ANRV331-PS59-08
ARI
1 December 2007
16:37
AR Further
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
Click here for quick links to
Annual Reviews content online,
including:
• Other articles in this volume
• Top cited articles
• Top downloaded articles
• AR’s comprehensive search
The Mind and Brain of
Short-Term Memory
John Jonides, Richard L. Lewis, Derek Evan Nee,
Cindy A. Lustig, Marc G. Berman,
and Katherine Sledge Moore
Department of Psychology, University of Michigan, Ann Arbor, Michigan 48109;
email: jjonides@umich.edu
Annu. Rev. Psychol. 2008. 59:193–224
Key Words
First published online as a Review in Advance on
September 12, 2007
working memory, attention, encoding, storage, retrieval
The Annual Review of Psychology is online at
http://psych.annualreviews.org
This article’s doi:
10.1146/annurev.psych.59.103006.093615
c 2008 by Annual Reviews.
Copyright
All rights reserved
0066-4308/08/0203-0193$20.00
Abstract
The past 10 years have brought near-revolutionary changes in psychological theories about short-term memory, with similarly great
advances in the neurosciences. Here, we critically examine the major
psychological theories (the “mind”) of short-term memory and how
they relate to evidence about underlying brain mechanisms. We focus
on three features that must be addressed by any satisfactory theory
of short-term memory. First, we examine the evidence for the architecture of short-term memory, with special attention to questions of
capacity and how—or whether—short-term memory can be separated from long-term memory. Second, we ask how the components
of that architecture enact processes of encoding, maintenance, and
retrieval. Third, we describe the debate over the reason about forgetting from short-term memory, whether interference or decay is the
cause. We close with a conceptual model tracing the representation
of a single item through a short-term memory task, describing the
biological mechanisms that might support psychological processes
on a moment-by-moment basis as an item is encoded, maintained
over a delay with some forgetting, and ultimately retrieved.
193
ANRV331-PS59-08
ARI
1 December 2007
16:37
Contents
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
INTRODUCTION . . . . . . . . . . . . . . . . .
WHAT IS THE STRUCTURE
OF SHORT-TERM MEMORY? .
Multistore Models that
Differentiate Short- and
Long-Term Memory . . . . . . . . . .
Unitary-Store Models that
Combine Short-Term and
Long-Term Memory . . . . . . . . . .
Controversies over Capacity . . . . . .
Summary . . . . . . . . . . . . . . . . . . . . . . . .
WHAT PROCESSES OPERATE
ON THE STORED
INFORMATION? . . . . . . . . . . . . . . .
The Three Core Processes of
Short-Term Memory:
Encoding, Maintenance,
and Retrieval . . . . . . . . . . . . . . . . . .
Neural Mechanisms of Short- and
Long-Term Memory Retrieval .
194
195
195
197
199
201
202
202
205
INTRODUCTION
Mentally add 324 and 468.
Follow the instructions to complete any
form for your federal income taxes.
Read and comprehend this sentence.
What are the features of the memory system
that allows us to complete these and other
complex tasks? Consider the opening example. First, you must create a temporary representation in memory for the two numbers.
This representation needs to survive for several seconds to complete the task. You must
then allocate your attention to different portions of the representation so that you can apply the rules of arithmetic required by the task.
By one strategy, you need to focus attention
on the “tens” digits (“2” and “6”) and mitigate interference from the other digits (e.g.,
“3” and “4”) and from partial results of previous operations (e.g., the “12” that results from
194
Jonides et al.
The Relationship of Short-Term
Memory Processes
to Rehearsal . . . . . . . . . . . . . . . . . . .
WHY DO WE FORGET? . . . . . . . . . .
Decay Theories: Intuitive
but Problematic . . . . . . . . . . . . . . .
Interference Theories:
Comprehensive but Complex . .
Interference Effects
in Short-Term Memory . . . . . . . .
A SUMMARY OF PRINCIPLES
AND AN ILLUSTRATION OF
SHORT-TERM MEMORY
AT WORK . . . . . . . . . . . . . . . . . . . . . .
Principles of Short-Term
Memory . . . . . . . . . . . . . . . . . . . . . .
A Sketch of Short-Term Memory
at Work . . . . . . . . . . . . . . . . . . . . . . .
Postscript: Revisiting Complex
Cognition . . . . . . . . . . . . . . . . . . . . .
206
207
207
210
210
212
212
213
216
adding “4” and “8”). While attending to local
portions of the problem, you must also keep
accessible the parts of the problem that are
not in the current focus of attention (e.g., that
you now have the units digit “2” as a portion
of the final answer). These tasks implicate a
short-term memory (STM). In fact, there is
hardly a task that can be completed without
the involvement of STM, making it a critical
component of cognition.
Our review relates the psychological phenomena of STM to their underlying neural
mechanisms. The review is motivated by three
questions that any adequate account of STM
must address:
1. What is its structure?
A proper theory must describe an architecture for short-term storage. Candidate components of this architecture include storage
buffers, a moving and varying focus of attention, or traces with differing levels of activation. In all cases, it is essential to provide
ANRV331-PS59-08
ARI
1 December 2007
16:37
a mechanism that allows a representation to
exist beyond the sensory stimulation that
caused it or the process that retrieved the representation from long-term memory (LTM).
This architecture should be clear about its
psychological constructs. Furthermore, being
clear about the neural mechanisms that implement those constructs will aid in development
of psychological theory, as we illustrate below.
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
2. What processes operate on the stored
information?
A proper theory must articulate the processes
that create and operate on representations.
Candidate processes include encoding and
maintenance operations, rehearsal, shifts of
attention from one part of the representation
to another, and retrieval mechanisms. Some
of these processes are often classified as executive functions.
3. What causes forgetting?
A complete theory of STM must account
for the facts of forgetting. Traditionally, the
two leading contending accounts of forgetting have relied on the concepts of decay and
interference. We review the behavioral and
neurophysiological evidence that has traditionally been brought to the table to distinguish decay and interference accounts, and we
suggest a possible mechanism for short-term
forgetting.
Most models of STM fall between two
extremes: Multistore models view STM and
LTM as architecturally separate systems that
rely on distinct representations. By contrast,
according to unitary-store models, STM and
LTM rely largely on the same representations,
but differ by (a) the level of activation of these
representations and (b) some of the processes
that normally act upon them. We focus on
the distinctions drawn by these theories as we
examine the evidence concerning the three
questions that motivate our review. In this discussion, we assume that a representation in
memory consists of a bundle of features that
define a memorandum, including the context
in which that memorandum was encountered.
WHAT IS THE STRUCTURE
OF SHORT-TERM MEMORY?
Multistore Models that Differentiate
Short- and Long-Term Memory
In his Principles of Psychology, William James
(1890) articulated the view that short-term
(“primary”) memory is qualitatively different
from long-term (“secondary”) memory (see
also Hebb 1949). The most influential successor to this view is the model of STM
developed by Baddeley and colleagues (e.g.,
Baddeley 1986, 1992; Baddeley & Hitch 1974;
Repov & Baddeley 2006). For the years 1980
to 2006, of the 16,154 papers that cited “working memory” in their titles or abstracts, fully
7339 included citations to Alan Baddeley.
According to Baddeley’s model, there are
separate buffers for different forms of information. These buffers, in turn, are separate
from LTM. A verbal buffer, the phonological
loop, is assumed to hold information that can
be rehearsed verbally (e.g., letters, digits). A
visuospatial sketchpad is assumed to maintain
visual information and can be further fractionated into visual/object and spatial stores
(Repov & Baddeley 2006, Smith et al. 1995).
An episodic buffer that draws on the other
buffers and LTM has been added to account
for the retention of multimodal information
(Baddeley 2000). In addition to the storage
buffers described above, a central executive
is proposed to organize the interplay between
the various buffers and LTM and is implicated
in controlled processing.
In short, the multistore model includes
several distinctions: (a) STM is distinct from
LTM, (b) STM can be stratified into different
informational buffers based on information
type, and (c) storage and executive processes
are distinguishable. Evidence in support of
these claims has relied on behavioral interference studies, neuropsychological studies, and
neuroimaging data.
Evidence for the distinction between
short- and long-term memory. Studies of
brain-injured patients who show a deficit
www.annualreviews.org • The Mind and Brain of Short-Term Memory
195
ARI
1 December 2007
16:37
in STM but not LTM or vice versa lead
to the implication that STM and LTM
are separate systems.1 Patients with parietal
and temporal lobe damage show impaired
short-term phonological capabilities but intact LTM (Shallice & Warrington 1970, Vallar
& Papagno 2002). Conversely, it is often
claimed that patients with medial temporal
lobe (MTL) damage demonstrate impaired
LTM but preserved STM (e.g., Baddeley &
Warrington 1970, Scoville & Milner 1957; we
reinterpret these effects below).
Neuroimaging data from healthy subjects
have yielded mixed results, however. A metaanalysis comparing regions activated during
verbal LTM and STM tasks indicated a great
deal of overlap in neural activation for the
tasks in the frontal and parietal lobes (Cabeza
et al. 2002, Cabeza & Nyberg 2000). Three
studies that directly compared LTM and STM
in the same subjects did reveal some regions
selective for each memory system (Braver
et al. 2001, Cabeza et al. 2002, Talmi et al.
2005). Yet, of these studies, only one found
that the MTL was uniquely activated for LTM
(Talmi et al. 2005). What might account for
the discrepancy between the neuropsychological and neuroimaging data?
One possibility is that neuroimaging tasks
of STM often use longer retention intervals
than those employed for neuropsychological
tasks, making the STM tasks more similar to
LTM tasks. In fact, several studies have shown
that the MTL is important when retention intervals are longer than a few seconds (Buffalo
et al. 1998, Cabeza et al. 2002, Holdstock et al.
1995, Owen et al. 1995). Of the studies that
compared STM and LTM in the same subjects, only Talmi et al. (2005) used an STM
retention interval shorter than five seconds.
