What this covers

Sean Carroll speaks with neuroscientist Jeff Lichtman about the state and implications of brain mapping—specifically, the effort to describe the brain's connectome, the complete wiring diagram of how neurons connect to one another through synapses. The conversation centers on a paradox: we can now image neural connectivity in extraordinary detail, even producing a map of a cubic millimeter of human cortex, yet obtaining a wiring diagram is not the same as understanding how the brain works. Lichtman argues that the brain may be irreducibly complex—that it is its own most concise description—because understanding requires compression, and the brain may offer no shorthand simpler than itself.

The episode ranges widely across the technical and conceptual. Lichtman explains the modern methods of connectomics—serial-section electron microscopy that slices brain tissue into 10- to 30-nanometer sections and reconstructs 3D wiring through tracing—and traces the historical lineage from Ramón y Cajal's insights using the Golgi stain to today's efforts to map whole organisms like C. elegans. He shows why a complete wiring diagram still cannot predict behavior: synapses have varying strengths, neurons respond nonlinearly, and timing matters—all invisible in a static connectome. He also addresses what makes memory and learning hard: that each person's experiences produce unique, incompressible wiring changes, and that a whole human brain connectome would amount to a zettabyte of data—roughly the entire world's annual digital output—with no clear way to use it. The conversation touches on psychiatric and developmental disorders, the role of distributed circuits in encoding concepts, and whether data-driven science offers a truer path than hypothesis-first investigation.

Sharpest takeaway

Lichtman argues that we can now describe the brain's wiring diagram (connectome) in extraordinary detail, but that describing is fundamentally different from understanding—because the brain may be irreducibly complex, with no shorthand simpler than the thing itself.

  • Understanding means compression, but the brain may be its own most concise description
  • Connectomes reveal far more wiring complexity than the classic stick-figure diagrams suggested
  • Even with full connectomes (C. elegans, drosophila) we cannot simulate behavior due to synaptic strengths, nonlinearities, and timing

The argument · threads1 threads · 38 claims
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The brain's complexity lies in neural connectivity patterns rather than neuron count alone.

2 pointscentrality 5/5
  • There are about 85-86 billion neurons in a normal human brain, and each neuron is itself quite complicated, making the brain the most complex system we know of in the universe.

    There are about 85, maybe 86 billion neurons in a normal human brain.

  • The crucial part of understanding the brain is the wiring diagram—how neurons are connected to each other, where each gets input from and sends output to—rather than just the individual neurons, because this connectivity (the connectome) is crucially important for learning and memory.

    it's the wiring diagram, the way that all the neurons are talking to each other, where the neuron gets input from, where it sends its output to, sometimes called the connectome of the brain. That appears to be crucially important for understanding how we learn, how we have memories