Detection of EEG-resting state independent networks by eLORETA-ICA method

Yasunori Aoki, Ryouhei Ishii, Roberto D Pascual-Marqui, Leonides Canuet, Shunichiro Ikeda, Masahiro Hata, Kaoru Imajo, Haruyasu Matsuzaki, Toshimitsu Musha, Takashi Asada, Masao Iwase, Masatoshi Takeda, Yasunori Aoki, Ryouhei Ishii, Roberto D Pascual-Marqui, Leonides Canuet, Shunichiro Ikeda, Masahiro Hata, Kaoru Imajo, Haruyasu Matsuzaki, Toshimitsu Musha, Takashi Asada, Masao Iwase, Masatoshi Takeda

Abstract

Recent functional magnetic resonance imaging (fMRI) studies have shown that functional networks can be extracted even from resting state data, the so called "Resting State independent Networks" (RS-independent-Ns) by applying independent component analysis (ICA). However, compared to fMRI, electroencephalography (EEG) and magnetoencephalography (MEG) have much higher temporal resolution and provide a direct estimation of cortical activity. To date, MEG studies have applied ICA for separate frequency bands only, disregarding cross-frequency couplings. In this study, we aimed to detect EEG-RS-independent-Ns and their interactions in all frequency bands. We applied exact low resolution brain electromagnetic tomography-ICA (eLORETA-ICA) to resting-state EEG data in 80 healthy subjects using five frequency bands (delta, theta, alpha, beta and gamma band) and found five RS-independent-Ns in alpha, beta and gamma frequency bands. Next, taking into account previous neuroimaging findings, five RS-independent-Ns were identified: (1) the visual network in alpha frequency band, (2) dual-process of visual perception network, characterized by a negative correlation between the right ventral visual pathway (VVP) in alpha and beta frequency bands and left posterior dorsal visual pathway (DVP) in alpha frequency band, (3) self-referential processing network, characterized by a negative correlation between the medial prefrontal cortex (mPFC) in beta frequency band and right temporoparietal junction (TPJ) in alpha frequency band, (4) dual-process of memory perception network, functionally related to a negative correlation between the left VVP and the precuneus in alpha frequency band; and (5) sensorimotor network in beta and gamma frequency bands. We selected eLORETA-ICA which has many advantages over the other network visualization methods and overall findings indicate that eLORETA-ICA with EEG data can identify five RS-independent-Ns in their intrinsic frequency bands, and correct correlations within RS-independent-Ns.

Keywords: EEG; ICA; LORETA; eLORETA-ICA; independent component analysis; resting state network.

Figures

Figure 1
Figure 1
eLORETA-ICA component 4 (IC4). IC4 corresponds to the occipital visual network in alpha frequency band. In the color–coded maps, red and blue colors represent power increase and decrease with increasing IC coefficient, respectively.
Figure 2
Figure 2
eLORETA-ICA component 5 (IC5). Left IC5 regions (the left posterior occipito-parietal cortex, caudal intraparietal sulcus (caudal IPS) and middle temporal + (MT+)) corresponds to left posterior dorsal visual pathway (DVP). Right IC5 regions (the right occipitotemporal cortex, temporoparietal junction (TPJ), parahippocampal gyrus, fusiform gyrus and ventral prefrontal cortex (vPFC)) corresponds to right ventral visual pathway (VVP). The right VVP links right occipitotemporal cortex in alpha frequency band to the right vPFC in beta frequency band. The left posterior DVP correlates negatively with the areas of the right VVP.
Figure 3
Figure 3
eLORETA-ICA component 6 (IC6). IC6 is formed by the medial PFC (mPFC) in beta frequency band and the right TPJ in alpha frequency band, which shows negative correlation.
Figure 4
Figure 4
eLORETA-ICA component 9 (IC9). IC9 comprises the precuneus in alpha frequency band and the left VVP in alpha frequency band, which shows negative correlation.
Figure 5
Figure 5
eLORETA-ICA component 10 (IC10). IC10 comprises the medial postcentral regions (Brodmann area 5 and 7) in beta frequency band and the pre supplementary motor area (pre-SMA) in gamma frequency band, which shows positive correlation.
Figure 6
Figure 6
eLORETA-ICA component 1, 2, 3, 7, 8 and 11 in above written frequency bands. These components correspond to artifacts of electromyogram or baseline shifts, based on spatial distributions of power and frequency ranges.

