Vertical System (VS) tangential cells network model (Trousdale et al. 2014)

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Network model of the VS tangential cell system, with 10 cells per hemisphere. Each cell is a two compartment model with one compartment for dendrites and one for the axon. The cells are coupled through axonal gap junctions. The code allows to simulate responses of the VS network to a variety of visual stimuli to investigate coding as a function of gap junction strength.
1 . Trousdale J, Carroll SR, Gabbiani F, Josic K (2014) Near-optimal decoding of transient stimuli from coupled neuronal subpopulations. J Neurosci 34:12206-22 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Axon; Synapse; Dendrite;
Brain Region(s)/Organism:
Cell Type(s): Fly vertical system tangential cell;
Gap Junctions: Gap junctions;
Receptor(s): Nicotinic; GabaA;
Transmitter(s): Acetylcholine; Gaba;
Simulation Environment: Python;
Model Concept(s): Activity Patterns; Spatio-temporal Activity Patterns; Simplified Models; Invertebrate; Connectivity matrix;
Implementer(s): Gabbiani, F; Trousdale, James [jamest212 at];
Search NeuronDB for information about:  Nicotinic; GabaA; Acetylcholine; Gaba;
Function:     axis_rot_mat

Arguments:    u - Unit vector in the direction of the axis of rotation.
              th - Magnitude of rotation. Positive values yield a clockwise rotation.
Output:       A size (3,3) rectangular coordinate rotation matrix.
Description:  When applied to a rectangular coordinate, the returned matrix rotates that point about the axis in the 
              direction of u, clockwise by an amount th.

Authors:     James Trousdale -

import numpy as np

from numpy import sin as sin
from numpy import cos as cos

def axis_rot_mat(u,th):
    rotmat = [[cos(th)+u[0]**2*(1-cos(th)),u[0]*u[1]*(1-cos(th))-u[2]*sin(th),u[0]*u[2]*(1-cos(th))+u[1]*sin(th)],
    return np.array(rotmat)

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