This study did find, in fact, that the MTL
was uniquely recruited at longer retention
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
ANRV331-PS59-08
1
Another line of neural evidence about the separability of
short- and long-term memory comes from electrophysiological studies of animals engaged in short-term memory
tasks. We review this evidence and its interpretation in The
Architecture of Unitary-Store Models section.
196
Jonides et al.
intervals, providing support for the earlier
neuropsychological work dissociating longand short-term memory. As we elaborate below, however, there are other possible interpretations, especially with regard to the
MTL’s role in memory.
Evidence for separate buffers in shortterm memory. The idea that STM can be
parceled into information-specific buffers first
received support from a series of studies of
selective interference (e.g., Brooks 1968, den
Heyer & Barrett 1971). These studies relied
on the logic that if two tasks use the same
processing mechanisms, they should show interfering effects on one another if performed
concurrently. This work showed a double dissociation: Verbal tasks interfered with verbal
STM but not visual STM, and visual tasks interfered with visual STM but not verbal STM,
lending support to the idea of separable memory systems (for reviews, see Baddeley 1986
and Baddeley & Hitch 1974).
The advent of neuroimaging has allowed
researchers to investigate the neural correlates
of the reputed separability of STM buffers.
Verbal STM has been shown to rely primarily
on left inferior frontal and left parietal cortices, spatial STM on right posterior dorsal
frontal and right parietal cortices, and object/visual STM on left inferior frontal, left
parietal, and left inferior temporal cortices
(e.g., Awh et al. 1996, Jonides et al. 1993,
Smith & Jonides 1997; see review by Wager &
Smith 2003). Verbal STM shows a marked left
hemisphere preference, whereas spatial and
object STM can be distinguished mainly by
a dorsal versus ventral separation in posterior cortices (consistent with Ungerleider &
Haxby 1994; see Baddeley 2003 for an account
of the function of these regions in the service
of STM).
The more recently postulated episodic
buffer arose from the need to account for interactions between STM buffers and LTM.
For example, the number of words recalled in
an STM experiment can be greatly increased
if the words form a sentence (Baddeley et al.
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
ANRV331-PS59-08
ARI
1 December 2007
16:37
1987). This “chunking” together of words to
increase short-term capacity relies on additional information from LTM that can be
used to integrate the words (Baddeley 2000).
Thus, there must be some representational
space that allows for the integration of information stored in the phonological loop and
LTM. This ability to integrate information
from STM and LTM is relatively preserved
even when one of these memory systems is
damaged (Baddeley & Wilson 2002, Baddeley
et al. 1987). These data provide support for an
episodic buffer that is separable from other
short-term buffers and from LTM (Baddeley
2000, Baddeley & Wilson 2002). Although
neural evidence about the possible localization of this buffer is thin, there is some suggestion that dorsolateral prefrontal cortex plays
a role (Prabhakaran et al. 2000, Zhang et al.
2004).
cortex and posterior parietal cortex (Wager &
Smith 2003). By contrast, storage processes
recruit predominately posterior areas in primary and secondary association cortex. These
results corroborate the evidence from lesion
studies and support the distinction between
storage and executive processing.
Evidence for separate storage and
executive processes. Baddeley’s multistore
model assumes that a collection of processes
act upon the information stored in the
various buffers. Jointly termed the “central
executive,” these processes are assumed to be
separate from the storage buffers and have
been associated with the frontal lobes.
Both lesion and neuroimaging data support the distinction between storage and executive processes. For example, patients with
frontal damage have intact STM under conditions of low distraction (D’Esposito & Postle
1999, 2000; Malmo 1942). However, when
distraction is inserted during a delay interval, thereby requiring the need for executive
processes to overcome interference, patients
with frontal damage show significant memory
deficits (D’Esposito & Postle 1999, 2000). By
contrast, patients with left temporo-parietal
damage show deficits in phonological storage,
regardless of the effects of interference (Vallar
& Baddeley 1984, Vallar & Papagno 2002).
Consistent with these patterns, a metaanalysis of 60 functional neuroimaging studies indicated that increased demand for executive processing recruits dorsolateral frontal
Contesting the idea of separate long-term
and short-term systems. The key data supporting separable short-term and long-term
systems come from neuropsychology. To review, the critical contrast is between patients
who show severely impaired LTM with apparently normal STM (e.g., Cave & Squire
1992, Scoville & Milner 1957) and those who
show impaired STM with apparently normal LTM (e.g., Shallice & Warrington 1970).
However, questions have been raised about
whether these neuropsychological studies do,
in fact, support the claim that STM and LTM
are separable. A central question is the role
of the medial temporal lobe. It is well established that the MTL is critical for long-term
declarative memory formation and retrieval
(Gabrieli et al. 1997, Squire 1992). However,
is the MTL also engaged by STM tasks?
Much research with amnesic patients showing preserved STM would suggest not, but
Ranganath & Blumenfeld (2005) have summarized evidence showing that MTL is engaged in short-term tasks (see also Ranganath
& D’Esposito 2005 and Nichols et al. 2006).
In particular, there is growing evidence
that a critical function of the MTL is to
Unitary-Store Models that Combine
Short-Term and Long-Term Memory
The multistore models reviewed above combine assumptions about the distinction between short-term and long-term systems, the
decomposition of short-term memory into
information-specific buffers, and the separation of systems of storage from executive functions. We now consider unitary models that
reject the first assumption concerning distinct
systems.
www.annualreviews.org • The Mind and Brain of Short-Term Memory
197
ARI
1 December 2007
16:37
establish representations that involve novel
relations. These relations may be among features or items, or between items and their
context. By this view, episodic memory is a
special case of such relations (e.g., relating a
list of words to the experimental context in
which the list was recently presented), and the
special role of the MTL concerns its binding
capabilities, not the timescale on which it operates. STM that is apparently preserved in
amnesic patients may thus reflect a preserved
ability to maintain and retrieve information
that does not require novel relations or binding, in keeping with their preserved retrieval
of remote memories consolidated before the
amnesia-inducing lesion.
If this view is correct, then amnesic patients should show deficits in situations that
require STM for novel relations, which they
do (Hannula et al. 2005, Olson et al. 2006b).
They also show STM deficits for novel materials (e.g., Buffalo et al. 1998, Holdstock et al.
1995, Olson et al. 1995, 2006a). As mentioned
above, electrophysiological and neuroimaging studies support the claim that the MTL
is active in support of short-term memories
(e.g., Miyashita & Chang 1968, Ranganath &
D’Esposito 2001). Taken together, the MTL
appears to operate in both STM and LTM to
create novel representations, including novel
bindings of items to context.
Additional evidence for the STM-LTM
distinction comes from patients with perisylvian cortical lesions who are often claimed to
have selective deficits in STM (e.g., Hanley
et al. 1991, Warrington & Shallice 1969).
However, these deficits may be substantially perceptual. For example, patients with
left perisylvian damage that results in STM
deficits also have deficits in phonological processing in general, which suggests a deficit
that extends beyond STM per se (e.g., Martin
1993).
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
ANRV331-PS59-08
The architecture of unitary-store models.
Our review leads to the conclusion that shortand long-term memory are not architecturally
separable systems—at least not in the strong
198
Jonides et al.
sense of distinct underlying neural systems.
Instead, the evidence points to a model in
which short-term memories consist of temporary activations of long-term representations.
Such unitary models of memory have a long
history in cognitive psychology, with early
theoretical unification achieved via interference theory (Postman 1961, Underwood &
Schultz 1960). Empirical support came from
demonstrations that memories in both the
short and long term suffered from proactive interference (e.g., Keppel & Underwood
1962).
Perhaps the first formal proposal that
short-term memory consists of activated longterm representations was by Atkinson &
Shiffrin (1971, but also see Hebb 1949). The
idea fell somewhat out of favor during the
hegemony of the Baddeley multistore model,
although it was given its first detailed computational treatment by Anderson (1983). It
has recently been revived and greatly developed by Cowan (1988, 1995, 2000), McElree
(2001), Oberauer (2002), Verhaeghen et al.
(2004), Anderson et al. (2004), and others.
The key assumption is the construct of a very
limited focus of attention, although as we
elaborate below, there are disagreements regarding the scope of the focus.
One shared assumption of these models
is that STM consists of temporary activations of LTM representations or of representations of items that were recently perceived.
The models differ from one to another regarding specifics, but Cowan’s model (e.g.,
Cowan 2000) is representative. According to
this model, there is only one set of representations of familiar material—the representations in LTM. These representations can vary
in strength of activation, where that strength
varies as a function of such variables as recency
and frequency of occurrence. Representations
that have increased strength of activation are
more available for retrieval in STM experiments, but they must be retrieved nonetheless
to participate in cognitive action. In addition,
these representations are subject to forgetting
over time. A special but limited set of these
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
ANRV331-PS59-08
ARI
1 December 2007
16:37
representations, however, can be within the
focus of attention, where being within the focus makes these representations immediately
available for cognitive processing. According
to this and similar models, then, STM is functionally seen as consisting of LTM representations that are either in the focus of attention
or at a heightened level of activation.
These unitary-store models suggest a different interpretation of frontal cortical involvement in STM from multistore models.
Early work showing the importance of frontal
cortex for STM, particularly that of Fuster
and Goldman-Rakic and colleagues, was first
seen as support for multistore models (e.g.,
Funahashi et al. 1989, Fuster 1973, Jacobsen
1936, Wilson et al. 1993). For example, singleunit activity in dorsolateral prefrontal cortex
regions (principal sulcus, inferior convexity)
that was selectively responsive to memoranda
during the delay interval was interpreted as evidence that these regions were the storage sites
for STM. However, the sustained activation
of frontal cortex during the delay period does
not necessarily mean that this region is a site
of STM storage. Many other regions of neocortex also show activation that outlasts the
physical presence of a stimulus and provides
a possible neural basis for STM representations (see Postle 2006). Furthermore, increasing evidence suggests that frontal activations
reflect the operation of executive processes
[including those needed to keep the representations in the focus of attention; see reviews
by Postle (2006), Ranganath & D’Esposito
(2005), Reuter-Lorenz & Jonides (2007), and
Ruchkin et al. (2003)]. Modeling work and lesion data provide further support for the idea
that the representations used in both STM
and LTM are stored in those regions of cortex that are involved in initial perception and
encoding, and that frontal activations reflect
processes involved in selecting this information for the focus of attention and keeping it
there (Damasio 1989, McClelland et al. 1995).
