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430 Exam 2 Review

Authored by Katherine Moen

Science

University

Used 7+ times

430 Exam 2 Review
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14 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Laura suffered brain damage and now has difficulty identifying objects. Specifically, she can see individual features, but has a hard time assembling those features into complex wholes. She is likely suffering from

prosopagnosia

apperceptive agnosia

aphasia

memory loss

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Participants’ recognition thresholds are

lower for frequently seen words.

higher for recently seen words.

not affected by priming.

lower for words with unusual spelling.

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is an example of feature search?

Looking for a black dog surrounded by black and brown cats and dogs.

Looking for a black dog surrounded by squirrels

Looking for a black dog surrounded by other black dogs

Looking for two black dogs that match

4.

MATCH QUESTION

1 min • 1 pt

Match the situation to the outcome based on signal detection theory.

Miss

Not hearing your phone when it IS ringing

False Alarm

Not hearing your phone when it isn't ringing

Hit

Hearing your phone when it IS ringing

Correct Rejection

Hearing your phone when it isn't ringing

5.

REORDER QUESTION

1 min • 1 pt

Reorder the detectors in feature nets from first to last

Feature

Word

Letter

Bigram

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Feature nets help with word recognition based on a combination of information from multiple sources, rather than just one source. This means that feature nets prioritize:

efficiency

accuracy

detail

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What's the main difference between the McClelland Rumelhart Model and Feature Nets?

Feature nets only focus on signal enhancement

McClelland Rumelhart only focus on signal enhancement

Feature nets only focus on signal inhibition

McClelland Rumelhart only focus on signal inhibition

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