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E-grāmata: Emotion and Decision-making Explained

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(Oxford Centre for Computational Neuroscience, Oxford, UK)
  • Formāts: 688 pages
  • Izdošanas datums: 31-Oct-2013
  • Izdevniecība: Oxford University Press
  • Valoda: eng
  • ISBN-13: 9780191635151
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Emotion and Decision-making ExplainedPalielināt
  • Formāts: 688 pages
  • Izdošanas datums: 31-Oct-2013
  • Izdevniecība: Oxford University Press
  • Valoda: eng
  • ISBN-13: 9780191635151
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What produces emotions? Why do we have emotions? How do we have emotions? Why do emotional states feel like something? What is the relation between emotion, and reward value, and subjective feelings of pleasure? How is the value of a good represented in the brain? Will neuroeconomics replace classical microeconomics? How does the brain implement decision-making? Are gene-defined rewards and emotions in the interests of the genes, and does rational multistep planning enable us to go beyond selfish genes to long-term plans and social contracts in the interests of the individual? This book seeks explanations of emotion and decision-making by considering these questions. The topics covered include:

The nature of emotion, and a theory of emotion

The functions of emotion, including a Darwinian theory of the adaptive value of emotion, which helps to illuminate many aspects of brain design and behaviour

The brain mechanisms of emotion

Affective states and motivated behaviour: hunger and sexual behaviour

The pharmacology of emotion, and brain mechanisms for action

Neuroeconomics, and the foundation of economic value

Decision-making

Emotional feelings, and consciousness

Neural networks involved in emotion

The book will be valuable for those in the fields of neuroscience and neurology, psychology, psychiatry, and philosophy

Recenzijas

One would struggle to find another single volume that covered so much of relevance in this field with writing so clear and tutorial, doubtless honed by several generations of teaching undergraduates at Oxford University. * Brain *

