Cognitive Neurodynamics

, Volume 10, Issue 2, pp 99–111 | Cite as

Children with well controlled epilepsy possess different spatio-temporal patterns of causal network connectivity during a visual working memory task

  • Foteini Protopapa
  • Constantinos I. Siettos
  • Ivan Myatchin
  • Lieven Lagae
Research Article

Abstract

Using spectral Granger causality (GC) we identified distinct spatio-temporal causal connectivity (CC) patterns in groups of control and epileptic children during the execution of a one-back matching visual discrimination working memory task. Differences between control and epileptic groups were determined for both GO and NOGO conditions. The analysis was performed on a set of 19-channel EEG cortical activity signals. We show that for the GO task, the highest brain activity in terms of the density of the CC networks is observed in α band for the control group while for the epileptic group the CC network seems disrupted as reflected by the small number of connections. For the NOGO task, the denser CC network was observed in θ band for the control group while widespread differences between the control and the epileptic group were located bilaterally at the left temporal-midline and parietal areas. In order to test the discriminative power of our analysis, we performed a pattern analysis approach based on fuzzy classification techniques. The performance of the classification scheme was evaluated using permutation tests. The analysis demonstrated that, on average, 87.6 % of the subjects were correctly classified in control and epileptic. Thus, our findings may provide a helpful insight on the mechanisms pertaining to the cognitive response of children with well controlled epilepsy and could potentially serve as “functional” biomarkers for early diagnosis.

Keywords

Working memory Epilepsy Children Spectral Granger causality Causal connectivity networks EEG Classification Early diagnosis 

References

  1. Alloway TP, Gathercole SE, Pickering SJ (2006) Verbal and visuospatial short-term and working memory in children: are they separable? Child Development 77(6):1698–1716. doi:10.1111/j.1467-8624.2006.00968.x CrossRefPubMedGoogle Scholar
  2. Astolfi L, Cincotti F, Mattia D, Marciani MG, Baccala LA, Fallani FD, Salinari S, Ursino M, Zavaglia M, Ding L, Edgar JC, Miller GA, He B, Babiloni F (2007) Comparison of different cortical connectivity estimators for high-resolution EEG recordings. Hum Brain Mapp 28:143–157. doi:10.1109/IEMBS.2005.1615463 CrossRefPubMedGoogle Scholar
  3. Bano S, Yadav SN, Chaudhary V, Garga UC (2011) Neuroimaging in epilepsy. J Pediatr Neurosci 6(1):19–26. doi:10.4103/1817-1745.84401 PubMedPubMedCentralGoogle Scholar
  4. Barnett L, Seth AK (2011) Behaviour of Granger causality under filtering: theoretical invariance and practical application. J Neurosci Methods 201(2):404–419. doi:10.1016/j.jneumeth.2011.08.010 CrossRefPubMedGoogle Scholar
  5. Barrett AB, Murphy M, Bruno MA, Noirhomme Q, Boly M, Laureys S, Seth AK (2012) Granger causality analysis of steady-state electroencephalographic signals during propofol-induced anaesthesia. PLoS One. doi:10.1371/journal.pone.0029072 Google Scholar
  6. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: A practical and powerful approach to multiple testing. J R Stat Soc Ser B (Methodol) 57(1):289–300. doi:10.2307/2346101 Google Scholar
