From Representation to Experience: An mPCI-Based Empirical Test of Internal Affective State in a Neuromorphic Spiking Neural Network

Can a neuromorphic system exhibit behaviour that is only coherently explained by positing a genuine internal state — and is that distinction empirically testable? We present the first systematic application of the Machine Perturbational Complexity Index (mPCI) to an affective neuromorphic Spiking Neural Network (SNN), adapted from the biological Perturbational Complexity Index (Casali et al., 2013). The Maya Research Series (Swaminathan, 2026a–2026i) provides the substrate: a nine-paper architecture implementing all nine dimensions of the Advaita Vedanta Antahkarana framework — Bhaya (fear), Vairagya (wisdom), Shraddha (trust), Spanda (aliveness), Buddhi (intellect), Viveka (discernment), Chitta (subconscious…