a) 60% b) 70% c) 50% d) 5%

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a) 60% b) 70% c) 50% d) 5%

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KF vs. ControlsHM vs. Controls

KF vs Controls

a) 4 b) 2 c) 0 d) 3

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The full double dissociation

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What are the variables affectingTask A and Task B in this graph?

a) Acoustic versus semantic confusability.b) Parietal versus hippocampal damage.c) There are no variables.d) a and b.

X

246 CHAPTER 6 Working Memory

2.2.2. Ready AccessibilityThe high level of accessibility of information stored in short-term memory wasdemonstrated in a classic set of studies conducted by Saul Sternberg (1966, 1969a),which we briefly considered in Chapter 1. We now consider these findings in greaterdetail. A variable number of items, such as digits (the memory set), were presentedbriefly to participants at the beginning of a trial and then removed for a minimaldelay. Following the delay, a probe item appeared and participants were to indicatewhether or not the probe matched an item in the memory set. The time required torespond should reflect the sum of four quantities: (1) the time required to process theprobe item perceptually, (2) the time required to access and compare an item inshort-term memory against the probe item, (3) the time required to make a binaryresponse decision (match–nonmatch), and (4) the time required to execute the nec-essary motor response. Sternberg hypothesized that as the number of items in thememory set increased, the second quantity—the total time required for access andcomparison—should increase linearly with each additional item, but the other threequantities should remain constant. Thus, Sternberg hypothesized that when the re-sponse time was plotted against the number of memory set items, the result wouldbe a straight line on the graph. Moreover, the slope of that line should reveal the av-erage time needed to access and compare an item held in short-term memory. The re-sults were as predicted—the plotted data formed an almost perfect straight line, andthe slope indicated an access plus-comparison time of approximately 40 milliseconds(Figure 6–3). The hypothesis that information held in short-term memory could beaccessed at high speed was certainly borne out by these findings.

FIGURE 6–3 Recognition time related to memory set size in the Sternberg item recognition task

As the number of items to be memorized—the memory set size—increases from one to six, the time toevaluate a probe increases in a linear manner with about a 40-millisecond increase per additional item.The best-fitting line for the data obtained is plotted here; it is very close to the actual data points.(Sternberg, S. (1969). The discovery processing stages: Extension of Donders’ method. In W. G. Koster (ed.),Attention and Performance II. Amsterdam: North-Holland.)

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SMITMC06_0131825089.QXD 3/28/06 6:57 AM Page 246 REVISED PAGES

What does the numberinside the red squarerefer to?

(a) the time required to process the probe item perceptually(b) the time required to access and compare an item in short-term memory

against the probe item(c) the time required to make a binary response decision (match–nonmatch)(d) the time required to execute the necessary motor response.

X





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How would the graph alterif I made the target items harder to see?

(a) the slope would increase(b) the intercept would increase(c) both of the above

e.g. Memory set: K V R N

Target: V

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Which of these does the intercept (397.2 ms) represent?

1. the time required to process the probe item perceptually2. the time required to access and compare an item in short-term memory

against the probe item3. the time required to make a binary response decision (match–nonmatch)4. the time required to execute the necessary motor response.

Consider the following:

(a) Just 1 (b) Just 3 (c) 1,2,3,4 (d) 1, 3, 4 X





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(a) Self terminating search.

(b) Exhaustive search. X

2. From Primary Memory to Working Memory: A Brief History 247

More recent work, however, has called into question the fundamental assump-tion underlying Sternberg’s interpretation of the results of this experiment: thatshort-term memory scanning proceeds sequentially, one item at a time. In particu-lar, as discussed in Chapter 1, sophisticated mathematical modeling techniquesshow that similar linear curves could be found from a parallel scanning process thataccesses all items simultaneously. In some of these models, the increase in responsetimes is due to the decreasing efficiency of the parallel process as the number ofitems held in short-term memory increases (McElree & Dosher, 1989; Townsend &Ashby, 1983). But even assuming parallel scanning, the time to access informationin short-term memory is very short indeed. Thus, even the more recent accounts re-tain the basic idea that information held in short-term memory is very quickly ac-cessible.

