1. Emotions S. Suchitra

2. Simplest way to introduce emotions into a computational model – add emotion nodes Nerb & Spada (2001) provided a computational account of how media information about environmental problems influences cognition and emotion Show how determinants of responsibilty, controllability of the cause, motive of the agent and knowledge about possible negative consequences can be incorporated into a coherent network called ITERA Models for emotions

3. ITERA – Intuitive Thinking in Environmental Risk Appraisal Extension of impression-formation model (Kunda & Thagard, 1996) Main innovation of ITERA – addition of units corresponding to emotions such as anger and sadness

4. ITERA model + DAMAGE HUMAN AGENCY CONTROLLABILITY HIGHER GOAL KNOWLEDGE ANGER SADNESS BOYCOTT HELP OBSERVED - OBSERVED +

5. ITERA is given input concerning whether or not an accident was observed to involve damage, human agency, controllability and other factors It then predicts a reaction of anger or sadness depending on their overall coherence with the observed features of the accident This reaction can be thought of as a kind of emotional summary of all the available information

6. Another way to introduce emotion into local neural networks is found in HOTCO (hot coherence) model (Thagard; 2000, 2003) Differs from other models – each unit is given a valence representing its applicability to the current situation ITERA and HOTCO models neurobiologically impossible as they use local units which are not like real neurons, and ignore the division of the brain into functional areas

7. GAGE model In honour of Phineas Gage, a 19 th century railroad worker Suffered brain damage from a pipe that penetrated his skull, but survived his injury Regained verbal and mathematical abilities Incapable of making sensible decisions about work or personal life

8. Damasio describes modern patients with similar problems Hypothesizes that they have lost the ability to make effective decisions because of disruptions between the emotional and cognitive parts of their brain

9. Ventromedial (bottom-middle) prefrontal cortex Provides links between the areas of cortex involved in judgments (amygdala) and areas involved in emotions and memory (hippocampus) Wagar &Thagard –How Gage’s deficit can be modeled using groups of spiking neurons corresponding to each of the crucial brain areas – the Ventromedial prefrontal cortex, amygdala, nucleus accumbens –Nucleus accumbens – strongly associated with rewards, and also addiction to drugs and alcohol

11. GAGE model uses distributed representations of input stimuli and associated emotions relies on the spiking properties of neurons to provide temporal activities of the activities of the different brain areas more neurologically realistic than ITERA and HOTCO models

12. When it operates fully, nucleus accumbens serves to integrate emotional and cognitive information from different parts of the brain But when it is “lesioned” by disruption, the neurons corresponding to the ventromedial prefrontal cortex, model behaves like Phineas gage and Damasio patients

13. GAGE is not a full model of cognitive/emotional processing But shows how such a model can take into account both cognitive aspects of judgment and appraisal performed by the prefrontal cortex, and the physiological aspects of emotions Bidirectional connections – interaction is the right way of thinking about the relation between cognitive and physiological aspects of emotion

14. Limitations ITERA, HOTCO, GAGE are just models Lack conscious experience of emotions Do not have bodily inputs that are a crucial part of human emotions Gage model takes for granted that amygdala collects information about bodily inputs –As computer model, doesn’t have any bodily inputs

15. Robot bodies and humans are different – can computers and robots have emotions like humans? Not implausible to describe the brain as a kind of emotional computer that integrates emotions and other sorts of information to enable people to make decisions Psychological, neurological and neurocomputational understanding of how emotions influence thinking is rapidly developing So, cognitive science is clearly responding well to the emotional challenge

16. Incomplete if it does not explain why we experience feelings Learning can be emotional Understanding importance of emotions in human thinking process and decision making Understanding emotions also important for success –Successful leaders need to be capable of empathy for others and able to inspire them by providing motivating emotions Diagnosing and treating mental illnesses and disorders such as schizophrenia, bipolar disorder Applications

17. References Mind (second edition) by Paul Thagard