项目作者: acnavasolive

项目描述 :
The LCN-HippoModel is a biophysically realistic model of CA1 pyramidal cells aimed to get novel insights on firing dynamics in deep and superficial populations during the theta rhythm.
高级语言: Python
项目地址: git://github.com/acnavasolive/LCN-HippoModel.git
创建时间: 2019-09-10T13:28:28Z
项目社区:https://github.com/acnavasolive/LCN-HippoModel

开源协议:

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LCN-HippoModel

Theta rhythm

One of the most studied brain rhythm is the theta rhythm. Theta (4-12 Hz) is considered
the “on-line” status of the hippocampus, a highly rhythmic activity that acts as a global
synchronizer mechanism for encoding and information processing. During a theta cycle different
neuronal populations of the hippocampus fire sequentially: each one at a distinct preferred phase.
Moreover, it has been recently discovered that pyramidal neurons of the CA1 hippocampal region,
generally considered a homogeneous population, can be classified into deep and superficial:
not only each cell type shows a different preferred phase along theta cycles, but also a different
response in other hippocampal rhythm, sharp wave-ripples, an oscillation associated to the
consolidation of memory. Understanding how this coordination holds up hippocampal
functions as spatial navigation and memory, is a major question in the field.

Biophysical realism

The LCN-HippoModel is a biophysically realistic model of CA1 pyramidal cells aimed to get
novel insights on firing dynamics in deep and superficial populations during the theta rhythm, and
the role of the differential contribution of both the excitatory and inhibitory synaptic inputs,
and the biophysical intrinsic properties.

The model includes known excitatory and inhibitory inputs, using morphologically reconstructions
from NeuroMorpho (http://neuromorpho.org/) (a public database), and a precise distribution of the
main ion channels via the Hodking-Huxley multi-compartment formalism in the NEURON+Python
(https://www.neuron.yale.edu/neuron/) platform.

To provide diversity among the pyramidal cells, we generated several sets of intrinsic properties
and, called individuals, through a genetic algorithm (GA). The GA allowed us to identify a range
of ionic conductances (called genes in the genetic algorithm terminology) that target experimental
values in each given morphology. So our individuals are some of those set of genes that targeted
experimental constraints. This procedure was repeated with the synaptic properties, so we ended up with
several intrinsic and synaptic individuals that would give us heterogenous responses.

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The LCN-HippoModel offers an easy way to test hypotheses about the role of different synaptic and intrinsic
factors in the firing dynamics of CA1 pyramidal cells by simply changing experimental parameters defined in the
LCNhm_configurationfile.py.

Place field modulation

As an addition to a constant theta state, here you can use an alternative version to the model in which we have added a place field asymmetric modulation to CA3, axo-axonic, PV-bc and CCK-bc synaptic conductances.

Documentation

Full documentation of the code can be found here:

https://pridalab.github.io/LCN-HippoModel/

Full article

You can read here the article where this model was used.

Navas-Olive, A., Valero, M., Jurado-Parras, T. et al. Multimodal determinants of phase-locked dynamics across deep-superficial hippocampal sublayers during theta oscillations. Nat Commun 11, 2217 (2020).