cognitive exam 4 review

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Psychology & Brain Sciences
Andrew Cohen

Chapter 10  Distinguish between thinking, problem solving, and reasoning (p. 412).  Thinking: mentally representing some aspects of the world and transforming these representations so that new representations, useful to our goals, are generated  Problem solving: set of cognitive processes that we apply to reach a goal when we must overcome obstacles to reach that goal  Reasoning: cognitive processes we use to make inferences from knowledge and draw conclusions  Describe the structure of a problem, including the initial state and the goal state (pp. 414-415).  There are three parts to a problem  Goal state: where you want to be at the solution of the problem  Initial state: where you are now as you face the problem that needs to be solved  Set of operations that you can apply: the actions to get from the initial state to the goal state  Compare well-defined problems to ill-defined problems, including special mention of insight problems (p. 415).  Well-defined problems: problems in which the initial state and the goal state are clearly defined at the possible moves are known  Ill-defined problems: problems in which the initial state, the operations, or even the goal of the problem are unknown. The problem solver must find the constraints that apply to particular situations  Insight problems: a special case of ill-defined problems that is characterized by a sudden “flash of understanding” despite all of the unknown factors  Define problem space theory (pp. 416-417).  Developed by Newell and Simon  The set of states or possible choices that faces the problem solver at each step in moving from initial state to goal state  Compare and contrast problem solving heuristics, including random search, hill climbing, means-ends analysis, and verbal protocol analysis (pp. 417-421).  Problem solving heuristics: a rule of thumb that usually, but not always, gives the correct answer in a rather quick fashion. An algorithm is a much more accurate procedure for problem solving though tends to take much longer.  Random search: the simplest and least demanding heuristic that is characterized by a process of trial and error. We frequently resort to this when everything else has failed.  Hill climbing: problem solver looks one move ahead and chooses the move that most closely resembles the goal state. This is often a more reliable heuristic than random search but can lead the problem solver astray  Means-ends analysis: the problem is broken into sub-problems. This is often a more demanding but more successful heuristic  Verbal protocol analysis: the analysis of the thought process of the problem solver as described aloud by the solver in the course of working on the problem. Identify what areas of the brain are involved in problem solving, as have been identified through neuroimaging techniques and brain damage patients (p. 421).  In healthy participants who are monitored while performing problem solving tasks, the right dorsolateral prefrontal cortex, bilateral parietal cortex and bilateral premotor cortex were activated. These regions are heavily associated with working memory and executive processes. Discuss how working memory might be involved in problem solving (p. 421).  When a problem solver is determining what operations are required to reach goal state using goals and sub-goals, working memory must be used to recall these tasks. Describe how expert problem solvers differ from novices in their organization and encoding of the problem, and direction of search (pp. 423-424).  Experts typically know more information about a particular topic than novices.  Novices often organize concepts in terms of surface features whereas experts organize in terms of deeper abstract principles.  This is because novices and experts encode information differently  Experts chunk information and can access related chunks of knowledge from long term memory thus making their problem solving more efficient Define analogical reasoning, including the identification of the five sub- processes involved (pp. 424-427).  Analogical reasoning: a process of comparison, using knowledge from one relatively known domain and applying it to another domain. Trying to think of a problem with similar characteristics that have been solved before and either use or adapt that solution to the present problem  Five sub-processes involved  Retrieval: holding a target in WM while accessing a similar example from LTM  Mapping: holding both source and target in WM while also aligning the source and target with similar sources  Evaluation: is the analogy useful?  Abstraction: isolating the structure shared by source and target  Predictions: developing hypotheses about the behavior of the target from what is known about the source Compare and contrast Structure Mapping Theory (SMT) and the LISA model as theories of analogical reasoning (pp. 427-428).  Structure mapping theory (SMT)  Stage 1: LTM is searched for potential sources that have a superficial feature that is contained in the target  State 2: how good does a match exist between what was retrieved in the first stage and the target  Although structural similarity is the key component of analogical reasoning, the human cognitive system looks for superficial matches when searching memory for possible sources and we find it difficult to retrieve true relational analogs  LISA model (learning and inference with schemas and analogies)  Mechanisms that are like neural networks that features both source and target may be considered as nodes in a network  Target is represented in terms of the activations of features of the source Describe inductive reasoning, including category-based induction (p. 429).  