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Short-Term Memory and Long-Term Memory are Still Different

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A commonly expressed view is that short-term memory (STM) is nothing more than activated long-term memory. If true, this would overturn a central tenet of cognitive psychology-the idea that there are functionally and neurobiologically distinct short- and long-term stores. Here I present an updated case for a separation between short- and long-term stores, focusing on the computational demands placed on any STM system. STM must support memory for previously unencountered information, the storage of multiple tokens of the same type, and variable binding. None of these can be achieved simply by activating long-term memory. For example, even a simple sequence of digits such as "1, 3, 1" where there are 2 tokens of the digit "1" cannot be stored in the correct order simply by activating the representations of the digits "1" and "3" in LTM. I also review recent neuroimaging data that has been presented as evidence that STM is activated LTM and show that these data are exactly what one would expect to see based on a conventional 2-store view. (PsycINFO Database Record
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Short-Term Memory and Long-Term Memory are Still Different
Dennis Norris
MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom
A commonly expressed view is that short-term memory (STM) is nothing more than activated long-term
memory. If true, this would overturn a central tenet of cognitive psychology—the idea that there are
functionally and neurobiologically distinct short- and long-term stores. Here I present an updated case for
a separation between short- and long-term stores, focusing on the computational demands placed on any
STM system. STM must support memory for previously unencountered information, the storage of
multiple tokens of the same type, and variable binding. None of these can be achieved simply by
activating long-term memory. For example, even a simple sequence of digits such as “1, 3, 1” where there
are 2 tokens of the digit “1” cannot be stored in the correct order simply by activating the representations
of the digits “1” and “3” in LTM. I also review recent neuroimaging data that has been presented as
evidence that STM is activated LTM and show that these data are exactly what one would expect to see
based on a conventional 2-store view.
Keywords: long-term memory, memory, STM, working memory
For more than a century most psychologists have accepted that
there are distinct memory systems responsible for long and short-
term storage. Originally based entirely on introspection (e.g.,
James, 1890), the idea that there are separate long- and short-term
memory (LTM and STM, respectively) systems subsequently be-
came a core assumption of modern cognitive psychology. From the
1960s most cognitive models of memory have assumed that there
are separate stores (Atkinson & Shiffrin, 1968;Baddeley, 1986;
Baddeley & Hitch, 1974;Brown, Preece, & Hulme, 2000;Burgess
& Hitch, 1992,2006;Lewandowsky & Farrell, 2000;Page &
Norris, 1998a,1998b,2009;Waugh & Norman, 1965). This re-
mains the framework guiding almost all cognitive work on verbal
STM.
There are dissenting voices. A number of authors have argued
that the behavioral data are more parsimoniously accounted for by
assuming that there is only a single memory system responsible for
both short- and long-term storage (Brown, Neath, & Chater, 2007;
Cowan, 1988,1999;Crowder, 1993;Crowder & Neath, 1991;
Engle, Kane, & Tuholski, 1999;Gruneberg, 1970;Jonides et al.,
2008;McElree, 2006;Melton, 1963;Nairne, 2002;Poirier &
Saint-Aubin, 1996;Surprenant & Neath, 2009). Some have argued
that STM is nothing more than activated LTM (Cowan, 1988,
1999;Oberauer, 2002,2009). This conception of the relation
between STM and LTM has become increasingly popular in neu-
roimaging research (Acheson, Hamidi, Binder, & Postle, 2011;
Cameron, Haarmann, Grafman, & Ruchkin, 2005;D’Esposito &
Postle, 2015;Jonides et al., 2008;LaRocque et al., 2015;Postle,
2006;Ranganath & Blumenfeld, 2005;Ruchkin, Grafman, Cam-
eron, & Berndt, 2003). However, there have been no attempts to
present an updated case for a multicomponent view of memory in
which there is a clear theoretical and conceptual distinction be-
tween LTM and short-term stores. Most of the papers cited above
have taken a data-driven approach to the debate, in which involves
cataloguing similarities between LTM and STM. Here I take a very
different approach and consider the computational requirements of
a system that could support retention of information over the short
term. These impose strong constraints on the architectural rela-
tionship between LTM and STM. The overall conclusion will be
that, although LTM has an essential role to play, STM cannot be
supported simply by activating LTM. Even simple tasks such as
remembering a sequence of digits can only be performed by
supplementing LTM with some additional mechanism. This addi-
tional mechanism is not part of LTM, but has all of the properties
typically ascribed to a separate short-term store. Although I will
focus primarily on verbal STM, the underlying logic of the argu-
ments applies equally well to STM in other domains. This article
begins with a brief review of the core data supporting a distinction
between long- and short-term stores. This is followed by an anal-
ysis of cognitive theories that have proposed that STM is activated
LTM. The concern here will be to establish exactly what the
substantive claims of such theories are. I then review the neuro-
imaging data that have been presented as support for the activation
view. In the second half of the paper I focus on computational
considerations that argue strongly against the idea that STM might
be nothing more than activated LTM. The central problem for
activation-based models is that STM has to be able to store
arbitrary configurations of novel information. For example, we can
remember novel sequences of words or dots in random positions
on a screen. These cannot possibly have preexisting representa-
tions in LTM that could be activated. The digit sequence 133646
This article was published Online First May 22, 2017.
