An mPCI-Based Empirical Test of Internal Affective State in a Neuromorphic SNN
Venkatesh Swaminathan · ORCID 0000-0002-3315-7907 · Nexus Learning Labs, Bengaluru
Three methodological controls were run after the main experiment. Control 1 (training depth) found that a model trained for 5 tasks without affective dimensions shows mPCI similar to Phase 3, partially confounding the affective state interpretation. Control 3 (shuffle) found that shuffled spike trains show larger differences between phases than structured ones. These findings are reported honestly in the paper. The mPCI shift is real and reproducible across 3 seeds. The interpretation requires nuance: training depth and affective state both contribute. Independent replication is needed to isolate the affective contribution cleanly.