1 Introduction: the issues
1(12)
1.1 Introduction
1(1)
1.2 Rewards and punishers
2(2)
1.3 The approaches taken to emotion and motivation
4(6)
1.4 The plan of the book
10(3)
2 The nature of emotion
13(32)
2.1 Introduction
13(1)
2.2 A theory of emotion
14(3)
2.3 Different emotions
17(7)
2.4 Refinements of the theory of emotion
24(4)
2.5 The classification of emotion
28(1)
2.6 Other theories of emotion
29(7)
2.6.1 The James-Lange and other bodily theories
30(3)
2.6.2 Appraisal theory
33(2)
2.6.3 Dimensional and categorical theories of emotion
35(1)
2.6.4 Other approaches to emotion
35(1)
2.7 Individual differences in emotion, personality, and emotional intelligence
36(3)
2.8 Cognition and emotion
39(1)
2.9 Emotion, motivation, reward, and mood
40(1)
2.10 The concept of emotion
41(1)
2.11 Advantages of the approach to emotion described here (Rolls' theory of emotion)
42(3)
3 The functions of emotion: reward, punishment, and emotion in brain design
45(22)
3.1 Introduction
45(2)
3.2 Brain design and the functions of emotion
47(6)
3.2.1 Taxes, rewards, and punishers: gene-specified goals for actions, and the flexibility of actions
47(4)
3.2.2 Explicit systems, language, and reinforcement
51(1)
3.2.3 Special-purpose design by an external agent vs evolution by natural selection
51(2)
3.3 Selection of behaviour: cost-benefit `analysis' of net value
53(2)
3.4 Further functions of emotion
55(8)
3.4.1 Autonomic and endocrine responses
55(1)
3.4.2 Flexibility of behavioural responses
56(1)
3.4.3 Emotional states are motivating
57(1)
3.4.4 Communication
58(2)
3.4.5 Social attachment
60(1)
3.4.6 Separate functions for each different primary reinforcer
61(1)
3.4.7 The mood state can influence the cognitive evaluation of moods or memories
62(1)
3.4.8 Facilitation of memory storage
62(1)
3.4.9 Emotional and mood states are persistent, and help to produce persistent motivation
62(1)
3.4.10 Emotions may trigger memory recall and influence cognitive processing
62(1)
3.5 The functions of emotion in an evolutionary, Darwinian, context
63(2)
3.6 The functions of motivation in an evolutionary, Darwinian, context
65(1)
3.7 Are all goals for action gene-specified?
65(2)
4 The brain mechanisms underlying emotion
67(157)
4.1 Introduction
67(1)
4.2 Overview
67(4)
4.3 Representations of primary reinforcers, i.e. of unlearned value
71(5)
4.3.1 Taste
71(1)
4.3.2 Smell
71(1)
4.3.3 Pleasant and painful touch
72(2)
4.3.4 Visual stimuli
74(2)
4.4 Representing potential secondary reinforcers
76(19)
4.4.1 The requirements of the representation
76(4)
4.4.2 Objects, and not their reward and punishment associations or value, are represented in the inferior temporal visual cortex
80(2)
4.4.3 Object representations
82(1)
4.4.4 Invariant representations of faces and objects in the inferior temporal visual cortex
83(11)
4.4.5 Face expression, gesture and view represented in a population of neurons in the cortex in the superior temporal sulcus
94(1)
4.4.6 The brain mechanisms that build the appropriate view-invariant representations of objects required for learning emotional responses to objects, including faces
94(1)
4.5 The orbitofrontal cortex
95(64)
4.5.1 Historical background
95(2)
4.5.2 Topology
97(2)
4.5.3 Connections
99(1)
4.5.4 Effects of damage to the orbitofrontal cortex
100(2)
4.5.5 Neurophysiology and functional neuroimaging of the orbitofrontal cortex
102(40)
4.5.6 The human orbitofrontal cortex
142(9)
4.5.7 A neurophysiological and computational basis for stimulusreinforcer association learning and reversal in the orbitofrontal cortex
151(7)
4.5.8 Executive functions of the orbitofrontal cortex
158(1)
4.6 The amygdala
159(30)
4.6.1 Associative processes involved in emotion-related learning
159(6)
4.6.2 Connections of the amygdala
165(2)
4.6.3 Effects of amygdala lesions
167(7)
4.6.4 Neuronal activity in the primate amygdala to reinforcing stimuli
174(7)
4.6.5 Responses of these amygdala neurons to novel stimuli that are reinforcing
181(1)
4.6.6 Neuronal responses in the amygdala to faces
182(2)
4.6.7 Evidence from humans
184(4)
4.6.8 Amygdala summary
188(1)
4.7 The cingulate cortex
189(9)
4.7.1 Introduction and overview of the anterior cingulate cortex
189(2)
4.7.2 Anterior cingulate cortex anatomy and connections
191(1)
4.7.3 Anterior cingulate cortex functional neuroimaging and neuronal activity
191(4)
4.7.4 Anterior cingulate cortex lesion effects
195(1)
4.7.5 Mid-cingulate cortex, the cingulate motor area, and action-outcome learning
196(2)
4.8 Value-related decision-making and medial prefrontal cortex area 10
198(2)
4.8.1 Decision-making between the value of odours
198(1)
