430 Exam 2 Review

430 Exam 2 Review

University

14 Qs

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430 Exam 2 Review

430 Exam 2 Review

Assessment

Quiz

Science

University

Practice Problem

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Created by

Katherine Moen

Used 7+ times

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14 questions

Show all answers

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.

Correct Rejection

Not hearing your phone when it isn't ringing

Miss

Not hearing your phone when it IS ringing

Hit

Hearing your phone when it isn't ringing

False Alarm

Hearing your phone when it IS ringing

5.

REORDER QUESTION

1 min • 1 pt

Reorder the detectors in feature nets from first to last

Letter

Feature

Word

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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