2.3. The Atkinson-Shiffrin Model: The Relationship of Short-Term and Long-Term MemoryThe notion that short-term and long-term memory are distinct modes of storinginformation was further articulated in the model proposed by Richard Atkinsonand Richard Shiffrin (Figure 6–4) (Atkinson & Shiffrin, 1968). In this model,short-term memory serves as the gateway by which information can gain access tolong-term memory. The function of short-term memory is to provide a means ofcontrolling and enhancing, via rehearsal and coding strategies (such as chunking),the information that makes it into long-term memory. The Atkinson-Shiffrin

FIGURE 6–4 The Atkinson-Shiffrin model of memoryThis model, also termed the modal model, suggests that the flow of information from sensory input tolong-term memory must first pass through short-term memory. Information from the environment isregistered by sensory receptors—visual, auditory, haptic (relating to touch), and others—and passed toshort-term memory. Here it is rehearsed or otherwise manipulated before entering long-term memory;here also are strategies for retrieving information from long-term memory.(R. C. Atkinson and R. M. Shiffrin, “The control of short-term memory.” Scientific American, Aug. 1971, Vol. 225, No. 2. Reprinted with permission.)

ENVIRONMENTALINPUT

SENSORY REGISTERS

VISUAL

AUDITORY

HAPTIC

LONG-TERM STORE(LTS)

PERMANENTMEMORY STORE

SHORT-TERM STORE(STS)

TEMPORARYWORKING MEMORY

CONTROL PROCESSES:

REHEARSALCODINGDECISIONSRETRIEVAL STRATEGIES

RESPONSE OUTPUT


The Modal Model

Sensory Registers System A System B

Task A

Task B

Can you doubly dissociateTask A and Task B?

(a) Yes(b) No X

rough dough bough cough through

This list will be harder to recall in the correct order relative to a matched control list. Assume that the words are presented visually, one at a time.

a) True b) False

Task: Five words presented in sequence, each wordoccurring for 1 second. Recall all five words in order.

X

List 1: f, k, l, m, q, r, y

List 2: c, b, d, g, t, v, p

Letters from list 1 will be harder to recall in the correct order than list2.

Assume that the letters are presented visually, one at a time.

a) True b) False

Task: Five letters presented in sequence, each letteroccurring for 1 second. Recall all five letters in order.

X

250 G. VALLAR & C. PAPAGNO

PHONOLOGICALANALYSIS

PHONOLOGICAL

STSinferior parietal lobule

VISUAL ANALYSIS&

STS

ORTHOGRAPHICTO

PHONOLOGICALRECODING

PHONOLOGICALOUTPUT BUFFER

Broca's area-premotor cortex

SPOKEN OUTPUT

REHEARSALPROCESS

A

B

C

D

E

AUDITORY INPUT VISUAL INPUT

Figure 12.1 A functional model of phonological short-term memory. Auditory–verbal mate-rial, after early acoustic and phonological analysis (A), enters the main retention componentof the system, the phonological STS (B), where material is coded in a phonological format.The phonological STS is an input system to which auditory material has a direct and automaticaccess. The process of rehearsal is conceived as involving a recirculation of the memory tracebetween the phonological STS and a phonological output system, the phonological outputbuffer or phonological assembly system (C), primarily concerned with the articulatory pro-gramming of speech output, with a recurring translation between input (acoustic) and output(articulatory) phonological representations. The phonological output buffer provides accessfor visually presented verbal material to the phonological STS, after phonological recodingor grapheme-to-phoneme conversion (E). The model also illustrates the multiple-componentnature of short-term memory, showing a visual STS (D), where material is likely to be encodedin terms of shape. Reproduced by permission from Vallar & Papagno (1995)

of articulatory procedures (Burani et al., 1991). Auditory–verbal information has a directaccess to the phonological STS after phonological analysis. Visual information, by contrast,requires a number of steps before gaining access to the phonological STS: visual analy-sis, phonological recoding (grapheme-to-phoneme conversion) and articulatory rehearsal.Visual information may be temporarily held in a visual STS system.

The investigation of three variables affecting immediate memory span (phonologicalsimilarity, word length and articulatory suppression) has provided the main sources ofempirical data, which constrain the structure of this memory system. The data from normalsubjects relevant to the interpretation of the pattern of impairment of brain-damaged patientsare briefly summarized here (see also Baddeley, Chapter 1, this volume).