Inductive reasoning: any thought process that uses our knowledge of specific known instances to draw an inference about unknown instances  Category-based induction: either generalizing from known instances to all instances or generalizing from some members of a category known to have a given property to other instances of that category Identify and describe the different strategies used in general inductions (pp. 429-432).  Describe the components of specific inductions, including the premise and the conclusion (pp. 432-433).  Describe the similarity-coverage model, and give examples (p. 434).  Similarity-coverage model  A model of category-based induction  Underlying the typicality effects observed in inductive reasoning is the notion of coverage Describe how deductive reasoning relies on syllogisms (p. 437).  Syllogisms: arguments that consist of two statements and a conclusion. The conclusion may be either true or false. A conclusion that follows from the two statements is a valid conclusion  The premise of deductive reasoning is that a valid conclusion follows from the premises as a matter of logical necessity Compare and contrast categorical and conditional syllogisms (pp. 437-440).  Categorical syllogism: relations between two categories of things  Often represented in venn diagrams  Conditional syllogisms: consists of two premises and a conclusion that follow the if p than q statement Discuss what types of errors are often witnessed in deductive thinking, including form and content errors (pp. 440-443).  Form errors: result from errors in the structural form or format of the premise-conclusion relationship  Atmosphere effect: the use of “some, all, or no” in the two premises conveys an overall mood that leads participants to accept a conclusion containing the same term  Matching bias: accepting a conclusion as valid if it contains the syntactic structure of the premises or some of the terms of the premise  Strongly influenced by quantifiers (some, all, no) used in the premises  Content errors: logical deductions should be influenced only by the structure of the premises however due to a world where content is often important, we focus on the truth or falsity of individual statements in the syllogism while ignoring the logical connection between statements  Belief-bias effect: tendency to be more likely to accept a believable conclusion to a syllogism than an unbelievable one Compare and contrast the various theories of deductive reasoning, including rule-based approaches and mental models (pp. 443-446).  Ruled-based approaches: deduction depends on formal rules of inference akin to those of a logical calculus  Humans naturally possess a logical system that enables us to make deductions  We attempt to solve deductive reasoning problems by generating sentences that link the premises to the conclusion  Mental models: internal representations of real or imaginary situations that can be derived from information such as that in syllogisms.  Constructed that best represents the information in the premises  A tentative conclusion is generated and evaluated to be determined if it’s consistent with the model derived in the first stage  Must be validated  Provides a good account for both form and content errors in deduction Describe the linguistic versus spatial differentiation in reasoning (pp. 446-447).  Linguistic model: because deductive reasoning involves language-like properties of representations, we should see activation of the left- hemisphere language structures such as frontal and posterior temporal regions  Patients with left hemisphere damage have a deficit in simple deductive reasoning tasks  Spatial model: in order to reason we create spatial representations of linguistic information and we would expect to see activation of the visual-spatial perceptual structures such as the parietal and occipital lobes  Significant activations in right middle temporal cortex and right inferior frontal gyrus for a similar task of deductive reasoning Chapter 11  Explain what motor cognition is (p. 452).  Mental processing in which the motor system draws on stored information to plan and produce our own actions, as well as to anticipate, predict, and interpret the actions of others.  Identify the difference between movement and action (pp. 452-453).  Movement is a voluntary displacement of a body part in a physical space  Action is a series of movements that must be accomplished to reach a goal  Describe the perception-action cycle and the role of intentions (p. 453).  Perception-action cycle: transformation of perceived patterns into coordinated patterns of movement. It relies on a sophisticated set of neural processes.  Role of intentions: intentions are mental plans that are designed to achieve a goal through action. The contents of both perceptions and intentions depend on neural processes with both perceptual and motor aspects working together  Locate and describe the three parts of the brain that are involved in motor processing (pp. 453-454).  M1: responsible for specific movements  SMA: supplementary motor area is responsible for the planning of an action  PM: premotor area that is responsible for generalized or less precise movements  Describe how shared motor representations complement our social environment (pp. 455-456).  Shared motor representations: our ability mentally to represent actions made by other people
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