CA1 network model for place cell dynamics (Turi et al 2019)

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Biophysical model of CA1 hippocampal region. The model simulates place cells/fields and explores the place cell dynamics as function of VIP+ interneurons.
1 . Turi GF, Li W, Chavlis S, Pandi I, O’Hare J, Priestley JB, Grosmark AD, Liao Z, Ladow M, Zhang JF, Zemelman BV, Poirazi P, Losonczy A (2019) Vasoactive Intestinal Polypeptide-Expressing Interneurons in the Hippocampus Support Goal-Oriented Spatial Learning Neuron
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Hippocampus; Mouse;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell; Hippocampus CA1 basket cell; Hippocampus CA1 basket cell - CCK/VIP; Hippocampus CA1 bistratified cell; Hippocampus CA1 axo-axonic cell; Hippocampus CA1 stratum oriens lacunosum-moleculare interneuron ; Hippocampal CA1 CR/VIP cell;
Channel(s): I A; I h; I K,Ca; I Calcium; I Na, leak; I K,leak; I M;
Gap Junctions:
Receptor(s): GabaA; GabaB; NMDA; AMPA;
Simulation Environment: NEURON; Brian;
Model Concept(s): Place cell/field;
Implementer(s): Chavlis, Spyridon [schavlis at]; Pandi, Ioanna ;
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; GabaA; GabaB; AMPA; NMDA; I A; I K,leak; I M; I h; I K,Ca; I Calcium; I Na, leak;
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
Created on Tue Mar 27 09:03:49 2018.

@author: spiros
import numpy as np

def gridfield(theta, lambda_var, xo, yo, x, y):
    Description goes here
    th1 = np.array([np.cos(theta), np.sin(theta)]).reshape(-1, 1)
    th2 = np.array(
        [np.cos(theta + np.pi/3), np.sin(theta + np.pi/3)]).reshape(-1, 1)
    th3 = np.array([np.cos(theta + 2*np.pi/3),
                    np.sin(theta + 2*np.pi/3)]).reshape(-1, 1)

    x -= xo
    y -= yo

    y /= float(lambda_var)
    x /= float(lambda_var)

    p = np.array([x, y]).reshape(-1, 1)

    g = (1/4.5) * (np.cos(, th1)) +
                   np.cos(, th2)) + np.cos(, th3)) + 1.5).item()

    return g