Skip to main content

Advertisement

SpringerLink
Log in

Uncovering Gamma in Visual Tasks

  • Original Paper
  • Published:
Brain Topography Aims and scope Submit manuscript

Abstract

Gamma is an important frequency band of the electroencephalogram (EEG), but its study has been impaired by problems with artefacts. This paper focuses on the artefacts caused by contraction of the extra-ocular muscles at the start of a saccade, which produces spurious gamma oscillations in the EEG. An algorithm was written and tested which detects and reduces the effect of this artefact. It involves novel adaptations of standard regression techniques which have traditionally been used to reduce blink artefacts, so as to render them applicable to the gamma band ocular artefact. Before the algorithm can be applied any power-line noise must be removed by noise cancellation and not notch filtering. The sharp, broadband gamma peak at around 200 ms was substantially reduced by the algorithm in all three subjects tested. However, there may be lower amplitude, task related, modulations in gamma which are uncovered when the artefact is reduced. The amplitude of the artefact had its largest positive value at the most anterior electrodes and its largest negative value at midline central and parietal electrodes, and these two sets of locations also showed the greatest reductions in gamma band magnitude after application of the algorithm. This study demonstrates the feasibility of reducing the saccade linked gamma band artefact.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Balaban CD, Weinstein JM (1985) The human pre-saccadic spike potential: influences of a visual target, saccade direction, electrode laterality and instructions to perform saccades. Brain Res 347:49–57

    Article  CAS  PubMed  Google Scholar 

  • Collewijn H (2001) Interocular timing differences in the horizontal components of human saccades. Vision Res 41:3413–3423

    Article  CAS  PubMed  Google Scholar 

  • Croft RJ, Barry RJ (2000) Removal of ocular artifact from the EEG: a review. Neurophysiol Clin 30:5–19

    Article  CAS  PubMed  Google Scholar 

  • Crone NE, Miglioretti DL, Gordon B, Lesser RP (1998) Functional mapping of human sensorimotor cortex with electrocorticographic spectral analysis. II. Event-related synchronization in the gamma band. Brain 121(Pt 12):2301–2315

    Google Scholar 

  • Engel AK, Singer W (2001) Temporal binding and the neural correlates of sensory awareness. Trends Cogn Sci 5:16–25

    Article  PubMed  Google Scholar 

  • Fries P, Reynolds JH, Rorie AE, Desimone R (2001) Modulation of oscillatory neuronal synchronization by selective visual attention. Science 291:1560–1563

    Article  CAS  PubMed  Google Scholar 

  • Fries P, Scheeringa R, Oostenveld R (2008) Finding gamma. Neuron 58:303–305

    Article  CAS  PubMed  Google Scholar 

  • Itier RJ, Latinus M, Taylor MJ (2006) Face, eye and object early processing: what is the face specificity? Neuroimage 29:667–676

    Article  PubMed  Google Scholar 

  • Jerbi K, Freyermuth S, Dalal S, Kahane P, Bertrand O, Berthoz A, Lachaux JP (2009) Saccade related gamma-band activity in intracerebral EEG: dissociating neural from ocular muscle activity. Brain Topogr 22:18–23

    Article  PubMed  Google Scholar 

  • Lachaux JP, George N, Tallon-Baudry C, Martinerie J, Hugueville L, Minotti L, Kahane P, Renault B (2005) The many faces of the gamma band response to complex visual stimuli. Neuroimage 25:491–501

    Article  PubMed  Google Scholar 

  • McMenamin BW, Shackman AJ, Maxwell JS, Greischar LL, Davidson RJ (2009) Validation of regression-based myogenic correction techniques for scalp and source-localized EEG. Psychophysiology 46:578–592

    Article  PubMed  Google Scholar 

  • Melloni L, Schwiedrzik CM, Wibral M, Rodriguez E, Singer W (2009) Response to: Yuval-Greenberg et al., “Transient induced gamma-band response in EEG as a manifestation of miniature saccades.” Neuron 58:429–441, Neuron 62:8–10

    Google Scholar 

  • Michel CM, Murray MM (2009) Discussing gamma. Brain Topogr 22:1–2

    Article  PubMed  Google Scholar 

  • Moster ML, Goldberg G (1990) Topography of scalp potentials preceding self-initiated saccades. Neurology 40:644–648

    CAS  PubMed  Google Scholar 

  • Semlitsch HV, Anderer P, Schuster P, Presslich O (1986) A solution for reliable and valid reduction of ocular artefacts, applied to the P300 ERP. Psychophysiology 23:695–703