The principle of posterior storage also
allows some degree of reconciliation between
multi- and unitary-store models. Posterior
regions are clearly differentiated by information type (e.g., auditory, visual, spatial),
which could support the information-specific
buffers postulated by multistore models.
Unitary-store models focus on central capacity limits, irrespective of modality, but they
do allow for separate resources (Cowan 2000)
or feature components (Lange & Oberauer
2005, Oberauer & Kliegl 2006) that occur at
lower levels of perception and representation.
Multi- and unitary-store models thus both
converge on the idea of modality-specific
representations (or components of those representations) supported by distinct posterior
neural systems.
Controversies over Capacity
Regardless of whether one subscribes to
multi- or unitary-store models, the issue of
how much information is stored in STM has
long been a prominent one (Miller 1956).
Multistore models explain capacity estimates
largely as interplay between the speed with
which information can be rehearsed and the
speed with which information is forgotten
(Baddeley 1986, 1992; Repov & Baddeley
2006). Several studies have measured this limit
by demonstrating that approximately two seconds worth of verbal information can be recirculated successfully (e.g., Baddeley et al.
1975).
Unitary-store models describe capacity as
limited by the number of items that can be
activated in LTM, which can be thought of as
the bandwidth of attention. However, these
models differ on what that number or bandwidth might be. Cowan (2000) suggested a
limit of approximately four items, based on
performance discontinuities such as errorless
performance in immediate recall when the
number of items is less than four, and sharp
increases in errors for larger numbers. (By this
view, the classic “seven plus or minus two” is
an overestimate because it is based on studies that allowed participants to engage in processes of rehearsal and chunking, and reflected
contributions of both the focus and LTM; see
www.annualreviews.org • The Mind and Brain of Short-Term Memory
199
ANRV331-PS59-08
ARI
1 December 2007
16:37
also Waugh & Norman 1965.) At the other
extreme are experimental paradigms suggesting that the focus of attention consists of a
single item (Garavan 1998, McElree 2001,
Verhaeghen & Basak 2007). We briefly consider some of the central issues behind current
controversies concerning capacity estimates.
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
Behavioral and neural evidence for the
magic number 4. Cowan (2000) has reviewed an impressive array of studies leading
to his conclusion that the capacity limit is four
items, plus or minus one (see his Table 1).
Early behavioral evidence came from studies showing sharp drop-offs in performance
at three or four items on short-term retrieval
tasks (e.g., Sperling 1960). These experiments
were vulnerable to the criticism that this limit
might reflect output interference occurring
during retrieval rather than an actual limit on
capacity. However, additional evidence comes
from change-detection and other tasks that
do not require the serial recall of individual
items. For example, Luck & Vogel (1997) presented subjects with 1 to 12 colored squares
in an array. After a blank interval of nearly
a second, another array of squares was presented, in which one square may have changed
color. Subjects were to respond whether the
arrays were identical. These experiments and
others that avoid the confound of outputinterference (e.g., Pashler 1988) likewise have
yielded capacity estimates of approximately
four items.
Electrophysiological and neuroimaging
studies also support the idea of a four-item
capacity limit. The first such report was by
Vogel & Machizawa (2004), who recorded
event-related potentials (ERPs) from subjects
as they performed a visual change-detection
task. ERP recording shortly after the onset
of the retention interval in this task indicated
a negative-going wave over parietal and occipital sites that persisted for the duration of
the retention interval and was sensitive to the
number of items held in memory. Importantly,
this signal plateaued when array size reached
between three and four items. The amplitude
200
Jonides et al.
of this activity was strongly correlated with estimates of each subject’s memory capacity and
was less pronounced on incorrect than correct trials, indicating that it was causally related to performance. Subsequent functional
magnetic resonance imaging (fMRI) studies
have observed similar load- and accuracydependent activations, especially in intraparietal and intraoccipital sulci (Todd & Marois
2004, 2005). These regions have been implicated by others (e.g., Yantis & Serences 2003)
in the control of attentional allocation, so it
seems plausible that one rate-limiting step in
STM capacity has to do with the allocation of
attention (Cowan 2000; McElree 1998, 2001;
Oberauer 2002).
Evidence for more severe limits on focus
capacity. Another set of researchers agree
there is a fixed capacity, but by measuring a
combination of response time and accuracy,
they contend that the focus of attention is
limited to just one item (e.g., Garavan 1998,
McElree 2001, Verhaeghen & Basak 2007).
For example, Garavan (1998) required subjects to keep two running counts in STM, one
for triangles and one for squares—as shape
stimuli appeared one after another in random
order. Subjects controlled their own presentation rate, which allowed Garavan to measure the time spent processing each figure
before moving on. He found that responses
to a figure of one category (e.g., a triangle)
that followed a figure from the other category (e.g., a square) were fully 500 milliseconds longer than responses to the second of
two figures from the same category (e.g., a
triangle followed by another triangle). These
findings suggested that attention can be focused on only one internal counter in STM at
a time. Switching attention from one counter
to another incurred a substantial cost in time.
Using a speed-accuracy tradeoff procedure,
McElree (1998) came to the same conclusion
that the focus of attention contained just one
item. He found that the retrieval speed for the
last item in a list was substantially faster than
for any other item in the list, and that other
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
ANRV331-PS59-08
ARI
1 December 2007
16:37
items were retrieved at comparable rates to
each other even though the accuracy of retrieval for these other items varied.
Oberauer (2002) suggested a compromise
solution to the “one versus four” debate. In
his model, up to four items can be directly accessible, but only one of these items can be in
the focus of attention. This model is similar to
that of Cowan (2000), but adds the assumption that an important method of accessing
short-term memories is to focus attention on
one item, depending on task demands. Thus,
in tasks that serially demand attention on several items (such as those of Garavan 1998 or
McElree 2001), the mechanism that accomplishes this involves changes in the focus of
attention among temporarily activated representations in LTM.
Alternatives to capacity limits based on
number of items. Attempting to answer the
question of how many items may be held in
the focus implicitly assumes that items are the
appropriate unit for expressing capacity limits. Some reject this basic assumption. For example, Wilken & Ma (2004) demonstrated
that a signal-detection account of STM, in
which STM capacity is primarily constrained
by noise, better fit behavioral data than an
item-based fixed-capacity model. Recent data
from change-detection tasks suggest that object complexity (Eng et al. 2005) and similarity (Awh et al. 2007) play an important role in
determining capacity. Xu & Chun (2006) offer neuroimaging evidence that may reconcile
the item-based and complexity accounts: In a
change-detection task, they found that activation of inferior intra-parietal sulcus tracked a
capacity limit of four, but nearby regions were
sensitive to the complexity of the memoranda,
as were the behavioral results.
Other researchers disagree with fixed
item-based limits because they have demonstrated that the limit is mutable. Practice may
improve subjects’ ability to use processes such
as chunking to allow greater functional capacities (McElree 1998, Verhaeghen et al. 2004;
but see Oberauer 2006). However, this type
of flexibility appears to alter the amount of information that can be compacted into a single
representation rather than the total number
of representations that can be held in STM
(Miller 1956). The data of Verhaegen et al.
(2004; see Figure 5 of that paper) suggest that
the latter number still approximates four, consistent with Cowan’s claims.
Building on these findings, we suggest a
new view of capacity. The fundamental idea
that attention can be allocated to one piece
of information in memory is correct, but the
definition of what that one piece is needs to
be clarified. It cannot be that just one item is
in the focus of attention because if that were
so, hardly any computation would be possible.
How could one add 3+4, for example, if at any
one time, attention could be allocated only
to the “3” or the “4” or the “+” operation?
We propose that attention focuses on what is
bound together into a single “functional context,” whether that context is defined by time,
space, some other stimulus characteristic such
as semantic or visual similarity or momentary
task relevance. By this account, attention can
be placed on the whole problem “3+4,” allowing relevant computations to be made. Complexity comes into play by limiting the number
of subcomponents that can be bound into one
functional context.
Summary
What are we to conclude from the data concerning the structure of STM? We favor the
implication that the representational bases for
perception, STM, and LTM are identical.
That is, the same neural representations initially activated during the encoding of a piece
of information show sustained activation during STM (or retrieval from LTM into STM;
Wheeler et al. 2000) and are the repository
of long-term representations. Because regions
of neocortex represent different sorts of information (e.g., verbal, spatial), it is reasonable to
expect that STM will have an organization by
type of material as well. Functionally, memory in the short term seems to consist of items
www.annualreviews.org • The Mind and Brain of Short-Term Memory
201
ANRV331-PS59-08
ARI
1 December 2007
16:37
in the focus of attention along with recently
attended representations in LTM. These
items in the focus of attention number no
more than four, and they may be limited to just
a single representation (consisting of items
bound within a functional context).
We turn below to processes that operate
on these representations.
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
WHAT PROCESSES OPERATE
ON THE STORED
INFORMATION?
Theoretical debate about the nature of STM
has been dominated by discussion of structure
and capacity, but the issue of process is also
important. Verbal rehearsal is perhaps most
intuitively associated with STM and plays a
key role in the classic model (Baddeley 1986).
However, as we discuss below, rehearsal most
likely reflects a complex strategy rather than a
primitive STM process. Modern approaches
offer a large set of candidate processes, including encoding and maintenance (Ranganath
et al. 2004), attention shifts (Cowan 2000),
spatial rehearsal (Awh & Jonides 2001), updating (Oberauer 2005), overwriting (Neath
& Nairne 1995), cue-based parallel retrieval
(McElree 2001), and interference-resolution
( Jonides & Nee 2006).
