Brains as Engines of Association tackles a fundamental question in neuroscience: what is the operating principle of the human brain?While a similar question has been asked and answered for virtually every other human organ during the last few centuries, how the brain operates has remained a central challenge in biology. Based on evidence derived from vision, audition, speech and music--much of it based on the author's own work over the last twenty years--Brains as Engines of Association argues that brains operate wholly on the basis of trial and error experience, encoded in neural circuitry over evolutionary and individual time.This concept of neural function runs counter to current concepts that view the brain as a computing machine, and research programs based on the idea that the only way to answer such questions is by reconstructing the connectivity of brains in their entirety. This view also implies that the best way to understand the details of brain function is to recapitulate their history using artificial neural networks. While this viewpoint has received support in the last few years from work showing that computers can win complex games, the brain plays a much more complex game--the "game" of biological survival--which Purves concludes is based on trial-and-error experience.

PrefacePART I. What Nervous Systems Do for AnimalsChapter 1. Putting the Question in PerspectiveIntroductionLife on EarthDefining lifeEnergyEvolutionMechanismsTeleologyConclusionSuggested ReadingChapter 2. Organisms without Nervous SystemsIntroductionBacteriaProtistsPlantsThe general strategyConclusionSuggested ReadingChapter 3. Organisms with Nervous SystemsIntroductionDefining nervous systemsThe emergence of nervous systemsThe emergence of central nervous systemsWhat do nervous systems add?What do brains add?ConclusionSuggested ReadingPART II. Neural Systems as Engines of AssociationChapter 4. The Organization of Nervous SystemsIntroductionStimuliPre-neural processingNeural processingBehavioral outputNeural systems and subsystems are interactiveConclusionSuggested ReadingChapter 5. The ProblemIntroductionVision as an exampleThe basic challengeThe answer in general termsQualia determined by empirical rankingPerceptual discrepanciesMechanismsOther modalitiesThe meaning of 'illusions'ConclusionSuggested ReadingChapter 6. Neural AssociationsIntroductionAssociations wrought be evolutionAssociations wrought by lifetime learningAssociations wrought by cultureBehavioral categories of associationsRewardBehavioral responses as reflexesWhat gets associated?CounterargumentsConclusionSuggested ReadingPART III. Evidence that Neural Systems Operate EMPIRICALLYChapter 7. Evidence from Lightness and ColorIntroductionLuminance and lightnessAnalyzing the occurrence of luminance patternsEffects of other luminance patternsSpectral energy and colorThe general strategyConclusionSuggested ReadingChapter 8. Evidence from GeometryIntroductionSeeing intervalsSeeing anglesSeeing object sizes in 2-DSeeing object sizes in 3-DSeeing stereo depthConclusionSuggested ReadingChapter 9. Evidence from MotionIntroductionApparent motionThe perception of speedImplications for the perception of timeThe perception of directionConclusionSuggested ReadingChapter 10. Evidence from AuditionIntroductionSound signalsSources of tonesSound signal spectraThe problem in auditionAn empirical approachEvidence from speechEvidence from musicImplications for any sensory systemConclusionSuggested ReadingPART IV. alternative Concepts Neural FunctionChapter 11. The Major OptionsIntroductionNeural function as feature detectionNeural function as statistical inferenceNeural function as efficient codingNeural function as computationConclusionSuggested ReadingChapter 12. Summing UpIntroductionA way around some fundamental obstaclesEmpirical rankingInsight from gamesArtificial intelligenceConsequences for neuroscienceThe status of reasoningNovel situationsChoiceCultureThe frequency of stimuliConclusionSuggested ReadingBibliographyGlossaryIndexAcknowledgments