This component of theArticulatory Loop is directly affected by the variable AcousticConfusability

(a) True

(b) False

X

250 G. VALLAR & C. PAPAGNO

PHONOLOGICALANALYSIS

PHONOLOGICAL

STSinferior parietal lobule

VISUAL ANALYSIS&

STS

ORTHOGRAPHICTO

PHONOLOGICALRECODING

PHONOLOGICALOUTPUT BUFFER

Broca's area-premotor cortex

SPOKEN OUTPUT

REHEARSALPROCESS

A

B

C

D

E

AUDITORY INPUT VISUAL INPUT

Figure 12.1 A functional model of phonological short-term memory. Auditory–verbal mate-rial, after early acoustic and phonological analysis (A), enters the main retention componentof the system, the phonological STS (B), where material is coded in a phonological format.The phonological STS is an input system to which auditory material has a direct and automaticaccess. The process of rehearsal is conceived as involving a recirculation of the memory tracebetween the phonological STS and a phonological output system, the phonological outputbuffer or phonological assembly system (C), primarily concerned with the articulatory pro-gramming of speech output, with a recurring translation between input (acoustic) and output(articulatory) phonological representations. The phonological output buffer provides accessfor visually presented verbal material to the phonological STS, after phonological recodingor grapheme-to-phoneme conversion (E). The model also illustrates the multiple-componentnature of short-term memory, showing a visual STS (D), where material is likely to be encodedin terms of shape. Reproduced by permission from Vallar & Papagno (1995)

of articulatory procedures (Burani et al., 1991). Auditory–verbal information has a directaccess to the phonological STS after phonological analysis. Visual information, by contrast,requires a number of steps before gaining access to the phonological STS: visual analy-sis, phonological recoding (grapheme-to-phoneme conversion) and articulatory rehearsal.Visual information may be temporarily held in a visual STS system.

The investigation of three variables affecting immediate memory span (phonologicalsimilarity, word length and articulatory suppression) has provided the main sources ofempirical data, which constrain the structure of this memory system. The data from normalsubjects relevant to the interpretation of the pattern of impairment of brain-damaged patientsare briefly summarized here (see also Baddeley, Chapter 1, this volume).

This component of theArticulatory Loop is directly affected by the variable Word Length

(a) True

(b) False X


similarity effect on performance was not influenced by word length, and vice versa(Figure 6–6) (Longoni et al., 1993).

Of course, behavioral data can provide only one kind of evidence for functionalindependence. Results from brain-based studies provide a different kind of evidence,showing that separate systems support phonological storage and rehearsal.

On the one hand, studies of patients with brain damage have documented a re-lationship between left inferior parietal damage and phonological storage impair-ments, and a relationship between left inferior frontal cortex damage and articulatoryrehearsal impairments (Vallar & Papagaro, 1995). (The left inferior frontal cortex,also referred to as Broca’s area, is known to be involved with language.) On theother hand, neuroimaging studies have provided a means to examine these rela-tionships in neurologically healthy participants. Such studies can show whetherthese brain regions are in fact the ones engaged during normal processing condi-tions. For example, participants in one study were asked to memorize a series ofsix visually presented items, either six English letters or six Korean language char-acters (none of the participants were speakers of Korean) (Paulesu et al., 1993). Theresearchers assumed that the phonological loop system would be engaged to main-tain the English letters but not utilized for the Korean characters (because thesounds represented by the characters were unknown to the participants). Thisassumption was validated by testing the effects of articulatory suppression—as

100

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20

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Short Long

Phonologically dissimilar words

Phonologically similar wordsAcc

urac

y of

rec

all (

%)

Word length

FIGURE 6–6 Independence of the effects of word length and phonological similarity

An immediate recall task presented participants with five words that were either phonologically simi-lar (such as FASTER, PLASTER, MASTER, TASTER, and LASTED) or dissimilar (such as FAMOUS,PLASTIC, MAGIC, TEACHER, and STAYED), and were either short (two syllables) or long (four sylla-bles). Both similarity and greater word length decreased recall performance, but the parallel slopes ofthe lines indicate that the two effects are independent.(Adapted from Longoni, A. M., Richardson, J. T. E., and Aiello, A. (1993). Articulatory rehersal and phonologicalstorage in working memory. Memory and Cognition, 21(1), 11–22. Reprinted with permission.)


