Skip to main content

Modulated Neuronal Activity and Connectivity of Smoking Resist Using Real-Time fMRI Neurofeedback

  • Conference paper
  • 4369 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8228))

Abstract

Recent functional magnetic resonance imaging (fMRI) technique with real-time (rt) feedback has widely been adopted to regulate one’s own neuronal activity within regions-of-interest (ROIs). Despite the fact that the functional connectivity (FC) between ROIs has also been modulated via rt-fMRI neurofeedback (NF), however there is no study to explicitly provide the FC patterns in addition to neuronal activity levels during rt-fMRI NF trials. In this study, we adopted both neuronal activities within an ROI and FC patterns between ROIs to investigate a potential utility of the FC information. Fourteen heavy smokers could voluntarily control their brain activity based on the neurofeedback of both neuronal activation within an ROI related to smoking resist and FC patterns between ROIs. Our proposed rt-fMRI method appears to modulate not only the neuronal activity but also the neuronal connectivity levels.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Logothetis, N.K., Pauls, J., Augath, M., Trinath, T., Oeltermann, A.: Neurophysiological Investigation of the Basis of the fMRI Signal. Nature 412, 150–157 (2001)

    Article  Google Scholar 

  2. LaConte, S.M.: Decoding fMRI brain states in real-time. Neuroimage 56, 753–765 (2011)

    Article  Google Scholar 

  3. Soldati, N., Calhoun, V.D., Bruzzone, L., Jovicich, J.: The Use of a Priori Information in ICA-based Techniques for Real-Time fMRI: an Evaluation of Static/Dynamic and Spatial/Temporal Characteristics. Front. Hum. Neurosci. 7, 64 (2013)

    Google Scholar 

  4. de Charms, R.C., Maeda, F., Glover, G.H., Ludlow, D., Pauly, J.M., Soneji, D., Gabrieli, J.D., Mackey, S.C.: Control over Brain Activation and Pain Learned by Using Real-Time Functional MRI. Proc. Natl. Acad. Sci. U. S. A. 102, 18626–18631 (2005)

    Article  Google Scholar 

  5. Subramanian, L., Hindle, J.V., Johnston, S., Roberts, M.V., Husain, M., Goebel, R., Linden, D.: Real-Time Functional Magnetic Resonance Imaging Neurofeedback for Treatment of Parkinson’s Disease. J. Neurosci. 31, 16309–16317 (2011)

    Article  Google Scholar 

  6. Ruiz, S., Lee, S., Soekadar, S.R., Caria, A., Veit, R., Kircher, T., Birbaumer, N., Sitaram, R.: Acquired Self-Control of Insula Cortex Modulates Emotion Recognition and Brain Network Connectivity in Schizophrenia. Hum. Brain. Mapp. 34, 200–212 (2013)

    Article  Google Scholar 

  7. Linden, D.E., Habes, I., Johnston, S.J., Linden, S., Tatineni, R., Subramanian, L., Sorger, B., Healy, D., Goebel, R.: Real-Time Self-Regulation of Emotion Networks in Patients with Depression. PLoS One 7, e38115 (2012)

    Google Scholar 

  8. Hanlon, C.A., Hartwell, K.J., Canterberry, M., Li, X., Owens, M., Lematty, T., Prisciandaro, J.J., Borckardt, J., Brady, K.T., George, M.S.: Reduction of Cue-Induced Craving through Realtime Neurofeedback in Nicotine Users: The Role of Region of Interest Selection and Multiple Visits. Psychiatry. Res. 213, 79–81 (2013)

    Article  Google Scholar 

  9. Heatherton, T.F., Kozlowski, L.T., Frecker, R.C., Fagerström, K.O.: The Fagerström Test for Nicotine Dependence: a Revision of the Fagerström Tolerance Questionnaire. Br. J. Addict. 86, 1119–1127 (1991)

    Article  Google Scholar 

  10. Hartwell, K.J., Johnson, K.A., Li, X., Myrick, H., LeMatty, T., George, M.S., Brady, K.T.: Neural Correlates of Craving and Resisting Craving for Tobacco in Nicotine Dependent Smokers. Addict. Biol. 16, 654–666 (2011)

    Article  Google Scholar 

  11. Lee, J.H., Kim, D.Y., Kim, J.: Mesocorticolimbic Hyperactivity of Deprived Smokers and Brain Imaging. Neuroreport 23, 1039–1043 (2012)

    Article  Google Scholar 

  12. Van De Ville, D., Jhooti, P., Haas, T., Kopel, R., Lovblad, K.O., Scheffler, K., Haller, S.: Recovery of the Default Mode Network after Demanding Neurofeedback Training Occurs in Spatio-Temporally Segregated Subnetworks. Neuroimage 63, 1775–1781 (2012)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kim, DY., Lee, JH. (2013). Modulated Neuronal Activity and Connectivity of Smoking Resist Using Real-Time fMRI Neurofeedback. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8228. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42051-1_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-42051-1_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-42050-4

  • Online ISBN: 978-3-642-42051-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics