Dendritic Impedance in Neocortical L5 PT neurons (Kelley et al. 2021)

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We simulated chirp current stimulation in the apical dendrites of 5 biophysically-detailed multi-compartment models of neocortical pyramidal tract neurons and found that a combination of HCN channels and TASK-like channels produced the best fit to experimental measurements of dendritic impedance. We then explored how HCN and TASK-like channels can shape the dendritic impedance as well as the voltage response to synaptic currents.
1 . Kelley C, Dura-Bernal S, Neymotin SA, Antic SD, Carnevale NT, Migliore M, Lytton WW (2021) Effects of Ih and TASK-like shunting current on dendritic impedance in layer 5 pyramidal-tract neurons. J Neurophysiology 125:1501-1516 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Neocortex L5/6 pyramidal GLU cell; Neocortex M1 L5B pyramidal pyramidal tract GLU cell;
Channel(s): I h; TASK channel;
Gap Junctions:
Simulation Environment: NEURON; Python; NetPyNE;
Model Concept(s): Impedance;
Implementer(s): Kelley, Craig;
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; Neocortex M1 L5B pyramidal pyramidal tract GLU cell; I h; TASK channel;
from getCells import AckerAnticCell
import numpy as np
import sys
from import savemat
from math import nan

pt_cell = AckerAnticCell()

sec_list = [pt_cell.apical[15],

soma_seg = pt_cell.soma[0](0.5)

from chirpUtils import applyChirp
from chirpUtils import getChirp
amp = 0.0025
amp = amp * 10 # as per srdjan's suggestion
f0, f1, t0, Fs, delay = 0.5, 50, 50, 1000, 5 # 12 # original for all cells
I, t = getChirp(f0, f1, t0, amp, Fs, delay)

loc = 0.5
for sec in sec_list:
    out = applyChirp(I, t, sec(loc), soma_seg, t0, delay, Fs, f1, out_file_name='/u/craig/L5PYR_Resonance/amplitude_test/' + str(sec))

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