DOI: 10.5061/dryad.pvmcvdnr2
title: Data from: Basolateral amygdala oscillations enable fear learning in a biophysical model

description: The basolateral amygdala (BLA) is a key site where fear learning takes
 place through synaptic plasticity. Rodent research shows prominent low
 theta (∼3-6 Hz), high theta (∼6-12 Hz), and gamma (&gt;30 Hz) rhythms
 in the BLA local field potential recordings. However, it is not understood
 what role these rhythms play in supporting the plasticity. Here, we create
 a biophysically detailed model of the BLA circuit to show that several
 classes of interneurons (PV, SOM, and VIP) in the BLA can be critically
 involved in producing the rhythms; these rhythms promote the formation of
 a dedicated fear circuit shaped through spike-timing-dependent plasticity.
 Each class of interneurons is necessary for the plasticity. We find that
 the low theta rhythm is a biomarker of successful fear conditioning. The
 model makes use of interneurons commonly found in the cortex and, hence,
 may apply to a wide variety of associative learning situations.
description: # Title of Dataset: Basolateral amygdala oscillations enable fear learning
 in a biophysical model --- This repository contains the simulated data
 used to generate the figures presented in "Basolateral amygdala
 oscillations enable fear learning in a biophysical model" by Anna
 Cattani, Don B Arnold, Michelle McCarthy, Nancy Kopell
 ([https://doi.org/10.7554/eLife.89519.1](https://doi.org/10.7554/eLife.89519.1)) ## File structure and Data description Types of neurons in the network: * ECS: pyramidal cell encoding the CS input * PN: pyramidal cell encoding the US input * VIP: vasoactive intestinal peptide-expressing interneuron * SOM: somatostatin-expressing interneuron * PV: parvalbumin-expressing interneuron * PYRCS: auxiliary pyramidal cell receiving CS * PYRUS: auxiliary pyramidal cell receiving US ### SINGLE NEURON NETWORK: "Data\_Fig3" and "Data\_Fig4" "Data_Fig3" and "Data_Fig4" contains text files named "`singleneuronnet_cond1_stim3_exp...rule1..._numtrial.txt`". More specifically, * "Singleneuronnet" specifies that the network is made by only one neuron per type * cond1 refers to simulations performed during fear conditioning * stim3 refers to the presence of concomitant CS and US * exp... is followed by 0, 1, 2, 6, and 7. exp0 refers to the full network with all the interneuron subtypes, exp1: network with no SOM, exp2: no PV, 6: no VIP, exp7: only PV. * rule1 refers to the depression-dominated plasticity rule used to generate these data * "STDP", "AMPA_ECS_PN", and "LFP" contains different information related to the network dynamics (STDP), change in the conductance between ECS and PN (AMPA_ECS_PN), local field potential (LFP), as detailed below. * numtrial goes from 0 to 39, representing 40 network realizations. A) "STDP.txt": \[1] time [ms] \[2] VIP membrane potential [mV] \[3] SOM membrane potential [mV] \[4] PV membrane potential [mV] \[5] ECS membrane potential [mV] \[6] PN (called F in the article) membrane potential [mV]\ \[7] auxiliary pyramidal neuron representing CS [mV] \[8] auxiliary pyramidal neuron representing US [mV] \[9] potentiation ECS -&gt; F \[10] depression ECS-&gt;F \[11] potentiation F -&gt; VIP (not used for simulations in the article) \[12] depression F-&gt; VIP (not used for simulations in the article) B) "AMPA_ECS_PN.txt": \[1] evolution in time of the ECS to F conductance \[2] evolution in time of F to VIP conductance (no actual variation is reported since plasticity from F to VIP has not been considered in the main manuscript) C) "LFP.txt": \[1] time \[2] sum of the AMPA currents (coming from ECS to F, F to VIP, and F to PV connections) \[3] H-current in the SOM