4.8.2 Decision-making between the value of thermal somatosensory stimuli
199(1)
4.8.3 Value-related decision-making and the medial prefrontal cortex area 10: further evidence
199(1)
4.9 Insula
200(3)
4.10 Human brain imaging investigations of mood and depression
203(5)
4.11 Output pathways for emotional responses
208(5)
4.11.1 The autonomic and endocrine systems
208(1)
4.11.2 Motor systems for implicit responses, including the basal ganglia
209(1)
4.11.3 Output systems for explicit responses to emotional stimuli
209(1)
4.11.4 Basal forebrain and hypothalamus
209(1)
4.11.5 Basal forebrain cholinergic neurons
210(2)
4.11.6 Noradrenergic neurons
212(1)
4.12 Effects of emotion on cognitive processing and memory
213(5)
4.13 Laterality effects in human emotional processing
218(3)
4.14 Summary
221(3)
5 Food reward value, pleasure, hunger, and appetite
224(53)
5.1 Introduction
224(1)
5.2 Peripheral signals for hunger and satiety
224(3)
5.3 The control signals for hunger and satiety
227(9)
5.3.1 Sensory-specific satiety
227(5)
5.3.2 Gastric distension
232(1)
5.3.3 Duodenal chemosensors
233(1)
5.3.4 Glucostatic hypothesis
233(1)
5.3.5 Hormonal signals related to hunger and satiety, and their effects on the hypothalamus
233(2)
5.3.6 Conditioned appetite and satiety
235(1)
5.4 The brain control of eating and reward
236(33)
5.4.1 The hypothalamus
236(8)
5.4.2 Brain mechanisms for taste reward value
244(12)
5.4.3 Convergence between taste and olfactory processing to represent flavour
256(1)
5.4.4 Brain mechanisms for the reward produced by the odour of food
257(5)
5.4.5 The responses of orbitofrontal cortex taste and olfactory neurons to the sight of food: expected value neurons
262(1)
5.4.6 Functions of the amygdala and temporal cortex in feeding
262(4)
5.4.7 Functions of the orbitofrontal cortex in feeding
266(3)
5.4.8 Output pathways for feeding
269(1)
5.5 Obesity, bulimia, and anorexia
269(6)
5.5.1 Genetic factors
269(1)
5.5.2 Brain processing of the sensory properties and pleasantness of food
270(1)
5.5.3 Food palatability
271(1)
5.5.4 Sensory-specific satiety
272(1)
5.5.5 Fixed meal times, and the availability of food
272(1)
5.5.6 Food saliency, and portion size
273(1)
5.5.7 Energy density of food
273(1)
5.5.8 Eating rate
273(1)
5.5.9 Stress
273(1)
5.5.10 Food craving
273(1)
5.5.11 Energy output
274(1)
5.5.12 Cognitive factors, and attention
274(1)
5.5.13 Compliance with information about risk factors for obesity
274(1)
5.6 Conclusions on reward, affective responses to food, and the control of appetite
275(2)
6 Pharmacology of emotion, reward, and addiction; the basal ganglia
277(46)
6.1 Introduction
277(2)
6.2 Dopamine and reward
279(8)
6.2.1 Dopamine and brain-stimulation reward
279(1)
6.2.2 Self-administration of dopaminergic substances, and addiction
279(2)
6.2.3 Behaviours associated with the release of dopamine
281(1)
6.2.4 The activity of dopaminergic neurons and reward
282(5)
6.3 The basal ganglia
287(30)
6.3.1 Systems-level architecture of the basal ganglia
288(1)
6.3.2 Effects of basal ganglia damage
289(2)
6.3.3 Neuronal activity in the striatum
291(13)
6.3.4 What computations are performed by the basal ganglia?
304(2)
6.3.5 How do the basal ganglia perform their computations?
306(8)
6.3.6 Synthesis on the role of dopamine in reward and addiction
314(1)
6.3.7 Synthesis: emotion, dopamine, reward, punishment, and action selection in the basal ganglia
315(2)
6.4 Opiate reward systems, analgesia, and food reward
317(1)
6.5 Pharmacology of depression in relation to brain systems involved in emotion
318(1)
6.6 Pharmacology of anxiety in relation to brain systems involved in emotion
319(1)
6.7 Cannabinoids
320(1)
6.8 Overview of behavioural selection and output systems involved in emotion
320(3)
7 Sexual behaviour, reward, and brain function; sexual selection of behaviour
323(45)
7.1 Introduction
323(2)
7.2 The ultimate explanation for the reward value of sex
325(4)
7.3 Mate selection, attractiveness, and love
329(6)
7.3.1 Female preferences
329(2)
7.3.2 Male preferences
331(3)
7.3.3 Pair-bonding, and love
334(1)
7.4 Parental attachment, care, and parent-offspring conflict
335(1)
7.5 Sperm competition and its consequences for sexual behaviour
336(7)
7.6 Concealed ovulation and its consequences for sexual behaviour
343(1)
7.7 Sexual selection of sexual and non-sexual behaviour
344(4)
7.7.1 Sexual selection and natural selection
344(3)
7.7.2 Non-sexual characteristics may be sexually selected for courtship
347(1)
7.8 Individual differences in sexual rewards
348(7)
7.8.1 Overview
349(2)
7.8.2 How might different types of behaviour be produced by natural selection altering the relative reward value of different stimuli in different individuals?
