Skip to main content
Top
Published in:

10-01-2022 | Research Article

Dynamic networks of P300-related process

Authors: Qin Tao, Lin Jiang, Fali Li, Yuan Qiu, Chanlin Yi, Yajing Si, Cunbo Li, Tao Zhang, Dezhong Yao, Peng Xu

Published in: Cognitive Neurodynamics | Issue 5/2022

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

P300 as an effective biomarker to index attention and memory has been widely used for brain-computer interface, cognitive evaluation, and clinical diagnosis. To evoke clear P300, an oddball paradigm consisting of two types of stimuli, i.e., infrequent target stimuli and frequent standard stimuli, is usually used. However, to simply and quickly explore the P300-related process, previous studies predominately focused on the target condition but ignored the fusion of target and standard conditions, as well as the difference of brain networks between them. Therefore, in this study, we used the hidden Markov model to investigate the fused multi-conditional electroencephalogram dataset of P300, aiming to effectively identify the underlying brain networks and explore the difference between conditions. Specifically, the inferred networks, including their transition sequences and spatial distributions, were scrutinized first. Then, we found that the difference between target and standard conditions was mainly concentrated in two phases. One was the stimulation phase that mainly related to the cortical activities of the postcentral gyrus and superior parietal lobule, and the other corresponded to the response phase that involved the activities of superior and medial frontal gyri. This might be attributed to distinct cognitive functions, as the stimulation phase is associated with visual information integration whereas the response phase involves stimulus discrimination and behavior control. Taken together, the current work explored dynamic networks underlying the P300-related process and provided a complementary understanding of distinct P300 conditions, which may contribute to the design of P300-related brain-machine systems.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
go back to reference Badre D, Wagner AD (2004) Selection, integration, and conflict monitoring; assessing the nature and generality of prefrontal cognitive. Control Mech Neuron 41:473–487 Badre D, Wagner AD (2004) Selection, integration, and conflict monitoring; assessing the nature and generality of prefrontal cognitive. Control Mech Neuron 41:473–487
go back to reference Baker AP, Brookes MJ, Rezek IA, Smith SM, Behrens T, Probert Smith PJ, Woolrich M (2014) Fast transient networks in spontaneous human. Brain Activity Elife 3:e01867PubMed Baker AP, Brookes MJ, Rezek IA, Smith SM, Behrens T, Probert Smith PJ, Woolrich M (2014) Fast transient networks in spontaneous human. Brain Activity Elife 3:e01867PubMed
go back to reference Bishop CM (2006) Pattern recognition and machine learning. Springer, New York Bishop CM (2006) Pattern recognition and machine learning. Springer, New York
go back to reference Borst JP, Anderson JR (2015) The discovery of processing stages: analyzing EEG data with hidden semi-Markov models. Neuroimage 108:60–73PubMed Borst JP, Anderson JR (2015) The discovery of processing stages: analyzing EEG data with hidden semi-Markov models. Neuroimage 108:60–73PubMed
go back to reference Caviness VS Jr, Meyer J, Makris N, Kennedy DN (1996) MRI-based topographic parcellation of human neocortex: an anatomically specified method with estimate of reliability. J Cogn Neurosci 8:566–587PubMed Caviness VS Jr, Meyer J, Makris N, Kennedy DN (1996) MRI-based topographic parcellation of human neocortex: an anatomically specified method with estimate of reliability. J Cogn Neurosci 8:566–587PubMed