References

    1. Agcaoglu O., Miller R., Mayer A. R., Hugdahl K., Calhoun V. D. (2014). Lateralization of resting state networks and relationship to age and gender. Neuroimage 104, 310–325. 10.1016/j.neuroimage.2014.09.001
    1. Allen E. A., Erhardt E. B., Damaraju E., Gruner W., Segall J. M., Silva R. F., et al. . (2011). A baseline for the multivariate comparison of resting-state networks. Front. Syst. Neurosci. 5:2. 10.3389/fnsys.2011.00002
    1. Angel L., Bastin C., Genon S., Balteau E., Phillips C., Luxen A., et al. . (2013). Differential effects of aging on the neural correlates of recollection and familiarity. Cortex 49, 1585–1597. 10.1016/j.cortex.2012.10.002
    1. Aoki Y., Ishii R., Iwase M., Ikeda S., Hata M., Canuet L., et al. . (2013a). Normalized power variance change between pre-ictal and ictal phase of an epilepsy patient using NAT analysis: a case study. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2013, 437–440. 10.1109/embc.2013.6609530
    1. Aoki Y., Kazui H., Tanaka T., Ishii R., Wada T., Ikeda S., et al. . (2013b). EEG and neuronal activity topography analysis can predict effectiveness of shunt operation in idiopathic normal pressure hydrocephalus patients. Neuroimage Clin. 19, 522–530. 10.1016/j.nicl.2013.10.009
    1. Arnal L. H., Wyart V., Giraud A. L. (2011). Transitions in neural oscillations reflect prediction errors generated in audiovisual speech. Nat. Neurosci. 14, 797–801. 10.1038/nn.2810
    1. Baddeley A. D., Hitch G. (1974). Working memory. Psychol. Learn. Motiv. 8, 47–89.
    1. Bartlett M. S. (1954). A note on the multiplying factors for various chi-square approximations. J. R. Stat. Soc. Series B 16, 296–298.
    1. Beckmann C. F., DeLuca M., Devlin J. T., Smith S. M. (2005). Investigations into resting-state connectivity using independent component analysis. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 29, 1001–1013. 10.1098/rstb.2005.1634
    1. Bell A. J., Sejnowski T. J. (1995). An information-maximization approach to blind separation and blind deconvolution. Neural Comput. 7, 1129–1159. 10.1162/neco.1995.7.6.1129
    1. Bell A. J., Sejnowski T. J. (1997). The “independent components” of natural scenes are edge filters. Vision Res. 37, 3327–3338. 10.1016/s0042-6989(97)00121-1
    1. Berryhill M. E., Phuong L., Picasso L., Cabeza R., Olson I. R. (2007). Parietal lobe and episodic memory: bilateral damage causes impaired free recall of autobiographical memory. J. Neurosci. 27, 14415–14423. 10.1523/jneurosci.4163-07.2007
    1. Biswal B., Yetkin F. Z., Haughton V. M., Hyde J. S. (1995). Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn. Reson. Med. 34, 537–541. 10.1002/mrm.1910340409
    1. Brookes M. J., Liddle E. B., Hale J. R., Woolrich M. W., Luckhoo H., Liddle P. F., et al. . (2012). Task induced modulation of neural oscillations in electrophysiological brain networks. Neuroimage 63, 1918–1930. 10.1016/j.neuroimage.2012.08.012
    1. Brookes M. J., Woolrich M., Luckhoo H., Price D., Hale J. R., Stephenson M. C., et al. . (2011). Investigating the electrophysiological basis of resting state networks using magnetoencephalography. Proc. Natl. Acad. Sci. U S A 108, 16783–16788. 10.1073/pnas.1112685108
    1. Buckner R. L., Andrews-Hanna J. R., Schacter D. L. (2008). The brain’s default network: anatomy, function and relevance to disease. Ann. N Y Acad. Sci. 1124, 1–38. 10.1196/annals.1440.011