Rather than navigating this complex and
growing list, we take as our cornerstone the
concept of a limited focus of attention. The
central point of agreement for the unitarystore models discussed above is that there is
a distinguishable focus of attention in which
representations are directly accessible and
available for cognitive action. Therefore, it is
critical that all models must identify the processes that govern the transition of memory
representations into and out of this focused
state.
The Three Core Processes of
Short-Term Memory: Encoding,
Maintenance, and Retrieval
If one adopts the view that a limited focus of
attention is a key feature of short-term stor202
Jonides et al.
age, then understanding processing related to
this limited focus amounts to understanding
three basic types of cognitive events2 : (a) encoding processes that govern the transformation from perceptual representations into the
cognitive/attentional focus, (b) maintenance
processes that keep information in the focus (and protect it from interference or decay), and (c) retrieval processes that bring
information from the past back into the cognitive focus (possibly reactivating perceptual
representations).
Encoding of items into the focus. Encoding processes are the traditional domain of
theories of perception and are not treated explicitly in any of the current major accounts
of STM. Here we outline three implicit assumptions about encoding processes made in
most accounts of STM, and we assess their
empirical and theoretical support.
First, the cognitive focus is assumed to
have immediate access to perceptual processing—that is, the focus may include contents from the immediate present as well as
contents retrieved from the immediate past.
In Cowan’s (2000) review of evidence in favor of the number four in capacity estimates,
several of the experimental paradigms involve
focused representations of objects in the immediate perceptual present or objects presented less than a second ago. These include visual tracking experiments (Pylyshyn
et al. 1994), enumeration (Trick & Pylyshyn
1993), and whole report of spatial arrays and
spatiotemporal arrays (Darwin et al. 1972,
Sperling 1960). Similarly, in McElree’s (2006)
and Garavan’s (1998) experiments, each incoming item in the stream of material (words
or letters or objects) is assumed to be represented momentarily in the focus.
2
This carving up of STM processes is also consistent
with recent approaches to individual differences in working memory, which characterize individual variation not in
terms of variation in buffer capacity, but rather in variation
in maintenance and retrieval processes (Unsworth & Engle
2007).
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
ANRV331-PS59-08
ARI
1 December 2007
16:37
Second, all of the current theories assume that perceptual encoding into the focus of attention results in a displacement of
other items from the focus. For example, in
McElree’s single-item focus model, each incoming item not only has its turn in the focus,
but it also replaces the previous item. On the
one hand, the work reviewed above regarding
performance discontinuities after the putative
limit of STM capacity has been reached appears to support the idea of whole-item displacement. On the other hand, as also described above, this limit may be susceptible
to factors such as practice and stimulus complexity. An alternative to whole-item displacement as the basis for interference is a graded
similarity-based interference, in which new
items entering the focus may partially overwrite features of the old items or compete
with old items to include those featural components in their representations as a function
of their similarity. At some level, graded interference is clearly at work in STM, as Nairne
(2002) and others have demonstrated (we review this evidence in more detail below). But
the issue at hand is whether the focus is subject to such graded interference, and if such
interference is the process by which encoding
(or retrieving) items into the focus displaces
prior items. Although there does not appear
to be evidence that bears directly on this issue (the required experiments would involve
manipulations of similarity in just the kinds of
paradigms that Cowan, McElree, Oberauer,
and others have used to provide evidence for
the limited focus), the performance discontinuities strongly suggest that something like
displacement is at work.
Third, all of the accounts assume that perceptual encoding does not have obligatory access to the focus. Instead, encoding into the
focus is modulated by attention. This follows
rather directly from the assumptions about the
severe limits on focus capacity: There must
be some controlled way of directing which aspects of the perceptual present, as well as the
cognitive past, enter into the focused state.
Stated negatively, there must be some way of
preventing aspects of the perceptual present
from automatically entering into the focused
state. Postle (2006) recently found that increased activity in dorsolateral prefrontal cortex during the presentation of distraction during a retention interval was accompanied by a
selective decrease in inferior temporal cortical
activity. This pattern suggests that prefrontal
regions selectively modulated posterior perceptual areas to prevent incoming sensory input from disrupting the trace of the taskrelevant memorandum.
In summary, current approaches to STM
have an obligation to account for how controlled processes bring relevant aspects of perception into cognitive focus and leave others
out. It is by no means certain that existing
STM models and existing models of perceptual attention are entirely compatible on this
issue, and this is a matter of continued lively
debate (Milner 2001, Schubert & Frensch
2001, Woodman et al. 2001).
Maintenance of items in the focus. Once
an item is in the focus of attention, what
keeps it there? If the item is in the perceptual present, the answer is clear: attentionmodulated, perceptual encoding. The more
pressing question is: What keeps something
in the cognitive focus when it is not currently
perceived? For many neuroscientists, this is
the central question of STM—how information is held in mind for the purpose of future action after the perceptual input is gone.
There is now considerable evidence from primate models and from imaging studies on humans for a process of active maintenance that
keeps representations alive and protects them
from irrelevant incoming stimuli or intruding
thoughts (e.g., Postle 2006).
We argue that this process of maintenance is not the same as rehearsal. Indeed,
the number of items that can be maintained
without rehearsal forms the basis of Cowan’s
(2000) model. Under this view, rehearsal is
not a basic process but rather is a strategy
for accomplishing the functional demands for
sustaining memories in the short term—a
www.annualreviews.org • The Mind and Brain of Short-Term Memory
203
ARI
1 December 2007
16:37
strategy composed of a series of retrievals and
re-encodings. We consider rehearsal in more
detail below, but we consider here the behavioral and neuroimaging evidence for maintenance processes.
There is now considerable evidence from
both primate models and human electroencephalography and fMRI studies for a set of
prefrontal-posterior circuits underlying active maintenance. Perhaps the most striking
is the classic evidence from single-cell recordings showing that some neurons in prefrontal
cortex fire selectively during the delay period in delayed-match-to-sample tasks (e.g.,
Funahashi et al. 1989, Fuster 1973). As mentioned above, early interpretations of these
frontal activations linked them directly to
STM representations (Goldman-Rakic 1987),
but more recent theories suggest they are
part of a frontal-posterior STM circuit that
maintains representations in posterior areas (Pasternak & Greenlee 2005, Ranganath
2006, Ruchkin et al. 2003). Furthermore,
as described above, maintenance operations
may modulate perceptual encoding to prevent
incoming perceptual stimuli from disrupting the focused representation in posterior
cortex (Postle 2006). Several computational
neural-network models of circuits for maintenance hypothesize that prefrontal cortical
circuits support attractors, self-sustaining patterns observed in certain classes of recurrent
networks (Hopfield 1982, Rougier et al. 2005,
Polk et al. 2002). A major challenge is to develop computational models that are able to
engage in active maintenance of representations in posterior cortex while simultaneously
processing, to some degree, incoming perceptual material (see Renart et al. 1999 for a related attempt).
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
ANRV331-PS59-08
Retrieval of items into the focus. Many
of the major existing STM architectures are
silent on the issue of retrieval. However, all
models that assume a limited focus also assume that there is some means by which items
outside that focus (either in a dormant longterm store or in some highly activated portion
204
Jonides et al.
of LTM) are brought into the focus by switching the attentional focus onto those items.
Following Sternberg (1966), McElree (2006),
and others, we label this process “retrieval.”
Despite this label, it is important to keep in
mind that the associated spatial metaphor of
an item moving from one location to another
is misleading given our assumption about the
common neural representations underlying
STM and LTM.
There is now considerable evidence,
mostly from mathematical models of behavioral data, that STM retrieval of item
information is a rapid, parallel, contentaddressable process. The current emphasis
on parallel search processes is quite different
from the earliest models of STM retrieval,
which postulated a serial scanning process
(i.e., Sternberg 1966; see McElree 2006 for
a recent review and critique). Serial-scanning
models fell out of favor because of empirical
and modeling work showing that parallel
processes provide a better account of the
reaction time distributions in STM tasks (e.g.,
Hockley 1984). For example, McElree has
created a variation on the Sternberg recognition probe task that provides direct support
for parallel, rather than serial, retrieval. In the
standard version of the task, participants are
presented with a memory set consisting of a
rapid sequence of verbal items (e.g., letters or
digits), followed by a probe item. The task is
to identify whether the probe was a member
of the memory set. McElree & Dosher’s
(1989) innovation was to manipulate the
deadline for responding. The time course of
retrieval (accuracy as a function of response
deadline) can be separately plotted for each
position within the presentation sequence,
allowing independent assessments of accessibility (how fast an item can be retrieved)
and availability (asymptotic accuracy) as a
function of set size and serial position. Many
experiments yield a uniform rate of access
for all items except for the most recent item,
which is accessed more quickly. The uniformity of access rate is evidence for parallel
access, and the distinction between the most
ANRV331-PS59-08
ARI
1 December 2007
16:37
recent item and the other items is evidence
for a distinguished focus of attention.
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
Neural Mechanisms of Short- and
Long-Term Memory Retrieval
The cue-based retrieval processes described
above for STM are very similar to those
posited for LTM (e.g., Anderson et al. 2004,
Gillund & Shiffrin 1984, Murdock 1982).
As a result, retrieval failures resulting from
similarity-based interference and cue overlap are ubiquitous in both STM and LTM.
Both classic studies of recall from STM (e.g.,
Keppel & Underwood 1962) and more recent
studies of interference in probe-recognition
tasks (e.g., Jonides & Nee 2006, McElree &
Dosher 1989, Monsell 1978) support the idea
that interference plays a major role in forgetting over short retention intervals as well as
long ones (see below). These common effects
would not be expected if STM retrieval were
a different process restricted to operate over
a limited buffer, but they are consistent with
the notion that short-term and long-term retrieval are mediated by the same cue-based
mechanisms.
The heavy overlap in the neural substrates for short-term and long-term retrieval provides additional support for the
idea that retrieval processes are largely the
same over different retention intervals. A network of medial temporal regions, lateral prefrontal regions, and anterior prefrontal regions has been extensively studied and shown
to be active in long-term retrieval tasks (e.g.,
Buckner et al. 1998, Cabeza & Nyberg 2000,
Fletcher & Henson 2001). We reviewed above
the evidence for MTL involvement in both
short- and long-term memory tasks that require novel representations (see section titled
“Contesting the Idea of Separate Long-Term
and Short-Term Systems”). Here, we examine
whether the role of frontal cortex is the same
for both short- and long-term retrieval.