go back to reference Chun J et al (2013) Can P300 distinguish among schizophrenia, schizoaffective and bipolar I disorders? An ERP study of response inhibition. Schizophr Res 151:175–184PubMed Chun J et al (2013) Can P300 distinguish among schizophrenia, schizoaffective and bipolar I disorders? An ERP study of response inhibition. Schizophr Res 151:175–184PubMed
go back to reference Collins DL, Neelin P, Peters TM, Evans AC (1994) Automatic 3D intersubject registration of MR volumetric data in standardized Talairach spaceJ Comput Assist Tomogr 18:192–205PubMed Collins DL, Neelin P, Peters TM, Evans AC (1994) Automatic 3D intersubject registration of MR volumetric data in standardized Talairach spaceJ Comput Assist Tomogr 18:192–205PubMed
go back to reference Dayan P, Abbott LF (2001) Theoretical neuroscience: computational and mathematical modeling of neural systems. J Cognit Neurosci 15(1):154–155 Dayan P, Abbott LF (2001) Theoretical neuroscience: computational and mathematical modeling of neural systems. J Cognit Neurosci 15(1):154–155
go back to reference de Hollander G, Forstmann BU, Brown SD (2016) Different ways of linking behavioral and neural data via computational cognitive models. Biol Psychiatry Cogn Neurosci Neuroimaging 1:101–109PubMed de Hollander G, Forstmann BU, Brown SD (2016) Different ways of linking behavioral and neural data via computational cognitive models. Biol Psychiatry Cogn Neurosci Neuroimaging 1:101–109PubMed
go back to reference Deary IJ, Der G (2005) Reaction time, age, and cognitive ability: Longitudinal findings from age 16 to 63 years in representative population samples. Aging Neuropsychol Cogn 12:187–215 Deary IJ, Der G (2005) Reaction time, age, and cognitive ability: Longitudinal findings from age 16 to 63 years in representative population samples. Aging Neuropsychol Cogn 12:187–215
go back to reference Dehaene S, Kerszberg M, Changeux J (1998) A neuronal model of a global workspace in effortful cognitive tasks. Proc Natl Acad Sci USA 95:14529–14534PubMedPubMedCentral Dehaene S, Kerszberg M, Changeux J (1998) A neuronal model of a global workspace in effortful cognitive tasks. Proc Natl Acad Sci USA 95:14529–14534PubMedPubMedCentral
go back to reference Demiralp T, Ademoglu A, Istefanopulos Y, Basar-Eroglu C, Basar E (2001) Wavelet analysis of oddball P300. Int J Psychophysiol 39:221–227PubMed Demiralp T, Ademoglu A, Istefanopulos Y, Basar-Eroglu C, Basar E (2001) Wavelet analysis of oddball P300. Int J Psychophysiol 39:221–227PubMed
go back to reference Dong L, Bai J, Jiang X, Yang MM, Zheng Y, Zhang H, Lin D (2017) The gene polymorphisms of IL-8(-251T/A) and IP-10(-1596 C/T) are associated with susceptibility and progression of type 2 diabetic retinopathy in northern Chinese population. Eye (Lond) 31:601–607 Dong L, Bai J, Jiang X, Yang MM, Zheng Y, Zhang H, Lin D (2017) The gene polymorphisms of IL-8(-251T/A) and IP-10(-1596 C/T) are associated with susceptibility and progression of type 2 diabetic retinopathy in northern Chinese population. Eye (Lond) 31:601–607
go back to reference Eichele T, Specht K, Moosmann M, Jongsma ML, Quiroga RQ, Nordby H, Hugdahl K (2005) Assessing the spatiotemporal evolution of neuronal activation with single-trial event-related potentials and functional MRI. Proc Natl Acad Sci USA 102:17798–17803PubMedPubMedCentral Eichele T, Specht K, Moosmann M, Jongsma ML, Quiroga RQ, Nordby H, Hugdahl K (2005) Assessing the spatiotemporal evolution of neuronal activation with single-trial event-related potentials and functional MRI. Proc Natl Acad Sci USA 102:17798–17803PubMedPubMedCentral
go back to reference Finc K et al (2017) Transition of the functional brain network related to increasing cognitive demands. Hum Brain Mapp 38:3659–3674PubMedPubMedCentral Finc K et al (2017) Transition of the functional brain network related to increasing cognitive demands. Hum Brain Mapp 38:3659–3674PubMedPubMedCentral
