FullSimulation

This is the folder where the core simulation is built and run.

Files

bmtk_modifications.py

Contains run time modications to BMTK. Just import and run modify_bmtk().

Connections.csv

Contains information for each synapse in the simulation. Created during the run step.

Columns:

  • Node ID: the integer id of the presynaptic node within its population (exc, prox_inh, dist_inh)

  • Distance: float representing the distance (um) from the synapse to the soma

  • Conductance: the weight of the synapse (already scaled by distance)

  • Type: what part of the cell the synapse is on (soma, dend, apic)

  • Name: the full string that NEURON associates with the postsynaptic segment.

  • Source Population: the node population that the presynaptic node is a member of (exc, prox_inh, dist_inh)

  • Release Probability: release probability for the synapse

FunctionalGroups.csv

Contains the functional group id for each excitatory presynaptic node. Created during the build step by SimulationBuilder.save_groups

NetParams.json

Contains parameters for the simulation that SimulationBuilder uses.

Structure:

  • “cells”: bmtk parameters for building the cell

    • “dynamic_params”: a JSON file of conductances

    • “model_template”: the hoc file used to build the cell

    • “morphology”: the file containging the cell morphol0gy

    • “model_processing”: a function BMTK will use to modify the cell

    • “segments_file”: csv file containing all of the cell’s segments

  • “lengths”: total lengths of different types of segments (um)

    • “basal_dist”: basal dendrites more than 50 um from the soma,

    • “basal_prox”: basal dendrites less than 50 um from the soma,

    • “apic”: apical dendrites

  • “syn_density”: number of synapses per um

    • “exc”: excitatory synapses,

    • “inh”: inhibitory synapses

  • “n_soma_syns”: number of (PV+) synapses on the soma,

  • “divergence”: distributions of connections per cell pairing

    • “exc”: uniform with {“min”, “max”} counts,

    • “peri_inh”: normal with {“m”: mean, “s”: standard deviation, “min”:floor, “max”:cap},

    • “basal_inh”: normal with {“m”: mean, “s”: standard deviation, “min”:floor, “max”:cap},

    • “apic_inh”: normal with {“m”: mean, “s”: standard deviation, “min”:floor, “max”:cap},

  • “groups”: properties of functional groups

    • “cells_per_group”: number of cells per functional group,

    • “cluster_radius”: radius of the sphere that clusters are constrained to,

    • “group_radius”: radius of the sphere that groups are constrained to

  • “file_current_clamp”: name of file to use as current clamp

  • “record_cellvars”: cellvars to record and on what part of the cell

    • “vars”: variable name

    • “locs”: location on cell (“all”, “soma”, “axon”, “apic”, “dend”)

  • “inh_frs”: inhibitory firing rates

    • “proximal”: PV+, normal with {“m”:mean, “s”:standard deviation},

    • “distal”: SOM+, normal with {“m”:mean, “s”:standard deviation}

  • “time”: {“start”:when input should start (ms),”stop”:simulation run time (ms)},

  • “dL”: target length of each segment,

  • “dt”: time (ms) between each simulation step,

  • “inh_shift”: how many ms the average excitation trace is shifted to make the inhibition noise trace

L2-3NetParams.csv

Same structure as NetParams.csv above. This is the parameters file for an L2-3 cell used. The cell is from the Allen Cell Database: https://celltypes.brain-map.org/experiment/electrophysiology/477127614.

Segments.csv

Contains information about every segment in the morphology. Each segment is approximately 1 um in length.

Columns:

  • BMTK ID: the ID that bmtk associates with the segments’s section

  • X: standardized (0 to 1) distance along the segment’s section

  • Type: whether the segment is soma, apic, dend (basal), or axon

  • Sec ID: the ID of the segments’s section within the morphology

  • Distance: length (um) of closest path to soma

  • Coord X: x coordinate (um) of the segment

  • Coord Y: y coordinate (um) of the segment

  • Coord Z: z coordinate (um) of the segment

batch_expanse_build.sh/batch_expanse_run.sh

Batch scripts used to build and run the simulation on Expanse.

synapses.py

Contains functionality called in the run step of the simulation. Used to set the parameters for different synapses, including things like weight and release probability.

build_network.py

Contains the class SimulationBuilder which performs the build step of the simulation. This uses BMTK to create files that are then loaded in for the simulation step.

run_network.py