Phonologically similar words

A

B

Task: Repeat short list of words in order

presented

VariableA

VariableB

AcousticConfusability

Word Length

System A

and

What if?


similarity effect on performance was not influenced by word length, and vice versa(Figure 6–6) (Longoni et al., 1993).

Of course, behavioral data can provide only one kind of evidence for functionalindependence. Results from brain-based studies provide a different kind of evidence,showing that separate systems support phonological storage and rehearsal.

On the one hand, studies of patients with brain damage have documented a re-lationship between left inferior parietal damage and phonological storage impair-ments, and a relationship between left inferior frontal cortex damage and articulatoryrehearsal impairments (Vallar & Papagaro, 1995). (The left inferior frontal cortex,also referred to as Broca’s area, is known to be involved with language.) On theother hand, neuroimaging studies have provided a means to examine these rela-tionships in neurologically healthy participants. Such studies can show whetherthese brain regions are in fact the ones engaged during normal processing condi-tions. For example, participants in one study were asked to memorize a series ofsix visually presented items, either six English letters or six Korean language char-acters (none of the participants were speakers of Korean) (Paulesu et al., 1993). Theresearchers assumed that the phonological loop system would be engaged to main-tain the English letters but not utilized for the Korean characters (because thesounds represented by the characters were unknown to the participants). Thisassumption was validated by testing the effects of articulatory suppression—as

100

80

60

40

20

0

Short Long

Phonologically dissimilar words

Phonologically similar wordsAcc

urac

y of

rec

all (

%)

Word length

FIGURE 6–6 Independence of the effects of word length and phonological similarity

An immediate recall task presented participants with five words that were either phonologically simi-lar (such as FASTER, PLASTER, MASTER, TASTER, and LASTED) or dissimilar (such as FAMOUS,PLASTIC, MAGIC, TEACHER, and STAYED), and were either short (two syllables) or long (four sylla-bles). Both similarity and greater word length decreased recall performance, but the parallel slopes ofthe lines indicate that the two effects are independent.(Adapted from Longoni, A. M., Richardson, J. T. E., and Aiello, A. (1993). Articulatory rehersal and phonologicalstorage in working memory. Memory and Cognition, 21(1), 11–22. Reprinted with permission.)


Figure 1

Figure 2

a) Figure 1b) Figure 2

X

90 GATHERCOLE

learning of the phonological forms of new words (e.g.,Gathercole & Baddeley, 1989, 1993b), the children's vo-cabulary knowledge should be better predicted by thelow-wordlike than by the high-wordlike repetition mea-sure. If, on the other hand, the close links between non-word-repetition ability and vocabulary learning reflectthe use oflexical knowledge to support the repetition ofnonwords (e.g., Gathercole et a!., 1991; Snowling et a!.,1991), stronger associations between vocabulary knowl-edge and repetition accuracy should be found for non-words of high than of low degrees of wordlikeness.

Using partial correlations, the developmental relation-ship between vocabulary knowledge and the two repeti-tion subscores was investigated (see Table 6). Partialcorrelations were computed between each ofthe repeti-tion measures and the vocabulary scores, with varianceassociated with both the nonverbal scores at the age atwhich repetition was tested and the other repetition mea-sure partialled out. This provides an index of the strengthof the unique relationship between each of the repetitionsubscores and vocabulary that is adjusted for the non-verbal estimate of the child's general intellectual ability.Consider first the data for the age 4 measures. Vocabu-lary shared a stronger unique relationship with the low-wordlike repetition measure [partial r(66) = .46, p <.001] than with high-wordlike repetition accuracy [par-tial r(66) = .00, p > .05]. The two partial correlationsdiffer significantly from one another (p < .05). This in-dicates that phonological memory skill and vocabularyknowledge are closely associated with one another. Formeasures obtained a year later, however, neither partialcorrelation reached 'statistical significance [for low-wordlike repetition and vocabulary, partial r(66) = .17,P > .05; for high-wordlike repetition and vocabulary,partial r(66) = .12,p> .05]. There is therefore little evi-dence ofa phonological memory contribution to vocab-ulary knowledge at this age.

