Event Abstract

Global Structural Brain Networks underlining Binocular Rivalry

  • 1 Indiana University, United States
  • 2 University of Tokyo, Japan
  • 3 AIST, Japan

This study reports how the global organization of the structural brain network relates with stability of perceptions in Binocular Rivalry.
Binocular Rivalry is a phenomenon which is shown when right and left eyes are presented with different images simultaneously at the same retinal position, then the perceptions of the two images compete, and shift back and forth between them. For many decades, psychophysical and neuroscientific researches have asked where the competing neuron pools exist in our brain: Especially, contributions of low-level visual regions, such as the primary visual cortex or lateral geniculate nucleus, and/or high-level visual regions, such as extrastriate visual regions, were often discussed (Logothetis et al., 1996; Lee, Blake, 1999; Kovacs et al., 1996; Lee, Blake, 2004; Logothetis, Schall, 1989; Tong et al., 1998; Wunderlich, et al., 2005; Haynes et al., 2005). Additional to these researches, several fMRI studies reported that prefrontal and parietal regions also become active at the times when perceptions alternate (Lumer, Friston, 1998; Knapen et al., 2011). Although many studies reported contribution of various brain regions to Binocular Rivalry, there is no study about what structural brain networks lay behind dynamic interactions among these various brain regions.
From these backgrounds, we asked how structural brain networks relate with perceptual alternation phenomenon in Binocular Rivalry. Especially, we tried to find properties as the global organization of the structural brain network.

Ten male and seven female right-handed volunteers (aged from 20 to 29, normal or corrected-to-normal vision) joined the experiment. After informed consents, we performed the Binocular Rivalry experiment for one hour total and DTI recordings. The analysis process consisted of four proceedures: First, we performed noise reductions and co-registrations, and calculated three dimensional maps of Fractional Anisotropy (FA) values. Second, we created 68 cortical and 16 subcortical region of interests (ROIs) in FreeSurfer. Third, we reconstructed fiber tracts connecting between each pair of these ROIs by tracking the vector map of FA values using the FACT algorithm (Mori, Barker, 1999). Fourth, we evaluated correlations between the differences among the mean FA values in individuals’ fiber tract bundles and the differences among individuals’ speeds of perceptual alternation. Here, the fiber tract bundle showing positive or negative correlation was named positive or negative Correlation Networks (CNs) respectively.

Figure (a) shows a spatial map of these two types of fiber tract bundles, which were entangled with each other. Red lines indicate positive CNs, and blue lines indicate negative CNs. The thick lines represent significantly strong connections because the Correlation 0.7 corresponds with expected value of false discovery rate 0.05 [Benjamini, Hochberg, 1995]. From these entangled networks, we observed the difference of averaged values of the Correlations for cortical regions and for subcortical regions. Figure (b) is the average of the correlations in cortico-cortical connections. Figure (c) is the averaged correlation in subcortico-subcortical connections. Figure (d) is the comparison between averages of all bars in (b) and (c). These results showed that all subcortical regions strongly connect with negative CNs, and that many cortical regions strongly connect with positive CNs. The ratio of number of positive to negative connections also showed the same inverse trend between cortex and subcortex as averages of correlations.

This study revealed, for the first time, the global organization of brain networks relating to stabilization and destabilization of perceptual alternation. Revealing the general contrast between the contribution of the cortical regions to destabilization and the contribution of the subcortical regions to stabilization of perceptions in Binocular Rivalry will help to give deeper understandings of interactions between many brain regions and will further develop this idea of global interaction beyond the individual brain regions previously discussed.

Figure 1


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Keywords: Binocular Rivalry, Whole Brain Network, Diffusion Tensor Imaging, Subcortex, Cortex, Stability of perception

Conference: Neuroinformatics 2013, Stockholm, Sweden, 27 Aug - 29 Aug, 2013.

Presentation Type: Poster

Topic: Neuroimaging

Citation: Shimono M and Niki K (2013). Global Structural Brain Networks underlining Binocular Rivalry. Front. Neuroinform. Conference Abstract: Neuroinformatics 2013. doi: 10.3389/conf.fninf.2013.09.00086

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Received: 08 Apr 2013; Published Online: 11 Jul 2013.

* Correspondence: Dr. Masanori Shimono, Indiana University, Bloomington, IN, United States, nori417@gmail.com