12: 563-571
• 39 Berg AT, Scheffer IE. New concepts in classification of the epilepsies: Entering the 21^st century. Epilepsia 2011; 52: 1058-1062
• 40 van Mierlo P, Papadopoulou M, Carrette E. et al. Functional brain connectivity from EEG in epilepsy: Seizure prediction and epileptogenic focus localization. Prog Neurobiol 2014; 121: 19-35
• 41 Lehnertz K, Ansmann G, Bialonski S. et al. Evolving networks in the human epileptic brain. Physica D 2014; 267: 7-15
• 42 Horstmann M-T, Bialonski S, Noennig N. et al. State dependent properties of epileptic brain networks: Comparative graph-theoretical analyses of simultaneously recorded EEG and MEG. Clin Neurophysiol 2010; 121: 172-185
• 43 Lehnertz K, Dickten H, Porz S. et al. Predictability of uncontrollable multifocal seizures – towards new treatment options. Sci Rep 2016; 6: 24584
• 44 Kini LG, Bernabei JM, Mikhail F. et al. Virtual resection predicts surgical outcome for drug-resistant epilepsy. Brain 2019; 142: 3892-3905
• 45 Kuhnert M-T, Elger CE, Lehnertz K. Long-term variability of global statistical properties of epileptic brain networks. Chaos 2010; 20: 43126
• 46 Rings T, von Wrede R, Lehnertz K. Precursors of seizures due to specific spatial-temporal modifications of evolving large-scale epileptic brain networks. Sci Rep 2019; 9: 10623
• 47 Geier C, Lehnertz K, Bialonski S. Time-dependent degree-degree correlations in epileptic brain networks: from assortative to dissortative mixing. Front Hum Neurosci 2015; 9: 462
• 48 Rings T, Mazarei M, Akhshi A. et al. Traceability and dynamical resistance of precursor of extreme events. Sci Rep 2019; 9: 1744