Analysis of Morris Water Maze data with Bayesian statistical methods

Neuroscientists commonly use a Morris Water Maze to assess learning in rodents. In his kind of a maze, the subjects learn to swim toward a platform hidden in opaque water as they orient themselves according to the cues on the walls. This protocol presents a challenge to statistical analysis, because an artificial cut-off must be set for those experimental subjects that do not reach the platform so as they do not drown from exhaustion. This fact leads to the data being right censored. In our experimental data, which compares learning in rodents that have chemically induced symptoms of schizophrenia to a control group of rodents a cut-off of 60 seconds was used, and is the mode of the distribution. Utilizing Bayesian inferential procedures, we account for the censoring in the data and compare the results of learning between the treatment and control group

2009- 2010 UNLV McNair Journal

Journal articles based on research conducted by undergraduate students in the McNair Scholars Program Table of Contents Biography of Dr. Ronald E. McNair Statements: Dr. Neal J. Smatresk, UNLV President Dr. Juanita P. Fain, Vice President of Student Affairs Dr. William W. Sullivan, Associate Vice President for Retention and Outreach Mr. Keith Rogers, Deputy Executive Director of the Center for Academic Enrichment and Outreach McNair Scholars Institute Staf

2011-2012 UNLV McNair Journal

Journal articles based on research conducted by undergraduate students in the McNair Scholars Program Table of Contents Biography of Dr. Ronald E. McNair Statements: Dr. Neal J. Smatresk, UNLV President Dr. Juanita P. Fain, Vice President of Student Affairs Dr. William W. Sullivan, Associate Vice President for Retention and Outreach Mr. Keith Rogers, Deputy Executive Director of the Center for Academic Enrichment and Outreach McNair Scholars Institute Staf

A consistent map in the medial entorhinal cortex supports spatial memory

Abstract The medial entorhinal cortex (MEC) is hypothesized to function as a cognitive map for memory-guided navigation. How this map develops during learning and influences memory remains unclear. By imaging MEC calcium dynamics while mice successfully learned a novel virtual environment over ten days, we discovered that the dynamics gradually became more spatially consistent and then stabilized. Additionally, grid cells in the MEC not only exhibited improved spatial tuning consistency, but also maintained stable phase relationships, suggesting a network mechanism involving synaptic plasticity and rigid recurrent connectivity to shape grid cell activity during learning. Increased c-Fos expression in the MEC in novel environments further supports the induction of synaptic plasticity. Unsuccessful learning lacked these activity features, indicating that a consistent map is specific for effective spatial memory. Finally, optogenetically disrupting spatial consistency of the map impaired memory-guided navigation in a well-learned environment. Thus, we demonstrate that the establishment of a spatially consistent MEC map across learning both correlates with, and is necessary for, successful spatial memory