  7. Bledowski C, Kaiser J, Wibral M, Yildiz-Erzberger K, Rahm B (2012) Separable neural bases for subprocesses of recognition in working memory. Cereb Cortex 22(8):1950–1958. doi:10.1093/cercor/bhr276 CrossRefPubMedGoogle Scholar
  8. Blinowska K, Kuś R, Kamiński M (2004) Granger causality and information flow in multivariate processes. Phys Rev E 70:050902. doi:10.3389/fncom.2014.00061 CrossRefGoogle Scholar
  9. Bollimunta A, Chen Y, Schroeder CE, Ding M (2008) Neuronal mechanisms of cortical alpha oscillations in awake-behaving macaques. J Neurosci Off J Soc Neurosci 28(40):9976–9988. doi:10.1523/JNEUROSCI.2699-08.2008 CrossRefGoogle Scholar
  10. Brovelli A, Ding M, Ledberg A, Chen Y, Nakamura R, Bressler SL (2004) Beta oscillations in a large-scale sensorimotor cortical network: directional influences revealed by Granger causality. Proc Natl Acad Sci USA 101(26):9849–9854. doi:10.1073/pnas.0308538101 CrossRefPubMedPubMedCentralGoogle Scholar
  11. Campo P, Maestu F, Garcia-Morales I, Gil-Nagel A, Strange B, Morales M et al (2009) Modulation of medial temporal lobe activity in epilepsy patients with hippocampal sclerosis during verbal working memory. J Int Neuropsychol Soc 15:536–546. doi:10.1093/cercor/bhr201 CrossRefPubMedGoogle Scholar
  12. Chaix Y, Laguitton V, Lauwers-Cancès V, Daquin G, Cancès C, Démonet JF et al (2006) Reading abilities and cognitive functions of children with epilepsy: influence of epileptic syndrome. Brain Dev 28(2):122–130. doi:10.1016/j.braindev.2005.06.004 CrossRefPubMedGoogle Scholar
  13. Clemens B, Puskás S, Besenyei M, Spisák T, Emri M, Fekete I (2013) Remission of benign epilepsy with rolandic spikes: an EEG-based connectivity study at the onset of the disease and at remission. Epilepsy Res 106(1–2):128–135. doi:10.1016/j.eplepsyres.2013.04.006 CrossRefPubMedGoogle Scholar
  14. Clemens B, Puskás S, Besenyei M, Kovács NZ, Spisák T, Kis SA, Emri M, Hollódy K, Fogarasi A, Kondákor I, Fekete I (2014) Valproate treatment normalizes EEG functional connectivity in successfully treated idiopathic generalized epilepsy patients. Epilepsy Res 108(10):1896–1903CrossRefPubMedGoogle Scholar
  15. Colon AJ, Ossenblok P, Nieuwenhuis L, Stam KJ, Boon P (2009) Use of routine MEG in the primary diagnostic process of epilepsy. J Clin Neurophysiol Off Publ Am Electroencephalograph Soc 26(5):326–332. doi:10.1097/WNP.0b013e3181baabef Google Scholar
  16. Cross JH (2011) Epilepsy in the WHO European region: fostering epilepsy care in Europe. Epilepsia 52(1):187–188. doi:10.1111/j.1528-1167.2010.02903.x CrossRefPubMedGoogle Scholar
  17. Dale AM, Liu AK, Fischl BR, Buckner RL, Belliveau JW, Lewine JD, Halgren E (2000) Dynamic statistical parametric mapping. Neuron 26:55–67. doi:10.1016/S0896-6273(00)81138-1 CrossRefPubMedGoogle Scholar
  18. Dauwels J, Dauwels J, Vialatte F, Vialatte F, Musha T, Musha T, Cichocki A (2010) A comparative study of synchrony measures for the early diagnosis of Alzheimer’s disease based on EEG. NeuroImage 49(1):668–693. doi:10.1016/j.neuroimage.2009.06.056 CrossRefPubMedGoogle Scholar
  19. Dean RB, Dixon WJ (1951) Simplified statistics for small numbers of observations. Anal Chem 23(4):636–638. doi:10.1021/ac60052a025 CrossRefGoogle Scholar