go back to reference Foti N, Xu J, Laird D, Fox E (2014) Stochastic variational inference for hidden Markov models. Adv Neural Inf Process Syst 4 Foti N, Xu J, Laird D, Fox E (2014) Stochastic variational inference for hidden Markov models. Adv Neural Inf Process Syst 4
go back to reference Friedman-Hill SR, Robertson LC, Treisman A (1995) Parietal contributions to visual feature binding: evidence from a patient with bilateral lesions. Science 269:853–855PubMed Friedman-Hill SR, Robertson LC, Treisman A (1995) Parietal contributions to visual feature binding: evidence from a patient with bilateral lesions. Science 269:853–855PubMed
go back to reference Fuchs M, Kastner J, Wagner M, Hawes S, Ebersole JS (2002) A standardized boundary element method volume conductor model. Clin Neurophysiol 113:702–712PubMed Fuchs M, Kastner J, Wagner M, Hawes S, Ebersole JS (2002) A standardized boundary element method volume conductor model. Clin Neurophysiol 113:702–712PubMed
go back to reference Harper J, Malone SM, Bernat EM (2014) Theta and delta band activity explain N2 and P3 ERP component activity in a go/no-go task. Clin Neurophysiol 125:124–132PubMed Harper J, Malone SM, Bernat EM (2014) Theta and delta band activity explain N2 and P3 ERP component activity in a go/no-go task. Clin Neurophysiol 125:124–132PubMed
go back to reference Hoffman MD, Blei DM, Wang C, Paisley J (2013) Stochastic variational inference. J Mach Learn Res 14:1303–1347 Hoffman MD, Blei DM, Wang C, Paisley J (2013) Stochastic variational inference. J Mach Learn Res 14:1303–1347
go back to reference Houlihan ME, Stelmack RM, Campbell KB (1998) Intelligence and the effects of perceptual processing demands, task difficulty and processing speed on P300, reaction time and movement time. Intelligence 26:9-25 Houlihan ME, Stelmack RM, Campbell KB (1998) Intelligence and the effects of perceptual processing demands, task difficulty and processing speed on P300, reaction time and movement time. Intelligence 26:9-25
go back to reference Howe AS, Bani-Fatemi A, De Luca V (2014) The clinical utility of the auditory P300 latency subcomponent event-related potential in preclinical diagnosis of patients with mild cognitive impairment and Alzheimer’s disease. Brain Cogn 86:64–74PubMed Howe AS, Bani-Fatemi A, De Luca V (2014) The clinical utility of the auditory P300 latency subcomponent event-related potential in preclinical diagnosis of patients with mild cognitive impairment and Alzheimer’s disease. Brain Cogn 86:64–74PubMed
go back to reference Jorge J, van der Zwaag W, Figueiredo P (2014) EEG-fMRI integration for the study of human brain function. Neuroimage 1(102 Pt):24–34 Jorge J, van der Zwaag W, Figueiredo P (2014) EEG-fMRI integration for the study of human brain function. Neuroimage 1(102 Pt):24–34
go back to reference Lee WC, Bonin V, Reed M, Graham BJ, Hood G, Glattfelder K, Reid RC (2016) Anatomy and function of an excitatory network in the visual cortex. Nature 532:370–374PubMedPubMedCentral Lee WC, Bonin V, Reed M, Graham BJ, Hood G, Glattfelder K, Reid RC (2016) Anatomy and function of an excitatory network in the visual cortex. Nature 532:370–374PubMedPubMedCentral
go back to reference Li Y, Pan J, Wang F, Yu Z (2013) A hybrid BCI system combining P300 and SSVEP and its application to wheelchair control. IEEE Trans Biomed Eng 60:3156–3166PubMed Li Y, Pan J, Wang F, Yu Z (2013) A hybrid BCI system combining P300 and SSVEP and its application to wheelchair control. IEEE Trans Biomed Eng 60:3156–3166PubMed
go back to reference Li F et al (2016) The time-varying networks in P300: a task-evoked EEG study. IEEE Trans Neural Syst Rehabil Eng 24:725–733PubMed Li F et al (2016) The time-varying networks in P300: a task-evoked EEG study. IEEE Trans Neural Syst Rehabil Eng 24:725–733PubMed
go back to reference Li F et al (2019a) Transition of brain networks from an interictal to a preictal state preceding a seizure revealed by scalp EEG network analysis. Cogn Neurodyn 13:175–181PubMedPubMedCentral Li F et al (2019a) Transition of brain networks from an interictal to a preictal state preceding a seizure revealed by scalp EEG network analysis. Cogn Neurodyn 13:175–181PubMedPubMedCentral
