Table Of ContentHow to Build
a Brain
OXFORD SERIES ON
COGNITIVE MODELS AND ARCHITECTURES
SeriesEditor
FrankE.Ritter
SeriesBoard
RichCarlson
GaryCottrell
RobertL.Goldstone
EvaHudlicka
PatLangley
RobertSt.Amant
RichardM.Young
IntegratedModelsofCognitiveSystems
EditedbyWayneD.Gray
InOrdertoLearn:
HowtheSequenceofTopicsInfluencesLearning
EditedbyFrankE.Ritter,JosefNerb,
ErnoLehtinen,andTimothyO’Shea
HowCantheHumanMindOccur
inthePhysicalUniverse?
ByJohnR.Anderson
PrinciplesofSyntheticIntelligencePSI:
AnArchitectureofMotivatedCognition
ByJoschaBach
TheMultitaskingMind
ByDavidD.SalvucciandNielsA.Taatgen
HowtoBuildaBrain:
ANeuralArchitectureforBiologicalCognition
ByChrisEliasmith
How to
Build a Brain
A Neural Architecture for
Biological Cognition
Chris Eliasmith
1
3
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LibraryofCongressCataloging-in-PublicationData
Eliasmith,Chris.
Howtobuildabrain:aneuralarchitectureforbiologicalcognition/ChrisEliasmith.
pagescm
Includesbibliographicalreferencesandindex.
ISBN978–0–19–979454–6(acid-freepaper) 1. Brain. 2. Neuralcircuitry
3. Neuralnetworks(Neurobiology) 4. Cognition. I. Title.
QP376.E5452013
(cid:2)
612.82—dc23
2012046211
9 8 7 6 5 4 3 2 1
PrintedintheUnitedStatesofAmerica
onacid-freepaper
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andJessie–myfamily.
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Contents
Preface xi
Acknowledgments xv
1 TheScienceofCognition 1
1.1 TheLast50Years 1
1.2 HowWeGotHere 5
1.3 WhereWeAre 14
1.4 QuestionsandAnswers 18
1.5 Nengo:AnIntroduction 25
PARTI HOWTOBUILDABRAIN
2 AnIntroductiontoBrainBuilding 33
2.1 BrainParts 33
2.2 AFrameworkforBuildingaBrain 40
2.2.1 Representation 43
2.2.2 Transformation 52
2.2.3 Dynamics 55
2.2.4 TheThreePrinciples 60
2.3 Levels 62
2.4 Nengo:NeuralRepresentation 66
3 BiologicalCognition:Semantics 77
3.1 TheSemanticPointerHypothesis 78
3.2 WhatIsaSemanticPointer? 83
3.3 Semantics:AnOverview 84
3.4 ShallowSemantics 87
viii contents
3.5 DeepSemanticsforPerception 90
3.6 DeepSemanticsforAction 100
3.7 TheSemanticsofPerceptionandAction 107
3.8 Nengo:NeuralComputations 111
4 BiologicalCognition–Syntax 121
4.1 StructuredRepresentations 121
4.2 BindingWithoutNeurons 122
4.3 BindingWithNeurons 128
4.4 ManipulatingStructuredRepresentations 133
4.5 LearningStructuralManipulations 139
4.6 Clean-UpMemoryandScaling 141
4.7 Example:FluidIntelligence 146
4.8 DeepSemanticsforCognition 152
4.9 Nengo:StructuredRepresentationsinNeurons 156
5 BiologicalCognition–Control 163
5.1 TheFlowofInformation 163
5.2 TheBasalGanglia 164
5.3 BasalGanglia,Cortex,andThalamus 169
5.4 Example:FixedSequencesofActions 172
5.5 AttentionandtheRoutingofInformation 175
5.6 Example:FlexibleSequencesofActions 183
5.7 TimingandControl 187
5.8 Example:TheTowerofHanoi 191
5.9 Nengo:QuestionAnswering 198
6 BiologicalCognition–MemoryandLearning 209
6.1 ExtendingCognitionThroughTime 209
6.2 WorkingMemory 211
6.3 Example:SerialListMemory 215
6.4 BiologicalLearning 219
6.5 Example:LearningNewActions 226
6.6 Example:LearningNewSyntacticManipulations 230
6.7 Nengo:Learning 241
7 TheSemanticPointerArchitecture 247
7.1 ASummaryoftheSemanticPointerArchitecture 247
7.2 ASemanticPointerArchitectureUnifiedNetwork 249
7.3 Tasks 258
7.3.1 Recognition 258
7.3.2 CopyDrawing 259
7.3.3 ReinforcementLearning 260
7.3.4 SerialWorkingMemory 263
7.3.5 Counting 264
contents ix
7.3.6 QuestionAnswering 267
7.3.7 RapidVariableCreation 269
7.3.8 FluidReasoning 272
7.3.9 Discussion 274
7.4 AUnifiedView:SymbolsandProbabilities 278
7.5 Nengo:AdvancedModelingMethods 284
PARTII ISTHATHOWYOUBUILDABRAIN?
8 EvaluatingCognitiveTheories 295
8.1 Introduction 295
8.2 CoreCognitiveCriteria 296
8.2.1 RepresentationalStructure 296
8.2.1.1Systematicity 297
8.2.1.2Compositionality 297
8.2.1.3Productivity 299
8.2.1.4TheMassiveBindingProblem 300
8.2.2 PerformanceConcerns 301
8.2.2.1SyntacticGeneralization 301
8.2.2.2Robustness 303
8.2.2.3Adaptability 304
8.2.2.4Memory 305
8.2.2.5Scalability 306
8.2.3 ScientificMerit 308
8.2.3.1Triangulation(ContactWithMore
SourcesofData) 308
8.2.3.2Compactness 309
8.3 Conclusion 310
8.4 NengoBonus:HowtoBuildaBrain–aPracticalGuide 311
9 TheoriesofCognition 321
9.1 TheStateoftheArt 321
9.1.1 AdaptiveControlofThought-Rational 323
9.1.2 Synchrony-BasedApproaches 326
9.1.3 NeuralBlackboardArchitecture 329
9.1.4 TheIntegratedConnectionist/Symbolic
Architecture 332
9.1.5 Leabra 335
9.1.6 DynamicFieldTheory 338
9.2 AnEvaluation 340
9.2.1 RepresentationalStructure 340
9.2.2 PerformanceConcerns 344
Description:One goal of researchers in neuroscience, psychology, and artificial intelligence is to build theoretical models that are able to explain the flexibility and adaptiveness of biological systems. How to build a brain provides a detailed guided exploration of a new cognitive architecture that takes biol