The conclusion derived from neuroimaging studies of various different STM
procedures is that this frontal role is the
same in short-term and long-term retrieval.
For example, several event-related fMRI
studies of the retrieval stage of the proberecognition task found increased activation
in lateral prefrontal cortex similar to the
activations seen in studies of LTM retrieval
(e.g., D’Esposito et al. 1999, D’Esposito &
Postle 2000, Manoach et al. 2003). Badre &
Wagner (2005) also found anterior prefrontal
activations that overlapped with regions
implicated in episodic recollection. The relatively long retention intervals often used in
event-related fMRI studies leaves them open
to the criticism that by the time of the probe,
the focus of attention has shifted elsewhere,
causing the need to retrieve information
from LTM (more on this discussion below).
However, a meta-analysis of studies that
involved bringing very recently presented
items to the focus of attention likewise found
specific involvement of lateral and anterior
prefrontal cortex ( Johnson et al. 2005). These
regions appear to be involved in retrieval,
regardless of timescale.
The same conclusion may be drawn from
recent imaging studies that have directly compared long- and short-term retrieval tasks
using within-subjects designs (Cabeza et al.
2002, Ranganath et al. 2003, Talmi et al.
2005). Ranganath et al. (2003) found the same
bilateral ventrolateral and dorsolateral prefrontal regions engaged in both short- and
long-term tasks. In some cases, STM and
LTM tasks involve the same regions but differ in the relative amount of activation shown
within those regions. For example, Cabeza
et al. (2002) reported similar engagement of
medial temporal regions in both types of task,
but greater anterior and ventrolateral activation in the long-term episodic tasks. Talmi
et al. (2005) reported greater activation in
both medial temporal and lateral frontal cortices for recognition probes of items presented early in a 12-item list (presumably necessitating retrieval from LTM) versus items
presented later in the list (presumably necessitating retrieval from STM). One possible reason for this discrepancy is that recognition for
www.annualreviews.org • The Mind and Brain of Short-Term Memory
205
ARI
1 December 2007
16:37
late-list items did not require retrieval because
these items were still in the focus of attention.
This account is plausible since late-list items
were drawn either from the last-presented or
second-to-last presented item and preceded
the probe by less than two seconds.
In summary, the bulk of the neuroimaging evidence points to the conclusion that the
activation of frontal and medial temporal regions depends on whether the information is
currently in or out of focus, not whether the
task nominally tests STM or LTM. Similar
reactivation processes occur during retrieval
from LTM and from STM when the active
maintenance has been interrupted (see Sakai
2003 for a more extensive review).
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
ANRV331-PS59-08
The Relationship of Short-Term
Memory Processes to Rehearsal
Notably, our account of core STM processes
excludes rehearsal. How does rehearsal fit in?
We argue that rehearsal is simply a controlled
sequence of retrievals and re-encodings of
items into the focus of attention (Baddeley
1986, Cowan 1995). The theoretical force of
this assumption can be appreciated by examining the predictions it makes when coupled
with our other assumptions about the structures and processes of the underlying STM
architecture. Below we outline these predictions and the behavioral, developmental, neuroimaging, and computational work that support this view.
Rehearsal as retrieval into the focus.
When coupled with the idea of a single-item
focus, the assumption that rehearsal is a sequence of retrievals into the focus of attention
makes a very clear prediction: A just-rehearsed
item should display the same retrieval dynamics as a just-perceived item. McElree (2006)
directly tested this prediction using a version
of his response-deadline recognition task, in
which subjects were given a retention interval between presentation of the list and the
probe rather than presented with the probe
immediately after the list. Subjects were ex206
Jonides et al.
plicitly instructed to rehearse the list during
this interval and were trained to do so at a particular rate. By controlling the rate, it was possible to know when each item was rehearsed
and hence re-established in the focus. The results were compelling: When an item was predicted to be in focus because it had just been
rehearsed, it showed the same fast retrieval
dynamics as an item that had just been perceived. In short, the speed-accuracy tradeoff
functions showed the familiar in-focus/outof-focus dichotomy of the standard paradigm,
but the dichotomy was established for internally controlled rehearsal as well as externally
controlled perception.
Rehearsal as strategic retrieval. Rehearsal
is often implicitly assumed as a component
of active maintenance, but formal theoretical considerations of STM typically take the
opposite view. For example, Cowan (2000)
provides evidence that although first-grade
children do not use verbal rehearsal strategies, they nevertheless have measurable focus capacities. In fact, Cowan (2000) uses this
evidence to argue that the performance of
very young children is revealing of the fundamental capacity limits of the focus of attention because it is not confounded with
rehearsal.
If rehearsal is the controlled composition
of more primitive STM processes, then rehearsal should activate the same brain circuits
as the primitive processes, possibly along with
additional (frontal) circuits associated with
their control. In other words, there should
be overlap of rehearsal with brain areas subserving retrieval and initial perceptual encoding. Likewise, there should be control
areas distinct from those of the primitive
processes.
Both predictions receive support from
neuroimaging studies. The first prediction
is broadly confirmed: There is now considerable evidence for the reactivation of areas associated with initial perceptual encoding in tasks that require rehearsal (see Jonides
et al. 2005 for a recent review; note also that
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
ANRV331-PS59-08
ARI
1 December 2007
16:37
evidence exists for reactivation in LTM retrieval: Wheeler 2000, 2006).
The second prediction—that rehearsal engages additional control areas beyond those
participating in maintenance, encoding, and
retrieval—receives support from two effects.
One is that verbal rehearsal engages a set of
frontal structures associated with articulation
and its planning: supplementary motor, premotor, inferior frontal, and posterior parietal areas (e.g., Chein & Fiez 2001, Jonides
et al. 1998, Smith & Jonides 1999). The
other is that spatial rehearsal engages attentionally mediated occipital regions, suggesting rehearsal processes that include retrieval
of spatial information (Awh et al. 1998, 1999,
2001).
Computational modeling relevant to
strategic retrieval. Finally, prominent symbolic and connectionist computational models
of verbal STM tasks are based on architectures
that do not include rehearsal as a primitive
process, but rather assume it as a strategic
composition of other processes operating over
a limited focus. The Burgess & Hitch (2005,
2006) connectionist model, the ExecutiveProcess/Interactive Control (EPIC) symbolic
model (Meyer and Kieras 1997), and the
Atomic Components of Thought (ACT-R)
hybrid model (Anderson & Matessa 1997) all
assume that rehearsal in verbal STM consists
of a controlled sequence of retrievals of items
into a focused state. They all assume different
underlying mechanisms for the focus (the
Burgess & Hitch model has a winner-take-all
network; ACT-R has an architectural buffer
with a capacity of one chunk; EPIC has a
special auditory store), but all assume strategic use of this focus to accomplish rehearsal.
These models jointly represent the most
successful attempts to account for a range of
detailed empirical phenomena traditionally
associated with rehearsal, especially in verbal
serial recall tasks. Their success therefore
provides further support for the plausibility
of a compositional view of rehearsal.
WHY DO WE FORGET?
Forgetting in STM is a vexing problem: What
accounts for failures to retrieve something encoded just seconds ago? There are two major explanations for forgetting, often placed in
opposition: time-based decay and similaritybased interference. Below, we describe some
of the major findings in the literature related
to each of these explanations, and we suggest
that they may ultimately result from the same
underlying principles.
Decay Theories: Intuitive
but Problematic
The central claim of decay theory is that as
time passes, information in memory erodes,
and so it is less available for later retrieval.
This explanation has strong intuitive appeal.
However, over the years there have been
sharp critiques of decay, questioning whether
it plays any role at all (for recent examples,
see Lewandowsky et al. 2004 and the review
in this journal by Nairne 2002).
Decay explanations are controversial for
two reasons: First, experiments attempting
to demonstrate decay can seldom eliminate alternative explanations. For example,
Keppel & Underwood (1962) demonstrated
that forgetting in the classic Brown-Peterson
paradigm (designed to measure time-based
decay) was due largely, if not exclusively,
to proactive interference from prior trials.
Second, without an explanation of how decay occurs, it is difficult to see decay theories
as more than a restatement of the problem.
Some functional arguments have been made
for the usefulness of the notion of memory
decay—that decaying activations adaptively
mirror the likelihood that items will need
to be retrieved (Anderson & Schooler 1991),
or that decay is functionally necessary to reduce interference (Altmann & Gray 2002).
Nevertheless, McGeoch’s famous (1932) criticism of decay theories still holds merit:
Rust does not occur because of time itself,
but rather from oxidation processes that occur with time. Decay theories must explain
www.annualreviews.org • The Mind and Brain of Short-Term Memory
207
ANRV331-PS59-08
ARI
1 December 2007
16:37
the processes by which decay could occur,
i.e., they must identify the oxidation process
in STM.
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
Retention-interval confounds: controlling
for rehearsal and retroactive interference.
The main problem in testing decay theories
is controlling for what occurs during the
retention interval. Many experiments include
an attention-demanding task to prevent
participants from using rehearsal that would
presumably circumvent decay. However, a
careful analysis of these studies by Roediger
et al. (1977) makes one wonder whether
the use of a secondary task is appropriate
to prevent rehearsal at all. They compared
conditions in which a retention interval was
filled by nothing, by a relatively easy task, or
by a relatively difficult one. Both conditions
with a filled interval led to worse memory performance, but the difficulty of the intervening
task had no effect. Roediger et al. (1977)
concluded that the primary memory task and
the interpolated task, although demanding,
used different processing pools of resources,
and hence the interpolated tasks may not
have been effective in preventing rehearsal.
So, they argued, this sort of secondary-task
technique may not prevent rehearsal and may
not allow for a convincing test of a decay
hypothesis.