go back to reference Li F et al (2019b) Differentiation of Schizophrenia by Combining the Spatial EEG Brain Network Patterns of Rest and Task P300. IEEE Trans Neural Syst Rehabil Eng 27:594–602PubMed Li F et al (2019b) Differentiation of Schizophrenia by Combining the Spatial EEG Brain Network Patterns of Rest and Task P300. IEEE Trans Neural Syst Rehabil Eng 27:594–602PubMed
go back to reference Li F et al (2020) Inter-subject P300 variability relates to the efficiency of brain networks reconfigured from resting- to task-state: evidence from a simultaneous event-related EEG-fMRI. Study Neuroimage 205:116285PubMed Li F et al (2020) Inter-subject P300 variability relates to the efficiency of brain networks reconfigured from resting- to task-state: evidence from a simultaneous event-related EEG-fMRI. Study Neuroimage 205:116285PubMed
go back to reference Maziero D, Velasco TR, Hunt N, Payne E, Lemieux L, Salmon CEG, Carmichael DW (2016) Towards motion insensitive EEG-fMRI: Correcting motion-induced voltages and gradient artefact instability in EEG using an fMRI prospective motion correction (PMC). Syst Neuroimage 138:13–27 Maziero D, Velasco TR, Hunt N, Payne E, Lemieux L, Salmon CEG, Carmichael DW (2016) Towards motion insensitive EEG-fMRI: Correcting motion-induced voltages and gradient artefact instability in EEG using an fMRI prospective motion correction (PMC). Syst Neuroimage 138:13–27
go back to reference McGrory CA, Titterington DM (2009) VVariational Bayesian analysis for hidden Markov models Australian & New Zealand. J Stat 51:227–244 McGrory CA, Titterington DM (2009) VVariational Bayesian analysis for hidden Markov models Australian & New Zealand. J Stat 51:227–244
go back to reference Miller EK, Cohen JD (2001) An integrative theory of prefrontal cortex function. Annu Rev Neurosci 24:167–202PubMed Miller EK, Cohen JD (2001) An integrative theory of prefrontal cortex function. Annu Rev Neurosci 24:167–202PubMed
go back to reference Nichols TE, Holmes AP (2002) Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp 15:1–25PubMed Nichols TE, Holmes AP (2002) Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp 15:1–25PubMed
go back to reference Och FJ, Ney H (2003) A systematic comparison of various statistical alignment models. Comput Linguist 29:c-51 Och FJ, Ney H (2003) A systematic comparison of various statistical alignment models. Comput Linguist 29:c-51
go back to reference Osten DW (1988) Selection of optimal regression models via cross-validation. J Chemometr 2:39–48 Osten DW (1988) Selection of optimal regression models via cross-validation. J Chemometr 2:39–48
go back to reference Pascual-Marqui RD (2002) Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details Methods. Find Exp Clin Pharmacol 24:5–12PubMed Pascual-Marqui RD (2002) Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details Methods. Find Exp Clin Pharmacol 24:5–12PubMed
go back to reference Pascual-Marqui RD, Esslen M, Kochi K, Lehmann D (2002) Functional imaging with low-resolution brain electromagnetic tomography (LORETA): a review. Methods Find Exp Clin Pharmacol 24:91-95PubMed Pascual-Marqui RD, Esslen M, Kochi K, Lehmann D (2002) Functional imaging with low-resolution brain electromagnetic tomography (LORETA): a review. Methods Find Exp Clin Pharmacol 24:91-95PubMed
go back to reference Pfabigan DM et al (2014) P300 amplitude variation is related to ventral striatum BOLD response during gain and loss anticipation: an EEG and fMRI. Exp Neuroimage 96:12–21 Pfabigan DM et al (2014) P300 amplitude variation is related to ventral striatum BOLD response during gain and loss anticipation: an EEG and fMRI. Exp Neuroimage 96:12–21
