Abstract
Spatial learning involves the storage and replay of temporally ordered spatial information. The hippocampus is a key brain structure involved in spatial learning in rats. Temporally ordered spatial memories are encoded and replayed by the firing rate and phase of hippocampal pyramidal cells and inhibitory interneurons with respect to ongoing network theta and ripple oscillations paced by intra- and extrahippocampal areas. Theta oscillations (4–7 Hz) may contribute to memory formation, whereas fast ripple oscillations to temporally compressed forward and reverse replay of previously stored memories. Different classes of CA1 excitatory and inhibitory neurons and medial septal inhibitory neurons have been shown to differentially phase their activities with respect to theta and ripples. Understanding how the different hippocampal and extrahippocampal areas and their neuronal classes interact during these network oscillations and how they facilitate the storage and replay of spatiotemporal memories is of great importance. A computational model of the hippocampal CA1 microcircuit that uses biophysical representations of the major cell types, including pyramidal cells and four types of inhibitory interneurons, is extended. Inputs to the network come from the entorhinal cortex (EC), the CA3 Schaffer collaterals and the medial septum. A biophysical mechanism of spike timing-dependent plasticity (STDP) is used for learning spatial memory patterns in the correct order. The model addresses two important issues: (1) How are the storage and replay (forward and reverse) of temporally ordered memory patterns controlled in the CA1 microcircuit during theta and ripples? (2) What roles do the various types of inhibitory interneurons play in these processes?
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This work was funded by NSF Science of Learning Center CELEST grant SMA 0835976.
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Appendix: Mathematical Formalism
Appendix: Mathematical Formalism
This Appendix contains the mathematical formalisms of the model cell types. Simulations were performed using the XPPAUT [23]. Data analysis was performed by MATLAB. Parameter units are measured in mV for potentials, μA/cm2 for applied currents, mS/cm2 for maximal conductances, and μF/cm2 for capacitances.
CA1 Pyramidal Cell
The axonic (ax), somatic (s), proximal dendritic (pd) and distal dendritic (dd) compartments of the pyramidal neuron obey the following current balance equations
where I L is the leak current, I Na is the sodium current, I K is the delayed rectifier potassium current, I A is the type-A potassium current [61], I m,AHP is the medium Ca2+-activated K+ after-hyperpolarization current [61], I CaL is the L-type Ca2+ current [61], I coup is the electrical coupling between compartments, I in is the injected current and I syn is the synaptic current. Table 1 displays the ionic parameter values of the CA1 pyramidal cell.
The coupling currents for all compartments are
The leak current is described by
where g L is the leak conductance and V L is the leak reversal potential.
The sodium current at the axon and soma is described by
where g Na is the maximal conductance of the Na+ current, M Na and H Na are the activation and inactivation constants and V Na is the reversal potential of the Na+ current. The activation and inactivation constants at the soma are given by
The sodium current at the dendrite is described by
where
where T is the temperature in Celcius and natt is the Na+ attenuation. The type-A K+ current at the soma and dendrite is given by
The activation and inactivation constants are given by
The delayed rectifier K+ current at the axon and soma is given by
where g Kds is the maximal conductance. The activation constant N is given by
The delayed rectifier K+ current at the dendrite is given by
where g Kdr,d is the maximal conductance. The activation constant N d is given by
The medium Ca2+-activated K+ after-hyperpolarization current at the soma is given by
where g KmAHP is the maximal conductance. The activation constant Q m is given by
The h-current [13, 14] at the soma and dendrite is described by
where gh is the maximal conductance of the h-current and E h is the reversal potential. The L-type Ca2+ current at the soma is described by
where g CaL,s is the maximal conductance and
The Ca2+ concentrations in the soma and dendrites [71] are given by
The L-type Ca2+ current at the dendrite is described by
The calcium detector model is governed by the following six equations:
where P is the potentiation detector dynamics, V is the veto detector dynamics, D is the depression detector dynamics, A and B are the intermediate steps leading up to D and W is the readout variable (see Fig. 2). The Hill equations are
The calcium detector parameter values are displayed in Table 2.
Basket, Axoaxonic and Bistratified Cells
where C m is the membrane capacitance, V is the membrane potential, I L is the leak current, I Na is the sodium current, I Kdr is the fast delayed rectifier K+ current, I A is the A-type K+ current and I syn is the synaptic current.
The sodium current and its kinetics are described by
The fast delayed rectifier K+ current I Kdr is given by
The A-type K+ current I A is described by
The ionic parameter values are depicted in Table 3.
OLM Cell
where C m is the membrane capacitance, V is the membrane potential, I L is the leak current, I Na is the sodium current, I Kdr is the fast delayed rectifier K+ current, I NaP is the persistent sodium current, I h is the h-current and I syn is the synaptic current.
The sodium current and its kinetics are described by
The fast delayed rectifier K+ current I Kdr is given by
The NaP current was assembled from the Kunec et al.’s [49] and Dickson et al.’s [19, 25, 26, 76] studies, and it was described by
Similarly, the h-current was assembled from Kunec et al.’s [49] and Dickson et al.’s [19, 25, 26, 76] studies, and it was described by
The ionic parameter values are depicted in Table 3.
Input-to-Cell Synaptic Currents
The Ca2+-NMDA, AMPA, GABAA and NMDA synaptic currents are given by [66] and references therein
where g syn is the synaptic conductance expressed either by Eqs. 47 or 1–3 and
with Mg2+ = 2 mM. The activation equations for AMPA, NMDA and GABAA currents are
where x stands for AMPA, NMDA, GABA and
and
where F pre is the input spike generator simulating the CA3 Schaffer collateral, the EC perforant path and the MS inputs. The input-to-cell synaptic parameter values are displayed in Table 4.
Input Spike Generator
The input spike generator simulating the CA3 Schaffer collateral, the EC perforant path and the MS inputs were described by
where T is the period of oscillation and H() is the Heaviside function.
Cell-to-Cell Synaptic Currents
The synaptic current is given by
where g syn is the synaptic conductance and E rev is the reversal potential. The synaptic conductance is expressed by
where g max is the maximal synaptic conductance and w is the synaptic strength. The values of the synaptic strengths are given in Table 6. In the model, three synaptic currents are included: AMPA, NMDA and GABAA. The values of the synaptic parameters are displayed in Table 4. The gating variable, s, which represents the fraction of the open synaptic ion channels, obeys the following differential equation
where the normalized concentration of the postsynaptic transmitter–receptor complex, F(Vpre), is assumed to be an instantaneous and sigmoid functions of the presynaptic membrane potential
where θ = 0 mV is high enough so that the transmitter release occurs only when the presynaptic cell emits a spike [16]. The values of the channel opening and closing rates are displayed in Table 5.
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Cutsuridis, V., Hasselmo, M. Spatial Memory Sequence Encoding and Replay During Modeled Theta and Ripple Oscillations. Cogn Comput 3, 554–574 (2011). https://doi.org/10.1007/s12559-011-9114-3
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DOI: https://doi.org/10.1007/s12559-011-9114-3