How are sentences stored in LTS? Explicit tasks; episodic memory Sachs (1967) STUDY subjects hear a story “…A wealthy manufacturer, Matthew Boulton, sought out the young inventor…” TEST yes-no recognition correct response (1) identical sentence yes (2) change form, but not no meaning (formal) (3) active/passive change no (4) semantic change no ONLY (4) CHANGES MEANING
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How are sentences stored in LTS? Explicit tasks; episodic memory Sachs (1967) STUDY subjects hear a story “…A wealthy manufacturer, Matthew Boulton, sought.
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How are sentences stored in LTS?
Explicit tasks; episodic memorySachs (1967)
STUDY subjects hear a story
“…A wealthy manufacturer,Matthew Boulton, sought outthe young inventor…”
TEST yes-no recognition
correct response(1) identical sentence yes(2) change form, but not no meaning (formal)(3) active/passive change no(4) semantic change no
ONLY (4) CHANGES MEANING
Sachs Results
You forget the form of the sentence, butremember the meaning
FalseAlarms
immediate 80 syllableslater
160 syllableslater
| | |
10%
50%
Test is
FormChange
Active/Passive
SemanticChange
In STS, you remember the actual words of thesentence.
In LTS, you remember the meaning, but forgetthe wording.
False Alarm Method
Try to get subjects to make a false alarm on a yes-no recognition test
It shows what part of the episode they remembered and what part they forgot
e.g., in Sachs (1967), false alarms to items withsame meaning, but different wording
Sentences in LTS are stored as propositions
Ratcliff & McKoon (1978)
Study list of sentences...
“The geese crossed the horizon as the wind shuffledthe clouds.”
.
.
.
1. CROSS (GEESE, HORIZON)
2. SHUFFLE (WIND, CLOUDS)
3. AS (1,2)
Predict horizon “closer” togeese than to wind
Item recognition priming test
“clouds” “yes”“chair” “no”
.
.
.“geese” OR “wind” “yes” PRIME“horizon” “yes” TARGET
RT to horizonwhen geese is prime when wind is prime
600 msec 630 msec
Why?
Either because GEESE is closer to HORIZONin sentence (surface structure)
Or because GEESE and HORIZON are in the same proposition (propositional hypothesis)
STUDY“The kitten that the girl was carrying scratched the lawyer”
SCRATCH (KITTEN1, LAWYER1)CARRY (GIRL1, KITTEN1)
TEST (item recognition priming)
PRIME “kitten” “girl”
TARGET “lawyer” “lawyer”
Integration Hypothesis
Propositions that contain the same conceptsconnect together in memory
Example:“A car hit a tree. The tree fell on a wire,
and the wire touched another car.”
HIT (CAR1, TREE1)FALL-ON (TREE1, WIRE1)TOUCH (WIRE1, CAR2)
Car Tree Wire
Concepts already in semantic memory
Tree1Car1
Car2
Wire1
is isis
is
hit fall on
touch
Tree1Car1 Wire1
is isis
hit fall on
Tree1Car1
is is
hit
Based on Bransford & Franks (1971)
Actually presented“The tree shaded the man who wassmoking a pipe”
Never presented (but consistent)“The tree in the front yard shadedthe man”
Never presented (inconsistent)“The tree broke the window”
frontyard
tall
tree
man pipesmoked
in
shad
ed
is
Support for integration hypothesis
Bransford & Franks (1971)
McKoon & Ratcliff (1980)
“The lawyer gestured to a waiter.”
The waiter brought coffee.
The coffee stained the napkins.
The lawyer flourished documents.
The documents explained a contract.
The contract satisfied a client.
Propositions
GESTURE TO (LAWYER1, WAITER1)...etc.
Document1
Client1
Contract1
Lawyer1
Waiter1
Coffee1
Napkins1
is is is
is
is is is
gesture
to
NapkinsCoffee
Document Contract Client
Lawyer
Waiter
Nodes for Conceptsalready in semantic memory
is is is
is
is is is
Document to Waiter = 2 linksDocument to Napkins = 4 links
Prediction“waiter” primes document more than “napkins” does