go back to reference Picard RR, Cook RD (1984) Cross-validation of regression models. J Am Stat Assoc 79:575–583 Picard RR, Cook RD (1984) Cross-validation of regression models. J Am Stat Assoc 79:575–583
go back to reference Picton TW (1992) The P300 wave of the human event-related potential. J Clin Neurophysiol 9:456–479PubMed Picton TW (1992) The P300 wave of the human event-related potential. J Clin Neurophysiol 9:456–479PubMed
go back to reference Prinzmetal W, McCool C, Park S (2005) Attention: reaction time and accuracy reveal different mechanisms. J Exp Psychol Gen 134:73–92PubMed Prinzmetal W, McCool C, Park S (2005) Attention: reaction time and accuracy reveal different mechanisms. J Exp Psychol Gen 134:73–92PubMed
go back to reference Quinn AJ, Vidaurre D, Abeysuriya R, Becker R, Nobre AC, Woolrich MW (2018) Markov Modeling Front Neurosci 12:603Task-Evoked Dynamic Network Analysis Through Hidden Quinn AJ, Vidaurre D, Abeysuriya R, Becker R, Nobre AC, Woolrich MW (2018) Markov Modeling Front Neurosci 12:603Task-Evoked Dynamic Network Analysis Through Hidden
go back to reference Quinn AJ et al (2019) Unpacking transient event dynamics in electrophysiological power. Spectra Brain Topogr 32:1020–1034PubMed Quinn AJ et al (2019) Unpacking transient event dynamics in electrophysiological power. Spectra Brain Topogr 32:1020–1034PubMed
go back to reference Rabiner LR, Juang B (1986) An introduction to hidden Markov models. IEEE Assp Mag 3:4–16 Rabiner LR, Juang B (1986) An introduction to hidden Markov models. IEEE Assp Mag 3:4–16
go back to reference Rezek I, Roberts S (2005) Ensemble hidden Markov models with extended observation densities for biosignal analysis. In: Probabilistic modeling in bioinformatics and medical informatics. Advanced information and knowledge processing. pp 419–450. https://doi.org/10.1007/1-84628-119-9_14 Rezek I, Roberts S (2005) Ensemble hidden Markov models with extended observation densities for biosignal analysis. In: Probabilistic modeling in bioinformatics and medical informatics. Advanced information and knowledge processing. pp 419–450. https://​doi.​org/​10.​1007/​1-84628-119-9_​14
go back to reference Ridderinkhof KR, Ullsperger M, Crone EA, Nieuwenhuis S (2004) The role of the medial frontal cortex in cognitive control. Science 306:443–447PubMed Ridderinkhof KR, Ullsperger M, Crone EA, Nieuwenhuis S (2004) The role of the medial frontal cortex in cognitive control. Science 306:443–447PubMed
go back to reference Rutiku R, Martin M, Bachmann T, Aru J (2015) Does the P300 reflect conscious perception or its consequences? Neuroscience 298:180–189PubMed Rutiku R, Martin M, Bachmann T, Aru J (2015) Does the P300 reflect conscious perception or its consequences? Neuroscience 298:180–189PubMed
go back to reference Saygin AP, Sereno MI (2008) Retinotopy and attention in human occipital, temporal, parietal, and frontal cortex. Cereb Cortex 18:2158–2168PubMed Saygin AP, Sereno MI (2008) Retinotopy and attention in human occipital, temporal, parietal, and frontal cortex. Cereb Cortex 18:2158–2168PubMed
go back to reference Schall JD, Stuphorn V, Brown JW (2002) Monitoring and control of action by the frontal lobes. Neuron 36:309–322PubMed Schall JD, Stuphorn V, Brown JW (2002) Monitoring and control of action by the frontal lobes. Neuron 36:309–322PubMed
go back to reference Si Y et al (2019a) Predicting individual decision-making responses based on the functional connectivity of resting-state. EEG J Neural Eng 16:066025PubMed Si Y et al (2019a) Predicting individual decision-making responses based on the functional connectivity of resting-state. EEG J Neural Eng 16:066025PubMed
go back to reference Si Y et al (2019b) Different decision-making responses occupy different brain networks for information processing: a study based on EEG and TMS. Cereb Cortex 29:4119–4129PubMed Si Y et al (2019b) Different decision-making responses occupy different brain networks for information processing: a study based on EEG and TMS. Cereb Cortex 29:4119–4129PubMed