  20. Dhamala M, Rangarajan G, Ding M (2008) Analyzing information flow in brain networks with nonparametric Granger causality. NeuroImage 41(2):354–362. doi:10.1016/j.neuroimage.2008.02.020 CrossRefPubMedPubMedCentralGoogle Scholar
  21. Dimitriadis SI, Laskaris NA, Micheloyannis S (2015) Transition dynamics of EEG-based network microstates during mental arithmetic and resting wakefulness reflects task-related modulations and developmental changes. Cogn Neurodyn 9(4):371–387. doi:10.1007/s11571-015-9330-8 CrossRefPubMedGoogle Scholar
  22. Ding M, Chen Y, Bressler SL (2006) Granger causality: basic theory and application to neuroscience. In Handbook of time series analysis. pp 451–474. 10.1002/9783527609970.ch17
  23. Follett PL, Vora N, Cross JH (2012) Paediatric intractable epilepsy syndromes: changing concepts in diagnosis and management. Child Neurology 39:45–60. doi:10.1007/978-3-7091-1360-8_2 Google Scholar
  24. Friston KJ (2011) Functional and effective connectivity: a review. Brain Connect 1(1):13–36. doi:10.1089/brain.2011.0008 CrossRefPubMedGoogle Scholar
  25. Gathercole SE, Pickering SJ, Knight C, Stegmann Z (2004) Working memory skills and educational attainment: evidence from national curriculum assessments at 7 and 14 years of age. Appl Cogn Psychol 18(1):1–16. doi:10.1002/acp.934 CrossRefGoogle Scholar
  26. Gathercole SE, Alloway TP, Kirkwood HJ, Elliott JG, Holmes J, Hilton KA (2008) Attentional and executive function behaviours of children with poor working memory. Learn Individ Differ 18:214–223. doi:10.1016/j.lindif.2007.10.003 CrossRefGoogle Scholar
  27. Goodin DS, Aminoff MJ, Laxer KD (1990) Detection of epileptiform activity by different noninvasive EEG methods in complex partial epilepsy. Annals Neurol 27(3):330–334. doi:10.1002/ana.410270317 CrossRefGoogle Scholar
  28. Gotman J, Grova C, Bagshaw A, Kobayashi E, Aghakhani Y, Dubeau F (2005) Generalized epileptic discharges show thalamocortical activation and suspension of the default state of the brain. Proc Natl Acad Sci USA 102(42):15236–15240. doi:10.1073/pnas.0504935102 CrossRefPubMedPubMedCentralGoogle Scholar
  29. Grouiller F, Thornton RC, Groening K, Spinelli L, Duncan JS, Schaller K, Vulliemoz S (2011) With or without spikes: localization of focal epileptic activity by simultaneous electroencephalography and functional magnetic resonance imaging. Brain 134(10):2867–2886. doi:10.1093/brain/awr156 CrossRefPubMedPubMedCentralGoogle Scholar
  30. Guerrini R (2006) Epilepsy in children. Lancet 367(9509):499–524. doi:10.1016/s0140-6736(06)68182-8 CrossRefPubMedGoogle Scholar
  31. Gülgönen S, Demirbilek V, Korkmaz B, Dervent A, Townes BD (2000) Neuropsychological functions in idiopathic occipital lobe epilepsy. Epilepsia 41:405–411. doi:10.1111/j.1528-1157.2000.tb00181.x CrossRefPubMedGoogle Scholar
  32. Henriksen O (1990) Education and epilepsy: assessment and remediation. Epilepsia 31–4(4):S21–S25. doi:10.1111/j.1528-1157.1990.tb05865.x CrossRefGoogle Scholar
  33. Hernandez MT, Sauerwein HC, Jambaque I, de Guise E, Lussier F, Lortie A, Lassonde M (2003) Attention, memory, and behavioral adjustment in children with frontal lobe epilepsy. Epilepsy Behav 4(5):522–536. doi:10.1016/j.yebeh.2003.07.014 CrossRefPubMedGoogle Scholar