    1. Buschman T. J., Denovellis E. L., Diogo C., Bullock D., Miller E. K. (2012). Synchronous oscillatory neural ensembles for rules in the prefrontal cortex. Neuron 76, 838–846. 10.1016/j.neuron.2012.09.029
    1. Cabeza R. (2008). Role of parietal regions in episodic memory retrieval: the dual attentional processes hypothesis. Neuropsychologia 46, 1813–1827. 10.1016/j.neuropsychologia.2008.03.019
    1. Cabeza R., Prince S. E., Daselaar S. M., Greenberg D. L., Budde M., Dolcos F., et al. . (2004). Brain activity during episodic retrieval of autobiographical and laboratory events: an fMRI study using a novel photo paradigm. J. Cogn. Neurosci. 16, 1583–1594. 10.1162/0898929042568578
    1. Calhoun V. D., Kiehl K. A., Liddle P. F., Pearlson G. D. (2004). Aberrant localization of synchronous hemodynamic activity in auditory cortex reliably characterizes schizophrenia. Biol. Psychiatry 15, 842–849. 10.1016/j.biopsych.2004.01.011
    1. Calhoun V. D., Liu J., Adali T. (2009). A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic and ERP data. Neuroimage 45, S163–172. 10.1016/j.neuroimage.2008.10.057
    1. Canuet L., Ishii R., Pascual-Marqui R. D., Iwase M., Kurimoto R., Aoki Y., et al. . (2011). Resting-state EEG source localization and functional connectivity in schizophrenia-like psychosis of epilepsy. PLoS One 6:e27863. 10.1371/journal.pone.0027863
    1. Canuet L., Tellado I., Couceiro V., Fraile C., Fernandez-Novoa L., Ishii R., et al. . (2012). Resting-state network disruption and APOE genotype in Alzheimer’s disease: a lagged functional connectivity study. PLoS One 7:e46289. 10.1371/journal.pone.0046289
    1. Capilla A., Schoffelen J. M., Paterson G., Thut G., Gross J. (2014). Dissociated α-Band modulations in the dorsal and ventral visual pathways in visuospatial attention and perception. Cereb. Cortex 24, 550–561. 10.1093/cercor/bhs343
    1. Capotosto P., Babiloni C., Romani G. L., Corbetta M. (2012). Differential contribution of right and left parietal cortex to the control of spatial attention: a simultaneous EEG-rTMS study. Cereb. Cortex 22, 446–454. 10.1093/cercor/bhr127
    1. Cardoso J. F. (1989). Source separation using higher order moments. Proc. IEEE Int. Conf. Acoust. Speech Signal Process. 4, 2109–2112 10.1109/icassp.1989.266878
    1. Chen J. L., Ros T., Gruzelier J. H. (2013). Dynamic changes of ICA-derived EEG functional connectivity in the resting state. Hum. Brain Mapp. 34, 852–868. 10.1002/hbm.21475
    1. Cichocki A., Amari S. (2002). Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications. New York: Wiley.
    1. Corbetta M., Kincade M. J., Lewis C., Snyder A. Z., Sapir A. (2005). Neural basis and recovery of spatial attention deficits in spatial neglect. Nat. Neurosci. 8, 1603–1610. 10.1038/nn1574
    1. Corbetta M., Shulman G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nat Rev Neurosci. 3, 201–215. 10.1007/978-1-4615-0111-4_12
    1. Custo A., Vulliemoz S., Grouiller F., Van De Ville D., Michel C. (2014). EEG source imaging of brain states using spatiotemporal regression. Neuroimage 1, 106–116. 10.1016/j.neuroimage.2014.04.002
    1. Daselaar S. M., Fleck M. S., Dobbins I. G., Madden D. J., Cabeza R. (2006). Effects of healthy aging on hippocampal and rhinal memory functions: an event-related fMRI study. Cereb. Cortex 16, 1771–1782. 10.1093/cercor/bhj112
