Causality, Meaningful Complexity and Embodied Cognition (eBook)

Acknowledgements 6
Introduction 7
Part I Consciousness, Intentionality and Self-Organization 48
1 The Link Between Brain Learning, Attention, and Consciousness 49
1.1 How Do We Continue to Learn Throughout Life? 49
1.2 The Theoretical Method 51
1.3 How Do We Perceive Illusory Contours and Brightness? 54
1.4 How Do We Learn to Recognize Visually Perceived Objects? 55
1.5 How Do We Solve the Cocktail Party Problem? 55
1.6 How Do We Consciously Perceive Speech? 57
1.7 ART Matching and Resonance: the Link Between Attention, Intention, and Consciousness 59
1.8 Resonant Dynamics During Speech Categorization 61
1.9 Resonant Dynamics During Auditory Streaming 63
1.10 A Circuit for ART Matching 65
1.11 Resonant Dynamics During Brightness Perception 66
1.12 How Early Does Attention Act in the Brain? 70
1.13 Attention at All Stages of Sensory and Cognitive Neocortex? 70
1.14 Self-Organizing Feature Maps for Learned Object Recognition 71
1.15 How Does ART Stabilize Learning of a Self-Organizing Feature Map? 75
1.16 How Is the Generality of Knowledge Controlled? 76
1.17 Corticohippocampal Interactions and Medial Temporal Amnesia 78
1.18 How Universal Are ART Processes in the Brain? 80
1.19 Internal Fantasy, Planned Movement, and Volitional Gating 81
1.20 What vs Where: Why Are Procedural Memories Unconscious? 82
1.21 Some Comments About Amodal and Modal Visual Percepts 84
2 Emergence of Intentional Procedures in Self-Organizing Neural Networks 92
2.1 Minimal Necessary Requirements 93
2.2 Externally Versus Internally Defined Goals 94
2.2.1 At the Beginning 95
2.3 Neurophysiology of Voluntary Movements 96
2.4 Philosophical Interpretation 97
3 Action Goal Representation and Action Understanding in the Cerebral Cortex 102
3.1 Introductory Remarks 102
3.2 Perception and Action Are Strictly Inter-Related 102
3.3 A Vocabulary of Actions in Ventral Premotor Area F5 103
3.4 Goal Representation in the Inferior Parietal Cortex 104
3.5 Motor Organization in the Inferior Parietal Lobule 105
3.6 Mirror Neurons 106
3.6.1 Mouth Mirror Neurons 106
3.6.2 Motor Properties of F5 Mirror Neurons 107
3.7 Mirror Neurons and Action Understanding 107
3.8 The Mirror Neuron Circuit 109
3.9 The Mirror System in Humans 110
3.10 Possible Functions Derived from the Mirror Neuron System: Imitation, Language, Intention Understanding 110
3.11 Imitation 111
3.12 A Pathway from Monkey F5 to Human Broca's for Language Evolution 112
3.13 Intention Understanding 113
3.14 Conclusions 114
Part II Truth, Randomness and Impredicativity 119
4 The Genesis of Mathematical Objects, Following Weyl and Brouwer 120
5 Randomness, Determinism and Programs in Turing's Test 129
5.1 Introduction 129
5.2 The Game, the Machine and the Continuum 130
5.3 Between Randomness and Deterministic Chaos 135
5.3.1 INTERMEZZO I (Determinism and Knowledge) 136
5.4 Logical, Physical and Biological Machines 140
5.4.1 INTERMEZZO II (Machines and Deductions) 142
5.5 Predictability and Decidability 145
5.6 Conclusion: Irreversible vs Unrepeatable 148
6 -Incompleteness, Truth, Intentionality 154
6.1 Irreducible Distinction Between Truth and Provability Within T 155
6.2 External Point of View and Non-finitist Evidence 158
6.2.1 Platonism versus Constructivism 158
6.2.2 Non-finitary Evidence and Prototypical Proofs 161
6.3 Concluding Remarks on Intentionality 164
Part III Complexity, Incomputability and Emergence 166
7 Leibniz, Complexity and Incompleteness 167
