Behave: The Biology of Humans at Our Best and Worst
Robert Sapolsky
Why do we do the things we do? Over a decade in the making, this game-changing book is Robert Sapolsky's genre-shattering attempt to answer that question as fully as perhaps only he could, looking at it from every angle. Sapolsky's storytelling concept is delightful but it also has a powerful intrinsic logic: he starts by looking at the factors that bear on a person's reaction in the precise moment a behavior occurs, and then hops back in time from there, in stages, ultimately ending up at the deep history of our species and its genetic inheritance. And so the first category of explanation is the neurobiological one. What goes on in a person's brain a second before the behavior happens? Then he pulls out to a slightly larger field of vision, a little earlier in time: What sight, sound, or smell triggers the nervous system to produce that behavior?
Award History
2 wins · 3 total
| Award | Year | Result | Category / Notes |
|---|---|---|---|
| Los Angeles Times Book Prize for Science and TechnologyMajor | 2017 | Winner | Secondary source |
| Phi Beta Kappa Book Awards: Phi Beta Kappa Award in Science | 2018 | Winner | Official source |
| PEN/E.O. Wilson Literary Science Writing Award | 2018 | Finalist | Secondary source |
Experimental book profileGenerated by GPT-5.4 nano · may contain inaccuracies
This is an unverified interpretation of the catalog description, offered as an opt-in discovery experiment—not as bibliographic fact.
01 Central figures
None extracted with sufficient confidence.
02 Central places
None extracted with sufficient confidence.
03 Suggested argument
Behaviors can be fully explained by tracing causes from immediate neurobiology and triggers, backward through earlier factors, to deep evolutionary history and genetic inheritance.
Model confidence 72%
04 Reading orientation
55 / 100 academicTrade / academic crossover
An estimate of intended readership and scholarly apparatus—not quality or importance.
Confidence percentages are the model's own estimates. Profile confidence: 76%.