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Sketch of a Neurocomputational Explanation of Emotional Consciousness

Sketch of a Neurocomputational Explanation of Emotional Consciousness. Paul Thagard University of Waterloo. Mechanistic Explanation of Emotional Consciousness. Consciousness Explanation Brains GAGE Objections Conclusions. Origins of Consciousness. Creation: God’s gift.

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Sketch of a Neurocomputational Explanation of Emotional Consciousness

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  1. Sketch of a Neurocomputational Explanation of Emotional Consciousness Paul Thagard University of Waterloo

  2. Mechanistic Explanation of Emotional Consciousness • Consciousness • Explanation • Brains • GAGE • Objections • Conclusions

  3. Origins of Consciousness • Creation: God’s gift. • None: consciousness is mythical, like demons and caloric. • By-product of evolution of cognitive complexity. • Evolution by natural selection: increases ability to survive and reproduce.

  4. What is the Function of Consciousness? • Emergency interrupt? • Improve perception, sensation, inference? • Improve problem solving? • Improve teaching of skills? • All of these seem like minor improvements.

  5. Humphrey’s Social Theory • Humphrey: The function of consciousness is social, improving the ability to understand, predict, and manipulate the behavior of others. • Implication: Emotional consciousness is central.

  6. What are Emotions? • Cognitive theory: Emotions are appraisals of situations. • Physiological theory: Emotions are physiological reactions to situations. • Integration: Emotions are mental (brain) states caused by interplay of physiological reactions and cognitive appraisals.

  7. Explanation Targets • What is it like to be happy? Highly misleading question. Alive. • Why does someone become happy? • Why does someone go from being happy to being sad? • How does happiness affect behavior?

  8. How Consciousness Helps • There are unconscious emotions. • If you become conscious of your emotions, then you make approximate generalizations: • If <situation> then <emotion> • If <emotion> then <behavior> • Linguistic representation of emotional states requires conscious awareness of them. • Explanation target: How do brains become aware of emotional states in order to reason about them?

  9. Mechanistic Explanation • How does a bicycle move? • Parts: frame, wheels, gears, chain, pedals, etc. • Relations: e.g. pedal connected to gear. • Behaviors: e.g. pedal moves when pressed.

  10. Brains: Neurons • Parts of brains: neurons, glia, neural populations, brain areas. • 100 billion neurons, with thousands of connections. • Main behavior: spike as result of chemical inputs.

  11. Brains: Neural Populations • Computational Functions of Neural Populations (Eliasmith & Anderson, 2003). • Encode information, e.g. perceptual input encoded by spiking patterns of a population. • Decode information, taking inputs from other neural populations. • Transform information, changing the internal representation of information. EXAMPLES?

  12. Brains: Areas • Areas are anatomically identifiable collections of neural populations that are highly interconnected with each other. • For emotion, some important areas are: amygdala (fear), nucleus accumbens (reward), insula, ventromedial and dorsolateral prefrontal cortex.

  13. Neural Mechanism • GAGE model: Wagar & Thagard, Psychological Review, 2004. VMPFC Amg Somatic state HC VTA NAc To Action/ Overt

  14. Key Brain Areas • Prefrontal cortex: responsible for reasoning. • Ventromedial PFC: connects input from sensory cortices with amygdala etc. • Amygdala: processes emotional signals, especially fear. Somatic input. • Nucleus accumbens: processes emotional signals, especially reward. • Hippocampus: crucial for memory formation.

  15. How GAGE Explains Phineas • Damasio: Effective decision making depends on integration of cognitive information with somatic markers. • Damage to VMPFC prevents this integration. • GAGE shows a plausible mechanism for integration that is disrupted by VMPFC damage.

  16. GAGE II - under development • Incorporate additional brain areas: insula, anterior cingulate cortex, dorsolateral prefrontal cortex. • Incorporate higher level representations of relational information, to describe situation-emotion-behavior connections.

  17. Components of Emotional Consciousness • Spiking neurons are organized into neural populations. • Some neural populations encode perceptual and somatic inputs. • Some neural populations decode, encode, and transform inputs from (2) plus cognitive inputs. • Feedback loops are common.

  18. Higher Order Representations Hypothesis 1: There are neural populations, possibly distributed across brain areas, that encode emotions. Hypothesis 2: There are neural populations that encode generalizations of the form <situation> <emotion> <emotion> <behavior>

  19. Agenda • Design system of brain areas that conducts neural transformations of transformations of sensory, somatosensory, and memory inputs. • Apply this system to explaining emotional phenomena.

  20. Explanation Targets Intense • Onset and end of positive and negative emotions. • Increase and decrease in intensity. grief elation anger joy sadness happiness - + bored anxious amused Weak

  21. Mechanisms • Onset of positive emotions results from perceptual or memory input that activates reward areas. • Intensity is a function of degree of cognitive evaluation and physiological inputs.

  22. Scientific Objections • Need for more detail about how the encodings work. • Need application to specific aspects of emotional consciousness.

  23. Philosophical Objections • Zombies: We can imagine creatures just like us but lacking emotional consciousness. Response: imagination is a poor guide to reality. • What Mary knows: Mary (without emotional consciousness) could know everything about the neuroscience of happiness, but not know what happiness is. Response: Mary would never have made it through kindergarten.

  24. Philosophical Objections • The mechanistic theory of emotional consciousness doesn’t tell us what it is like to be emotional. • Response: it also doesn’t tell us how many hours there are in a kilogram. • Better response: it should be able to explain why we feel positive/negative, weak/intense,

  25. Conclusion Mechanistic explanations of emotional consciousness are feasible. They will require further understanding of the functions of different brain areas.

  26. Web sites • http://cogsci.uwaterloo.ca/ • http://faculty.washington.edu/chudler/neurok.html • http://www.thebrain.mcgill.ca/flash/index_i.html

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