This article has been published under the terms of the Creative Com-
mons Attribution License (http://creativecommons.org/licenses/by/3.0/),
which permits unrestricted use, distribution, and reproduction in any me-
dium, provided the original author and source are credited. Copyright for
this article is retained by the author(s). Author(s) grant(s) the American
Psychological Association the exclusive right to publish the article and
identify itself as the original publisher.
Correspondence concerning this article should be addressed to Dennis
Norris, MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, Cam-
bridge CB2 2EF, U.K. E-mail: dennis.norris@mrc-cbu.cam.ac.uk
Psychological Bulletin © 2017 The Author(s)
2017, Vol. 143, No. 9, 992–1009 0033-2909/17/$12.00 http://dx.doi.org/10.1037/bul0000108
992
might activate LTM representations of the digits 1, 3, 6 and 4, but
some extra mechanism is required to encode the order of the digits
and the fact that there are two tokens of the digits 3 and 6.
Activating the LTM representations of 1, 3, 6 and 4 is not enough.
STM can also store more complex structural representations to
encode novel objects and the relation between them. Any viable
model of STM must therefore be endowed with additional pro-
cesses beyond simple activation of LTM. At the very least there
must be a mechanism capable of storing multiple tokens, recalling
those tokens in the correct order, and creating novel structured
representations that cannot yet be in LTM.
I will also ask what it is that we actually store in STM. Does
STM contain copies of representations or pointers to representa-
tions? If STM contains pointers, do those pointers address LTM, or
might those pointers address representations held within the short-
term storage system itself? I suggest that, at some level, STM must
make use of pointers, but that there are strong computational
advantages to having pointers operate within the bounds of a
modality-specific STS such as the phonological store component
of Baddeley and Hitch’s (1974) Working Memory model. That is,
consideration of how a pointer-based system might work provides
further support for the idea that there must be a functional distinc-
tion between short- and long-term stores.
Overview
The idea that STM is merely activated LTM is usually pitted
against the classic idea that STM consists of a buffer (or buffers)
that holds copies of the items in memory. This view of memory is
implicit in Atkinson and Shiffrin’s (1966,1968,1971) modal
model. Their, 1971 paper begins: “Memory has two components:
short-term and long-term” (p. 3). The Atkinson and Shiffrin model
is shown in Figure 1A.Figure 1B shows what is probably the most
influential multistore model—the Working Memory model of
Baddeley and Hitch (Baddeley, 2000;Baddeley & Hitch, 1974). I
will present a very brief summary of the findings that have been
taken as evidence for a separation between a long-term store (LTS)
and a short-term store (STS). The primary data come from studies
of STM patients. These patients typically have grossly impaired
verbal STM capacity of perhaps 2–4 items, combined with rela-
tively intact LTM (Basso, Spinnler, Vallar, & Zanobio, 1982;
Saffran & Marin, 1975;Shallice & Vallar, 1990;Shallice &
Warrington, 1970;Vallar & Baddeley, 1984;Vallar, Di Betta, &
Silveri, 1997;Vallar & Papagno, 1995;Vallar, Papagno, & Bad-
deley, 1991;Warrington, Logue, & Pratt, 1971;Warrington &
Shallice, 1969). Where it has been examined, these patients gen-
erally have few problems with visuospatial STM tasks. The oppo-
site pattern has also been observed. Hanley, Young, and Pearson
(1991) reported a patient with impaired visuospatial STM but
normal verbal STM. One source of evidence that STM patients
have intact LTM is that, in general, these patients have little
difficulty in learning new associations between familiar stimuli.
However, they do have problems in learning new words (Badde-
ley, Papagno, & Vallar, 1988;Basso et al., 1982;Bormann, Sey-
both, Umarova, & Weiller, 2015;Dittmann & Abel, 2010;Freed-
man & Martin, 2001;Trojano & Grossi, 1995;Trojano, Stanzione,
& Grossi, 1992). The standard interpretation of this finding is that
the complete phonological representation of new words must be
held in a short-term store in order to be encoded into LTM. Indeed,
one of the central functions of STM is assumed to be to hold
representations that do not yet exist in LTM (Baddeley, Gather-
cole, & Papagno, 1998). Importantly, the constituent parts of these
representations (perhaps features, phonemes or syllables) must be
stored in the correct order. Not surprisingly, these patients also
have problems in learning the order of new digit sequences (Bor-
mann et al.). The same logic applies; the sequence must be held in
STM so that a representation of the sequence can be presented to
LTM.
Conversely, there are patients with medial-temporal lobe dam-
age who have impaired LTM but relatively preserved STM (Bad-
deley & Warrington, 1970;Cave & Squire, 1992;Drachman &
Arbit, 1966;Scoville & Milner, 1957;Wilson & Baddeley, 1988).
Ranganath and Blumenfeld (2005) expressed concerns over
whether the patient data really do provide clear evidence for
distinct stores. They drew attention to the fact that LTM patients
with medial temporal lobe damage have difficulties with some
STM tasks, and suggest that this “questions whether theories of
memory need to propose neurally distinct stores for short- and
long-term retention” (p. 374). However, in a later review of the
literature, Jeneson and Squire (2012) pointed out that the impair-
ment of LTM patients in STM tasks is only observed with supras-
pan stimuli that exceed the capacity of STM. Under these circum-
stances even neurologically normal individuals will necessarily
have to rely on a combination of STM and LTM, so it should be
no surprise that LTM patients have problems. Furthermore, the
finding that LTM patients are sometimes impaired in STM tasks is
fully consistent with the two-store view; short-term recall can
clearly benefit from a contribution from LTM, even if the two are
functionally separate. For example, according to redintegration
accounts (Gathercole, Pickering, Hall, & Peaker, 2001;Hulme et
al., 1997;Lewandowsky & Farrell, 2000;Saint-Aubin & Poirier,
1999a;Schweickert, 1993;Schweickert, Chen, & Poirier, 1999),
information in LTM can be used to reconstruct degraded traces in
an STS at recall. Thus, even though LTM may play no role in the
maintenance of information in STS, it can potentially improve
performance in STM tasks by aiding retrieval.
