Contributors |
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v | |
Preface |
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xi | |
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Chapter 1 Vital brains: On the entanglement of media, minds, and models |
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1 | (24) |
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1 The Presence of the Brain |
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3 | (2) |
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2 Vital Abstraction at Work in Past Theories of Brain Work |
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5 | (3) |
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3 Entanglements of Theory and Technology: Brain Models in Relation to Visualization Strategies |
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8 | (4) |
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4 Brain Models From Static Machines to Dynamic System and Virtual Avatars |
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12 | (3) |
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5 Grey Walter, The Living Brain and Vital Abstraction |
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15 | (3) |
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6 Conclusion: Abstract and Concrete Brain Models |
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18 | (7) |
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21 | (4) |
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Chapter 2 Slicing the cortex to study mental illness: Alois Alzheimer's pictures of equivalence |
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25 | (28) |
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26 | (3) |
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29 | (5) |
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3 Cortex Pathology as a Means for Bettering Clinical Psychiatry |
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34 | (4) |
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4 The Normal Vital Brain in Alzheimer's Pathological Anatomy |
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38 | (5) |
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5 Picturing Pathological Preparations |
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43 | (5) |
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48 | (5) |
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49 | (1) |
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49 | (4) |
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Chapter 3 Opaque models: Using drugs and dreams to explore the neurobiological basis of mental phenomena |
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53 | (20) |
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1 Pharmacological Models of Psychosis |
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55 | (3) |
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2 An Animal Model of Psychosis |
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58 | (3) |
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3 Dreaming as a Model of Psychosis |
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61 | (2) |
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4 Dreaming as a Model of Consciousness |
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63 | (2) |
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5 The Functions of Opaque Models |
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65 | (8) |
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69 | (1) |
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69 | (4) |
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Chapter 4 Man not a machine: Models, minds, and mental labor, c. 1980 |
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73 | (28) |
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74 | (3) |
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2 Role Models of the Mind |
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77 | (4) |
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3 Men vs Machines: The Somatization of Mental Labor |
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81 | (6) |
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4 Your Friend, the Computer |
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87 | (8) |
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95 | (6) |
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96 | (5) |
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Chapter 5 Infrastructural intelligence: Contemporary entanglements between neuroscience and Al |
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101 | (28) |
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101 | (3) |
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2 From Open Minds to DeepMind |
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104 | (1) |
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105 | (3) |
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4 Infrastructural Intelligence |
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108 | (4) |
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5 The Default Mode (Network) |
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112 | (3) |
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6 The Infrastructuralization of the Brain |
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115 | (3) |
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7 A Mathematical Laboratory |
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118 | (2) |
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8 The Space Itself Is the Event |
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120 | (2) |
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122 | (7) |
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123 | (5) |
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128 | (1) |
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Chapter 6 Learning from large-scale neural simulations |
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129 | (20) |
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129 | (2) |
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2 Directions in the Epistemology of Computer Simulations |
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131 | (4) |
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2.1 Model-Oriented and Data-Oriented Simulations |
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133 | (2) |
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3 Varieties of Large-scale Neural Simulations |
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135 | (6) |
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3.1 The Blue Brain Project |
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136 | (2) |
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3.2 A Large-Scale Model of the Mammalian Thalamocortical System |
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138 | (1) |
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3.3 The Cognitive Computation Project |
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139 | (2) |
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141 | (5) |
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4.1 On the Blue Brain and the Human Brain Projects |
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141 | (2) |
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4.2 On Izhikevich and Edelman Large-Scale Simulations |
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143 | (2) |
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4.3 On the Cognitive Computation Project |
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145 | (1) |
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146 | (3) |
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147 | (2) |
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Chapter 7 Connectomes as constitutively epistemic objects: Critical perspectives on modeling in current neuroanatomy |
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149 | (30) |
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150 | (1) |
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2 Connectomes in Neuroscientific Practice |
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151 | (14) |
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2.1 The C. elegans Wiring Diagram as a Descriptive Model |
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152 | (3) |
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2.2 Descriptive Modeling in Contemporary Connectomics |
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155 | (4) |
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2.3 Connectomes as Constitutively Epistemic Objects |
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159 | (6) |
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3 Critical Neuroscience of Connectomics |
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165 | (14) |
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3.1 The Brain's Next Top Model |
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166 | (3) |
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3.2 The Elusive Network: Brain Connectivity and Contemporary Network Sociality |
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169 | (3) |
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3.3 Concluding Outlook: Critical Neuroscience and Model Domain Realism |
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172 | (2) |
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174 | (5) |
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Chapter 8 Bridging the gap between system and cell: The role of ultra-high field MRI in human neuroscience |
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179 | (42) |
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180 | (4) |
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184 | (11) |
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184 | (5) |
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2.2 Description and Attribution of Function |
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189 | (3) |
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2.3 Prediction and Predictive Coding |
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192 | (1) |
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2.4 Connectionism and Spatial Modularity |
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193 | (1) |
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2.5 Issues of Granularity: Level of Explanation and Consistency |
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194 | (1) |
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195 | (4) |
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3.1 The Neuron Doctrine of Cajal |
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195 | (1) |
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196 | (1) |
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3.3 Compactness of Brain Areas |
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197 | (1) |
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3.4 Networks and Connectivity |
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197 | (2) |
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4 MRI, Brain Function, and Neuroanatomy |
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199 | (7) |
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4.1 Sources of MRI Contrast |
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200 | (1) |
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201 | (2) |
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203 | (1) |
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4.4 Functional MRI, Local Connectivity, and Causal Directionality |
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204 | (2) |
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5 Data-driven Functional Categorization |
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206 | (2) |
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5.1 Representational Models |
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207 | (1) |
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5.2 Population Receptive Fields (Dumoulin and Wandell) |
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208 | (1) |
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6 Conclusions: The Prospects of Linking Cell and System |
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208 | (13) |
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212 | (8) |
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220 | (1) |
Index |
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221 | |