How Meaning Emerges From Brain Circuitry |
How does meaning arise from matter? This is Part 2 of a four-part series exploring how the brain generates meaning. In Part 1, I argued that meaning emerges from relations among neural patterns, evolutionary history, learned associations, and goal-directed action. But that leaves the hardest question unanswered: how do electrical signals in your brain become about apples, dangers, and desires? How does the "aboutness" of meaning emerge from purely physical circuits? Here, in Part 2, we confront the mechanisms directly.
For decades, much of neuroscience sought to understand how brains make meaning by looking for specialized neurons or localized representations. The classic finding: neurons in the medial temporal lobe—often called “concept cells”—that respond selectively when a person recognizes a specific individual, whether shown in different photos, drawings, or even written names.[1]
These cells do exist. But they can't explain meaning. Meaning is compositional: you understand "purple elephant" immediately, though no neuron is pre-tuned to purple-elephantness. Meaning is context-dependent: "bank" means different things in "river bank" versus "savings bank." Neuroimaging reveals that semantic processing engages distributed networks spanning frontal, temporal, and parietal cortices.[2]
Neuroscientist Friedemann Pulvermüller has developed a comprehensive neural theory of how meaning arises from brain circuits.[3] His framework identifies four interacting mechanisms:
1. Referential Semantics
Words activate sensory and motor patterns associated with their referents. "Apple" activates visual features (red, round), taste (sweet, tart), and the physical sensation of sinking your teeth into it. These are functional links forged through experience.
When you first learn "apple," you see apples, taste them, bite them, and hear the word. Neurons active during these correlated experiences develop strong connections—a principle called Hebbian learning ("neurons that fire together wire together")—creating distributed networks linking word forms to multimodal experiences.[4]
2. Combinatorial Semantics
But meaning can't be purely experiential. How do we understand "unicorn" or "democracy"? Syntax provides combinatorial rules for constructing novel meanings from familiar elements.
These aren't abstract symbolic rules; they're implemented in the timing and sequencing of neural activation. When processing "the cat chased the mouse," different patterns activate for who's chasing versus being chased. Grammar is embodied in the temporal dynamics of neural networks.[5]
3. Emotional-Affective Semantics
Many concepts carry affective valence—positive or negative feeling tone—integral to their meaning. Words like "love" and "hate" activate emotional systems. Even supposedly neutral words have subtle emotional colorings.
This connects to Part 1's argument: meaning is grounded in value. The brain's evaluation systems aren't optional add-ons; they're part of what makes representations meaningful rather than merely informational.[6]
4. Abstract-Symbolic Semantics
Some meaning is genuinely abstract, not reducible to sensory experience. Mathematical concepts and logical relations require mechanisms beyond embodied simulation.
Abstract meanings emerge through........