Cog Psych Midterm 4 Part 1

Front 1

myth of media multitasking

Back 1

frequent media multitaskers are cognitively skilled and good at multitasking and often highly confident about their own multitasking ability

Front 2

reality of media multitasking

Back 2

frequent media multitaskers are bad at multitasking and perform poorly on cognitive tasks

1. particularly bad at filtering out irrelevant information

2. lower academic performance (course grades)

3. tend to be impulsive and sensation seeking

Front 3

is multitasking negative relationship casual in nature?

Back 3

we know for sure their is a negative correlation between high media multitasking frequency and poor cognitive performance

Front 4

casual relationship between media multitasking and cognitive performance

Back 4

high media multitasking frequency leads to poor cognitive performance

Front 5

non casual relationship between media multitasking and cognitive performance

Back 5

there is a third variable that connects the corelation of high media multitasking frequency and poor cognitive performance

Front 6

watson and strayer 2010 study

Back 6

procedure was

singly task-driving

single task-operation span

dual task- driving and operation span

dependent measures

driving--brake speed and following distance

operation span--memory and math accuracy

only 2% could do the two

Front 7

automatic processes

Back 7

1. involve a minimal amount of mental resources

2. performance of highly familiar/skilled tasks

Front 8

controlled processes

Back 8

require a deliberate allocation of mental resources

performance of unfamoiliar tasks or acquisition of new skills

Front 9

stroop effect

Back 9

word reading can interfere with color naming when the color word is incongruent with the ink color

a more automatic task (word reading) intereferes with a less automatic task (color naming)

Front 10

effects of practice on automatization

Back 10

practice diminishes demand on mental resources--practice turns controlled into automatic processes (automatization)

Front 11

macleod and dunbar study

Back 11

backed practice of automatization with naming shapes vs naming arbitrary shapes

before, colors interere with shape naming (color naing is more automatic than shape naming)

after practice, shapes interfere with color naming

Front 12

are all subprocesses automatic?

Back 12

some sub. are more automatic than others and some may never achieve high levels of auomaticity

Front 13

posner and peterson's attentional network theory

Back 13

1. arousal (alerting) system

2. posterior attention (orienting) system

2. anterior attention (executive attention) system

Front 14

orienting attention key regions

Back 14

parietal love and superior colliculus

Front 15

executive attention key regions

Back 15

frontal lobe and the anterior cingulate

Front 16

alertness key regions

Back 16

reticular formation and thalamus

Front 17

posterior attention system

Back 17

for the primarily bottom up orienting of attention

Front 18

component processes for posterior attention system

Back 18

1. disengagin the "spotlight"

2. moving the "spotlight"

3. locking into position (enhacning)

Front 19

disorder related to the posterior attention system

Back 19

unilateral neglect

Front 20

unilateral neglect

Back 20

the lack of attention to one side of space, usually as a result of parietal lobe damage--almost always left side, but some info may get through

Front 21

anterior attention system

Back 21

top down regulation of attention (executive attention). selectively attending to one dimension while ignoring the other (stroop) and coordinating multiple activities or multitasking (divided attention)

Front 22

anterior attention system related disorder

Back 22

ADHD

Front 23

central symptoms of ADHD

Back 23

1. inattentive

2. impulsive

3. hyperactive

Front 24

some symptoms of inattentive in ADHD

Back 24

1. high distractibility

2. dificulty focusing and sustaining attention

Front 25

definition of impulsive behaviors in ADHD

Back 25

behavioral control (inhibition) problems

Front 26

definition of hyperactive behavior in ADHD

Back 26

1. fidgeting

2. always being "on the go"

3. excessive talking

Front 27

symptoms linked to the anterior attention system

Back 27

1. diminished blood flow in the frontal lobe

2. sitmulating frontal lobe function (eg via drugs like ritalin) improves concentration and alleviate hyperactivity

Front 28

hierarchical network model

Back 28

collins and quillian. knowledge is organized in a hierarchical manner and each "node" represents a concept

nodes are linked to categorically related concepts

each node is also linked to associated properties

Front 29

principle of cognitive economy

Back 29

1. associated properties are stored at the highest [possible level of hierarchy

2. ex "breaths" is stored at the level of "animal" not "bird" or "canary"

Front 30

problems of the hierarchical network model

Back 30

1. typicality effects --"a robin is a bird" verified faster than "a peacock is a bird"

2. prominent feature effect--"a peacock has feathers" is verified as quickly as "a canary can sing"

3. unlikely neat herarchical structures exist for some concepts or categories

4. most things can be classified in more than one way

Front 31

spreading activation model

Back 31

collins and loftus. nodes interconnected by links

links are between associated concepts (bread and butter) and have differential strengths (indicated by the distance between nodes

activation soreads along the links, making related concepts more accessible

related to semantic priming effect

Front 32

semantic priming effect

Back 32

meyer and schwanevelt

method: deciding whether each word presented is real of not (lexical decision)

results: response was fasater if the target word is preceded by a related word than by an unrelated word

Front 33

difference between semantic priming and repetition priming

Back 33

semantic priming is short lived and does not last multiple days or even minutes

Front 34

strengths of evaluation of the spreading activation model

Back 34

1. can explain the semantic priming effect

2. can epxlin the findings that the hierarchical network model failed to explain (typicality effect)

Front 35

weaknesses of evaluation of the spreading activation model

Back 35

the model may be too flexible and is difficult to falsify (the model can be easily tweaked to fit the data

Front 36

distributed network approach

Back 36

assumes that the brain represents a concept in a distrubuted manner

a concept is represented by multiple nodes and similar concepts are associated with similar patterns

Front 37

difference between semantic knowledge impairment and visual agnosia

Back 37

agnosia patients can demonstrate intact semantic knowledge when tested verbally (but not visually)

Front 38

symptoms or brain damage and impaired semantic knowledge

Back 38

dissociation between living things and nonliving things

2. more specific deficits have been reported (eg fruits and vegetables)

Front 39

multiple semanti memory systems basic assumptions

Back 39

farah and mcclelland,

1. each comcept is represented in the brain in a distributed manner

2. there are multiple semantic systems supported by different brain regions

Front 40

semantic systems in farah and mcclelland

Back 40

visual system--representing one's knowledge of visual features

function system (representing one's knowledge of functions)

Front 41

multiple semantic memory systems main proposal

Back 41

1. living things are represented more strongly in the visual system than in the functional system

2. nonliving things are represented equally strongly in the two semantic memory systems

3. category specific impairments refelct damage to different parts of the semantic memory system

Front 42

category specific impairments

Back 42

visual system--impairs living things more severely

functional system--impairs nonliving things more severely

Front 43

distributed network approach strengths

Back 43

1. can explain category specific impairments

2. idea is tested in neural network simulation models

3. idea of distributed semantic knowledge is consistent with the way information is represented in the brain

Front 44

distributed network approach weaknesses

Back 44

more semantic knowledge systems are probably necessary (eg auditory, motion, etc)