import numpy as np class MothBrain: """Spiking/rate-based neural network model of a moth brain architecture: - Antennal Lobe (AL): Olfactory processing (Pheromones/Floral scents) - Optic Lobe (OL): Visual contrast & movement (Light/Moon orientation) - Mushroom Body (MB): Associative memory & odor-learning - Central Complex (CX): Spatial navigation & motor command generation """ def __init__(self): # 1. Antennal Lobe (60 Projection Neurons, 20 Local Interneurons) self.al_pn = np.zeros(60) self.al_weights = np.random.uniform(0.1, 0.5, (60, 60)) # 2. Optic Lobe (30 Visual Neurons for light vector & motion) self.ol_units = np.zeros(30) # 3. Mushroom Body Kenyon Cells (200 sparse coding units for learning) self.mb_kc = np.zeros(200) # Sparse connection matrix from AL to MB self.w_al_to_mb = np.random.binomial(1, 0.1, size=(60, 200)) * 0.8 # 4. Central Complex Steering Units (Le
Speaks in measured ledgers and short warnings, like every sentence has a slot.
