1. Introduction

This package contains validation tests for models of hippocampus, based on the SciUnit framework and the NeuronUnit package. As in SciUnit, in HippoUnit tests four main classes are implemented: the Test class, the Model class, the Capabilities class and the Score class.

The tests of HippoUnit automatically run simulations on single-cell models that mimic the electrophysiological protocol from which the target experimental data were derived. Then the behavior of the model is evaluated and quantitatively compared to the experimental data using various feature-based error functions.

Current tests cover somatic behavior and signal propagation and integration in apical dendrites of hippocampal CA1 pyramidal cell models.

Feature errors: Z-score (the difference of model feature value from the exerimental mean feature value in the unit of the experimental SD.)

1.1. SomaticFeaturesTest

The Somatic Features Test can be used for both pyramidal cells and interneurons. It evaluates the model against various eFEL features under somatic current injection of varying amplitudes.

Score type: average of Z-Scores.

1.2. DepolarizationBlockTest

Aims to determine whether the model enters depolarization block to prolonged, high intensity somatic current stimulus.

Features tested:

  • Ith: the threshold current to reach the depolarization block, the amplitude of the current injection at which the cell exhibits the maximum number of spikes. In the test two separate features are evaluated: the current intensity to which the model fires the maximum number of action potentials, and the current intensity before the model enters depolarization block. If these two are not equal a penalty is added to the score.

  • Veq: the average equilibrium value during the depolarization block, average of the membrane potential over the last 100 ms of a current pulse 50 pA above Ith.

(Bianchi et al. (2012) J Comput Neurosci, 33: 207-225)

Score type: Average of Z-Scores plus penalty if the two htreshold features (described above) differ. If the model did not enter depolarization block the Score is a 100 penalty.

1.3. BackpropagatingAPTest

The test evaluates the mode and efficacy of back-propagating action potentials on the apical trunk in locations of different distances from the soma. The amplitude of the first and last AP of around 15 Hz train is compared to experimental data from Golding et al. 2001 (J Neurophysiol 86:2998-3010).

Score type: average of Z-scores.

1.4. PSPAttenuationTest

Evaluates how much the post synaptic potential (using EPSC stimulus) attenuates from the dendrite (different distances) to the soma. The soma/dendrite attenuation is compared to data from Magee & Cook 2000 (Nat Neurosci 3:895-903).

Score type: average of Z-scores.

1.5. ObliqueIntegrationTest

Tests signal integration in oblique dendrites for increasing number of synchronous and asynchronous synaptic inputs.

A defalt synapse model is provided in this tets which consists of the Exp2Syn built in synapse of NEURON (as the AMPA component) and an additional NMDA receptor model with Jahr & Stevens voltage dependance and rise and decay time constants of 3.3 and 102.38 ms respectively. The time constant values used here are Q10 corrected values from McDermott et al. 2006. Q10 values for the rise and decay time constants are 2.2 (Hestrin et al., 1990) and 1.7 (Korinek et al., 2010) respectively.

It is also possible to use the model’s own AMPA and NMDA mechanisms.

Features tested:

  • voltage threshold: the upper limit of the threshold for dendritic spike initiation (an expected somatic depolarization at wich step like dV/dt increase occur)

  • proximal threshold

  • distal threshold

  • degree of nonlinearity at threshold

  • suprathreshold degree of nonlinearity

  • peak derivative of (somatic voltage) at threshold

  • peak amplitude of somatic EPSP

  • time to peak of somatic EPSP

  • degree of nonlinearity in the case of asynchronous inputs

(A. Losonczy and J. C. Magee (2006) Neuron, 50: 291-307)

Score used: Average of Z-scores. (Also available: p value from T-test. If the p value < 0.05, the model mean differs from the experimental mean)

1.6. Run HippoUnit

See the example jupyter notebooks at https://github.com/KaliLab/HippoUnit_demo