    Article  CAS  PubMed  Google Scholar 

  • Shackman AJ, McMenamin BW, Slagter HA, Maxwell JS, Greischar LL, Davidson RJ (2009) Electromyogenic artefacts and electroencephalographic inferences. Brain Topogr 22:7–12

    Article  PubMed  Google Scholar 

  • Thickbroom GW, Mastaglia FL (1985) Presaccadic spike potential—investigation of topography and source. Brain Res 339:271–280

    Article  CAS  PubMed  Google Scholar 

  • Thickbroom GW, Mastaglia FL (1986) Presaccadic spike potential. Relation to eye movement direction. Electroencephalogr Clin Neurophysiol 64:211–214

    Article  CAS  PubMed  Google Scholar 

  • Traub RD, Spruston N, Soltesz I, Konnerth A, Whittington MA, Jefferys GR (1998) Gamma-frequency oscillations: a neuronal population phenomenon, regulated by synaptic and intrinsic cellular processes, and inducing synaptic plasticity. Prog Neurobiol 55:563–575

    Article  CAS  PubMed  Google Scholar 

  • Whitham EM, Pope KJ, Fitzgibbon SP, Lewis T, Clark CR, Loveless S, Broberg M, Wallace A, DeLosAngeles D, Lillie P et al (2007) Scalp electrical recording during paralysis: quantitative evidence that EEG frequencies above 20 Hz are contaminated by EMG. Clin Neurophysiol 118:1877–1888

    Article  PubMed  Google Scholar 

  • Whitham EM, Lewis T, Pope KJ, Fitzgibbon SP, Clark CR, Loveless S, DeLosAngeles D, Wallace AK, Broberg M, Willoughby JO (2008) Thinking activates EMG in scalp electrical recordings. Clin Neurophysiol 119:1166–1175

    Article  PubMed  Google Scholar 

  • Yuval-Greenberg S, Deouell LY (2009) The broadband-transient induced gamma-band response in scalp EEG reflects the execution of saccades. Brain Topogr 22:3–6

    Article  PubMed  Google Scholar 

  • Yuval-Greenberg S, Tomer O, Keren AS, Nelken I, Deouelll LY (2008) Transient induced gamma-band response in EEG as a manifestation of miniature saccades. Neuron 58:429–441

    Article  CAS  PubMed  Google Scholar 

  • Yuval-Greenberg S, Keren AS, Tomer O, Nelken I, Deouell LY (2009) Response to letter: Melloni et al., “Transient induced gamma-band response in eeg as a manifestation of miniature saccades.” Neuron 58:429–441, Neuron 62:10–12

    Google Scholar 

  • Zambarbieri D, Schmid R, Magenes G, Prablanc C (1982) Saccadic responses evoked by presentation of visual and auditory targets. Exp Brain Res 47(3):417–427

    Article  CAS  PubMed  Google Scholar 

  • Zion-Golumbic E, Golan T, Anaki D, Bentin S (2008) Human face preference in gamma-frequency EEG activity. Neuroimage 39:1980–1987

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

I would like to acknowledge the help and advice given by Dr Dominic ffytche and Dr Alex Sumich and assistance with EEG recording by Eleni Filippou. Also I would like to thank the reviewers for their constructive comments.

Author information

Authors and Affiliations

  1. Centre for Neuroimaging Sciences, Institute of Psychiatry, King’s College London, De Crespigny Park, PO Box 89, SE5 8AF, Denmark Hill, London, UK

    Judith F. Nottage

Authors
  1. Judith F. Nottage
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Judith F. Nottage.

Appendix 1

Appendix 1

The threshold function used in the current study is shown in Eq. 2. The signal at each time point is subtracted from the mean of the signal 8 ms before and after. Also the signal at time points 3.5 ms apart are added together since this acts to suppress the effect of surface EMG.

$$ F_{t} = 0.25 \times \left( {H_{t - 9.75} + H_{t - 7.25} } \right) + 0.25 \times \left( {H_{t + 9.75} + H_{t + 7.25} } \right) - 0.5 \times \left( {H_{t + 1.75} + H_{t - 1.75} } \right) $$
(2)

where F t = threshold function at time t; H t+9.75 = mean of the signal at the left and right eye electrodes, at t + 9.75 ms.

Note: with 2000 Hz sampling rate the threshold function is calculated between sampling points, not at the times of the EEG samples. A quadratic curve is fitted around the maximum to find the sampling point with the maximum threshold function.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nottage, J.F. Uncovering Gamma in Visual Tasks. Brain Topogr 23, 58–71 (2010). https://doi.org/10.1007/s10548-009-0129-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10548-009-0129-y

Keywords

Search

Navigation