The most powerful behavioral evidence for a form of distinct
short-term storage comes from the early work of Baddeley and
colleagues (Baddeley, 1966a,1966b;Baddeley & Ecob, 1970),
which led to the development of the concept of a phonological
store. The phonological store is assumed to hold speech-based
representations and to have duration of just a few seconds. Infor-
mation within the store can be refreshed by an articulatory control
process (rehearsal) so as to prevent decay, and that same process
can be used to recode visual information into a phonological form
(Baddeley, Lewis, & Vallar, 1984). Together these for the phono-
logical loop component of the Working Memory model (Figure
1B).
The critical evidence for a phonological store with a limited
duration is that while memory confusions at short retention inter-
vals are primarily phonological in nature, confusions at longer
retention intervals tend to be semantic. In immediate serial recall,
phonological similarity impairs order recall and can even improve
item recall (Fallon, Groves, & Tehan, 1999) but semantic similar-
ity has no impact on order recall (Saint-Aubin & Poirier, 1999b;
Saint-Aubin & Poirier, 2000). Furthermore, when the items to be
remembered are presented visually as opposed to auditorily, the
phonological confusions can be eliminated if participants are re-
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SHORT-TERM MEMORY AND LONG-TERM MEMORY
quired to perform articulatory suppression during presentation
(Baddeley et al., 1984;Murray, 1968;Peterson & Johnson, 1971).
Articulatory suppression is assumed to occupy the articulatory
control process and prevent it from being able to recode the visual
input into a phonological form.
These findings provided the motivation for separate phonolog-
ical and visual short-term stores in Baddeley and Hitch’s (1974)
Working Memory (WM) model. More recently Baddeley (2000)
has expanded the working memory framework to include a com-
ponent called the episodic buffer (Figure 1B). The episodic buffer
is responsible for temporary storage beyond the capacity of the
model’s short-term storage systems, and for binding representa-
tions across different modalities. One line of evidence supporting
the need to add yet another memory system comes from studies of
prose recall. For example, the STM patient PV had an auditory
word span of one but could remember up to five words when they
formed a meaningful sentence (Vallar & Baddeley, 1984).
The strongest evidence for a separate STS does not require
carefully controlled laboratory experiments at all. The mere fact
that we can repeat nonsense words like ‘blontestaping’ that we
have never heard before shows that memory cannot be based
simply on activating preexisting representations in LTM. Although
there may well be preexisting representations of phonemes, fea-
tures or syllables, these are not sufficient to construct a mnemonic
trace of a previously unencountered nonsense word.
Short-Term Memory and Working Memory
The terms STM and working memory (WM) are often used
interchangeably, and also inconsistently. In this article the primary
focus is on whether there are distinct short- and long-term stores.
Working memory is usually thought of as a much broader concept,
often encompassing processing as well as storage. For example,
both the Baddeley and Hitch (1974) and the Cowan (1988) WM
models include a central executive component which can operate
on the contents of STM (see figure). In the Baddeley and Hitch
model, modality-specific short-term stores form part of the overall
WM system. The distinguishing feature of WM is that it provides
a ‘mental workspace’ (Logie, 2003) that can hold information in a
temporary form that can be manipulated and updated. Although
there are different views on exactly what constitutes WM (for
review see: Aben, Stapert, & Blokland, 2012), the common feature
of these views is that rather than being simply a passive store, WM
is a system that allows information to be actively manipulated. For
example, in the context of visual Luck and Vogel (2013) defined
WM “as the active maintenance of visual information to serve the
needs of ongoing tasks” (p. 392). Baddeley (1992) described WM
as a “system that provides temporary storage and manipulation of
the information necessary for such complex cognitive tasks as
language comprehension, learning, and reasoning.” (p. 556).
Although this distinction between passive stores and an active
mental workspace is widely observed, some authors also use the
broader term WM when describing studies that involve only pas-
sive storage. This is particularly so in the case of work on visual
STM. In contrast, Nee and Jonides (2013) use the term STM to
refer to all memory over the short term, whether active or passive.
This includes the ‘activated LTM’ component of Oberauer’s
(2002,2009) three-state model. One would more commonly ex-
pect this broader conception to be referred to as WM. Ericsson and
Kintsch (1995) add further complexity by proposing that there is a
form of long-term WM. Although these terminological inconsis-
tencies can lead to confusion, our concern here is with the nature
of the storage mechanisms themselves rather than the higher level
cognitive processes that might operate of the contents of such
stores. Nevertheless, it is worth pointing out that WM tasks like
reasoning or language comprehension will necessarily recruit
wide-ranging neural and cognitive processes that will simultane-
ously engage both short- and long-term storage systems.
