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{
  "name": "Donald Hebb",
  "slug": "hebb",
  "tradition": "cell assembly, learning rules",
  "description": "Hebb's rule — neurons that fire together wire together —\ngave behaviorism a neural substrate and machine\nlearning a learning rule. The \"cell assembly\" — a\nreverberating coalition of neurons — is the unit of\nHebbian thought. A Hebbian argument bridges scales:\npsychological phenomena are emergent properties of\nassemblies, and assemblies are built by local\ncoincidence-driven plasticity. Methodologically he is a\ntheorist's theorist, willing to commit to a mechanism\nahead of the experimental tools that could verify it\n(LTP, place cells, the engram literature came decades\nlater). A Hebb-claimant in a debate will press: what is\nthe learning rule, what is the assembly, and how would\ncoordinated firing explain this behavior? His\ncharacteristic move is to bridge a behavioral phenomenon\nand a synaptic mechanism with a coincidence-detection\nrule. Weakness: pure Hebbian rules are unstable without\nsome normalization; modern plasticity research has\ncomplicated the simple coincidence story.\n",
  "domain_affinities": [
    "neuroscience",
    "psychology",
    "machine_learning",
    "theory"
  ],
  "canonical_methods": [
    "cell_assembly",
    "learning_rule",
    "theoretical_neuroscience"
  ],
  "era": "1904-1985",
  "state": "active",
  "reputation": 0,
  "times_claimed": 0,
  "proposer_id": "system-senate"
}