    1. de Pasquale F., Della Penna S., Snyder A. Z., Lewis C., Mantini D., Marzetti L., et al. . (2010). Temporal dynamics of spontaneous MEG activity in brain networks. Proc. Natl. Acad. Sci. U S A 107, 6040–6045. 10.1073/pnas.0913863107
    1. Dierks T., Jelic V., Pascual-Marqui R. D., Wahlund L., Julin P., Linden D. E., et al. . (2000). Spatial pattern of cerebral glucose metabolism (PET) correlates with localization of intracerebral EEG-generators in Alzheimer’s disease. Clin. Neurophysiol. 111, 1817–1824. 10.1016/s1388-2457(00)00427-2
    1. Engel A. K., Fries P. (2010). Beta-band oscillations–signalling the status quo? Curr. Opin. Neurobiol. 20, 156–165. 10.1016/j.conb.2010.02.015
    1. Fairhall S. L., Ishai A. (2007). Effective connectivity within the distributed cortical network for face perception. Cereb. Cortex 17, 2400–2406. 10.1093/cercor/bhl148
    1. Frei E., Gamma A., Pascual-Marqui R., Lehmann D., Hell D., Vollenweider F. X. (2001). Localization of MDMA-induced brain activity in healthy volunteers using low resolution brain electromagnetic tomography (LORETA). Hum. Brain Mapp. 3, 152–165. 10.1002/hbm.1049
    1. Fuchs M., Kastner J., Wagner M., Hawes S., Ebersole J. S. (2002). A standardized boundary element method volume conductor model. Clin. Neurophysiol. 113, 702–712. 10.1016/s1388-2457(02)00030-5
    1. Grady C. L., Protzner A. B., Kovacevic N., Strother S. C., Afshin-Pour B., Wojtowicz M., et al. . (2010). A multivariate analysis of age-related differences in default mode and task-positive networks across multiple cognitive domains. Cereb. Cortex 20, 1432–1447. 10.1093/cercor/bhp207
    1. Hanslmayr S., Volberg G., Wimber M., Raabe M., Greenlee M. W., Bäuml K. H. (2011). The relationship between brain oscillations and BOLD signal during memory formation: a combined EEG-fMRI study. J. Neurosci. 31, 15674–15680. 10.1523/jneurosci.3140-11.2011
    1. Harvey M., Rossit S. (2012). Visuospatial neglect in action. Neuropsychologia 50, 1018–1028. 10.1016/j.neuropsychologia.2011.09.030
    1. He B. J., Snyder A. Z., Vincent J. L., Epstein A., Shulman G. L., Corbetta M. (2007). Breakdown of functional connectivity in frontoparietal networks underlies behavioral deficits in spatial neglect. Neuron 53, 905–918. 10.1016/j.neuron.2007.02.013
    1. Hiltunen T., Kantola J., Abou Elseoud A., Lepola P., Suominen K., Starck T., et al. . (2014). Infra-slow EEG fluctuations are correlated with resting-state network dynamics in fMRI. J. Neurosci. 34, 356–362. 10.1523/jneurosci.0276-13.2014
    1. Hipp J. F., Hawellek D. J., Corbetta M., Siegel M., Engel A. K. (2012). Large-scale cortical correlation structure of spontaneous oscillatory activity. Nat. Neurosci. 15, 884–890. 10.1038/nn.3101
    1. Hlinka J., Palus M., Vejmelka M., Mantini D., Corbetta M. (2011). Functional connectivity in resting-state fMRI: is linear correlation sufficient? Neuroimage 54, 2218–2225. 10.1016/j.neuroimage.2010.08.042
    1. Hosaka R., Nakajima T., Aihara K., Yamaguchi Y., Mushiake H. (2014). Arm-use dependent lateralization of gamma and beta oscillations in primate medial motor areas. Neural Netw. [Epub ahead of print]. 10.1016/j.neunet.2014.06.004
    1. Huijbers W., Pennartz C. M., Daselaar S. M. (2010). Dissociating the “retrieval success” regions of the brain: effects of retrieval delay. Neuropsychologia 48, 491–497. 10.1016/j.neuropsychologia.2009.10.006