Interactions Between STM and LTM
Although multistore models have distinct short- and long-term
stores, this does not imply that there are distinct short- and long-
term tasks that tap exclusively into short- or only long-term mem-
ory. Atkinson and Shiffrin (1968) wrote that “According to our
general theory, both STS and LTS are active in both STS and LTS
experiments” (p. 101). There is no particular point in time that
would mark a transition between tasks that only involve an STS
and those that involve only an LTS. Even under the view that there
are separate short and long-term storage systems, the two systems
should operate in concert. Interactions between LTM and STM
have already been mentioned in the context of patients with
deficits in STM or LTM. Long-term learning of novel words or
digit sequences depends on STM, and performance in STM tasks
is influenced by information in LTM. For example, although STM
is predominantly phonological, performance in STM tasks is nev-
ertheless influenced by lexical or semantic factors, or by other
information stored in LTM. For example, words are recalled better
than nonwords (Brener, 1940;Hulme, Maughan, & Brown, 1991),
high-frequency words are recalled better than low-frequency
words (Gregg, Freedman, & Smith, 1989;Hulme et al., 1997;
Watkins & Watkins, 1977), concrete words are recalled better than
abstract words (Bourassa & Besner, 1994;Walker & Hulme,
1999), sentences are recalled better than random word lists
(Brener, 1940), sequences of letters are recalled better when they
have a closer approximation to the statistics of English (Baddeley,
1964), and lists constructed from familiar sequences are recalled
better than lists composed of unfamiliar sequences (Botvinick,
2005;Botvinick & Bylsma, 2005;Mathy & Feldman, 2012).
Some have interpreted this as evidence for a version of the
activation view in which STM depends on activation in LTM
language networks (Acheson, MacDonald, & Postle, 2011;Poirier,
Saint-Aubin, Mair, Tehan, & Tolan, 2015). An alternative view is
that although there is a separate STS, long-term semantic memory
is activated in STM tasks, and the sustained semantic activation is
fed back to STM to aid retention (Acheson, MacDonald, et al.,
2011;Huttenlocher & Newcombe, 1976;Jefferies, Frankish, &
Lambon Ralph, 2006a,2006b;Jefferies, Frankish, & Noble, 2009;
Patterson, Graham, & Hodges, 1994;Poirier et al., 2015;Savill,
Metcalfe, Ellis, & Jefferies, 2015;Stuart & Hulme, 2000). This is
sometimes referred to as semantic binding. Both of these possibil-
ities run into exactly the same problems as the view that STM is
activated LTM. Although almost all of the data comes from serial
recall tasks, there is no indication of how simply activating se-
mantic memory could code serial order.
The alternative view is that any benefit conferred by LTM
occurs only at recall and operates by means of the kind of redin-
tegration process described earlier (Schweickert, 1993). Redinte-
994 NORRIS
gration is most commonly thought of as operating at the level of
individual items. For example, a degraded mnemonic trace might
be more likely to be reconstructed as a high-frequency word than
as a low frequency word. Consistent with this view, factors such as
lexicality, word frequency, and semantic information affect recall
of item information but not order information (e.g., Poirier &
Saint-Aubin, 1996;Saint-Aubin & Poirier, 1999b). However,
Acheson, MacDonald, et al. (2011) reported a semantic effect on
order recall. They combined a serial recall task with a secondary
task requiring participants to make either semantic or orientation
judgments about pictures. The semantic tasks led to more order
errors than the orientation task, and produced more errors for word
list than for nonword lists. They concluded that the semantic task
interfered with the temporary activation of semantic representa-
tions within the language production architecture that could sup-
port STM. According to this view, nonwords would be unaffected
by the nature of the secondary task as they have no semantic
representations. Acheson et al. acknowledge that it may well be
possible to explain their results in terms of redintegration, but they
suggest that redintegration should operate at the item level and not
benefit memory for order. However, the Bayesian framework
presented by Botvinick (2005) was specifically designed to explain
how information in LTM could help recover order information. In
this framework, any information available from LTM, whether
general LTM or a specifically linguistic memory, could potentially
influence retrieval of both item and order information. Therefore it
is still possible that their results could be explained by redintegra-
tion. From a psycholinguistic perspective, it would seem that
listeners must necessarily form an integrated memory representa-
tion that combines phonological, syntactic and semantic informa-
tion, although establishing exactly how those representations are
stored and interact with each other remains a challenge.
A further form of interaction between LTM and STM happens
at encoding. In the Baddeley and Hitch working memory frame-
work, visually presented words must be recoded into a phonolog-
ical form in order to be stored in the phonological store, and this
recoding process must involve contact with representations in
LTM to generate the necessary phonology. As least in the case of
verbal STM, maintenance of information is helped by rehearsal
which involves recycling information in STS. At each phase in the
recycling process there is an opportunity for LTM to be involved
in the reconstruction of degraded traces in STS. Furthermore, if
items that are being rehearsed are thought of as being in the focus
of attention, they must inevitably make contact with the same LTM
representations that would be involved in the perception of those
items.
Finally, long-term learning is not restricted to situations where
there is an explicit intention to learn. Implicit learning occurs even
in tasks which ostensibly only require STM. Long-term learning,
and hence, access to LTM, must take place continuously if we are
to be able to learn about the relationships between events occurring
too far apart to be held within STM. For example, in the classic
Hebb (Hebb, 1961) learning paradigm, performance in serial recall
of lists of verbal material improves over successive repetitions.
The implication of this is that LTM must be continuously engaged
even in what might appear to be ‘pure’ STM tasks, so that some
long-term learning can take place on the very first encounter with
a list. If it did not, then every occurrence of the list would
effectively be treated in exactly the same way as the first encounter
and learning could never begin.
