The NEURON code implements a DG-CA3-CA1 network model (100 DG GCs, 2
DG MCs, 2 DG BCs, 1 HC, 100 CA3 PCs, 2 CA3 BCs, 1 CA3 AAC, 1 CA3 OLM
cell, 100 CA1 PCs, 1 CA1 AAC, 2 CA1 BCs, and 1 CA1 BSC) on how theta
modulated inhibition accounts for the long temporal windows in the
entorhinal-hippocampal loop.


Cutsuridis V*, Poirazi P. (2015). A computational study on how theta
modulated inhibition can account for the long temporal delays in the
entorhinal-hippocampal loop. Neurobiology of Learning and Memory, 120:


A recent experimental study (Mizuseki, Sirota, Pastalkova, & Buzsaki,
2009) has shown that the temporal delays between population activities
in successive entorhinal and hippocampal anatomical stages are longer
(about 70-80 ms) than expected from axon conduction velocities and
passive synaptic integration of feed-forward excitatory inputs. We
investigate via computer simulations the mechanisms that give rise to
such long temporal delays in the hippocampus structures. A model of
the dentate gyrus (DG), CA3 and CA1 microcircuits is presented that
uses biophysical representations of the major cell types including
granule cells, CA3 and CA1 pyramidal cells (PCs) and six types of
interneurons: basket cells (BCs), axo-axonic cells (AACs),
bistratified cells (BSCs), oriens lacunosum-moleculare cells (OLMs),
mossy cells (MCs) and hilar perforant path associated cells
(HC). Inputs to the network came from the entorhinal cortex (EC)
(layers 2 and 3) and the medial septum (MS). The model simulates
accurately the timing of firing of different hippocampal cells with
respect to the theta rhythm. The model shows that the experimentally
reported long temporal delays in the DG, CA3 and CA1 hippocampal
regions are due to theta modulated somatic and axonic inhibition. The
model further predicts that the phase at which the CA1 PCs fire with
respect to the theta rhythm is determined primarily by their increased
dendritic excitability caused by the decrease of the axial resistance
and the A-type K+ conductance along their dendritic trunk.  The model
predicted latencies by which the DG, CA3 and CA1 principal cells fire
are inline with the experimental evidence. Finally, the model proposes
functional roles for the different inhibitory interneurons in the
retrieval of the memory pattern by the DG, CA3 and CA1 networks. The
model makes a number of predictions, which can be tested
experimentally, thus leading to a better understanding of the
biophysical computations in the hippocampus.

Main file: mosinit.hoc 

This file is configured to produce the results presented in figures
5-9 of the paper, showing the temporal relationships of voltage traces
of the network's cells when the network is stimulated by EC-L2, EC-L3
and medial septum (MS) inputs. Example results are in the Results
directory, in which there are also Matlab files for plotting figure
11, an example pattern recall when the EC-L2 input to DG-GCs is cueing
the pattern, EC-L2 and EC-L3 inputs are present to drive the
inhibitory interneurons, but they are disconnected from the CA3-PCs
and CA1-PCs, respectively, so that recall is purely due to the EC-L2
input cue.


First compile the mod files (nrnivmodl on unix/linux, mknrndll on
mswin or mac os x).  Then start with the command "nrngui mosinit.hoc"
(unix/linux), or by double clicking the mosinit.hoc (mswin), or
dragging and dropping mosinit.hoc onto the nrngui icon (mac os x).

After the simulation starts it takes about a minute to setup the
network, then you can run the default simulation (takes just under 20
minutes) or explore the model with the nrngui.

When running the model, hide the graphs for faster run times.  An
example graph generated:


is similar to Fig7D.


20150524 Update from Ted Carnevale: Changed integration method from
euler to derivimplicit which is appropriate for simple ion
accumulation mechanisms.  See Integration methods for SOLVE statements

20150525 Update from Ted Carnevale: Fixed ca initialization by
inserting cai = ca into INITIAL block in cad.mod

20220523 Updated MOD files to contain valid C++ and be compatible with
the upcoming versions 8.2 and 9.0 of NEURON.