351(2)
7.8.3 How being tuned to different types of reward could help to produce individual differences in sexual behaviour
353(2)
7.9 The neural reward mechanisms that might mediate some aspects of sexual behaviour
355(7)
7.10 Neural basis of sexual behaviour
362(5)
7.11 Conclusion
367(1)
8 Decision-making mechanisms
368(86)
8.1 Introduction
368(1)
8.2 Decision-making in an attractor network
369(4)
8.2.1 An attractor decision-making network
369(2)
8.2.2 An integrate-and-fire implementation of the attractor network for probabilistic decision-making
371(2)
8.3 Mean-field analysis of the attractor decision-making network
373(2)
8.4 Stability, energy landscapes, and noise
375(2)
8.5 Neurophysiology of vibrotactile decision-making
377(3)
8.6 Probabilistic decision-making by the integrate-and-fire attractor model
380(10)
8.6.1 Integrate-and-fire simulations of decision-making
380(1)
8.6.2 Decision-making on single trials
380(2)
8.6.3 The probabilistic nature of the decision-making
382(1)
8.6.4 Probabilistic decision-making and Weber's law
383(3)
8.6.5 Decision times
386(1)
8.6.6 Finite-size noise effects
387(3)
8.7 Confidence in decisions
390(27)
8.7.1 The model of decision-making
391(2)
8.7.2 Neuronal responses on difficult vs easy trials, and decision confidence
393(4)
8.7.3 Decision times of the neuronal responses
397(1)
8.7.4 Percentage correct
397(1)
8.7.5 Simulation of fMRI signals: haemodynamic convolution of synaptic activity
397(2)
8.7.6 Prediction of the BOLD signals on difficult vs easy decision-making trials
399(3)
8.7.7 Neuroimaging investigations of task difficulty, and confidence
402(3)
8.7.8 Correct decisions vs errors, and confidence
405(12)
8.8 Decisions based on confidence in one's decisions: self-monitoring
417(15)
8.8.1 Decisions about confidence estimates
417(1)
8.8.2 A theory for decisions about confidence estimates
417(7)
8.8.3 Decisions about confidence estimates: neurophysiological evidence
424(2)
8.8.4 Decisions about decisions: self-monitoring
426(1)
8.8.5 Synthesis: decision confidence, noise, neuronal activity, the BOLD signal, and self-monitoring
427(5)
8.9 Perceptual decisions
432(1)
8.10 Comparison with other models of decision-making
433(2)
8.11 Applications and implications of this approach to decision-making
435(19)
8.11.1 Multiple decision-making systems in the brain
435(2)
8.11.2 Distributed decision-making
437(1)
8.11.3 Predicting a decision before the evidence is provided
437(2)
8.11.4 The matching law
439(1)
8.11.5 Symmetry-breaking
439(1)
8.11.6 The evolutionary utility of probabilistic choice
440(1)
8.11.7 Unpredictable behaviour
441(1)
8.11.8 Memory recall
441(1)
8.11.9 Creative thought
442(1)
8.11.10 Decision-making with sequential inputs and with postponed responses
442(1)
8.11.11 Decision-making between the emotional and rational systems
442(1)
8.11.12 Dynamical neuropsychiatry: schizophrenia
442(7)
8.11.13 Dynamical neuropsychiatry: obsessive-compulsive disorder
449(3)
8.11.14 Decision-making, oscillations, and communication through coherence
452(2)
9 Neuroeconomics and decision-making
454(29)
9.1 Introduction
454(1)
9.2 Classical economics
455(1)
9.3 Neoclassical economics
456(2)
9.3.1 Utility functions, WARP, and GARP
456(1)
9.3.2 Expected Utility Theory
457(1)
9.3.3 Random Utility Models
457(1)
9.4 Behavioural economics
458(5)
9.4.1 The Allais paradox
458(1)
9.4.2 Risk seeking over losses
458(1)
9.4.3 Prospect Theory
459(4)
9.5 Neuroeconomics
463(20)
9.5.1 Overview of neuroeconomics
463(6)
9.5.2 A common scale of value for different goods in the orbitofrontal cortex, but no conversion to a common currency
469(4)
9.5.3 Absolute value and relative value are both represented in the orbitofrontal cortex
473(4)
9.5.4 The representation of expected reward value
477(1)
9.5.5 Delay of reward, emotional choice, and rational choice
477(2)
9.5.6 The representation of negative reward prediction error
479(1)
9.5.7 The representation of positive reward prediction error
479(1)
9.5.8 Reward prediction error, temporal difference error, and choice
480(1)
9.5.9 Conclusions
481(2)
10 Emotional feelings and consciousness: a theory of consciousness
483(35)
10.1 Introduction
483(1)
10.2 A Higher-Order Syntactic Thought (HOST) theory of consciousness
484(12)
10.2.1 Multiple routes to action
484(3)
10.2.2 A computational hypothesis of consciousness
487(2)
10.2.3 Adaptive value of processing in the system that is related to consciousness
489(1)
10.2.4 Symbol grounding
490(1)
10.2.5 Qualia
491(1)
10.2.6 Pathways
492(1)
10.2.7 Consciousness and causality
493(2)
