An attempt at probing the human mEC for grid cell scale layers using a free-navigation virtual reality task and functional magnetic resonance imaging

Simple item page
dc.contributor.advisorGerven, M.A.J. van
dc.contributor.advisorGrabovetsky, A.V.
dc.contributor.advisorDoeller, C.
dc.contributor.authorBergman, W.A.L.
dc.date.issued2015-08-31
dc.description.abstractIt 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.en_US
dc.embargo.lift2036-07-31
dc.identifier.urihttp://hdl.handle.net/123456789/1870
dc.language.isoenen_US
dc.thesis.facultyFaculteit der Sociale Wetenschappenen_US
dc.thesis.specialisationBachelor Artificial Intelligenceen_US
dc.thesis.studyprogrammeArtificial Intelligenceen_US
dc.thesis.typeBacheloren_US
dc.titleAn attempt at probing the human mEC for grid cell scale layers using a free-navigation virtual reality task and functional magnetic resonance imagingen_US
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Bergman, T._BA_Thesis_2015.pdf
Size:
3.62 MB
Format:
Adobe Portable Document Format
Description:
Thesis text
Download
Collections
Faculteit der Sociale Wetenschappen