Psyc 310 1st EditionExam # 3 Study Guide Lectures: 12-17Lecture 12 (March 24)Chapter 8:Can “leading” information make you remember something that didn’t actually happen? Yes.For instance, when asking about a crime committed, someone might ask, “What kind of gun wasthe criminal holding?” Because they assumed the weapon was a gun, you now have a false memory of the criminal holding a gun when the criminal may have been unarmed or armed in adifferent way. You may also have false familiarity. In a line-up, they may ask who the shooter was. However, there was another hostage in the line-up and you think he is startlingly familiar. You can misplace that familiarity and end up identifying the wrong person because of it.Reminiscence Bump: can remember memory from early 20s but can’t remember something that happened a couple of days agoSelf image hypothesis – important time in your life, defines who you are which is why it is a more prominent memoryCognitive Hypothesis – rapid change, big shifts in lifestyleCultural Life Script Hypothesis – map our life to social norm like graduation or marriage and so those memories stand out more Lecture 13 (March 26)Chapter 8: Flashbulb memories typically have more confidence when retelling a memory though it typicallyhas less detail.Normal memory: typically you feel the full experience of the memory whereas with a flashbulb you wouldn’t.Lecture 14 (March 31)Chapter 9:Prototypical – take averages of features and make a prototype (birds have wings, beaks, etc)Exemplar – Birds = Robin (give example of certain thing)Typicality Effect between the 2? Yes Higher familiarity, more likely to categorize an apple as a fruit than a pear.Lecture 15 (April 2)Original Semantics Network Model: Hierarchy – broader things at the top of hierarchy while more specific things are at the bottomSee Spreading Activation in textbook.Lecture 16 (April 7)The new model has less emphasis on hierarchy but acknowledges the way you interpret something can depend on experiences. Length of nodes also plays a role. Criticisms of this model: (both good and bad) new model is more flexible which is good. It can handle more exceptions. However, it is not very testable. It is difficult to prove/disprove.Connectionist Model: computer models, learning can be generalized.Different input units: input, output, hidden.Lecture 17 (April 9)Spatial – picture of a saluki dogPropositional – breaking down image of saluki dog into features such as long tail, medium sized, four legs, etc.Be able to know the difference between Visual Imagery (takes effort and is considered fragile) and Visual Perception (automatic and stable). Are there dissociations between the
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