The relationships between the repetition and vocabu-lary measures across time also provide a valuable meansof assessing the theoretical underpinnings of thedynamic relationship between nonword repetition andvocabulary development. One way oftesting causal de-velopmental hypotheses is by comparing cross-lagged

Table 6Partial Correlations Between Vocabulary Scores and

Nonword Repetition Measures, withNonverbal Scores Controlledt

correlations (e.g., Crano & Mellon, 1978; Gathercoleet a!., 1992). The logic of cross-lagged correlations isthat associations between pairs of measures that arecausally related should be stronger in the causal direc-tion across time than in the noncausal direction. So, ifphonological memory skill does directly contribute tolearning novel words, the associations between low-wordlike repetition scores at age 4 and vocabularyknowledge a year later, at age 5, should be stronger thanthe converse noncausal association, between vocabularyscores at age 4 and the low-wordlike repetition measureat 5 years. If, however, the developmental associationbetween nonword repetition and vocabulary knowledgeduring this period is primarily mediated by the use oflexical knowledge in repeating novel words, vocabularyknowledge at 4 years should be more strongly associatedwith later repetition accuracy for high-wordlike non-words than the converse association across time betweenearlier high-wordlike repetition scores and later vocab-ulary. Thus, by comparing cross-lagged correlations,both of the causal hypotheses for the developmental as-sociation between nonword repetition and vocabularyknowledge between 4 and 5 years of age can be testedsimply.

The partial correlations shown in Table 6 provide thenecessary statistical information to make the compar-isons. Comparing vocabulary knowledge and low-word-like repetition measures across time (providing a test ofthe causal phonological working-memory hypothesis),there is a statistically significant association betweenearly repetition scores and later vocabulary [partialr( 66) = .28, p < .05] but not between vocabulary knowl-edge at 4 years and repetition accuracy at 5 years [par-tial r(66) = .12, p > .05]. These findings are thereforeconsistent with the hypothesis that phonological mem-ory contributes to vocabulary learning.

Turning now to the relationship between vocabularyknowledge and repetition accuracy for high-wordlikenonwords, a different developmentalrelationship emerges.Repetition of high-wordlike items at age 4 and later vo-cabulary scores do not share a significant unique asso-ciation [partial r(66) = .03,p > .05], but the vocabularymeasure at age 4 is significantly linked with later repe-tition ofhighly wordlike nonwords [partial r(66) = .24,P < .oS]. So, the pattern ofassociations is consistent withthe lexical mediation hypothesis, according to whichstored knowledge about familiar words is used to sup-port repetition of wordlike nonwords.

Vocabulary Scores

Measures Age 4 Age 5

Age 5:Low wordlike repetition .12 .17High wordlike repetition .24* .12

*Significant at the 5% level. tNonverbal score taken at same age aswas the measure shown in left-hand column.

Age 4:Low wordlike repetitionHigh wordlike repetition

.46*

.00.28*.03

ReadingThe contribution of phonological memory to early

reading achievement was also assessed, using the low-wordlike repetition measure as the most sensitive indexof children's phonological memory skill. The cross-lagged correlation technique cannot be applied to thesedata as no reading measure is available for the childrenat the earlier wave of the study. It is, however, possibleto investigate the strength of the unique links between

High wordlike repetition scores at age 5 depends on vocabularyscores at age 4.

a) Trueb) False

X

90 GATHERCOLE

learning of the phonological forms of new words (e.g.,Gathercole & Baddeley, 1989, 1993b), the children's vo-cabulary knowledge should be better predicted by thelow-wordlike than by the high-wordlike repetition mea-sure. If, on the other hand, the close links between non-word-repetition ability and vocabulary learning reflectthe use oflexical knowledge to support the repetition ofnonwords (e.g., Gathercole et a!., 1991; Snowling et a!.,1991), stronger associations between vocabulary knowl-edge and repetition accuracy should be found for non-words of high than of low degrees of wordlikeness.