Another problem with tasks that fill the retention interval is that they require subjects
to use STM (consider counting backward, as
in the Brown-Peterson paradigm). This could
lead to active displacement of items from
the focus according to views (e.g., McElree
2001) that posit such displacement as a mechanism of STM forgetting, or increase the
noise according to interference-based explanations (see discussion below in What Happens Neurally During the Delay?). By either
account, the problem with retention-interval
tasks is that they are questionable ways to prevent rehearsal of the to-be-remembered information, and they introduce new, distracting information that may engage STM. This
double-edged sword makes it difficult to tie
208
Jonides et al.
retention-interval manipulations directly to
decay.
Attempts to address the confounding
factors. A potential way out of the rehearsal
conundrum is to use stimuli that are not easily
converted to verbal codes and that therefore
may be difficult to rehearse. For example,
Harris (1952) used tones that differed so
subtly in pitch that they would be difficult to
name by subjects without perfect pitch. On
each trial, participants were first presented
with a to-be-remembered tone, followed by
a retention interval of 0.1 to 25 seconds, and
finally a probe tone. The accuracy of deciding
whether the initial and probe tones were the
same declined with longer retention intervals, consistent with the predictions of decay
theory.
Using another technique, McKone (1995,
1998) reduced the probability of rehearsal or
other explicit-memory strategies by using an
implicit task. Words and nonwords were repeated in a lexical-decision task, with the measure of memory being faster performance on
repeated trials than on novel ones (priming).
To disentangle the effects of decay and interference, McKone varied the time between
repetitions (the decay-related variable) while
holding the number of items between repetitions (the interference-related variable) constant, and vice versa. She found that greater
time between repetitions reduced priming
even after accounting for the effects of intervening items, consistent with decay theory. However, interference and decay effects
seemed to interact and to be especially important for nonwords.
Procedures such as those used by Harris
(1952) and McKone (1995, 1998) do not
have the problems associated with retentioninterval tasks. They are, however, potentially vulnerable to the criticism of Keppel
& Underwood (1962) regarding interference
from prior trials within the task, although
McKone’s experiments address this issue to
some degree. Another potential problem is
that these participants’ brains and minds are
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
ANRV331-PS59-08
ARI
1 December 2007
16:37
not inactive during the retention interval
(Raichle et al. 2001). There is increasing evidence that the processes ongoing during nominal “resting states” are related to memory,
including STM (Hampson et al. 2006). Spontaneous retrieval by participants during the
retention interval could interfere with memory for the experimental items. So, although
experiments that reduce the influence of rehearsal provide some of the best evidence of
decay, they are not definitive.
with frontal lesions was able to perform a delayed response task extremely well (97% correct) if visual stimulation and motor movement (and therefore associated interference)
were restricted during a 10-second delay. By
contrast, in unrestricted conditions, performance was as low as 25% correct (see also
Postle & D’Esposito 1999). In summary, evidence for time-based declines in neural activity that would naturally be thought to be part
of a decay process is at best mixed.
What happens neurally during the
delay? Neural findings of delay-period
activity have also been used to support the
idea of decay. For example, at the single-cell
level, Fuster (1995) found that in monkeys
performing a delayed-response task, delayperiod activity in inferotemporal cortex
steadily declined over 18 seconds (see also
Pasternak & Greenlee 2005). At a molar level,
human neuroimaging studies often show
delay-period activity in prefrontal and posterior regions, and this activity is often thought
to support maintenance or storage (see review
by Smith & Jonides 1999). As reviewed above,
it is likely that the posterior regions support
storage and that frontal regions support
processes related to interference-resolution,
control, attention, response preparation,
motivation, and reward.
Consistent with the suggestive primate
data, Jha & McCarthy (2000) found a general decline in activation in posterior regions
over a delay period, which suggests some neural evidence for decay. However, this decline
in activation was not obviously related to performance, which suggests two (not mutually
exclusive) possibilities: (a) the decline in activation was not representative of decay, so it did
not correlate with performance, or (b) these
regions might not have been storage regions
(but see Todd & Marois 2004 and Xu & Chun
2006 for evidence more supportive of load
sensitivity in posterior regions).
The idea that neural activity decays also
faces a serious challenge in the classic results
of Malmo (1942), who found that a monkey
Is there a mechanism for decay? Although
there are data supporting the existence of decay, much of these data are subject to alternative, interference-based explanations. However, as Crowder (1976) noted, “Good ideas
die hard.” At least a few key empirical results
(Harris 1952; McKone 1995, 1998) do seem
to implicate some kind of time-dependent decay. If one assumes that decay happens, how
might it occur?
One possibility—perhaps most compatible
with results like those of Malmo (1942)—is
that what changes over time is not the integrity of the representation itself, but the
likelihood that attention will be attracted away
from it. As more time passes, the likelihood
increases that attention will be attracted away
from the target and toward external stimuli
or other memories, and it will be more difficult to return to the target representation.
This explanation seems compatible with the
focus-of-attention views of STM that we have
reviewed. By this explanation, capacity limits
are a function of attention limits rather than
a special property of STM per se.
Another explanation, perhaps complementary to the first, relies on stochastic variability in the neuronal firing patterns that
make up the target representation. The temporal synchronization of neuronal activity is
an important part of the representation (e.g.,
Deiber et al. 2007, Jensen 2006, Lisman &
Idiart 1995). As time passes, variability in the
firing rates of individual neurons may cause
them to fall increasingly out of synchrony
unless they are reset (e.g., by rehearsal). As
www.annualreviews.org • The Mind and Brain of Short-Term Memory
209
ANRV331-PS59-08
ARI
1 December 2007
16:37
the neurons fall out of synchrony, by this
hypothesis, the firing pattern that makes up
the representation becomes increasingly difficult to discriminate from surrounding noise
[see Lustig et al. (2005) for an example that
integrates neural findings with computational
(Frank et al. 2001) and behaviorally based
(Brown et al. 2000) models of STM].
Interference Theories:
Comprehensive but Complex
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
Interference effects play several roles in memory theory: First, they are the dominant explanation of forgetting. Second, some have
suggested that STM capacity and its variation among individuals are largely determined
by the ability to overcome interference (e.g.,
Hasher & Zacks 1988, Unsworth & Engle
2007). Finally, differential interference effects
in STM and LTM have been used to justify the idea that they are separate systems,
and common interference effects have been
used to justify the idea that they are a unitary
system.
Interference theory has the opposite problem of decay: It is comprehensive but complex (Crowder 1976). The basic principles are
straightforward. Items in memory compete,
with the amount of interference determined
by the similarity, number, and strength of the
competitors. The complexity stems from the
fact that interference may occur at multiple
stages (encoding, retrieval, and possibly storage) and at multiple levels (the representation itself or its association with a cue or a
response). Interference from the past (proactive interference; PI) may affect both the encoding and the retrieval of new items, and it
often increases over time. By contrast, interference from new items onto older memories (retroactive interference; RI) frequently
decreases over time and may not be as reliant on similarity (see discussion by Wixted
2004).
Below, we review some of the major findings with regard to interference in STM,
including a discussion of its weaknesses in
210
Jonides et al.
explaining short-term forgetting. We then
present a conceptual model of STM that attempts to address these weaknesses and the
questions regarding structure, process, and
forgetting raised throughout this review.
Interference Effects
in Short-Term Memory
Selection-based interference effects. The
Brown-Peterson task, originally conceived to
test decay theory, became a workhorse for
testing similarity-based interference as well.
In the “release-from-PI” version (Wickens
1970), short lists of categorized words are used
as memoranda. Participants learn one threeitem list on each trial, perform some other
task during the retention interval, and then
attempt to recall the list. For the first three
trials, all lists consist of words from the same
category (e.g., flowers). The typical PI effects
occur: Recall declines over subsequent trials.
The critical manipulation occurs at the final
list. If it is from a different category (e.g.,
sports), recall is much higher than if it is from
the same category as preceding trials. In some
cases, performance on this set-shift or releasefrom-PI trial is nearly as high as on the very
first trial.
The release-from-PI effect was originally
interpreted as an encoding effect. Even very
subtle shifts (e.g., from “flowers” to “wildflowers”) produce the effect if participants are
warned about the shift before the words are
presented (see Wickens 1970 for an explanation). However, Gardiner et al. (1972) showed
that release also occurs if the shift-cue is presented only at the time of the retrieval test—
i.e., after the list has been encoded. They suggested that cues at retrieval could reduce PI
by differentiating items from the most recent
list, thus aiding their selection.
Selection processes remain an important
topic in interference research. Functional
neuroimaging studies consistently identify a region in left inferior frontal gyrus
(LIFG) as active during interference resolution, at least for verbal materials (see
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
ANRV331-PS59-08
ARI
1 December 2007
16:37
a review by Jonides & Nee 2006). This
region appears to be generally important
for selection among competing alternatives,
e.g., in semantic memory as well as in STM
(Thompson-Schill et al. 1997). In STM,
LIFG is most prominent during the test
phase of interference trials, and its activation
during this phase often correlates with behavioral measures of interference resolution
(D’Esposito et al. 1999, Jonides et al. 1998,
Reuter-Lorenz et al. 2000, Thompson-Schill
et al. 2002). These findings attest to the
importance of processes for resolving retrieval interference. The commonality of the
neural substrate for interference resolution
across short-term and long-term tasks provides yet further support for the hypothesis
of shared retrieval processes for the two types
of memory.
Interference effects occur at multiple levels, and it is important to distinguish between
interference at the level of representations and
interference at the level of responses. The
LIFG effects described above appear to be familiarity based and to occur at the level of representations. Items on a current trial must be
distinguished and selected from among items
on previous trials that are familiar because of
prior exposure but are currently incorrect. A
separate contribution occurs at the level of responses: An item associated with a positive response on a prior trial may now be associated
with a negative response, or vice versa. This
response-based conflict can be separated from
the familiarity-based conflict, and its resolution appears to rely more on the anterior cingulate (Nelson et al. 2003).
Other mechanisms for interference effects? Despite the early work of Keppel &
Underwood (1962), most studies examining
encoding in STM have focused on RI: how
new information disrupts previous memories.