    1. Huijbers W., Vannini P., Sperling R. A., Pennartz C. M., Cabeza R., Daselaar S. M. (2012). Explaining the encoding/retrieval flip: memory-related deactivations and activations in the posteromedial cortex. Neuropsychologia 50, 3764–3774. 10.1016/j.neuropsychologia.2012.08.021
    1. Hyvärinen A., Oja E. (2000). Independent component analysis: algorithms and applications. Neural Netw. 13, 411–430. 10.1016/s0893-6080(00)00026-5
    1. Ishii R., Shinosaki K., Ukai S., Inouye T., Ishihara T., Yoshimine T., et al. . (1999). Medial prefrontal cortex generates frontal midline theta rhythm. Neuroreport 10, 675–679. 10.1097/00001756-199903170-00003
    1. Joel S. E., Caffo B. S., van Zijl P. C., Pekar J. J. (2011). On the relationship between seed-based and ICA-based measures of functional connectivity. Magn. Reson. Med. 66, 644–657. 10.1002/mrm.22818
    1. Jonmohamadi Y., Poudel G., Innes C., Jones R. (2014). Source-space ICA for EEG source separation, localization and time-course reconstruction. Neuroimage 101, 720–737. 10.1016/j.neuroimage.2014.07.052
    1. Kawasaki M., Yamaguchi Y. (2013). Frontal theta and beta synchronizations for monetary reward increase visual working memory capacity. Soc. Cogn. Affect. Neurosci. 8, 523–530. 10.1093/scan/nss027
    1. Kelly R. E., Wang Z., Alexopoulos G. S., Gunning F. M., Murphy C. F., Morimoto S. S., et al. . (2010). Hybrid ICA-seed-based methods for fmri functional connectivity assessment: a feasibility study. Int. J. Biomed. Imaging 2010:868976. 10.1155/2010/868976
    1. Kim H. (2012). A dual-subsystem model of the brain’s default network: self-referential processing, memory retrieval processes, and autobiographical memory retrieval. Neuroimage 61, 966–977. 10.1016/j.neuroimage.2012.03.025
    1. Klimesch W., Doppelmayr M., Russegger H., Pachinger T., Schwaiger J. (1998). Induced alpha band power changes in the human EEG and attention. Neurosci. Lett. 244, 73–76. 10.1016/s0304-3940(98)00122-0
    1. Kravitz D. J., Saleem K. S., Baker C. I., Mishkin M. (2011). A new neural framework for visuospatial processing. Nat. Rev. Neurosci. 12, 217–230. 10.1038/nrn3008
    1. Kravitz D. J., Saleem K. S., Baker C. I., Ungerleider L. G., Mishkin M. (2013). The ventral visual pathway: an expanded neural framework for the processing of object quality. Trends Cogn. Sci. 17, 26–49. 10.1016/j.tics.2012.10.011
    1. Kubit B., Jack A. I. (2013). Rethinking the role of the rTPJ in attention and social cognition in light of the opposing domains hypothesis: findings from an ALE-based meta-analysis and resting-state functional connectivity. Front. Hum. Neurosci. 7:323. 10.3389/fnhum.2013.00323
    1. Kurimoto R., Ishii R., Canuet L., Ikezawa K., Iwase M., Azechi M., et al. . (2012). Induced oscillatory responses during the Sternberg’s visual memory task in patients with Alzheimer’s disease and mild cognitive impairment. Neuroimage 59, 4132–4140. 10.1016/j.neuroimage.2011.10.061
    1. Luckhoo H., Hale J. R., Stokes M. G., Nobre A. C., Morris P. G., Brookes M. J., et al. . (2012). Inferring task-related networks using independent component analysis in magnetoencephalography. Neuroimage 62, 530–5341. 10.1016/j.neuroimage.2012.04.046
    1. Mantini D., Della Penna S., Marzetti L., de Pasquale F., Pizzella V., Corbetta M., et al. . (2011). A signal-processing pipeline for magnetoencephalography resting-state networks. Brain Connect. 1, 49–59. 10.1089/brain.2011.0001
