Encyclopedia of Computational Neuroscience

2015 Edition
| Editors: Dieter Jaeger, Ranu Jung

Decoding Field Potentials

  • Yan Tat Wong
  • Bijan PesaranEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-6675-8_704



The local field potential (LFP) is believed to represent the aggregated neuronal activity of populations of neurons. LFP activity encodes information related to the control of movements as well as information about sensory and other cognitive processes. LFP decoding refers to the process of extracting features of these processes from the measured LFP signals. LFP decoding is typically performed for a brain-machine interface application to allow control of an external device such as a prosthetic limb or a cursor on a screen.

Detailed Description


Neuromotor prosthesis is a class of brain-machine interfaces (BMIs) that aims to restore lost motor function by decoding control information from neural signals. The local field potential (LFP) is one such neural signal that can be utilized. The LFP is operationally defined as the low-frequency components (<~300 Hz) of neural activity recorded extracellularly using microelectrodes and...

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  1. Aggarwal V, Mollazadeh M, Davidson AG, Schieber MH, Thakor NV (2013) State-based decoding of hand and finger kinematics using neuronal ensemble and LFP activity during dexterous reach-to-grasp movements. J Neurophysiol 109:3067–3081PubMedCentralPubMedGoogle Scholar
  2. Andersen RA, Musallam S, Pesaran B (2004) Selecting the signals for a brain-machine interface. Curr Opin Neurobiol 14:720–726PubMedGoogle Scholar
  3. Bai O, Lin P, Vorbach S, Li J, Furlani S, Hallett M (2007) Exploration of computational methods for classification of movement intention during human voluntary movement from single trial EEG. Clin Neurophysiol 118:2637–2655PubMedCentralPubMedGoogle Scholar
  4. Bansal AK, Vargas-Irwin CE, Truccolo W, Donoghue JP (2011) Relationships among low-frequency local field potentials, spiking activity, and 3-D reach and grasp kinematics in primary motor and ventral premotor cortices. J Neurophysiol 105:1603–1619PubMedCentralPubMedGoogle Scholar
  5. Buzsáki G, Draguhn A (2004) Neuronal oscillations in cortical networks. Science 304:1926–1929PubMedGoogle Scholar
  6. Buzsáki G, Anastassiou CA, Koch C (2012) The origin of extracellular fields and currents–EEG, ECoG, LFP and spikes. Nat Rev Neurosci 13:407–420PubMedGoogle Scholar
  7. Donner TH, Siegel M (2011) A framework for local cortical oscillation patterns. Trends Cogn Sci 15:191–199PubMedGoogle Scholar
  8. Flint RD, Lindberg EW, Jordan LR, Miller LE, Slutzky MW (2012a) Accurate decoding of reaching movements from field potentials in the absence of spikes. J Neural Eng 9:046006PubMedCentralPubMedGoogle Scholar
  9. Flint RD, Wright ZA, Slutzky MW (2012b) Control of a biomimetic brain machine interface with local field potentials: performance and stability of a static decoder over 200 days. Proc Ann Int Conf IEEE Eng Med Biol Soc 2012:6719–6722Google Scholar
  10. Fries P (2005) A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends Cogn Sci 9:474–480PubMedGoogle Scholar
  11. Hwang EJ, Andersen RA (2013) The utility of multichannel local field potentials for brain-machine interfaces. J Neural Eng 10:046005PubMedCentralPubMedGoogle Scholar
  12. Markowitz DA, Wong YT, Gray CM, Pesaran B (2011) Optimizing the decoding of movement goals from local field potentials in Macaque cortex. J Neurosci 31:18412–18422PubMedCentralPubMedGoogle Scholar
  13. Mehring C, Rickert J, Vaadia E, Cardosa de Oliveira S, Aertsen A, Rotter S (2003) Inference of hand movements from local field potentials in monkey motor cortex. Nat Neurosci 6:1253–1254PubMedGoogle Scholar
  14. Mitra P, Pesaran B (1999) Analysis of dynamic brain imaging data. Biophys J 76:691–708PubMedCentralPubMedGoogle Scholar
  15. Mulliken GH, Musallam S, Andersen RA (2008) Decoding trajectories from posterior parietal cortex ensembles. J Neurosci 28:12913–12926PubMedCentralPubMedGoogle Scholar
  16. Pesaran B, Pezaris JS, Sahani M, Mitra PP, Andersen RA (2002) Temporal structure in neuronal activity during working memory in macaque parietal cortex. Nat Neurosci 5:805–811PubMedGoogle Scholar
  17. Pesaran B, Nelson MJ, Andersen RA (2008) Free choice activates a decision circuit between frontal and parietal cortex. Nature 453:406–409PubMedCentralPubMedGoogle Scholar
  18. Polikov VS, Tresco PA, Reichert WM (2005) Response of brain tissue to chronically implanted neural electrodes. J Neurosci Methods 148:1–18PubMedGoogle Scholar
  19. Scherberger H, Jarvis MR, Andersen RA (2005) Cortical local field potential encodes movement intentions in the posterior parietal cortex. Neuron 46:347–354PubMedGoogle Scholar
  20. Schomburg EW, Anastassiou CA, Buzsáki G, Koch C (2012) The spiking component of oscillatory extracellular potentials in the rat hippocampus. J Neurosci 32:11798–11811PubMedCentralPubMedGoogle Scholar
  21. Shpigelman L, Lalazar H, Vaadia E (2009) Kernel-arma for hand tracking and brain-machine interfacing during 3D motor control. Adv Neural Info Process Syst 21:1489–1496Google Scholar
  22. Siegel M, Donner TH, Engel AK (2012) Spectral fingerprints of large-scale neuronal interactions. Nat Rev Neurosci 13:121–134PubMedGoogle Scholar
  23. Wessberg J, Stambaugh CR, Kralik JD, Beck PD, Laubach M, Chapin JK, Kim J, Biggs SJ, Srinivasan MA, Nicolelis MA (2000) Real-time prediction of hand trajectory by ensembles of cortical neurons in primates. Nature 408:361–365PubMedGoogle Scholar
  24. Wu W, Gao Y, Bienenstock E, Donoghue JP, Black MJ (2006) Bayesian population decoding of motor cortical activity using a Kalman filter. Neural Comput 18:80–118PubMedGoogle Scholar
  25. Zhuang J, Truccolo W, Vargas-Irwin C, Donoghue JP (2010) Decoding 3-D reach and grasp kinematics from high-frequency local field potentials in primate primary motor cortex. IEEE Trans Biomed Eng 57:1774–1784PubMedCentralPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Center for Neural ScienceNew York UniversityNew YorkUSA