cell \[4] P-current in the SOM cell \[5] D-current in the VIP cell D) param contains the value of the following conductances: \[1] GABA from VIP to SOM \[2] GABA from VIP to PV \[3] GABA from SOM to ECS \[4] GABA from SOM to PN \[5] GABA from PV to PN \[6] AMPA from PN to PV \[7] GABA from PV to ECS \[8] AMPA from PN to VIP \[9] AMPA from PYRCS to ECS \[10] AMPA from PYRCS to PV \[11] AMPA from PYRUS to PN \[12] AMPA from PYRUS to VIP ## HETEROGENEOUS NETWORK: "Data\_Fig5" and "Data\_Fig6" "Data_Fig5" and "Data_Fig6" contains text files named "`het_cond..._stim...exp0_rule1..._numtrial.txt`". More specifically, * "het" refers to the heterogeneous network made by multiple neurons per type * cond0 refers to simulations performed before fear conditioning, cond1 during fear conditioning, and cond2 after fear conditioning * stim1 refers to the presence of only CS, stim3: concomitant CS and US * exp0 refers to the full network with all the interneuron subtypes * rule1 refers to the depression-dominated plasticity rule used to generate these data * "STDP", "AMPA_ECS_PN", and "LFP" contains different information related to the network dynamics (STDP), change in the conductance between ECS and PN (AMPA_ECS_PN), local field potential (LFP), as detailed below. * numtrial goes from 0 to 39, representing 40 network realizations. "Data_Fig5" and "Data_Fig6" also contain three files .txt named "STDP.txt", "AMPA_ECS_PN.txt", and "LFP.txt", which are structured as follows: A) "STDP.txt": \[1] time \[2] VIP1 membrane potential [mV] \[3] VIP2 membrane potential [mV] \[4] VIP3 membrane potential [mV] \[5] SOM1 membrane potential [mV] \[6] SOM2 membrane potential [mV] \[7] SOM3 membrane potential [mV] \[8] PV membrane potential (all three PV cells display identical activity) [mV] \[9-18] ECS cells' membrane potential [mV] \[19-28] PN cells' membrane potential [mV] \[29] auxiliary pyramidal neuron representing CS [mV] \[30] auxiliary pyramidal neuron representing US [mV] \[31] potentiation ECS1 -&gt; PN1 \[32] potentiation PN1 -&gt; VIP (not used for simulations in the article) \[33] depression ECS1 -&gt; PN1 \[34] depression PN1 -&gt; VIP (not used for simulations in the article) B) "AMPA_ECS_PN.txt": \[1] evolution of ECS1 to PN1 conductance over time \[2] evolution of PN1 to VIP1 conductance over time (no actual variation since plasticity from PN to VIP has not been considered in the main manuscript) \[3] evolution of PN1 to VIP2 conductance over time (no actual variation) \[4] evolution of PN1 to VIP3 conductance over time (no actual variation) \[5] evolution of PN2 to VIP1 conductance over time (no actual variation) C) "LFP.txt": \[1] time \[2] sum of the AMPA currents (coming from ECS to F, F to VIP cells, and F to PV connections) \[3] H-current in the SOM cell \[4] P-current in the SOM cell \[5] D-current in the VIP cell D) "param" contains the value of the following conductances: \[1] GABA from VIPs to SOMs \[2] GABA from VIPs to PVs \[3] GABA from SOMs to ECSs \[4] GABA from SOMs to PNs \[5] GABA from PVs to PNs \[6] AMPA from PNs to PVs \[7] GABA from PVs to ECSs \[8] AMPA from PN(1) to VIP(1) \[9] AMPA from PN(1) to VIP(2) \[10] AMPA from PN(1) to VIP(3) \[11] AMPA from PN(2) to VIP(1) \[12] AMPA from PYRCS to ECS(1) \[13] AMPA from PYRCS to PVs \[14] AMPA from PYRUS to PN(1) \[15] AMPA from PYRUS to VIP ## Sharing/access Information The codes to generate the figures can be found at [https://github.com/annacatt/Basolateral_amygdala_oscillations_enable_fear_learning_in_a_biophysical_model](https://github.com/annacatt/Basolateral_amygdala_oscillations_enable_fear_learning_in_a_biophysical_model) Help is available by contacting the creator, Anna Cattani ([acattani@bu.edu](mailto:acattani@bu.edu))