Encyclopedia of Computational Neuroscience

Living Edition
| Editors: Dieter Jaeger, Ranu Jung

Electrocorticogram (ECoG)

  • Biyu J. HeEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-7320-6_545-1



ECoG refers to the invasive technique of recording brain electrical field potentials with electrodes placed directly on the cortical surface. ECoG electrodes are typically placed subdurally, above the pia mater. In humans, ECoG is often conducted in patients with medically intractable epilepsy in order to monitor their seizures. Because a craniotomy (a surgical incision into the skull) is required to implant the electrode grid, ECoG is an invasive procedure. Clinical ECoG offers a rare and invaluable research opportunity for obtaining invasive electrophysiological signals in awake, behaving humans. Another avenue of research that is beginning to be explored is cortical stimulation using ECoG electrodes (e.g., Parvizi et al. ( 2013)). The electrode grids often cover much wider areas than the epileptogenic zone, allowing recordings from healthy brain tissue. A postoperative CT...


Power Spectrum Local Field Potential Electrode Grid Brain Oscillation Membrane Time Constant 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access.


  1. Berger H (1929) Uber das Elektroenkephalogramm des Menschen. Arch Psyhiatr Nervenkr 87:527–570CrossRefGoogle Scholar
  2. Brody CD, Romo R, Kepecs A (2003) Basic mechanisms for graded persistent activity: discrete attractors, continuous attractors, and dynamic representations. Curr Opin Neurobiol 13:204–211PubMedCrossRefGoogle Scholar
  3. Buzsaki G, Logothetis N, Singer W (2013) Scaling brain size, keeping timing: evolutionary preservation of brain rhythms. Neuron 80:751–764PubMedCrossRefGoogle Scholar
  4. Carter E, Wang XJ (2007) Cannabinoid-mediated disinhibition and working memory: dynamical interplay of multiple feedback mechanisms in a continuous attractor model of prefrontal cortex. Cereb Cortex 17(Suppl 1):i16–i26PubMedCrossRefGoogle Scholar
  5. Chaudhuri R, He BJ, Wang XJ (2014) The temporal structure of a random network near criticality and human ECoG dynamics. Cosyne, Salt Lake CityGoogle Scholar
  6. Dehghani N, Bedard C, Cash SS, Halgren E, Destexhe A (2010) Comparative power spectral analysis of simultaneous electroencephalographic and magnetoencephalographic recordings in humans suggests non-resistive extracellular media: EEG and MEG power spectra. J Comput Neurosci 29(3):405–421Google Scholar
  7. Destexhe A, Rudolph M, Pare D (2003) The high-conductance state of neocortical neurons in vivo. Nat Rev Neurosci 4:739–751PubMedCrossRefGoogle Scholar
  8. Einevoll GT, Kayser C, Logothetis NK, Panzeri S (2013) Modelling and analysis of local field potentials for studying the function of cortical circuits. Nat Rev Neurosci 14:770–785PubMedCrossRefGoogle Scholar
  9. El Boustani S, Marre O, Behuret S, Baudot P, Yger P, Bal T, Destexhe A, Fregnac Y (2009) Network-state modulation of power-law frequency-scaling in visual cortical neurons. PLoS Comput Biol 5:e1000519PubMedCentralPubMedCrossRefGoogle Scholar
  10. Freeman WJ, Zhai J (2009) Simulated power spectral density (PSD) of background electrocorticogram (ECoG). Cogn Neurodyn 3:97–103PubMedCentralPubMedCrossRefGoogle Scholar
  11. Gibb AJ, Colquhoun D (1991) Glutamate activation of a single NMDA receptor-channel produces a cluster of channel openings. Proc Biol Sci 243:39–45PubMedCrossRefGoogle Scholar