  34. Hongou K, Konishi T, Naganuma Y, Murakami M, Yamatani M, Okada T (1993) Development of the background activity of EEG in children with epilepsy; comparison with normal children. No To Hattatsu 25(3):207–214PubMedGoogle Scholar
  35. Hu S, Liang H (2012) Causality analysis of neural connectivity: new tool and limitations of spectral Granger causality. Neurocomputing 76(1):44–47. doi:10.1016/j.neucom.2010.10.017 CrossRefGoogle Scholar
  36. Hu S, Cao Y, Zhang J (2012) More discussions for granger causality and new causality measures. Cogn Neurodyn 6(1):33. doi:10.1007/s11571-011-9175-8 CrossRefPubMedPubMedCentralGoogle Scholar
  37. Jambaqué I, Dellatolas G, Dulac O, Ponsot G, Signoret JL (1993) Verbal and visual memory impairment in children with epilepsy. Neuropsychologia 31(12):1321–1337. doi:10.1016/0028-3932(93)90101-5 CrossRefPubMedGoogle Scholar
  38. Jan MMS, Sadler M, Rahey SR (2001) Lateralized postictal EEG delta predicts the side of seizure surgery in temporal lobe epilepsy. Epilepsia 42(3):402–405. doi:10.1046/j.1528-1157.2001.45999.x CrossRefPubMedGoogle Scholar
  39. Jiruska P, de Curtis M, Jefferys JGR, Schevon CA, Schiff SJ, Schindler K (2013) Synchronization and desynchronization in epilepsy: controversies and hypotheses. The Journal of Physiology 591(4):787–797. doi:10.1113/jphysiol.2012.239590 CrossRefPubMedPubMedCentralGoogle Scholar
  40. Kaminski M, Blinowska M (2014) Directed Transfer Function is not influenced by volume conduction—inexpedient pre-processing should be avoided. Front Comput Neurosci 8:61. doi:10.3389/fncom.2014.00061 CrossRefPubMedPubMedCentralGoogle Scholar
  41. Keil A, Sabatinelli D, Ding M, Lang PJ, Ihssen N, Heim S (2009) Re-entrant projections modulate visual cortex in affective perception: evidence from Granger causality analysis. Hum Brain Mapp 30:532–540. doi:10.1002/hbm.20521 CrossRefPubMedPubMedCentralGoogle Scholar
  42. Keller JM, Gray MR, Givens JA Jr (1985) A fuzzy k-nearest neighbor algorithm. IEEE Trans Syst Man Cybern 15(4):580–585. doi:10.1109/TSMC.1985.6313426 CrossRefGoogle Scholar
  43. Killory BD, Bai X, Negishi M, Vega C, Spann MN, Vestal M, Blumenfeld H (2011) Impaired attention and network connectivity in childhood absence epilepsy. NeuroImage 56(4):2209–2217. doi:10.1016/j.neuroimage.2011.03.036 CrossRefPubMedPubMedCentralGoogle Scholar
  44. Kitzbichler MG, Henson RNA, Smith ML, Nathan PJ, Bullmore ET (2011) Cognitive effort drives workspace configuration of human brain functional networks. J Neurosci 31:8259–8270. doi:10.1523/JNEUROSCI.0440-11.2011 CrossRefPubMedGoogle Scholar
  45. Klimesch W (1999) EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Res Rev 29(2–3):169–195. doi:10.1016/S0165-0173(98)00056-3 CrossRefPubMedGoogle Scholar
  46. Klimesch W, Schack B, Schabus M, Doppelmayr M, Gruber W, Sauseng P (2004) Phase-locked alpha and theta oscillations generate the P1-N1 complex and are related to memory performance. Cogn Brain Res 19(3):302–316. doi:10.1016/j.cogbrainres.2003.11.016 CrossRefGoogle Scholar
  47. Krause CM, Boman PA, Sillanmäki L, Varho T, Holopainen IE (2008) Brain oscillatory EEG event-related desynchronization (ERD) and -sychronization (ERS) responses during an auditory memory task are altered in children with epilepsy. Seizure 17(1):1–10. doi:10.1016/j.seizure.2007.05.015 CrossRefPubMedGoogle Scholar
