Grid cells are neurons in the medial entorhinal cortex (MEC) that are activated when the subject passes through multiple locations arranged in a hexagonal grid. Grid cells, along with other cells in the MEC such as head direction and speed cells, form circuits with place cells to create a comprehensive positioning system in the brain.
This project therefore attempts to provide a classification system to identify grid cells located in the medial entorhinal cortex in order to better understand the navigational building blocks necessary for important memory processes.
Performs the established grid scoring methods, which includes analyzing the periodicity of the autocorrelation matrix's correlation curve.
Extracts any significant periodict patterns from the firing rate map by utilizing the properties of two-dimensional Fourier transformations.
Identifies significant contributing components of the Fourier spectrogram by calculating the distribution of the average power of pixels within a defined annulus of various radial lengths and comparing this to the random distribution.
- python
- math
- numpy
- scipy
- matplotlib
Neuronal data was downloaded from the Kavli Institue for Systems Neuroscience Sargolini et al 2006 data set.