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Inter Subject Correlation of Brain Activity during Visuo-Motor Sequence Learning

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Neural Information Processing (ICONIP 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8834))

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Abstract

Brain imaging using functional MRI allows us to understand brain function while participants are engaged in meaningful tasks. Traditionally the experimental paradigms have been limited to repeated presentation of stimuli to participants followed by a model-based analysis of the data. The Inter Subject Correlation (ISC) analysis allows a model-free analysis while participants are presented with naturalistic stimuli such as watching a movie. We extend the ISC approach to a learning paradigm in which participants are repeatedly performing a motor sequence in response to visual stimuli. We qualitatively compare the correlation results across learning sessions. The preliminary result we observe is shift of correlation activity in cerebellum across sessions. A model-based analysis identifying task related activity compared to baseline is also reported.

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References

  1. Huettel, S., Song, A., McCarthy, G.: Functional Magnetic Resonance Imaging, 2nd edn. Sinauer, Massachusetts (2009)

    Google Scholar 

  2. Brown, G., Yamada, S., Sejnowski, T.: Independent component analysis at the neural cocktail party, pp. 54–63 (January 2001)

    Google Scholar 

  3. Hasson, U., Nir, Y., Levy, I., Fuhrmann, G., Malach, R.: Intersubject Synchronization of Cortical Activity During Natural Vision, 1634 (2004)

    Google Scholar 

  4. Chandrasekhar Pammi, V., Miyapuram, K., Samejima, A.K., Bapi, R., Doya, K.: Changing the structure of complex visuo-motor sequences selectively activates the fronto-parietal network. NeuroImage 59 (2011)

    Google Scholar 

  5. Miyapuram, K.P.: Visuomotor Mappings and Sequence Learning: A Whole-Brain fMRI Investigation. M.Tech. Thesis, University of Hyderabad, India (2004)

    Google Scholar 

  6. Jola, C., McAleer, P., Grosbras, M., Love, S., Morison, G., Pollick, F.: Uni- and multisensory brain areas are synchronised across spectators when watching unedited dance recordings, pp. 265–284 (June 2013)

    Google Scholar 

  7. Kauppi, J.-P., Jääskeläinen, I., Sams, M., Tohka, J.: Inter-subject correlation of brain hemodynamic responses during watching a movie: localization in space and frequency (March 2010)

    Google Scholar 

  8. Regev, M., Honey, C., Simony, E., Hasson, U.: Selective and Invariant Neural Responses to Spoken and Written Narratives. The Journal of Neuroscience 33(40), 15978–15988 (2013)

    Article  Google Scholar 

  9. Wilson, S., Molnar-Szakacs, I., Iacoboni, M.: Beyond Superior Temporal Cortex: Intersubject Correlations in Narrative Speech Comprehension. Cerebral Cortex 18, 230–242 (2008)

    Article  Google Scholar 

  10. Schmalzle, R., Hacker, F., Renner, B., Honey, C., Schupp, H.: Neural Correlates of Risk Perception during Real-Life Risk Communication. The Journal of Neuroscience 33(25), 10340–10347 (2013)

    Article  Google Scholar 

  11. Nummenmaa, L., Smirnov, D., Lahnakoski, J., Glearean, E., Jaaskelainen, I., Sams, M., Hari, R.: Mental Action Simulation Synchronizes Action–Observation Circuits across Individuals. The Journal of Neuroscience 34(3), 748–757 (2014)

    Article  Google Scholar 

  12. Hasson, U., Malach, R., Heeger, D.: Reliability of cortical activity during natural stimulation. Trends Cogn. Sci. 14(1), 40 (2010)

    Article  Google Scholar 

  13. Pajula, J., Kauppi, J.-P., Tohka, J.: Inter-Subject Correlation in fMRI: Method Validation against Stimulus-Model Based Analysis, e41196 (2012)

    Google Scholar 

  14. Friston, K., Ashburner, J., Kiebel, S., Nichols, T., Penny, W.: Statistical Parametric Mapping: The Analysis of Functional Brain Images. Academic Press (2007)

    Google Scholar 

  15. Kauppi, J.-P., Pajula, J., Tohka, J.: A versatile software package for inter-subject correlation based analysis of fMRI (2014)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Cognitive Science Program, Indian Institute of Technology, Gandhinagar, India

    Krishna Prasad Miyapuram & Ujjval Pamnani

  2. Neural Computation Unit, Okinawa Institute of Science and Technology, Okinawa, Japan

    Kenji Doya

  3. Center for Neural & Cognitive Sciences, Department of Computer and Information Sciences, University of Hyderabad, India

    Raju S. Bapi

Authors
  1. Krishna Prasad Miyapuram
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  2. Ujjval Pamnani
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  3. Kenji Doya
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  4. Raju S. Bapi
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Faculty of Computer Science and Information Technology Building, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Chu Kiong Loo

  2. Department of Electronics and Communication Engineering,College of Engineering, Jalan IKRAM-UNITEN, Universiti Tenaga Nasional, 43009, Kajang, Selangor, Malaysia

    Keem Siah Yap

  3. School of Engineering and Information Technology, Murdoch University, South St, 6150, Murdoch, Western Australia, Australia

    Kok Wai Wong

  4. Department of Electrical and Electronics Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, 120-749, Seoul, South Korea

    Andrew Teoh

  5. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Ren’ai Road 111, SIP 215123, Suzhou, Jiangsu Province, China

    Kaizhu Huang

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© 2014 Springer International Publishing Switzerland

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Miyapuram, K.P., Pamnani, U., Doya, K., Bapi, R.S. (2014). Inter Subject Correlation of Brain Activity during Visuo-Motor Sequence Learning. In: Loo, C.K., Yap, K.S., Wong, K.W., Teoh, A., Huang, K. (eds) Neural Information Processing. ICONIP 2014. Lecture Notes in Computer Science, vol 8834. Springer, Cham. https://doi.org/10.1007/978-3-319-12637-1_5

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  • DOI: https://doi.org/10.1007/978-3-319-12637-1_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12636-4

  • Online ISBN: 978-3-319-12637-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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