Early theorists described this disruption in
terms of displacement of entire items from
STM, perhaps by disrupting consolidation
(e.g., Waugh & Norman 1965). However,
rapid serial visual presentation studies sug-
gest that this type of consolidation is complete within a very short time—approximately
500 milliseconds, and in some situations
as short as 50 milliseconds (Vogel et al.
2006).
What about interference effects beyond
this time window? As reviewed above, most
current focus-based models implicitly assume
something like whole-item displacement is at
work, but these models may need to be elaborated to account for retroactive similaritybased interference, such as the phonological interference effects reviewed by Nairne
(2002). The models of Nairne (2002) and
Oberauer (2006) suggest a direction for such
an elaboration. Rather than a competition
at the item level for a single-focus resource,
these models posit a lower-level similaritybased competition for “feature units.” By this
idea, items in STM are represented as bundles
of features (e.g., color, shape, spatial location,
temporal location). Representations of these
features in turn are distributed over multiple units. The more two items overlap, the
more they compete for these feature units,
resulting in greater interference. This proposed mechanism fits well with the idea that
working memory reflects the heightened activation of representations that are distributed
throughout sensory, semantic, and motor cortex (Postle 2006), and that similarity-based interference constrains the capacity due to focusing (see above; Awh et al. 2007). Hence,
rather than whole-item displacement, specific
feature competition may underlie the majority of encoding-stage RI.
Interference-based decay? Above, we proposed a mechanism for decay based on the idea
that stochastic variability causes the neurons
making up a representation to fall out of synchrony (become less coherent in their firing
patterns). Using the terminology of Nairne
(2002) and Oberauer (2006), the feature units
become less tightly bound. Importantly, feature units that are not part of a representation
also show some random activity due to their
own stochastic variability, creating a noise
www.annualreviews.org • The Mind and Brain of Short-Term Memory
211
ARI
1 December 2007
16:37
distribution. Over time, there is an increasing
likelihood that the feature units making up the
to-be-remembered item’s representation will
overlap with those of the noise distribution,
making them increasingly difficult to distinguish. This increasing overlap with the noise
distribution and loss of feature binding could
lead to the smooth forgetting functions often
interpreted as evidence for decay.
Such a mechanism for decay has interesting implications. It may explain why PI effects interact with retention interval. Prior
trials with similar items would structure the
noise distribution so that it is no longer random but rather is biased to share components with the representation of the to-beremembered item (target). Representations of
prior, now-irrelevant items might compete
with the current target’s representation for
control of shared feature units, increasing the
likelihood (rate) at which these units fall out
of synchrony.
Prior similar items may also dampen the
fidelity of the target representation to begin with, weakening their initial binding and
thus causing these items to fall out of synchrony more quickly. In addition, poorly
learned items might have fewer differentiating feature units, and these units may be less
tightly bound and therefore more vulnerable
to falling out of synchrony. This could explain
why Keppel & Underwood (1962) found that
poorly learned items resulted in retentioninterval effects even on the first trial. It may
also underlie the greater decay effects that
McKone (1995, 1998) found for nonwords
than for words, if one assumes that nonwords have fewer meaning-based units and
connections.
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
ANRV331-PS59-08
ples, we offer a hypothetical sketch of the processes and neural structures that are engaged
by a canonical STM task, the probe recognition task with distracting material.
Principles of Short-Term Memory
We have motivated our review by questions
of structure, process, and forgetting. Rather
than organize our summary this way, we wish
to return here to the title of our review
and consider what psychological and neural
mechanisms seem best defended by empirical work. In that we have provided details
about each of these issues in our main discussion, we summarize them here as bullet
points. Taken together, they provide answers
to our questions about structure, process, and
forgetting.
The mind of short-term memory. Representations in memory are composed of bundles of features for stored information, including features representing the context in which
that information was encountered.
212
A SUMMARY OF PRINCIPLES
AND AN ILLUSTRATION OF
SHORT-TERM MEMORY
AT WORK
Here we summarize the principles of STM
that seem best supported by the behavioral
and neural evidence. Building on these princi-
Jonides et al.
Representations in memory vary in activation, with a dormant state characterizing long-term memories, and varying
states of activation due to recent perceptions or retrievals of those representations.
There is a focus of attention in which a
bound collection of information may be
held in a state that makes it immediately
available for cognitive action. Attention
may be focused on only a single chunk
of information at a time, where a chunk
is defined as a set of items that are bound
by a common functional context.
Items may enter the focus of attention via perceptual encoding or via cuebased retrieval from LTM.
Items are maintained in the focus via a
controlled process of maintenance, with
rehearsal being a case of controlled sequential allocation of attentional focus.
Forgetting occurs when items leave the
focus of attention and must compete
ANRV331-PS59-08
ARI
1 December 2007
16:37
with other items to regain the focus
(interference), or when the fidelity of
the representation declines over time
due to stochastic processes (decay).
The brain of short-term memory. Items in
the focus of attention are represented by patterns of heightened, synchronized firing of
neurons in primary and secondary association
cortex.
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
The sensorimotor features of items in
the focus of attention or those in a
heightened state of activation are the
same as those activated by perception
or action. Information within a representation is associated with the cortical region that houses it (e.g., verbal,
spatial, motor). In short, item representations are stored where they are
processed.
Medial temporal structures are important for binding items to their context
for both the short- and long-term and
for retrieving items whose context is no
longer in the focus of attention or not
yet fully consolidated in the neocortex.
The capacity to focus attention is constrained by parietal and frontal mechanisms that modulate processing as well
as by increased noise in the neural patterns arising from similarity-based interference or from stochastic variability
in firing.
Frontal structures support controlled
processes of retrieval and interference
resolution.
Placing an item into the focus of
attention from LTM involves reactivating the representation that is encoded in patterns of neural connection
weights.
Decay arises from the inherent variability of the neural firing of feature bundles
that build a representation: The likelihood that the firing of multiple features
will fall out of synchrony increases with
time due to stochastic variability.
A Sketch of Short-Term Memory
at Work
The theoretical principles outlined above
summarize our knowledge of the psychological and neural bases of STM, but further
insight can be gained by attempting to see
how these mechanisms might work together,
moment-by-moment, to accomplish the demands of simple tasks. We believe that working through an illustration will not only help
to clarify the nature of the proposed mechanisms, but it may also lead to a picture of STM
that is more detailed in its bridging of neural
process and psychological function.
Toward these ends, we present here a specific implementation of the principles that allows us to give a description of the mechanisms that might be engaged at each point
in a simple visual STM task. This exercise
leads us to a view of STM that is heavily
grounded in concepts of neural activation and
plasticity. More specifically, we complement
the assumptions about cognitive and brain
function above with simple hypotheses about
the relative supporting roles of neuronal firing and plasticity (described below). Although
somewhat speculative in nature, this description is consistent with the summary principles,
and it grounds the approach more completely
in a plausible neural model. In particular,
it has the virtue of providing an unbroken
chain of biological mechanisms that supports
the encoding of short-term memories over
time.
Figure 1 traces the representation of one
item in memory over the course of a few
seconds in our hypothetical task. The cognitive events are demarcated at the top of
the figure, and the task events at the bottom. In the hypothetical task, the subject must
keep track of three visual items (such as novel
shapes). The first item is presented for 700
milliseconds, followed by a delay of 2 seconds. The second stimulus then appears, followed by a delay of a few seconds, then the
third stimulus, and another delay. Finally, the
probe appears, and contact must be made with
www.annualreviews.org • The Mind and Brain of Short-Term Memory
213
ARI
1 December 2007
16:37
the memory for the first item. The assumption
is that subjects will engage in a strategy of actively maintaining each item during the delay
periods.
Before walking through the timeline in
Figure 1, let us take a high-level view. At any
given time point, a vertical slice through the
figure is intended to convey two key aspects of
the neural basis of the memory. The first is the
extent to which multiple cortical areas contribute to the representation of the item, as indicated by the colored layers corresponding to
different cortical areas. The dynamic nature of
the relative sizes of the layers captures several
of our theoretical assumptions concerning the
evolving contribution of those different areas
at different functional stages of STM. The
second key aspect is the distinction between
memory supported by a coherent pattern of
active neural firing (captured in solid layers)
and memory supported by synaptic plasticity
(captured in the hashed layers) (Fuster 2003,
Grossberg 2003, Rolls 2000). The simple hypothesis represented here is that perceptual
encoding and active-focus maintenance are
supported by neuronal firing, and memory of
items outside the focus is supported by shortterm synaptic plasticity (Zucker & Regehr
2002).3
We now follow the time course of the neural representation of the first item (in the order indicated by the numbers in the figure). (1)
The stimulus is presented and rapidly triggers
a coherent pattern of activity in posterior perceptual regions, representing both low-level
visual features of the item content and its abstract identification in higher-level regions.
(2) There is also a rapid onset of the representation of item-context binding (temporal con-
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
ANRV331-PS59-08
3
The alternative to this strong claim is that memory items
outside the focus might also be supported by residual active firing. The empirical results reviewed above indicating load-dependent posterior activation might lend support to this alternative if one assumes that the memory
load in those experiments was not entirely held in the focus,
and that these activations exclusively index firing associated
with the memory load itself.
214
Jonides et al.
text in our example) supported by the medialtemporal lobes (see section titled “Contesting
the Idea of Separate Long-Term and ShortTerm Systems”) (Ranganath & Blumenfeld
2005). (3) Over the first few hundred milliseconds, this pattern increases in quality, yielding
speed-accuracy tradeoffs in perceptual identification. (4) Concurrent with the active firing driven by the stimulus, very short-term
synaptic plasticity across cortical areas begins
to encode the item’s features and its binding to
context. Zucker & Regehr (2002) identify at
least three distinct plasticity mechanisms that
begin to operate on this time scale (tens of
milliseconds) and that together are sufficient
to produce memories lasting several seconds.