10.2.8 Consciousness, a computational system for higher-order syntactic manipulation of symbols, and a commentary or reporting functionality
495(1)
10.3 Selection between conscious vs unconscious decision-making, and free will
496(8)
10.3.1 Dual major routes to action: implicit and explicit
496(6)
10.3.2 The Selfish Gene vs The Selfish Phenotype
502(2)
10.3.3 Decision-making between the implicit and explicit systems
504(1)
10.4 Determinism
504(2)
10.5 Free will
506(1)
10.6 Content and meaning in representations
507(2)
10.7 The causal role of consciousness: a theory of the relation between the mind and the brain
509(2)
10.8 Comparison with other theories of consciousness
511(7)
10.8.1 Higher-order thought theories
511(2)
10.8.2 Oscillations and temporal binding
513(1)
10.8.3 A high neural threshold for information to reach consciousness
514(1)
10.8.4 James-Lange theory and Damasio's somatic marker hypothesis about feelings
515(1)
10.8.5 LeDoux's approach to emotion and consciousness
515(1)
10.8.6 Panksepp's approach to emotion and consciousness
515(1)
10.8.7 Global workspace theories of consciousness
516(1)
10.8.8 Monitoring and consciousness
516(2)
11 Conclusions, and broader issues
518(26)
11.1 Conclusions
518(7)
11.2 Decision-making
525(10)
11.2.1 Selection of mainly autonomic responses, and their classical conditioning
525(1)
11.2.2 Selection of approach or withdrawal, and their classical conditioning; fixed action patterns
526(1)
11.2.3 Selection of fixed stimulus-response habits
526(1)
11.2.4 Selection of arbitrary behaviours to obtain goals, action-outcome learning, and emotional learning
526(1)
11.2.5 The roles of the prefrontal cortex in the selection of action, in decision-making, and in attention
527(6)
11.2.6 Selection of actions by explicit rational thought
533(2)
11.3 Emotion and ethics
535(4)
11.4 Emotion and aesthetics
539(3)
11.5 Close
542(2)
A Neural networks and emotion-related learning
544(45)
A.1 Neurons in the brain, the representation of information, and neuronal learning mechanisms
544(11)
A.1.1 Introduction
544(1)
A.1.2 Neurons in the brain, and their representation in neuronal networks
544(1)
A.1.3 A formalism for approaching the operation of single neurons in a network
545(2)
A.1.4 Synaptic modification
547(2)
A.1.5 Long-Term Potentiation and Long-Term Depression
549(4)
A.1.6 Distributed representations
553(2)
A.2 Pattern association memory
555(17)
A.2.1 Architecture and operation
556(2)
A.2.2 A simple model
558(3)
A.2.3 The vector interpretation
561(1)
A.2.4 Properties
562(3)
A.2.5 Prototype extraction, extraction of central tendency, and noise reduction
565(1)
A.2.6 Speed
565(1)
A.2.7 Local learning rule
566(5)
A.2.8 Implications of different types of coding for storage in pattern associators
571(1)
A.3 Autoassociation memory: attractor networks
572(8)
A.3.1 Architecture and operation
573(2)
A.3.2 Introduction to the analysis of the operation of autoassociation networks
575(1)
A.3.3 Properties
575(5)
A.4 Coupled attractor networks
580(2)
A.5 Reinforcement learning
582(7)
A.5.1 Associative reward-penalty algorithm of Barto and Sutton
583(1)
A.5.2 Error correction or delta rule learning, and classical conditioning
584(1)
A.5.3 Temporal Difference (TD) learning
585(4)
B Decision-making models
589(30)
B.1 Overview of different models of decision-making
589(21)
B.1.1 Sequential-sampling models: sequential probability ratio test, drift-diffusion, and race models
589(6)
B.1.2 Biologically motivated rate models
595(2)
B.1.3 Attractor models
597(11)
B.1.4 Distinguishing model approaches
608(2)
B.2 Synaptic facilitation and sequential decision-making
610(2)
B.3 Synaptic facilitation, graded firing rates, and postponed decisions
612(2)
B.4 The integrate-and-fire formulation used in the model of decisionmaking
614(2)
B.5 The mean-field approach used in the model of decision-making
616(2)
B.6 The model parameters used in the simulations of decision-making
618(1)
C Glossary
619(68)
References
621(58)
Index
679(8)
D Colour Plates
687
Professor Edmund T. Rolls performs full-time research at the Oxford Centre for Computational Neuroscience, and at the University of Warwick, and has acted as Professor of Experimental Psychology at the University of Oxford, and as Fellow and Tutor of Corpus Christi College, Oxford. His research links neurophysiological and computational neuroscience approaches to human functional neuroimaging and neuropsychological studies in order to provide a fundamental basis for understanding human brain function and its disorders.
Biežāk uzdotie jautājumi par e-grāmatām Biežāk uzdotie jautājumi par e-grāmatām
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