- Test this by replicating the results of Pan et al.[4]
- Pedantic Heun's method[5] implemented (no longer utilises DifferentialEquations.jl)
- AdEx_Neuron_T1[2] implemented
- AdEx_Neuron_T2[1] implemented
- AdEx_Neuron_Excitatory[3] implemented
- AdEx_Interneuron_SST[3] implemented
- AdEx_Interneuron_PV[3] implemented
- All (inter-)neurons can have multiple types of synapses
- GABA_a, GABA_b, AMPA & NMDA synapses[1] implemented
- Now properly modelling interactions of Exc -> SST and PV -> Exc, as described by Park & Geffen[3] and Tremblay et al.[6]
- Comprehensive plots added
- For example, for model:
network_draft = [ AdEx_Model_Neurons( T=AdEx_Neuron_T1, N=2, S=[AdEx_Model_Synapses( T=AdEx_Synapse_AMPA, C=Int[4, 5] )] ), AdEx_Model_Neurons( T=AdEx_Neuron_T1, N=1, S=[AdEx_Model_Synapses( T=AdEx_Synapse_GABA_A, C=Int[1, 2] ), AdEx_Model_Synapses( T=AdEx_Synapse_AMPA, C=Int[6] )] ), AdEx_Model_Neurons( T=AdEx_Neuron_T1, N=2, S=[AdEx_Model_Synapses( T=AdEx_Synapse_NMDA, C=Int[1, 2] ), AdEx_Model_Synapses( T=AdEx_Synapse_AMPA, C=Int[3, 3, 3] )] ), AdEx_Model_Neurons( T=AdEx_Neuron_T1, N=1, S=[AdEx_Model_Synapses( T=AdEx_Synapse_GABA_A, C=Int[1, 2] )] ) ]; ... T = (0ms, 2000ms); I = [ (1, AdEx_boxcar(T[1]:T[2], 100ms, 1400ms, 2mV)), (2, AdEx_sin(T[1]:T[2], 2mV, 0.001)) ];
- We get:
- Spike train plots
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- Neuron history plots
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- Synapse history plots, left column I(t), right column g(t), rows = one synapse
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- Spike train plots
- For example, for model:
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[1] Gerstner, W., Kistler, W.M., Naud, R., & Paninski, L. (2014). Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition. New York: CUP.
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[2] Brette, R., & Gerstner, W. (2005). Adaptive exponential integrate-and-fire model as an effective description of neuronal activity. Journal of Neurophysiology, 94, 3637-3642. DOI: http://dx.doi.org/10.1152/jn.00686.2005.
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[3] Park, Y., & Geffen, M.N. (preprint). A unifying mechanistic model of excitatory-inhibitory interactions in the auditory cortex. bioRxiv, 626358. DOI: http://dx.doi.org/10.1101/626358
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[4] Pan, Z., Chua, Y., Wu, J., Zhang, M., Li, H., & Ambikairajah, E. (2020). Motivated auditory neural encoding and decoding algorithm for spiking neural networks. Frontiers in Neuroscience: Neuromorphic Engineering, 13, 1420. DOI: http://dx.doi.org/10.3389/fnins.2019.01420
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[5] Numerical Methods--Heun's method. (n.d.). CalculusLab, San Joaquin Delta College. Retrieved May 5, 2020, from http://calculuslab.deltacollege.edu/ODE/7-C-2/7-C-2-h.html
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[6] Tremblay, R., Lee, S., & Rudy, B. (2016). GABAergic interneurons in the neocortex: From cellular properties to circuits. Neuron, 91, 260-292. DOI: http://dx.doi.org/10.1016/j.neuron.2016.06.033