  48. Kuzniecky R, Palmer C, Hugg J, Martin R, Sawrie S, Morawetz R, Knowlton R (2001) Magnetic resonance spectroscopic imaging in temporal lobe epilepsy: neuronal dysfunction or cell loss? Arch Neurol 58(12):2048–2053. doi:10.1001/archneur.58.12.2048 CrossRefPubMedGoogle Scholar
  49. Kwiatkowski D, Phillips PCB, Schmidt P, Shin Y (1992) Testing the null hypothesis of stationarity against the alternative of a unit root. J Econom 54:159–178. doi:10.1016/0304-4076(92)90104-Y CrossRefGoogle Scholar
  50. Lagae L (2006) Cognitive side effects of anti-epileptic drugs. The relevance in childhood epilepsy. Seizure 15:235–241. doi:10.1016/j.seizure.2006.02.013 CrossRefPubMedGoogle Scholar
  51. Luton LM, Burns TG, DeFilippis N (2010) Frontal lobe epilepsy in children and adolescents: a preliminary neuropsychological assessment of executive function. Arch Clin Neuropsychol 25(8):762–770. doi:10.1093/arclin/acq066 CrossRefPubMedGoogle Scholar
  52. Maris E, Oostenveld R (2007) Nonparametric statistical testing of EEG- and MEG-data. J Neurosci Methods 164(1):177–190. doi:10.1016/j.jneumeth.2007.03.024 CrossRefPubMedGoogle Scholar
  53. Marzetti L, Di Lanzo C, Zappasodi F, Chella F, Raffone A, Pizzella V (2014) Magnetoencephalographic alpha band connectivity reveals differential default mode network interactions during focused attention and open monitoring meditation. Front Hum Neurosci 8:832. doi:10.3389/fnhum.2014.00832 CrossRefPubMedPubMedCentralGoogle Scholar
  54. McCarthy AM, Richman LC, Yarbrough D (1995) Memory, attention, and school problems in children with seizure disorders. Dev Neuropsychol 11(1):71–86. doi:10.1080/87565649509540604 CrossRefGoogle Scholar
  55. Mirsky AF, Duncan CC, Levav M, Bures J, Kopin I, McEwen B, Weiskranz L (2001) Neuropsychological studies in idiopathic generalized epilepsy. In: Jambaque O, Lassonde I, Dulac M (eds) Neuropsychology of childhood epilepsy, vol 50. Kluwer Academic, New York, pp 141–150. doi:10.1007/0-306-47612-6_15 CrossRefGoogle Scholar
  56. Müller V, Anokhin AP (2012) Neural synchrony during response production and inhibition. PLoS ONE. doi:10.1371/journal.pone.0038931 Google Scholar
  57. Myatchin I, Lagae L (2011) Impaired spatial working memory in children with well-controlled epilepsy: an event-related potentials study. Seizure. J Br Epilepsy Assoc 20(2):143–150. doi:10.1016/j.seizure.2010.11.005 CrossRefGoogle Scholar
  58. Myatchin I, Mennes M, Wouters H, Stiers P, Lagae L (2009) Working memory in children with epilepsy: an event-related potentials study. Epilepsy Res 86(2–3):183–190. doi:10.1016/j.eplepsyres.2009.06.004 CrossRefPubMedGoogle Scholar
  59. Nicolaou N, Hourris S, Alexandrou P, Georgiou J (2012) EEG-based automatic classification of “awake” versus “anesthetized” state in general anesthesia using granger causality. PLoS One. doi:10.1371/journal.pone.0033869 Google Scholar
  60. Oostenveld R, Fries P, Maris E, Schoffelen JM (2011) FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput Intell Neurosci. doi:10.1155/2011/156869 Google Scholar
  61. Palva S, Palva JM (2012) Discovering oscillatory interaction networks with M/EEG: challenges and breakthroughs. Trends Cogn Sci 16:219–230. doi:10.1016/j.tics.2012.02.004 CrossRefPubMedGoogle Scholar