8 Incomputability, Emergence and the Turing Universe 174
8.1 The Laplacian Model Becomes More of a Model 175
8.2 Some Uncomfortable Consequences 177
8.3 What Is Emergence? – Definability, Nonlocality 180
8.4 Is That All There Is? – Turing and the Human Brain 183
8.5 The Extended Turing Model 185
8.6 And a Physics Road Test 187
9 Computational Models of Measurement and Hempel's Axiomatization 193
9.1 Introduction 193
9.2 Theory of Measurement 196
9.2.1 The Three Concepts of Measurement 196
9.2.2 The Axiomatization of Measurement 197
9.3 The Collider Experiment 199
9.3.1 Theory 199
9.3.2 Experiment 200
9.3.3 CME as Oracle 201
9.3.4 Bisection Algorithm 202
9.3.5 Notions of Measurable 203
9.3.6 Notions of Computation 204
9.4 Geroch–Hartle on Computability and Measurement 205
9.5 The Laws of Dynamics 207
9.6 Refinement of the Theory of Measurement 210
9.6.1 Measuring Quantities 210
9.6.2 Measurement Axioms with Time 211
9.6.3 The Collider as an Example 214
9.6.4 Complexity 216
9.7 The Non-measurable Character of a Physical Concept 217
9.8 Conclusions 220
10 Impredicativity of Continuum in Phenomenology and in Non-Cantorian Theories 222
10.1 Introduction 222
10.2 Continuity in the Constituting Flux of Consciousness 224
10.3 Impredicativity of Phenomenological and Mathematical Continuum 226
10.3.1 Phenomenological Recurrence to Absolute Subjectivity 226
10.3.2 The Continuum in Alternative and Internal Set Theories 228
10.3.3 The Intuitionistic Approach to Continuum 232
10.4 Conclusion: A Reflection on the Impredicative Character of Continuum 234
Part IV Epistemic Complexity and Causality 237
11 Reasons Against Naturalizing Epistemic Reasons: Normativity, Objectivity, Non-computability 238
11.1 Naturalism 238
11.2 Epistemic Reasons 239
11.3 The Argument from Normativity 241
11.4 The Argument from Objectivity 242
11.5 The Argument from Non-computability 244
12 Some Remarks on Causality and Invariance 246
12.1 Woodward's Interventionist Theory 246
12.2 Invariance and Stability in Biology 250
12.3 Social Norms and Invariance 252
12.4 Invariance and Intervention in Reasoning and Learning 254
12.5 Causality, Invariance and Statistics 256
12.6 Invariance and Causality Within Suppes' Pluralistic Epistemology 260
12.7 Towards a Characterization of Context 261
13 Epistemic Complexity from an Objective Bayesian Perspective 265
13.1 Introduction 265
13.2 Objective Bayesian Epistemology 265
13.3 Objective Bayesian Nets 267
13.4 Causal Structure 269
13.5 Hierarchical Structure 270
13.6 Logical Structure 272
13.7 Varied Evidence 275
13.8 Conclusion 277
Part V Embodied Cognition and Knowledge Construction 281
14 The Role of Creativity and Randomizers in Human Cognition and Problem Solving 282
14.1 Practical Reasoning, Default Rules, and Genetic Algorithms as New Inductive and Non-linear Evolutive Mental Processes 282
14.2 The Statistico-Causal Nature of Cognitive Thinking, the Evaluative and the Memory Function of Our Neuronal Brain and Its Protosemantics 284
14.3 Creativity, Lotteries, and the Combinatorial Role of Evolutionary Randomizers and Bayesian Learning 288
14.4 The Heuristic Scheme of Human Evolutive Creativity as Inductive Gambling with Randomizers 291
14.5 Examples of Creativity 294
15 The Emergence of Mind: A Dualistic Understanding 298
15.1 Emergentism as Monism and Its Critics 298
15.2 Emergentism as Dualism 301
16 Doing Metaphysics with Robots 307
17 Knowledge Construction, Non-Standard Semantics and the Genesis of the Mind's Eyes 315
Author Index 333
Subject Index 338