Using partial correlations, the developmental relation-ship between vocabulary knowledge and the two repeti-tion subscores was investigated (see Table 6). Partialcorrelations were computed between each ofthe repeti-tion measures and the vocabulary scores, with varianceassociated with both the nonverbal scores at the age atwhich repetition was tested and the other repetition mea-sure partialled out. This provides an index of the strengthof the unique relationship between each of the repetitionsubscores and vocabulary that is adjusted for the non-verbal estimate of the child's general intellectual ability.Consider first the data for the age 4 measures. Vocabu-lary shared a stronger unique relationship with the low-wordlike repetition measure [partial r(66) = .46, p <.001] than with high-wordlike repetition accuracy [par-tial r(66) = .00, p > .05]. The two partial correlationsdiffer significantly from one another (p < .05). This in-dicates that phonological memory skill and vocabularyknowledge are closely associated with one another. Formeasures obtained a year later, however, neither partialcorrelation reached 'statistical significance [for low-wordlike repetition and vocabulary, partial r(66) = .17,P > .05; for high-wordlike repetition and vocabulary,partial r(66) = .12,p> .05]. There is therefore little evi-dence ofa phonological memory contribution to vocab-ulary knowledge at this age.

The relationships between the repetition and vocabu-lary measures across time also provide a valuable meansof assessing the theoretical underpinnings of thedynamic relationship between nonword repetition andvocabulary development. One way oftesting causal de-velopmental hypotheses is by comparing cross-lagged

Table 6Partial Correlations Between Vocabulary Scores and

Nonword Repetition Measures, withNonverbal Scores Controlledt

correlations (e.g., Crano & Mellon, 1978; Gathercoleet a!., 1992). The logic of cross-lagged correlations isthat associations between pairs of measures that arecausally related should be stronger in the causal direc-tion across time than in the noncausal direction. So, ifphonological memory skill does directly contribute tolearning novel words, the associations between low-wordlike repetition scores at age 4 and vocabularyknowledge a year later, at age 5, should be stronger thanthe converse noncausal association, between vocabularyscores at age 4 and the low-wordlike repetition measureat 5 years. If, however, the developmental associationbetween nonword repetition and vocabulary knowledgeduring this period is primarily mediated by the use oflexical knowledge in repeating novel words, vocabularyknowledge at 4 years should be more strongly associatedwith later repetition accuracy for high-wordlike non-words than the converse association across time betweenearlier high-wordlike repetition scores and later vocab-ulary. Thus, by comparing cross-lagged correlations,both of the causal hypotheses for the developmental as-sociation between nonword repetition and vocabularyknowledge between 4 and 5 years of age can be testedsimply.

The partial correlations shown in Table 6 provide thenecessary statistical information to make the compar-isons. Comparing vocabulary knowledge and low-word-like repetition measures across time (providing a test ofthe causal phonological working-memory hypothesis),there is a statistically significant association betweenearly repetition scores and later vocabulary [partialr( 66) = .28, p < .05] but not between vocabulary knowl-edge at 4 years and repetition accuracy at 5 years [par-tial r(66) = .12, p > .05]. These findings are thereforeconsistent with the hypothesis that phonological mem-ory contributes to vocabulary learning.

Turning now to the relationship between vocabularyknowledge and repetition accuracy for high-wordlikenonwords, a different developmentalrelationship emerges.Repetition of high-wordlike items at age 4 and later vo-cabulary scores do not share a significant unique asso-ciation [partial r(66) = .03,p > .05], but the vocabularymeasure at age 4 is significantly linked with later repe-tition ofhighly wordlike nonwords [partial r(66) = .24,P < .oS]. So, the pattern ofassociations is consistent withthe lexical mediation hypothesis, according to whichstored knowledge about familiar words is used to sup-port repetition of wordlike nonwords.

Vocabulary Scores

Measures Age 4 Age 5

Age 5:Low wordlike repetition .12 .17High wordlike repetition .24* .12

*Significant at the 5% level. tNonverbal score taken at same age aswas the measure shown in left-hand column.

Age 4:Low wordlike repetitionHigh wordlike repetition

.46*

.00.28*.03

ReadingThe contribution of phonological memory to early

reading achievement was also assessed, using the low-wordlike repetition measure as the most sensitive indexof children's phonological memory skill. The cross-lagged correlation technique cannot be applied to thesedata as no reading measure is available for the childrenat the earlier wave of the study. It is, however, possibleto investigate the strength of the unique links between

High wordlike repetition at age 4 depends on vocabularyscores at age 5.

a) Trueb) False X


Suppose you have a regular route you drive, perhaps from a job to where you live.At an intersection, your route directly home is straight through, but you always getyourself in the leftmost lane because it has a left-turn arrow and so the traffic movesthrough faster, either turning left or going straight ahead, than from the other lanes. Soordinarily—the default pattern—you’re in the leftmost lane but don’t turn left. But, ifyou need to stop at the grocery store on the way home, as you do now and then, youmust turn left at that intersection. Now you’re stopped at the light: do you turn left orgo straight ahead? That depends on your goal, which provides a context for determin-ing your action: do you want to go home or to the store? You may very likely find thatin the less frequent situation you have to keep the go-to-the-store goal active in work-ing memory while you’re waiting at the light, or you’ll blow it and go straight ahead.