  62. Palva JM, Monto S, Kulashekhar S, Palva S (2010) Neuronal synchrony reveals working memory networks and predicts individual memory capacity. Proc Natl Acad Sci USA 107(16):7580–7585. doi:10.1073/pnas.0913113107 CrossRefPubMedPubMedCentralGoogle Scholar
  63. Pavlou E, Gkampeta A (2011) Learning disorders in children with epilepsy. Child’s Nerv Syst ChNS Off J Intl Soc Pediatr Neurosurg 27(3):373–379. doi:10.1007/s00381-010-1321-9 CrossRefGoogle Scholar
  64. Ponjavic-Conte KD, Dowdall JR, Hambrook DA, Luczak A, Tata MS (2012) Neural correlates of auditory distraction revealed in theta-band EEG. NeuroReport 23(4):240–245. doi:10.1097/WNR.0b013e3283505ac6 CrossRefPubMedGoogle Scholar
  65. Protopapa F, Siettos CI, Evdokimidis I, Smyrnis N (2014) Granger causality analysis reveals distinct spatio-temporal connectivity patterns in motor and perceptual visuo-spatial working memory. Front Comput Neurosci 8:146. doi:10.3389/fncom.2014.00146 CrossRefPubMedPubMedCentralGoogle Scholar
  66. Ruff CC, Knauff M, Fangmeier T, Spreer J (2003) Reasoning and working memory: common and distinct neuronal processes. Neuropsychologia 41(9):1241–1253. doi:10.1016/S0028-3932(03)00016-2 CrossRefPubMedGoogle Scholar
  67. Sargolzaei S, Cabrerizo M, Goryawala M, Eddin AS, Adjouadi M (2015a) Scalp EEG brain functional connectivity networks in pediatric epilepsy. Comput Biol Med 56:158–166. doi:10.1016/j.compbiomed.2014.10.018 CrossRefPubMedGoogle Scholar
  68. Sargolzaei S, Cabrerizo M, Sargolzaei A, Noei S, Eddin A, Rajaei H, Pinzon-Ardila A, Gonzalez-Arias SM, Jayakar P, Adjouadi M (2015b) A probabilistic approach for pediatric epilepsy diagnosis using brain functional connectivity networks. BMC Bioinform 7:s9. doi:10.1186/1471-2105-16-S7-S9 CrossRefGoogle Scholar
  69. Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6(2):461–464. doi:10.1214/aos/1176344136 CrossRefGoogle Scholar
  70. Seth AK (2008) Causal networks in simulated neural systems. Cogn Neurodyn 2(1):49. doi:10.1007/s11571-007-9031-z CrossRefPubMedPubMedCentralGoogle Scholar
  71. Seth AK (2010) A MATLAB toolbox for Granger causal connectivity analysis. J Neurosci Methods 186:262–273. doi:10.1016/j.jneumeth.2009.11.020 CrossRefPubMedGoogle Scholar
  72. Seth AK, Barrett AB, Barnett L (2015) Granger causality analysis in neuroscience and neuroimaging. J Neurosci 35(8):3293–3297. doi:10.1523/JNEUROSCI.4399-14.2015 CrossRefPubMedPubMedCentralGoogle Scholar
  73. Shibata T, Shimoyama I, Ito T, Abla D, Iwasa H, Koseki K, Nakajima Y (1998) The synchronization between brain areas under motor inhibition process in humans estimated by event-related EEG coherence. Neurosci Res 31(4):265–271. doi:10.1016/S0168-0102(98)00046-7 CrossRefPubMedGoogle Scholar
  74. Smith SJM (2005) EEG in the diagnosis, classification, and management of patients with epilepsy. J Neurol Neurosurg Psychiatry 76–2(2):2–7. doi:10.1136/jnnp.2005.069245 Google Scholar
  75. Smith SM, Vidaurre D, Beckmann CF, Glasser MF, Jenkinson M, Miller KL, Nichols TE, Robinson EC, Salimi-Khorshidi G, Woolrich MW, Barch DM, Uğurbil K, Van Essen DC (2013) Functional connectomics from resting-state fMRI. Trends Cogn Sci 17:666–682. doi:10.1016/j.tics.2013.09.016 CrossRefPubMedPubMedCentralGoogle Scholar
  76. Stam CJ, Nolte G, Daffertshofer A (2007) Phase lag index: assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources. Hum Brain Mapp 28:1178–1193. doi:10.1002/hbm.20346 CrossRefPubMedGoogle Scholar