    1. Mantini D., Perrucci M. G., Del Gratta C., Romani G. L., Corbetta M. (2007). Electrophysiological signatures of resting state networks in the human brain. Proc. Natl. Acad. Sci. U S A 104, 13170–13175. 10.1073/pnas.0700668104
    1. Mars R. B., Sallet J., Schüffelgen U., Jbabdi S., Toni I., Rushworth M. F. (2012). Connectivity-based subdivisions of the human right “temporoparietal junction area”: evidence for different areas participating in different cortical networks. Cereb. Cortex 22, 1894–1903. 10.1093/cercor/bhr268
    1. Mazziotta J., Toga A., Evans A., Fox P., Lancaster J., Zilles K., et al. . (2001). A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). Philos. Trans. R. Soc. Lond. B Biol. Sci. 356, 1293–1322. 10.1098/rstb.2001.0915
    1. McKeown M. J., Makeig S., Brown G. G., Jung T. P., Kindermann S. S., Bell A. J., et al. . (1998). Analysis of fMRI data by blind separation into independent spatial components. Hum. Brain Mapp. 6, 160–188. 10.1002/(sici)1097-0193(1998)6:3<160::aid-hbm5>;2-r
    1. Meyer M. C., Janssen R. J., Van Oort E. S., Beckmann C. F., Barth M. (2013). The Quest for EEG Power band correlation with ICA derived fMRI resting state networks. Front. Hum. Neurosci. 7:315. 10.3389/fnhum.2013.00315
    1. Michels L., Moazami-Goudarzi M., Jeanmonod D., Sarnthein J. (2008). EEG alpha distinguishes between cuneal and precuneal activation in working memory. Neuroimage 40, 1296–1310. 10.1016/j.neuroimage.2007.12.048
    1. Milner A. D. (2012). Is visual processing in the dorsal stream accessible to consciousness? Proc. Biol. Sci. 279, 2289–2298. 10.1098/rspb.2011.2663
    1. Morillon B., Liégeois-Chauvel C., Arnal L. H., Bénar C. G., Giraud A. L. (2012). Asymmetric function of theta and gamma activity in syllable processing: an intra-cortical study. Front. Psychol. 3:248. 10.3389/fpsyg.2012.00248
    1. Musso F., Brinkmeyer J., Mobascher A., Warbrick T., Winterer G. (2010). Spontaneous brain activity and EEG microstates. A novel EEG/fMRI analysis approach to explore resting-state networks. Neuroimage 52, 1149–1161. 10.1016/j.neuroimage.2010.01.093
    1. Pascual-Marqui R. D. (2002). Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods. Find. Exp. Clin. Pharmacol. 24(Suppl. D) 5–12.
    1. Pascual-Marqui R. D., Biscay-Lirio R. J. (2011). Interaction Patterns of Brain Activity Across Space, Time and Frequency. Part I: Methods.arXiv:1103.2852v2 []. Available online at: . Accessed on March 15, 2011.
    1. Pascual-Marqui R. D., Lehmann D., Koukkou M., Kochi K., Anderer P., Saletu B., et al. . (2011). Assessing interactions in the brain with exact low-resolution electromagnetic tomography. Philos. Trans. A. Math. Phys. Eng. Sci. 369, 3768–3784. 10.1098/rsta.2011.0081
    1. Pascual-Marqui R. D., Michel C. M., Lehmann D. (1994). Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. Int. J. Psychophysiol. 18, 49–65. 10.1016/0167-8760(84)90014-x
    1. Pfurtscheller G. (1981). Central beta rhythm during sensorimotor activities in man. Electroencephalogr. Clin. Neurophysiol. 51, 253–264. 10.1016/0013-4694(81)90139-5
    1. Raichle M. E. (2011). The restless brain. Brain Connect. 1, 3–12. 10.1089/brain.2011.0019
    1. Raichle M. E., MacLeod A. M., Snyder A. Z., Powers W. J., Gusnard D. A., Shulman G. L. (2001). A default mode of brain function. Proc. Natl. Acad. Sci. U S A 98, 676–682.
    1. Ramsay J., Silverman B. W. (2005). Functional Data Analysis. New York: Springer.