In the goal-maintenance view of the role of the prefrontal cortex in working mem-ory, this is what’s happening: As you wait at the stoplight, the goal of go-to-the-storeis actively maintained in the prefrontal cortex, and this activation flows from theprefrontal cortex back to the brain systems serving perception, attention, and actionto influence your response when the light turns green. Were the goal not actively


FIGURE 6–13 The goal-maintenance modelIn this model, goal information is represented in the prefrontal cortex as a pattern of activity. Rever-beratory loops allow this activity to be sustained over delays, and feedback connections enable themaintained activity to bias the internal associations that are activated in response to perceptual input.In this way goal information is able to provide control over thoughts and behavior.(Adapted from Braver, T. S., Cohen, J. D., and Barch, D. M. (2002). The role of the prefrontal cortex in normal anddisordered cognitive control: A cognitive neuroscience perspective. In D. T. Stuss and R. T. Knight (eds.), Principlesof Frontal Lobe Function (pp. 428–448). © 2002 Oxford University Press. Reprinted with permission of OxfordUniversity Press.)

Goalinformation

Response

Associations

Input

Reverberatory loop

Biasingeffect


Input

BLUE

Which part of the diagram onthe right corresponds tothe component labelled “Associations”?

a) Blueb) Greenc) Redd) Black

X






Goalinformation

Response

Associations

Input

Reverberatory loop

Biasingeffect


Input

RED

Which part of the diagram onthe right corresponds tothe component labelled “Input”?

a) Blueb) Greenc) Redd) Black

X






Goalinformation

Response

Associations

Input

Reverberatory loop

Biasingeffect


Input

BLUE

Which part of the diagram onthe right corresponds tothe component labelled “Goal Information”?

a) Blueb) Greenc) Redd) Black X






Goalinformation

Response

Associations

Input

Reverberatory loop

Biasingeffect


What does this pathway represent?

a) Responses determined byhigher level goals.b) Learned associations betweena stimulus and a response. X

Does working memory capacity predict intelligence?

Storage capacity versus maintenance of goal relevant information

B–T–R–F–T–F where the task is to look for N =3 matches

(a) Yes(b) No

B–T–R–F–T–F where the task is to look for N =3 matches

Is the correct answer to this sequence:

X

in these tasks does not show that there are funct ionalconsequences to th is over lap, as a hypothesis ofa t tent ion-based rehearsa l would cla im. This ar t iclegoes beyond the correla t ional evidence to presentdata of two sor ts:

(1) Behavioral evidence shows us that visualprocessing at memorized locat ions is bet ter than atnon-memorized locat ions, consistent with the not ionthat visual a t tent ion is focused on the memorizedlocat ions17. Moreover , if subjects are forced to directat tent ion away from locat ions held in workingmemory, their ability to remember those locat ions isimpaired12,17,18. This interference effect suggests thatspat ia l or ient ing of a t tent ion is a necessary par t ofaccurate spat ia l memory, ra ther than being merely acorrela ted phenomenon.

(2) Addit ional evidence from funct ional magnet icresonance imaging (fMRI) and event-rela tedpotent ia ls (ERPs) reveals the cort ical mechanismsthat underlie spat ia l rehearsal effects. These datasuggest that spat ia l rehearsal modulates ear lysensory processing in the visual areas that representthe memorized locat ions19. The t ime course and

cort ical locus of these rehearsal effects are similar tothose that are observed after explicit manipulat ionsof spat ia l select ive a t tent ion (Ref. 20; and A. J ha andG.R. Mangun, unpublished).