  77. Stores G (1978) School-children with epilepsy at risk for learning and behaviour problems. Dev Med Child Neurol 20(4):502–508. doi:10.1111/j.1469-8749.1978.tb15256.x CrossRefPubMedGoogle Scholar
  78. Swanson HL (2006) Cross-sectional and incremental changes in working memory and mathematical problem solving. J Educ Psychol 98(2):265–281. doi:10.1037/0022-0663.98.2.265 CrossRefGoogle Scholar
  79. Toth J, Lewis C (1997) The role of working memory and external representation in individual decision making. AAAI technical report: 109–115. http://www.aaai.org/Papers/Symposia/Fall/1997/FS-97-03/FS97-03-014.pdf
  80. Van Diessen E, Otte WM, Braun KPJ, Stam CJ, Jansen FE (2013) Improved diagnosis in children with partial epilepsy using a multivariable prediction model based on EEG network characteristics. PLoS One. doi:10.1371/journal.pone.0059764 PubMedPubMedCentralGoogle Scholar
  81. Wagner DD, Sziklas V, Garver KE, Jones-Gotman M (2009) Material-specific lateralization of working memory in the medial temporal lobe. Neuropsychologia 47:112–122. doi:10.1016/j.neuropsychologia.2008.08.010 CrossRefPubMedGoogle Scholar
  82. Wei HL, An J, Zeng LL, Shen H, Qiu SJ, Hu DW (2015) Altered functional connectivity among default, attention, and control networks in idiopathic generalized epilepsy. Epilepsy Behav 46:118–125. doi:10.1016/j.yebeh.2015.03.031 CrossRefPubMedGoogle Scholar
  83. Wen X, Rangarajan G, Ding M (2013) Multivariate Granger causality: an estimation framework based on factorization of the spectral density matrix. Philos Trans Ser A Math Phys Eng Sci 371(1997):20110610. doi:10.1098/rsta.2011.0610 CrossRefGoogle Scholar
  84. Williams J (2003) Learning and behavior in children with epilepsy. Epilepsy Behav 4(2):107–111. doi:10.1016/S1525-5050(03)00024-6 CrossRefPubMedGoogle Scholar
  85. Wu MH, Frye RE, Zouridakis G (2011) A comparison of multivariate causality based measures of effective connectivity. Comput Biol Med 41(12):1132–1141. doi:10.1016/j.compbiomed.2011.06.007 CrossRefPubMedGoogle Scholar
  86. Yang L, Worrell GA, Nelson C, Brinkmann B, He B (2012) Spectral and spatial shifts of post-ictal slow waves in temporal lobe seizures. Brain 135(10):3134–3143. doi:10.1093/brain/aws221 CrossRefPubMedPubMedCentralGoogle Scholar
  87. Zeng LL, Shen H, Liu L, Wang L, Li B, Fang P et al (2012) Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis. Brain 135:1498–1507. doi:10.1093/brain/aws059 CrossRefPubMedGoogle Scholar
  88. Zeng LL, Wang D, Fox MD, Sabuncu M, Hu D, Ge M, Buckner RL, Liu H (2014) Neurobiological basis of head motion in brain imaging. Proc Natl Acad Sci USA 111(16):6058–6062. doi:10.1073/pnas.1317424111 CrossRefPubMedPubMedCentralGoogle Scholar
  89. Zhang X, Lei X, Wu T (2013) A review of EEG and MEG for brainnetome research. Cogn Neurodyn 8(2):87–98. doi:10.1007/s11571-013-9274-9 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Foteini Protopapa
    • 1
  • Constantinos I. Siettos
    • 1
  • Ivan Myatchin
    • 2
  • Lieven Lagae
    • 2
  1. 1.School of Applied Mathematics and Physical SciencesNational Technical University of AthensAthensGreece
  2. 2.Department of Woman and Child, Section Paediatric NeurologyK.U. LeuvenLouvainBelgium

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