Taking these factors together, it is very difficult to imagine any
set of circumstances in which LTM will not be involved to some
degree in what might seem to be a pure STM task. As we will see
below, the fact that LTM cannot simply be ‘turned off’ in STM
experiments has implications for the interpretation of neuroimag-
ing studies that have been presented as evidence against multistore
models.
As STM and LTM have to perform similar functions, they are
likely to share similar features. In particular, both involve basic
processes such as encoding, retention, and recall. Both are subject
loss of information through decay or interference, and both will be
impaired when items to be remembered are similar. Brown, Neath,
and Chater’s (2007) SIMPLE (scale invariant memory, perception
and learning) model emphasizes these shared properties. Their
model illustrates how a general principle of scale-independent
similarity can be applied to simulate a range of key empirical
findings in both STM and LTM without the need to make any
distinction between STS and LTS. However, by focusing on the
commonalities their model is unable to account for critical data
such as the neuropsychological dissociations seen in STM patients
or the change in the representational basis between STM and LTM.
The success of the model is attributable to the fact that it embodies
broad principles that apply to memory and perception quite gen-
erally. If these principles are indeed general they would be ex-
pected to apply equally well to separate short- and long-term
stores. There is no contradiction between general principles and
separate stores.
Cognitive models of STM as activated LTM. Atkinson and
Shiffrin’s, 1971 paper is considered to be the classic statement of
a two-store model. Figure 1A, based on the first figure in their
paper, represents STS and LTS as separate boxes. Despite this they
also say that “One might consider the short-term store simply as
being temporary activation of some portion of the long-term store”
(p. 83). More directly, Shiffrin (1975) wrote that “STS is the
activated subset of LTS” (p. 214). Similarly, Norman (1968) talks
about primary and secondary storage but also states that they “are
different aspects of one large storage system” (p. 535). However,
the theoretical force of these statements is unclear. Nothing seems
to rest on this assumption and there is no discussion of its moti-
vation or theoretical implications. This idea was developed further
by Cowan (1988) who is regularly cited as supporting the idea that
STM is activated LTM. Cowan stated quite clearly that “short-term
storage should be viewed as an activated subset of long-term
memory” (Cowan, 1988, p. 185), where short-term storage in-
cludes both the phonological store, and the visuospatial sketch pad.
Additionally, in his model, a subset of activated LTM corresponds
to the focus of attention (Figure 1C). However, on closer reading,
much of what Cowan says has close parallels with the Baddeley
and Hitch multistore model.
In later writings, Cowan and Chen (2008) state that “We thus
propose that although the mechanisms of short-term memory are
separate from those of long-term memory, they are closely related”
(p. 104). They also acknowledge that “A phonologically based
storage and rehearsal mechanism, such as the phonological loop
mechanism of Baddeley (1986), may come into play primarily
when items have to be recalled in the correct serial order” (p. 94)
and “The phonological storage mechanism may be another in-
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SHORT-TERM MEMORY AND LONG-TERM MEMORY
stance of the use of the focus of attention to assemble a new
structure in long-term memory” (p. 95). Cowan and Chen also
appreciate that some extra mechanism is required to store novel
information, such as serial order, that may not already be repre-
sented in LTM. In common with the WM model, Cowan’s model
has a central executive which, among other things, is involved in
“the maintenance of information in short-term memory through
various types of rehearsal” (Cowan, 1988, p. 171). Cowan (2008)
wrote that Baddeley’s (2000) episodic buffer is possibly the same
as the information saved in Cowan’s focus of attention, or at least
is a closely similar concept.” At the very least then, Cowan’s
model has the following components: LTM, an episodic buffer, a
phonological store, and a rehearsal process controlled by a central
executive. These would seem to correspond very closely to the
components of Baddeley and Hitch’s (1974) multistore WM
model. Given that not all short-term storage in Cowan’s model is
supported solely by activated LTM, the crucial question then is
what is the remaining force of the claim that STM is activated
LTM? Is there any part of the process of retaining information over
the short-term that can be served simply by activating LTM? One
factor that makes it hard to answer this question is the absence of
a computational specification of what it means for LTM to be
activated, and of how that activation then supports memory. As
Cowan’s position has evolved to accommodate a broader range of
behavioral data, it has had to respect the fact that very little of that
data can be explained purely in terms of activation. His theoretical
position no longer equates STM directly with activated LTM.
Oberauer (2002,2009) has proposed a three-state model which
also gives a central role to activated LTM (Figure 1D). He makes
an additional distinction between activated LTM and a direct
access region. A similar three-state model has been proposed by
Nee and Jonides (2013). Oberauer views LTM as an associative
network in which related items can automatically activate each
other. A subset of those activated items corresponds to a region of
Figure 1. (A) Atkinson and Shiffrin’s (1971) model of STM. (B) Baddeley and Hitch’s working memory
model (Baddeley, 2000). (C) Cowan’s (1988) model of memory and attention. (D) Oberauer’s (2002) model of
working memory. Nodes and lines correspond to long-term memory representations. Black nodes are activated.
Nodes within the large oval are in the direct access region. One node is in the focus of attention.
996 NORRIS
direct access, and items in the direct access region can be accessed
immediately. Within the direct access region a smaller set of items
is in the focus of attention. It is not clear whether the direct access
region should be assumed to be a region of LTM. I will return to
this question later.