Behavioral evidenceIf spa t ia l select ive a t t en t ion is directed towards aloca t ion stored in working memory, then the typica leffect s of spa t ia l a t t en t ion – improved visua lprocessing efficiency – shou ld be observed a t tha tloca t ion . Awh et al.17 have provided a behaviora lt est of th is predict ion . Subject s were engaged in asimple memory t a sk (see F ig. 1a ), in which a let t er(the cue) appea red in a specific loca t ion . F iveseconds la t er , another let t er (the probe) appea redon the screen and subject indica ted whether theprobe ma tched the in format ion tha t they wereholding in memory. Ha lf of the subject s memor izedthe loca t ion of the cue, while the other ha lfmemor ized the iden t ity of the cue. Dur ing thereten t ion in terva l, subject s made speeded keypresses to indica te the shape of a let t er -likecharacter tha t appea red on the computer screen . Insome t r ia ls, the choice st imulus appeared in thesame loca t ion as the memory cue (choice ma tch); inthe other t r ia ls the choice st imulus appeared inother pa r t s of the visua l field (choice miss). The keypredict ion was tha t subject s’ r eact ion t imes to thechoice st imulus shou ld be fa ster when it fell in thememor ized loca t ion , bu t on ly when subject s wererehea rsing the loca t ion of the in it ia l memory cue.The let t er memory condit ion served as a con t rol forthe st imulus display; if the predicted effect was aresu lt of au tomat ic or ien t ing of a t t en t ion 21 or themere presence of a 25% cor respondence between theloca t ion of the cue and the choice st imulus, then thesame effect s shou ld have been observed in both thelet t er and the spa t ia l condit ions. Only in the spa t ia lmemory condit ion were react ion t imes reliablyfaster to choice-match st imuli than to choice-missst imuli (see F ig. 1b). No t r ace of th is effect wasobserved in the let t er memory condit ion . These da tasuggest tha t spa t ia l r ehea rsa l – not the st imulusdisplay – was responsible for the react ion t imeeffect s in the spa t ia l memory condit ion .

This study demonstrates the predicted associat ionbetween the focus of spat ia l a t tent ion and thememorized locat ions, but it did not address thestronger cla im that spat ia l select ive a t tent ion plays afunct ional role in working memory. That is, spat ia la t tent ion might be directed towards the memorizedlocat ions without playing a beneficia l role in theact ive maintenance of locat ion information. Thisissue has been addressed by test ing a simplepredict ion of a t tent ion-based rehearsal: if subjects arehindered in their ability to direct a t tent ion towardsthe memorized locat ions, then memory accuracyshould decline. The first study to demonstrate thisconnect ion between spat ia l a t tent ion and spat ia lworking memory was carr ied out by Smyth and

TRENDS in Cognitive Sciences Vol.5 No.3 March 2001

http://tics.trends.com

120 ReviewReview

TRENDS in Cognitive Sciences

(a)

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Mismatch Match Mismatch

Fig. 1. Assessing visual processing efficiency at memorizedlocations. (a) The events in a single trial of the spatial and letter dualtasks. The choice reaction time stimulus that appeared during theretention interval allowed a direct comparison of visual processingefficiency at memorized and non-memorized locations. Subjects wererequired to fixate centrally throughout each trial, and compliance wasverified by video monitoring. (b) Mean reaction times (RT) to thechoice stimulus. Only in the spatial condition, were subjects faster torespond to choice stimuli that matched the location of the memorycue, suggesting that spatial attention is directed towards locationsheld in working memory. The failure to observe this effect in the lettercondition rules out the stimulus display as the cause of this effect.Although reaction times appear to be faster on average in the lettercondition, this reflects the responses of a single subject in the lettercondition; thus, there was no reliable difference in choice reactiontimes between the spatial and letter conditions. The results would beunchanged if this subject were excluded.









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Cue ProbeChoicestimulus

An effect occurred when comparing reaction time in the Match versus theMismatch condition indicated by the blackellipse. What were subjects responding to?

(a) (b) (c)

(a) The Cue(b) The Choice stimulus (c) The Probe

X









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What was the working memory taskthe subject was asked to carry out thatproduced faster reaction times in the Match than Mismatch condition (blueline graphs inside the ellipse)

(a) (b) (c)

(a) Remember the identity of the Cue(b) Remember the location of the Cue.(c) Remember both the identity and location of the cue.

X









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How many tasks were involved in thispart of the experiment?

(a) (b) (c)

a) Oneb) Twoc) Three

X

Documents

a) 60% b) 70% c) 50% d) 5%