go back to reference Squires NK, Squires KC, Hillyard SA (1975) Two varieties of long-latency positive waves evoked by unpredictable auditory stimuli in man. Electroencephalogr Clin Neurophysiol 38:387–401PubMed Squires NK, Squires KC, Hillyard SA (1975) Two varieties of long-latency positive waves evoked by unpredictable auditory stimuli in man. Electroencephalogr Clin Neurophysiol 38:387–401PubMed
go back to reference Tao Q, Si Y, Li F, Duan K, Xu P (2019) The different patterns of reward magnitude: a scalp EEG research. In: 2019 IEEE international conference on computational intelligence and virtual environments for measurement systems and applications (CIVEMSA) Tao Q, Si Y, Li F, Duan K, Xu P (2019) The different patterns of reward magnitude: a scalp EEG research. In: 2019 IEEE international conference on computational intelligence and virtual environments for measurement systems and applications (CIVEMSA)
go back to reference Tao Q et al (2021) Decision-feedback stages revealed by hidden Markov modeling of EEG international. J Neural Syst 31:2150031 Tao Q et al (2021) Decision-feedback stages revealed by hidden Markov modeling of EEG international. J Neural Syst 31:2150031
go back to reference Vidaurre D, Bielza C, Larrañaga P (2013) A Survey of L1 Regression. Int Stat Rev 81:361–387 Vidaurre D, Bielza C, Larrañaga P (2013) A Survey of L1 Regression. Int Stat Rev 81:361–387
go back to reference Vidaurre D, Smith SM, Woolrich MW (2017) Brain network dynamics are hierarchically organized in time. Proc Natl Acad Sci USA 114:12827–12832PubMedPubMedCentral Vidaurre D, Smith SM, Woolrich MW (2017) Brain network dynamics are hierarchically organized in time. Proc Natl Acad Sci USA 114:12827–12832PubMedPubMedCentral
go back to reference Vidaurre D, Hunt LT, Quinn AJ, Hunt BAE, Brookes MJ, Nobre AC, Woolrich MW (2018) Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks. Nat Commun 9:2987PubMedPubMedCentral Vidaurre D, Hunt LT, Quinn AJ, Hunt BAE, Brookes MJ, Nobre AC, Woolrich MW (2018) Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks. Nat Commun 9:2987PubMedPubMedCentral
go back to reference Vidaurre D, Myers NE, Stokes M, Nobre AC, Woolrich MW (2019) Temporally unconstrained decoding reveals consistent but time-varying stages of stimulus. Process Cereb Cortex 29:863–874 Vidaurre D, Myers NE, Stokes M, Nobre AC, Woolrich MW (2019) Temporally unconstrained decoding reveals consistent but time-varying stages of stimulus. Process Cereb Cortex 29:863–874
go back to reference Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE (2014) Permutation inference for the general. Linear Model Neuroimage 92:381–397PubMed Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE (2014) Permutation inference for the general. Linear Model Neuroimage 92:381–397PubMed
go back to reference Woolrich MW, Baker A, Luckhoo H, Mohseni H, Barnes G, Brookes M, Rezek I (2013) Dynamic state allocation for MEG. Source Reconstr Neuroimage 77:77–92 Woolrich MW, Baker A, Luckhoo H, Mohseni H, Barnes G, Brookes M, Rezek I (2013) Dynamic state allocation for MEG. Source Reconstr Neuroimage 77:77–92
go back to reference Yao D (2001) A method to standardize a reference of scalp EEG recordings to a point at infinity. Physiol Meas 22:693–711PubMed Yao D (2001) A method to standardize a reference of scalp EEG recordings to a point at infinity. Physiol Meas 22:693–711PubMed
Metadata
Title
Dynamic networks of P300-related process
Authors
Qin Tao
Lin Jiang
Fali Li
Yuan Qiu
Chanlin Yi
Yajing Si
Cunbo Li
Tao Zhang
Dezhong Yao
Peng Xu
Publication date
10-01-2022
Publisher
Springer Netherlands
Published in
Cognitive Neurodynamics / Issue 5/2022
Print ISSN: 1871-4080
Electronic ISSN: 1871-4099
DOI
https://doi.org/10.1007/s11571-021-09753-3

Other articles of this Issue 5/2022

Cognitive Neurodynamics 5/2022 Go to the issue