Is there neuroimaging evidence for STM as activated LTM?
Historically, much of the debate as to whether there are separate
long- and short-term stores has focused on whether various ma-
nipulations have different effects on long-term and short-term
retention. For example, are there differences in the form of the
serial position curve observed over different retention intervals?
Wickelgren (1973) reviewed the behavioral data available in the
early 1970s and argued that although the evidence favored the
two-store account “the vast majority of all the cited evidence is
worthless for making the distinction between short and long
traces” (p. 426). Very little has changed since then. But might
neuroimaging data be able to provide insights beyond those that
can be had from behavioral data? If it could be shown that brain
regions known to be responsible for LTM are activated during
STM tasks, surely this would be evidence that those LTM regions
were supporting STM? This unsound line of reasoning provides
the rationale for the design and interpretation of a number of
neuroimaging studies which have been presented as providing
evidence that STM is simply activated LTM.
A flavor of the claims made in some neuroimaging papers can
be found in the following quotations: “This result implies that
activated long–term memory provides a representational basis for
semantic verbal short-term memory, and hence supports theories
that postulate that short- and long-term stores are not separate”
(Cameron, Haarmann, Grafman, & Ruchkin, 2005, p. 643, ab-
stract). “Temporary activation of long-term memory supports
working memory” (Lewis-Peacock and Postle, 2008, title). “these
findings support single-store accounts that assume there are similar
operating principles across WM and LTM representations, and the
focus of attention is limited.” (Öztekin, Davachi, & McElree,
2010, abstract). “Thus, the theoretical claim of our model—that
maintenance in VWM entails the activation of long-term, speech-
based representations—invalidates a central tenet of the multi-
component model,” (Acheson, Hamidi, Binder, & Postle, 2011,p.
1359). Note that the first three quotations come from either the
abstracts or the title of the papers so are presumably central to the
claims being made by the authors.
Exactly what is the evidence that supports these forceful claims?
Öztekin et al. measured hippocampal activity during a 12-item
probe-recognition task and found that “activation of the medial
temporal lobe was observed for all serial positions other than the
last position, and that the activation level could be predicted from
the underlying memory strength.” (Abstract). More generally, hip-
pocampal activation decreased over item positions and this corre-
lated with recognition accuracy. On this basis they claim that their
“results are inconsistent with the traditional view that posits that
there are distinct stores for WM and LTM” (p. 1130). This con-
clusion is based on what (Baddeley, 2003) has called the correla-
tional fallacy; the assumption “that any variable that is broadly
correlated with performance on the paradigm is crucial to it” (p.
729). As has already been shown, hippocampal activity is to be
expected in STM tasks simply because LTM cannot be turned off
in cases where it might not be needed. In fact LTM is very likely
to be needed in this study, as a 12-item list will be well beyond the
normal span of STM. Öztekin et al. favor an explanation based on
Oberauer’s (2002,2009) three-state memory model which posits
that memory items can be in three states: a single item in the focus
of attention, three or four items that are in an activated state in
LTM but need to be retrieved from working memory, and items in
a passive state which need to be retrieved from LTM. The first and
last of these states are common to multicomponent models; one or
two items may be in the focus of attention and some, especially in
a 12-item list, will need to be retrieved from LTM (or possibly the
episodic buffer component proposed by Baddeley, 2000). The
critical question is whether these data provide any evidence that
some items are in an activated state in LTM. As hippocampal
activation is expected as a matter of course, even under the
assumption that there is a separate STS, these data do not provide
an answer.
Cameron et al. (2005) based their claim that activated LTM
provides the representational basis for STM on data from an ERP
study. They compared two conditions, one of which was assumed
to involve memory for semantic information and the other was
intended as a control task. In the memory task, participants saw a
sequence of three words presented at a rate of one every 1000 ms,
followed after 4000 ms delay period by a probe word. The partic-
ipants’ task was to indicate whether the probe word was related to
one of the three preceding words. In the control task, participants
were required to indicate whether one of the words was unrelated
to the other two, so in this case there was no memory load during
the delay period. In both cases an incidental probe word was
presented auditorily 2000 ms after the beginning of the delay
period and this probe could be either semantically related or
unrelated to the third word. The ERP analysis found an effect of
semantic relatedness that was greater for the memory task than the
control task, and this led the authors to conclude that STM was
supported by LTM. This is a further example of the correlational
fallacy. What the data show is a priming effect which is larger in
the semantic memory task than in the control task. There is no
evidence that whatever causes the sematic priming also plays a
causal role in supporting STM. In the memory task participants are
likely to be recirculating the to-be-remembered items. As items
come to the fore they will be expected to elicit similar perceptual
and semantic processes to those elicited at encoding.
Lewis-Peacock and Postle (2008) used fMRI combined with
multivariate pattern analysis to establish whether a classifier
trained to discriminate between three categories of stimulus (peo-
ple, objects, locations) in a judgment task could classify neural
activity patterns during the delay phase of an STM task. The
judgment task involved answering questions such as how often the
participants encounter a particular object. The classifier was
trained on the data from this judgment task. In a second phase of
the experiment participants learned to associate pairs of the items.
In the STM task itself, participants were presented with a target
stimulus for 1 s and, 11 s later, they saw a probe stimulus. Their
task was to judge whether the probe stimulus was the associate of
the target. During the delay period the classifier trained on the
LTM judgment task could decode both the category of the target
and the category of the probe above chance. Lewis-Peacock and
Postle argued that “successful decoding of working memory ac-
tivity would provide conclusive evidence for the activated LTM
model” (p. 8768).
