An attempt at probing the human mEC for grid cell scale layers using a free-navigation virtual reality task and functional magnetic resonance imaging
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2015-08-31
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en
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Abstract
It has been postulated the entorhinal cortex (EC) plays an inte-
gral role in the brain's navigation and environment mapping system.
The EC contains various spatially tuned cells, amongst which are the
grid cells: cells with ring patterns that span the environment in tri-
angular grids. These ring patterns di er in orientation, phase and
scale between cells, and this information can be used for cognitively
encoding Euclidean space, thereby contributing to the mechanisms
of self-location in spatial environments. Several implanted electrode-
recording studies have shown that in rats and bats, the scales of the
grids represented by the cells increase as one records from cells going
from the dorsomedial to ventrolateral EC, but in non-human primates,
this small-to-large eld layout exists to be in the posterior-to-anterior
axis due to the di erent orientation of the EC. In this study we at-
tempted to develop a method to show and quantify this layout in
humans through non-invasive functional magnetic resonance imaging
(fMRI). We approached this problem by using a General Linear Model
(GLM) with adaptation regressor models, based on data gained from
a virtual reality free-navigation task. In the process of investigating,
we found that the regressors extracted from the available data are
too correlated to be distinguishable. We hypothesize one potential
cause for this correlation, namely: the amount of movement stops
within a subject's path. Using this knowledge, future virtual reality
experiments where movement stops are discouraged could provide the
necessary data to extrapolate the small-to-large grid eld layout in
the human EC using fMRI.
Keywords: fMRI, adaptation, regression, regressors, RSA, repre-
sentational similarity analysis, grid cell, entorhinal cortex, movement,
navigation.
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Faculteit der Sociale Wetenschappen