Advertisement

A Neural Mass Model for Abnormal Beta-Rebound in Schizophrenia

  • Áine ByrneEmail author
  • Stephen Coombes
  • Peter F. Liddle
Chapter
Part of the Springer Series in Cognitive and Neural Systems book series (SSCNS, volume 13)

Abstract

Patients with schizophrenia demonstrate robust abnormalities of the synchronisation of beta oscillations that occur in diverse brain regions following sensory, motor or mental events. A prominent abnormality seen in primary motor cortex is a reduction in amplitude of so-called beta-rebound. Here a sharp decrease in neural oscillatory power in the beta band is observed during movement (MRBD) followed by an increase above baseline on movement cessation (PMBR). An understanding of how neural circuits give rise to MRBD and PMBR is clinically relevant to the pathophysiology of schizophrenia. Here we survey a very recent neural mass model for movement-induced changes in the beta rhythm and show that it is an ideal candidate for use in a clinical setting. The model arises as an exact mean-field reduction of a spiking network, has a realistic model of synaptic processing and is able to describe the dynamic changes in population synchrony that can underlie event-related desynchronisation/synchronisation for MRBD/PMBR. A lengthening of the synaptic response time to sensory drive, modelling NMDA receptor hypofunction, shows a reduction in beta-rebound consistent with that seen in schizophrenia.

Keywords

Neural mass Mean-field model Beta-rebound Schizophrenia 

References

  1. 1.
    Marin O (2012) Interneuron dysfunction in psychiatric disorders. Nat Rev Neurosci 13:107–120CrossRefGoogle Scholar
  2. 2.
    Lam NH, Borduqui T, Hallak J, Roque AC, Anticevic A, Krystal JH, Wang X-J, Murray JD (2017) Effects of altered excitation-inhibition balance on decision making in a cortical circuit model. bioRxivGoogle Scholar
  3. 3.
    Anticevic A, Lisman J (2017) How can global alteration of excitation/inhibition balance lead to the local dysfunctions that underlie schizophrenia? Biol Psychiatry 81:818–820CrossRefGoogle Scholar
  4. 4.
    Lytton WW, Arle J, Bobashev G, Ji S, Klassen TL, Marmarelis VZ, Schwaber J, Sherif MA, Sanger TD (2017) Multiscale modeling in the clinic: diseases of the brain and nervous system. Brain Inform 4(4):219–230CrossRefGoogle Scholar
  5. 5.
    Izhikevich EM, Edelman GM (2008) Large-scale model of mammalian thalamocortical systems. Proc Natl Acad Sci 105:3593–3598CrossRefGoogle Scholar
  6. 6.
    Coombes S, Beim Graben P, Potthast R, Wright J (eds) (2014) Neural fields: theory and applications. Springer, Berlin/HeidelbergGoogle Scholar
  7. 7.
    Breakspear M (2017) Dynamic models of large-scale brain activity. Nat Neurosci 20:340–352CrossRefGoogle Scholar
  8. 8.
    Vogels TP, Abbott LF (2009) Gating multiple signals through detailed balance of excitation and inhibition in spiking networks. Nat Neurosci 12:483–491CrossRefGoogle Scholar
  9. 9.
    Sanz-Leon P, Knock SA, Spiegler A, Jirsa VK (2015) Mathematical framework for large-scale brain network modeling in the virtual brain. NeuroImage 111:385–430CrossRefGoogle Scholar
  10. 10.
    Stancák A, Pfurtscheller G (1995) Desynchronization and recovery of beta rhythms during brisk and slow self-paced finger movements in man. Neurosci Lett 196:21–24CrossRefGoogle Scholar
  11. 11.
    Robson SE, Brookes MJ, Hall EL, Palaniyappan L, Kumar J, Skelton M, Christodoulou NG, Qureshic A, Jan F, Liddle EB, Katshu MZ, Liddle PF, Morris PG (2016) Abnormal visuomotor processing in schizophrenia. NeuroImage: Clin 12(Supplement C):869–878Google Scholar
  12. 12.
    Liddle EB, Price D, Palaniyappan L, Brookes MJ, Robson SE, Hall EL, Morris PG, Liddle PF (2016) Abnormal salience signaling in schizophrenia: the role of integrative beta oscillations. Hum Brain Mapp 37:1361–1374CrossRefGoogle Scholar
  13. 13.
    Byrne Á, Brookes MJ, Coombes S (2017) A mean field model for movement induced changes in the beta rhythm. J Comput Neurosci 43:143–158CrossRefGoogle Scholar
  14. 14.
    Olney JW, Newcomer JW, Farber NB (1999) NMDA receptor hypofunction model of schizophrenia. J Psychiatric Res 33:523–533CrossRefGoogle Scholar
  15. 15.
    Wilson HR, Cowan JD (1972) Excitatory and inhibitory interactions in localized populations of model neurons. Biophys J 12:1–24CrossRefGoogle Scholar
  16. 16.
    Valdes-Sosa P, Sanchez-Bornot JM, Sotero RC, Iturria-Medina Y, Aleman-Gomez Y, Bosch-Bayard J, Carbonell F, Ozaki T (2009) Model driven EEG/fMRI fusion of brain oscillations. Hum Brain Mapp 30:2701–21CrossRefGoogle Scholar
  17. 17.
    Coombes S, Byrne Á (2018) Next generation neural mass models. In: Torcini A, Corinto F (eds) Lecture notes in nonlinear dynamics in computational neuroscience: from physics and biology to ICT. Springer, ChamGoogle Scholar
  18. 18.
    Rogasch NC, Zafiris ZJ, Fitzgerald PB (2014) Cortical inhibition, excitation, and connectivity in schizophrenia: a review of insights from transcranial magnetic stimulation. Schizophr Bull 40:685–696CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Áine Byrne
    • 1
    Email author
  • Stephen Coombes
    • 2
  • Peter F. Liddle
    • 3
  1. 1.Centre for Neural SciencesNew York UniversityNew YorkUSA
  2. 2.Centre for Mathematical Medicine and Biology, School of Mathematical SciencesUniversity of NottinghamNottinghamUK
  3. 3.Institute of Mental Health, School of MedicineUniversity of NottinghamNottinghamUK

Personalised recommendations