(For the use of this mechanism in a prominent
neural network model of STM, see Burgess &
Hitch 1999, 2005, 2006.) (5) At the offset of
the stimulus, the active firing pattern decays
very rapidly (consistent with identified mechanisms of rapid decay in short-term potentiation; Zucker & Regehr 2002), but (6) active
maintenance, mediated by increased activity
in frontal and parietal systems, maintains the
firing pattern during the delay period (see
sections titled “The Architecture of UnitaryStore Models” and “Maintenance of Items
in the Focus”) (Pasternak & Greenlee 2005,
Ranganath 2006, Ruchkin et al. 2003). This
active delay firing includes sustained contribution of MTL to item-context binding (see
section titled “Contesting the Idea of Separate Long-Term and Short-Term Systems”).
Significant reduction in coherence of the firing pattern may occur as a result of stochastic drift as outlined above (in sections titled
“What Happens Neurally During the Delay?”
and “Interference-Based Decay?”), possibly
leading to a kind of short-term decay during
maintenance (see section titled “What Happens Neurally During the Delay?”) (Fuster
1995, Pasternak & Greenlee 2005). (7) The
active maintenance involves the reuse of posterior perceptual regions in the service of the
task demands on STM. This reuse includes
even early perceptual areas, but we show
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
ANRV331-PS59-08
ARI
1 December 2007
16:37
here a drop in the contribution of primary
perceptual regions to maintenance in order to
indicate a relatively greater effect of top-down
control on the later high-level regions (Postle
2006, Ranganath 2006). (8) During this delay
period of active maintenance, short-term potentiation continues to lay down a trace of the
item and its binding to context via connection weights both within and across cortical
regions. The overall efficacy of this memory
encoding is the result of the interaction of the
possibly decaying active firing pattern with
the multiple plasticity mechanisms and their
individual facilitation and depression profiles
(Zucker & Regehr 2002).
(9) At the end of the delay period and the
onset of the second stimulus, the focus rapidly
shifts to the new stimulus, and the active firing of the neural pattern of the target stimulus
ceases. (10) The memory of the item is now
carried completely by the changed synaptic
weights, but this change is partially disrupted
by the incoming item and its engagement of a
similar set of neural activity patterns. Cognitively, this disruption yields similarity-based
retroactive interference (see “Other Mechanisms for Interference Effects?”) (Nairne
2002). (11) Even in the absence of interference, a variety of biochemical processes give
rise to the decay of short-term neural change
and therefore the gradual loss of the memory trace over time. This pattern of interference and decay continues during processing
of both the second and third stimulus. The
probe triggers a rapid memory retrieval of the
target item (12), mediated in part by strategic
frontal control (see “Neural Mechanisms of
Short- and Long-Term Memory Retrieval”)
(Cabeza et al. 2002, Ranganath et al. 2004).
This rapid retrieval corresponds to the reinstantiation of the target item’s firing pattern
in both posterior perceptual areas (13) and
medial-temporal regions, the latter supporting the contextual binding. A plausible neural mechanism for the recovery of this activity
pattern at retrieval is the emergent patterncompletion property of attractor networks
(Hopfield 1982). Attractor networks depend
on memories encoded in a pattern of connection weights, whose formation and dynamics
we have sketched above in terms of shortterm synaptic plasticity. Such networks also
naturally give rise to the kind of similaritybased proactive interference clearly evident in
STM retrieval (see “Selection-Based Interference Effects”) ( Jonides & Nee 2006, Keppel
& Underwood 1962).
We have intentionally left underspecified
a precise quantitative interpretation of the
y-axis in Figure 1. Psychologically, it perhaps
corresponds to a combination of availability
(largely driven by the dichotomous nature
of the focus state) and accessibility (driven
by a combination of both firing and plasticity). Neurally, it perhaps corresponds to
some measure of both firing amplitude and
coherence and potential firing amplitude and
coherence.
We are clearly a long way from generating something like the plot in Figure 1 from
neuroimaging data on actual tasks—though
plots of event-related potentials in STM tasks
give us an idea of what these data may look
like (Ruchkin et al. 2003). There no doubt
is more missing from Figure 1 than is included (e.g., the role of subcortical structures
such as the basal ganglia in the frontal/parietal
mediated control, or the reciprocal corticalthalamic circuits that shape the nature of the
neocortical patterns). We nevertheless believe
that the time course sketched in Figure 1 is
useful for making clear many of the central
properties that characterize the psychological
and neural theory of human STM outlined
above: (a) STM engages essentially all cortical
areas—including medial temporal lobes—and
does so from the earliest moments, though
it engages these areas differentially at different functional stages. (b) STM reuses the
same posterior cortical areas and representations that subserve perception, and active
maintenance of these representations depends
on these posterior areas receiving input from
frontal-parietal circuits. (c) Focused items are
www.annualreviews.org • The Mind and Brain of Short-Term Memory
215
ANRV331-PS59-08
ARI
1 December 2007
16:37
distinguished both functionally and neurally
by active firing patterns, and nonfocused
memories depend on synaptic potentiation
and thereby suffer from decay and retroactive interference. (d ) Nonfocused memories
are reinstantiated into active firing states via
an associative retrieval process subject to
proactive interference from similarly encoded
patterns.
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
Postscript: Revisiting Complex
Cognition
A major goal of this review has been to bring
together psychological theorizing (the mind)
and neuroscientific evidence (the brain) of
STM. However, any celebration of this union
is premature until we address this question:
Can our account explain how the mind and
brain accomplish the everyday tasks (e.g.,
completing a tax form) that opened this review? The recognition probe task used in our
example and the other procedures discussed
throughout the main text are considerably
simpler than those everyday tasks. Is it plausible to believe that the system outlined here,
particularly in light of its severely limited capacity, could support human cognition in the
wild?
It is sobering to note that Broadbent (1993)
and Newell (1973, 1990) asked this question
nearly two decades ago, and at that time they
were considering models of STM with even
larger capacities than the one advocated here.
Even so, both observed that none of the extant computational models of complex cognitive tasks (e.g., the Newell & Simon 1972
models of problem solving) used contemporary psychological theories of STM. Instead,
the complex-cognition models assumed much
larger (in some cases, effectively unlimited)
working memories. The functional viability of
the STM theories of that time was thus never
clearly demonstrated. Since then, estimates of
STM capacity have only grown smaller, so
the question, it would seem, has grown correspondingly more pressing.
216
Jonides et al.
Fortunately, cognitive modeling and cognitive theory have also developed over that
time, and in ways that would have pleased both
Broadbent and Newell. Importantly, many
computational cognitive architectures now
make assumptions about STM capacity that
are congruent with the STM models discussed
in this review. The most prominent example
is ACT-R, a descendent of the early Newell
production-system models. ACT-R continues to serve as the basis of computational
models of problem solving (e.g., Anderson &
Douglass 2001), sentence processing (Lewis
& Vasishth 2005, Lewis et al. 2006), and complex interactive tasks (Anderson et al. 2004).
However, the current version of ACT-R has
a focus-based structure with an effective capacity limit of four or fewer items (Anderson
et al. 2004).
Another important theoretical development is the long-term working memory approach of Ericsson & Kintsch (1995). This
approach describes how LTM, using the kind
of fast-encoding and cue-based associative retrieval processes assumed here, can support
a variety of complex cognitive tasks ranging from discourse comprehension to specialized expert performance. In both the modern approaches to computational architecture and long-term working memory, the
power of cognition resides not in capacious
short-term buffers but rather in the effective use of an associative LTM. A sharply
limited focus of attention does not, after
all, seem to pose insurmountable functional
problems.
In summary, this review describes the stilldeveloping convergence of computational
models of complex cognition, neural network
models of simple memory tasks, modern psychological studies of STM, and neural studies
of memory in both humans and primates. The
points of contact among these different methods of studying STM have multiplied over the
past several years. As we have pointed out, significant and exciting challenges in furthering
this integration lie ahead.
ANRV331-PS59-08
ARI
1 December 2007
16:37
Annu. Rev. Psychol. 2008.59:193-224. Downloaded from www.annualreviews.org
by WAKE FOREST UNIVERSITY on 09/05/11. For personal use only.
LITERATURE CITED
Altmann EM, Gray WD. 2002. Forgetting to remember: the functional relationship of decay
and interference. Psychol. Sci. 13(1):27–33
Anderson JR. 1983. Retrieval of information from long-term memory. Science 220(4592):25–30
Anderson JR, Bothell D, Byrne MD, Douglass S, Lebiere C, Qin Y. 2004. An integrated theory
of mind. Psychol. Rev. 111:1036–60
Anderson JR, Douglass S. 2001. Tower of Hanoi: evidence for the cost of goal retrieval. J. Exp.
Psychol.: Learn. Mem. Cogn. 27:1331–46
Anderson JR, Matessa M. 1997. A production system theory of serial memory. Psychol. Rev.
104(4):728–48
Anderson JR, Schooler LJ. 1991. Reflections of the environment in memory. Psychol. Sci.
2(6):396–408
Atkinson RC, Shiffrin RM. 1971. The control of short-term memory. Sci. Am. 224:82–90
Awh E, Barton B, Vogel EK. 2007. Visual working memory represents a fixed number of items
regardless of complexity. Psychol. Sci. 18(7):622–28
Awh E, Jonides J. 2001. Overlapping mechanisms of attention and spatial working memory.
Trends Cogn. Sci. 5(3):119–26
Awh E, Jonides J, Reuter-Lorenz PA. 1998. Rehearsal in spatial working memory. J. Exp.
Psychol.: Hum. Percept. Perform. 24:780–90
Awh E, Jonides J, Smith EE, Buxton RB, Frank LR, et al. 1999. Rehearsal in spatial working
memory: evidence from neuroimaging. Psychol. Sci. 10(5):433–37
Awh E, Jonides J, Smith EE, Schumacher EH, Koeppe RA, Katz S. 1996. Dissociation of storage
and rehearsal in verbal working memory: evidence from PET. Psychol. Sci. 7:25–31
Baddeley AD. 1986. Working Memory. Oxford: Claren...
Purchase answer to see full
attachment