  12. Gilden DL (2001) Cognitive emissions of 1/f noise. Psychol Rev 108:33–56PubMedCrossRefGoogle Scholar
  13. He BJ (2011) Scale-free properties of the functional magnetic resonance imaging signal during rest and task. J Neurosci 31:13786–13795PubMedCentralPubMedCrossRefGoogle Scholar
  14. He BJ, Snyder AZ, Zempel JM, Smyth MD, Raichle ME (2008) Electrophysiological correlates of the brain’s intrinsic large-scale functional architecture. Proc Natl Acad Sci U S A 105:16039–16044PubMedCentralPubMedCrossRefGoogle Scholar
  15. He BJ, Zempel JM, Snyder AZ, Raichle ME (2010) The temporal structures and functional significance of scale-free brain activity. Neuron 66:353–369PubMedCentralPubMedCrossRefGoogle Scholar
  16. Ho EC, Struber M, Bartos M, Zhang L, Skinner FK (2012) Inhibitory networks of fast-spiking interneurons generate slow population activities due to excitatory fluctuations and network multistability. J Neurosci 32:9931–9946PubMedCrossRefGoogle Scholar
  17. Kello CT, Brown GD, Ferrer ICR, Holden JG, Linkenkaer-Hansen K, Rhodes T, Van Orden GC (2010) Scaling laws in cognitive sciences. Trends Cogn Sci 14:223–232PubMedCrossRefGoogle Scholar
  18. Koch C, Rapp M, Segev I (1996) A brief history of time (constants). Cereb Cortex 6:93–101PubMedCrossRefGoogle Scholar
  19. Letzkus JJ, Wolff SB, Meyer EM, Tovote P, Courtin J, Herry C, Luthi A (2011) A disinhibitory microcircuit for associative fear learning in the auditory cortex. Nature 480:331–335PubMedCrossRefGoogle Scholar
  20. Linkenkaer-Hansen K, Nikouline VV, Palva JM, Ilmoniemi RJ (2001) Long-range temporal correlations and scaling behavior in human brain oscillations. J Neurosci 21:1370–1377PubMedGoogle Scholar
  21. Litwin-Kumar A, Doiron B (2012) Slow dynamics and high variability in balanced cortical networks with clustered connections. Nat Neurosci 15:1498–1505PubMedCrossRefGoogle Scholar
  22. Lowen SB, Cash SS, Poo M, Teich MC (1997) Quantal neurotransmitter secretion rate exhibits fractal behavior. J Neurosci 17:5666–5677PubMedGoogle Scholar
  23. Lowen SB, Ozaki T, Kaplan E, Saleh BE, Teich MC (2001) Fractal features of dark, maintained, and driven neural discharges in the cat visual system. Methods 24:377–394PubMedCrossRefGoogle Scholar
  24. Major G, Tank D (2004) Persistent neural activity: prevalence and mechanisms. Curr Opin Neurobiol 14:675–684PubMedCrossRefGoogle Scholar
  25. Miller KJ, Sorensen LB, Ojemann JG, den Nijs M (2009) Power-law scaling in the brain surface electric potential. PLoS Comput Biol 5:e1000609PubMedCentralPubMedCrossRefGoogle Scholar
  26. Milstein J, Mormann F, Fried I, Koch C (2009) Neuronal shot noise and Brownian 1/f2 behavior in the local field potential. PLoS One 4:e4338PubMedCentralPubMedCrossRefGoogle Scholar
  27. Parvizi J, Rangarajan V, Shirer WR, Desai N, Greicius MD (2013) The will to persevere induced by electrical stimulation of the human cingulate gyrus. Neuron 80:1359–1367PubMedCrossRefGoogle Scholar
  28. Wong KF, Wang XJ (2006) A recurrent network mechanism of time integration in perceptual decisions. J Neurosci 26:1314–1328PubMedCrossRefGoogle Scholar
  29. Zhang Z, Seguela P (2010) Metabotropic induction of persistent activity in layers II/III of anterior cingulate cortex. Cereb Cortex 20:2948–2957PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science Business Media New York (outside the USA) 2014

Authors and Affiliations

  1. 1.National Institute of Neurological Disorders and StrokeNational Institutes of HealthBethesdaUSA