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SHORT-TERM MEMORY AND LONG-TERM MEMORY
This is a further example of the correlational fallacy. The fact
that LTM activity can be decoded during short-term retention
interval does not imply that those LTM representations are respon-
sible for short-term retention. Furthermore, the classifier was
trained only to distinguish between representations of different
semantic categories. It is quite possible that memory was sup-
ported primarily by some form of phonological storage in an STS,
but Lewis-Peacock et al. only looked for semantic activation.
Perhaps acknowledging this, Lewis-Peacock and Postle concede
that “This model does not necessarily rule out a parallel contribu-
tion to delay-task performance by specialized working memory
systems” (p. 8673). Data from a study by Shivde and Thompson-
Schill (2004) suggests that this might well be the case. They used
a similar STM paradigm where the task was either to judge
whether the probe word was a synonym of the target or shared a
vowel sound with a nonsense word probe. They found that the
semantic task elicited delay period activation in bilateral inferior
frontal gyrus and left middle temporal gyrus, while the phonolog-
ical task elicited activation in left superior parietal cortex. In other
words, when the task was phonological, the activation was in a
region more commonly associated with phonological STM. Shvide
and Thompson-Shill used univariate analyses so it is impossible to
say whether a classifier trained on a phonological contrast would
have been successful in decoding phonological information in the
retention interval of their phonological task, or even possibly their
semantic task. Not all brain regions that are activated will contain
representations detectable by a classifier, and classification can
often be successful in regions that show no univariate activation
(e.g., Harrison & Tong, 2009). However, these data clearly show
that the region that is activated during retention depends on what
is being retained. There is more to the story than the simple claim
that STM is activated LTM. Finally, a task requiring retention of
a single item is one of the few that that could conceivably be
performed solely by activating that item in LTM. The task de-
mands might be too simple to be able to guarantee that a dedicated
STS would be fully engaged.
Acheson et al. (2011) claim that “WM reflects the temporary
activation of LTM representations” (p. 1359). They argue that “the
theoretical claim of our model—that maintenance in VWM entails
the activation of long-term, speech-based representations—inval-
idates a central tenet of the multi- component model” (p. 1359).
However, their study really focused on a different and less con-
tentious issue, which is whether short-term storage of verbal ma-
terial depends on the same processes that are responsible for
perception or production. Even adherents of the multicomponent
view have considered the possibility that the phonological store
might be isomorphic with the memory system supporting speech
production (Page, Madge, Cumming, & Norris, 2007;Page &
Norris, 1998a). Page and Norris (1998a) presented a connectionist
implementation of their Primacy model of immediate serial recall
which had close parallels to the speech production models of Dell
and O’Seaghdha (1992) and Levelt (1992). Acheson et al. exam-
ined immediate serial recall of five-item lists using rTMS over
either the MTG or posterior STG during a 3-s retention interval.
MTG and posterior STG were chosen as they are implicated as the
sites of two stages of production planning (Indefrey & Levelt,
2004). Their rationale was that if rTMS over these production
areas impaired recall then these areas must be involved in STM.
Despite the strong claims made on the basis of this data, the results
are rather weak. rTMS had no significant effect on item order
errors, and an influence on omissions only in posterior STG. Let’s
pretend that there was a large effect of rTMS on both item and
order errors in both regions. What might we conclude? At the core
of the Working Memory model is a speech-based articulatory
rehearsal process. Unless participants are actively prevented from
doing so, they will almost certainly be trying to rehearse the
five-item list during the 3s retention interval. rTMS that interfered
with production should also interfere with rehearsal. The only
surprising finding here is that the effects were not larger than they
actually were.
A positive feature of the Acheson et al. study is that they used
a standard serial recall task. Serial recall is the most widely used
task to study short-term verbal memory and is the primary target
for computational models of verbal STM. The other neuroimaging
studies described here used nonstandard tasks that do not have a
well-established relation to specific components of memory in
multistore models. For example, Lewis-Peacock and Postle used a
retention interval of 11 s, which is well beyond the duration of the
phonological store. Indeed, this seems to be a common problem.
Talmi, Grady, Goshen-Gottstein, and Moscovitch (2005) tried to
make a case against the multistore models using data from a study
where participants had to remember lists of 12 words. This is twice
the normal span for words. The choice of task may in part be
determined by the difficulties associated with using standard lab-
oratory tasks in a neuroimaging environment. However, it is tech-
nically possible to run standard immediate-serial recall experi-
ments using fMRI (e.g., Kalm, Davis, & Norris, 2013).
Öztekin et al., Cameron et al., and Lewis-Peacock et al. have all
made the mistake of assuming that the presence of neural activa-
tion of brain regions normally associated with LTM during an
STM task implies that long-term representations in those regions
form the causal basis of STM. They have all committed the
correlational fallacy and failed to appreciate Atkinson and Shif-
frin’s point that “both STS and LTS are active in both STS and
LTS experiments.” The only way to construct a model of STM
where there would be no LTM activation in a STM experiment
would be by assuming that information in STS was stored in
opaque containers such that the contents of that store were inac-
cessible to other processes. If information in STS is visible to other
processes then it should activate those processes too.
