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Structural neural correlates of prosaccade and antisaccade eye movements in healthy humans.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

  • Ulrich Ettinger
  • Elena Antonova
  • Trevor J. Crawford
  • Martina T. Mitterschiffthaler
  • Sanchayita Goswani
  • Tonmoy Sharma
  • Veena Kumari
<mark>Journal publication date</mark>15/01/2005
Issue number2
Number of pages8
Pages (from-to)487-494
Publication StatusPublished
<mark>Original language</mark>English


We previously reported that prosaccade amplitude gain and antisaccade error rate are correlated with cerebellar and posterior frontal grey matter volume, respectively. This study sought to replicate and extend these findings in a sample of 32 right-handed, healthy volunteers (14 males, 18 females). Participants underwent structural magnetic resonance imaging (MRI) at 1.5 Tand an off-line eye movement assessment using infrared oculography at 500 Hz. Separate blocks of prosaccades and antisaccades were carried out (60 trials each). Optimised volumetric voxel-based morphometry (VBM) implemented in SPM99 was used to investigate the relationship of saccadic performance measures to regional grey matter volume, covarying for age. A significant negative correlation was obtained between prosaccade spatial error and grey matter volume in the right inferior cerebellar lobe (lobule VIIIB, extending into the vermis, centred at x = 11; y =64; z =61), indicating that more grey matter volume in this area was associated with better spatial accuracy.On the antisaccade task, the error rate was significantly negatively correlated with grey matter volume in the right middle frontal gyrus (Brodmann area 6) in an area anterior to the frontal eye field (centred at x = 27; y = 18; z = 50), indicating that more grey matter volume in this area was associated with fewer antisaccade errors. These findings extend our previous observations by identifying the relationship between brain structure and saccadic performance on a spatially highly localised scale and support the validity of structural neuroimaging methods in delineating the neural mechanisms underlying human oculomotor control.