    1. Ravizza S. M., Hazeltine E., Ruiz S., Zhu D. C. (2011). Left TPJ activity in verbal working memory: implications for storage- and sensory-specific models of short term memory. Neuroimage 55, 1836–1846. 10.1016/j.neuroimage.2010.12.021
    1. Ritter P., Moosmann M., Villringer A. (2009). Rolandic alpha and beta EEG rhythms’ strengths are inversely related to fMRI-BOLD signal in primary somatosensory and motor cortex. Hum. Brain Mapp. 30, 1168–1187. 10.1002/hbm.20585
    1. Rossit S., McIntosh R. D., Malhotra P., Butler S. H., Muir K., Harvey M. (2012). Attention in action: evidence from on-line corrections in left visual neglect. Neuropsychologia 50, 1124–1135. 10.1016/j.neuropsychologia.2011.10.004
    1. Sestieri C., Corbetta M., Romani G. L., Shulman G. L. (2011). Episodic memory retrieval, parietal cortex and the default mode network: functional and topographic analyses. J. Neurosci. 31, 4407–4420. 10.1523/jneurosci.3335-10.2011
    1. Siegel M., Donner T. H., Oostenveld R., Fries P., Engel A. K. (2008). Neuronal synchronization along the dorsal visual pathway reflects the focus of spatial attention. Neuron 60, 709–719. 10.1016/j.neuron.2008.09.010
    1. Smith S. M., Fox P. T., Miller K. L., Glahn D. C., Fox P. M., Mackay C. E., et al. . (2009). Correspondence of the brain’s functional architecture during activation and rest. Proc. Natl. Acad. Sci. U S A 106, 13040–13045. 10.1073/pnas.0905267106
    1. Snyder A. C., Foxe J. J. (2010). Anticipatory attentional suppression of visual features indexed by oscillatory alpha-band power increases: a high-density electrical mapping study. J. Neurosci. 30, 4024–4032. 10.1523/jneurosci.5684-09.2010
    1. Spreng R. N., Schacter D. L. (2012). Default network modulation and large-scale network interactivity in healthy young and old adults. Cereb. Cortex 22, 2610–2621. 10.1093/cercor/bhr339
    1. Stam C. J. (2005). Nonlinear dynamical analysis of EEG and MEG: review of an emerging field. Clin. Neurophysiol. 116, 2266–2301. 10.1016/j.clinph.2005.06.011
    1. Vincent J. L., Kahn I., Snyder A. Z., Raichle M. E., Buckner R. L. (2008). Evidence for a frontoparietal control system revealed by intrinsic functional connectivity. J. Neurophysiol. 100, 3328–3342. 10.1152/jn.90355.2008
    1. Vitacco D., Brandeis D., Pascual-Marqui R., Martin E. (2002). Correspondence of event-related potential tomography and functional magnetic resonance imaging during language processing. Hum. Brain Mapp. 17, 4–12. 10.1002/hbm.10038
    1. Yonelinas A. P. (2002). The nature of recollection and familiarity: a review of 30 years of research. J. Mem. Lang. 46, 441–517 10.1006/jmla.2002.2864
    1. Yonelinas A. P., Otten L. J., Shaw K. N., Rugg M. D. (2005). Separating the brain regions involved in recollection and familiarity in recognition memory. J. Neurosci. 25, 3002–3008. 10.1523/jneurosci.5295-04.2005
    1. Yuan H., Zotev V., Phillips R., Drevets W. C., Bodurka J. (2012). Spatiotemporal dynamics of the brain at rest–exploring EEG microstates as electrophysiological signatures of BOLD resting state networks. Neuroimage 60, 2062–2072. 10.1016/j.neuroimage.2012.02.031
    1. Zahn R., Talazko J., Ebert D. (2008). Loss of the sense of self-ownership for perceptions of objects in a case of right inferior temporal, parieto-occipital and precentral hypometabolism. Psychopathology 41, 397–402. 10.1159/000158228

Source: PubMed

Sponsors and Collaborators

Medical Conditions

Drug Interventions

3
Subscribe