• DocumentCode
    2222232
  • Title

    Independent components of oculomotor learning

  • Author

    Alkan, Yelda ; Alvarez, Tara L. ; Biswal, Bharat B. ; Vicci, Vincent R.

  • Author_Institution
    Dept. of Biomed. Eng., New Jersey Inst. of Technol., Newark, NJ, USA
  • fYear
    2009
  • fDate
    April 29 2009-May 2 2009
  • Firstpage
    163
  • Lastpage
    166
  • Abstract
    This research is an investigation of the visual circuit for saccadic and vergence eye movements using an oculomotor learning task to study the cerebral and cerebellar areas utilizing fMRI. Data from eight subjects were analyzed with analysis of functional neural images (AFNI) and the Infomax independent component analysis algorithm. This study showed that 1) neural activation is present in the prefrontal, frontal, parietal, occipital cortices, and cerebellar vermis (4/5) and cerebellar vermis (VI/VII) or declive for saccadic and vergence eye movements and 2) there are two distinct pathways involved in an oculomotor learning task. The first is a frontal-parietal and the second is cerebellar (VI/VII) pathway, for short-term oculomotor learning. These findings suggest that oculomotor learning utilizes two distinct circuits to learn a visual stimulus pattern.
  • Keywords
    biomechanics; biomedical MRI; eye; independent component analysis; neurophysiology; Infomax independent component analysis algorithm; analysis-of-functional neural image; cerebellar vermis (4/5); cerebellar vermis (VI/VII); fMRI; oculomotor learning; saccadic eye movement; vergence eye movement; visual circuit; visual stimulus pattern learning; Algorithm design and analysis; Circuits; Glass; Image analysis; Independent component analysis; Magnetic heads; Magnetic resonance imaging; Magnetic separation; Timing; USA Councils; AFNI; Informax-ICA; fMRI; saccades; vergence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Engineering, 2009. NER '09. 4th International IEEE/EMBS Conference on
  • Conference_Location
    Antalya
  • Print_ISBN
    978-1-4244-2072-8
  • Electronic_ISBN
    978-1-4244-2073-5
  • Type

    conf

  • DOI
    10.1109/NER.2009.5109260
  • Filename
    5109260