Rat hippocampus CA1¶

Approach:¶

The workflow is a sequence of independent steps manipulating volumetric data retrieved from the Neuroinformatics Platform. Each steps defines additional properties of the cells.

The sequence of steps is the following:

• Define the region of interest based on the parcellation given by the atlas

• Define cell positions based on given neuron densities

• Define excitatory/inhibitory properties based on given ratio

• Define ME-Type properties based on M-Type and E-Type ratio

• Define the morphology to be used based on available morphologies and previously defined properties

• Define cell orientation based on a computed orientation field in the volume

Input data:¶

Volume

Volume was adapted from Ropireddy et al., 2012

Cell composition

• Total number of cells: 350000 (adult rat - Bezaire and Soltesz, 2013)

• EI ratio: 89:11 (adult rat - Bezaire and Soltesz, 2013)

• Percentage of neuron types from (Bezaire and Soltesz, 2013 - adult rat)

Morphoelectrical-type composition

We collected 146 electrophysiological single cell recordings from different neuron types (Alex Thomson, Audrey Mercer and colleagues) (Wistar rat - for the methods see Hughes et al., 2000; Pawelzik et al., 2002). We classified the recordings on the basis of stereotypical firing patterns (electrical types, e-types) according to the Petilla Convention (Ascoli et al., 2008) in response to depolarizing step current injections. For some e-types, we had too few recordings and for this reason we restricted the e-types to classical accommodating (cAC), bursting accommodating (bAC) and classical non-accommodating (cNAC). Each morphology type (m-type) can show multiple firing patterns, leading to different morpho-electrical types (me-types).

Executing the Use Case¶

Execute the cell (SHIFT + ENTER) in the “Cell Placement Hippocampus Setup” notebook. Then navigate to the “Cell Placement Hippocampus” notebook and execute them sequentially (SHIFT + ENTER).

1. positioning neurons

   This step computes cell positions with downscaled densities as an illustration. It then displays the cell positions in a widget.

   

2. defining excitatory/inhibitory property

   This step computes the excitatory/inhibitory property based on the provided ratio and displays it in a widget.

   

3. defining M-Type and E-Type properties

   This step computes the M-Type property and E-Type property at the same time and displays them in a widget.

   M-Type property:

   

   E-Type property:

   

4. defining morphology for the cell position

   This step computes which morphology will be assigned to a particular cell position.

   

5. defining cell orientation

   This steps computes the 3 vector fields X, Y, and Z and uses them to orient each neuron.

   X vector field:

   

   Y vector field:

   

   Z vector field: