Does Size Matter? Cross-Species Analysis of Intelligence and Brain Size

Brain size correlates weakly with intelligence within species yet strongly across species, and several taxa—from corvids to honeybees—exhibit cognitive abilities that appear disproportionate to their brain mass. The Strong Electromagnetic Field Hypothesis (SEFH) proposes that consciousness and higher cognition emerge from hierarchically nested electromagnetic (EM) field dynamics in neural tissue, with neural firing serving primarily as an energy source for these fields rather than as the primary computational medium. This framework generates specific, quantitative predictions based on two variables: (i) wattage density—the EM field production intensity per unit volume of integrative tissue, driven by neuron density—and (ii) harmonic capacity—the number of distinct geometric eigenmodes (resonant standing-wave patterns) that the field-permeable tissue can sustain, determined by the geometry and volume of the ephaptically coupled neural medium. We systematically test these predictions by mining existing comparative neuroscience datasets, including isotropic fractionator studies of cortical/pallial neuron counts and densities across primates, corvids, parrots, cetaceans, elephants, carnivores, rodents, and invertebrates (honeybees). After excluding cerebellar neurons (which serve motor control, not integrative cognition), we calculate estimated EM field production density (watts per cubic centimetre) for associative tissue across taxa. We find that SEFH predictions are strongly confirmed in several key comparisons: corvids and parrots achieve primate-rival cognition with 3–5× higher pallial wattage density than human cortex; honeybees achieve remarkable cognitive feats with the highest neural density measured in any animal (~960,000 neurons/mg); and elephants dramatically underperform their total neuron count when cerebellar (motor control) neurons are excluded. Drawing on recent work showing that brain geometry—rather than connectome topology—fundamentally constrains neural dynamics (Pang et al., 2023) and that harmonic brain modes govern spatiotemporal dynamics of cognition and consciousness (Atasoy et al., 2016, 2018), we propose a two-variable predictive model: cognitive capacity ∝ wattage density × log(harmonic capacity). A honeybee’s mushroom body is an exquisitely tuned tiny drum—remarkable domain-specific performance from a handful of harmonic modes—while the human cortex is a cathedral, sustaining thousands of resonant modes across its vast field-permeable geometry. This framework accounts for cross-species cognitive patterns better than any single neural measure and, unlike models built on the McCulloch–Pitts neuron-as-logic-gate framework, is fully native to field-based physics. A preliminary cross-species regression using these two variables explains R² = 91.8% of cognitive variance across ten focal taxa (Spearman ρ = 0.976, p < 0.00001), compared with 39.2% for brain mass and 64.8% for neuron count alone.