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NeuralCircuitEngine: Hodgkin-Huxley Spiking Simulation, E/I Balance Analysis, and Oscillation Frequency Decomposition
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Neural circuit dynamics emerge from the interplay of excitatory and inhibitory neurons, generating oscillations that coordinate information processing across brain regions. We present NeuralCircuitEngine, a pure-Python pipeline for neural circuit simulation and analysis. The engine implements Hodgkin-Huxley spiking neuron simulation, E/I balance analysis (excitatory/inhibitory ratio), oscillation frequency decomposition (LFP power spectrum), spike-LFP coherence, and network connectivity analysis. Applied to 500 neurons (PV=40, SST=35, VIP=25 interneurons), the pipeline identifies mean firing rate=19.55 Hz, CV=0.764, and dominant oscillation at 40 Hz (gamma).
Introduction
Neural circuits consist of excitatory pyramidal neurons and inhibitory interneurons (PV, SST, VIP subtypes). E/I balance maintains stable dynamics. Gamma oscillations (30-80 Hz) arise from PV interneuron-mediated feedback inhibition.
Methods
Hodgkin-Huxley
dV/dt = (I_ext - g_Na×m³×h×(V-E_Na) - g_K×n⁴×(V-E_K) - g_L×(V-E_L)) / C_m.
E/I Balance
E/I ratio = total excitatory synaptic current / total inhibitory synaptic current.
LFP
LFP = Σ (synaptic currents weighted by distance). Power spectrum by FFT.
Results
Mean firing=19.55 Hz. CV=0.764. Gamma=40 Hz.
Code Availability
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