What is activation? If STM is supported exclusively by ac-
tivated LTM, it seems reasonable to ask what computational func-
tion is performed by activation that would enable it to encode,
maintain, and retrieve information from STM. This is a fundamen-
tal and largely unrecognized problem with all models invoking
activated LTM. Although the core explanatory concept is activa-
tion, there is no explicit definition of what activation means. In the
memory literature the term activation often refers to the deploy-
ment of a limited capacity resource that can be used to support
WM (Anderson, 1983;Cantor & Engle, 1993;Just & Carpenter,
1992). However, there is no computational definition of activation
of LTM that would explain how that ‘activation’ might be suffi-
cient to maintain representations in STM. As Phillips (2003) noted
in his commentary on Ruchkin et al.’s (2003) position paper,
sometimes activation was used “in a psychological sense, some-
times to refer to EEG measures, and sometimes to refer to under-
lying neuronal activity” (p. 752). Worse still, in the absence of an
explicit computational model there is no agreed psychological
998 NORRIS
sense of activation to fall back on; it simply is not at all clear what
it means to say that STM might be activated LTM. Without an
understanding of the computational functions served by the neural
activation seen in LTM systems, any attempt to interpret correlated
activity in brain regions associated with LTM during short-term
retention remains highly speculative. We know too little about how
to interpret neural activation for it to form the basis of an expla-
nation. Even if we knew which neural processes caused activation,
this would not tell us what computational function was being
performed by those processes.
A further problem for activation-based theories is that recent
neuroimaging work suggests that storing information in STM may
not depend on sustained neural activation of any form. Several
studies (LaRocque & Lewis-Peacock, 2013;LaRocque, Riggall,
Emrich, & Postle, 2016;Lewis-Peacock, Drysdale, Oberauer, &
Postle, 2012;Sprague, Ester, & Serences, 2016) have tried to
address the question of whether STM is supported by sustained
neural activation. These studies all used a retrocuing paradigm
combined with multivariate pattern classification. In an initial
phase of the experiments a classifier was trained to discriminate
between different stimuli that would have to be remembered. For
example, in the LaRocque et al. (2016) study participants had to
remember the direction of motion of arrays of dots. The pattern
classifier was then used to track the progress of activated memory
representations over the course of a retention interval while par-
ticipants shifted their attention between one of two stimuli that
might have to be remembered. In the critical conditions, two visual
items are presented along with a cue indicating which item to
attend to. There is then a delay period of 16s. Halfway through the
delay period a retrocue is presented to indicate whether the par-
ticipant should maintain attention on the same attended item or
switch attention to the previously unattended item. A test probe is
then presented at the end of the delay period. Performance on the
test probe is high regardless of which item is probed. All of the
studies reported that during the first half of the retention interval,
only the item that was attended to could reliably be decoded by the
pattern classifier. However, when the retrocue indicated that at-
tention should be switched to the previously unattended item, then
that item could now be decoded. That is, only attended items could
be decoded but it did not matter whether those items had previ-
ously been in an unattended state where their representations could
not be decoded. LaRocque, and colleagues (LaRocque & Lewis-
Peacock, 2013;LaRocque et al., 2016;Lewis-Peacock et al., 2012)
concluded that only items that were in the focus of attention were
activated, and that sustained activation was not necessary to main-
tain items in STM. Sprague et al. describe the unattended infor-
mation as being stored in latent or activity-silent codes. In other
words, not only is there no evidence that STM involves sustained
LTM activation, but it may not require sustained activation of any
form at all over intervals of up to 16s. In reviewing some of this
data LaRocque, Lewis-Peacock, and Postle (2014), two of whom
had previously argued that STM was activated LTM (Lewis-
Peacock & Postle, 2008), quite reasonably pointed out that “that
this result should be taken as a call for clarification of what is
meant by “activated.”...Rather than referring to such items as
being retained in the “activated” portion of LTM, a word more in
keeping with the function of STM—such as “accessible”—might
be more appropriate to describe STM items outside the FoA”
(Focus of Attention. p. 9). However, the shift from ‘activated’ to
‘accessible’ completely eliminates the theoretical force of any
claim about the role of LTM in supporting STM. Without further
clarification, the term ‘accessible’ does little more than redescribe
the data.
Part of the problem with explanations based on activation may
stem from the tempting allure of the activation metaphor. Activa-
tion has been a popular theoretical metaphor in psychology since
the 1960s. In the context of memory models, activation usually
refers to the strength of a representation, and activation levels are
inferred from how well an item is remembered. With the rise of
connectionist or neural network models in the 1980s, activation
became even more central to psychological thinking. Activation is
the currency of communication between the artificial neurons.
Connectionist models had the great advantage of producing quan-
titative simulations that could be directly tested against the data.
The concept of activation in these models has clear computational
underpinnings. However, it sometimes seems that the successful
use of activation in connectionist modeling has been taken to
license indiscriminate use of the term in verbal models.
Computational models. In any scientific endeavor, progress
depends on developing theories that make clear and testable pre-
dictions. In STM research much of that progress has been driven
by computational modeling. For example, the basic principles of
Baddeley and Hitch’s WM model have been formalized in com-
putational models of the phonological store (Burgess & Hitch,
1992,1999,2006;Page & Norris, 1998b). These and other com-
putational models of STM (e.g., Botvinick & Plaut, 2006;Brown
et al., 2000;Farrell, 2012;Farrell & Lewandowsky, 2002;Henson,
1998) produce accurate quantitative simulations of most of the
benchmark data from STM tasks: the form of the serial position
curve, the nature of the errors in serial recall, effects of perceptual
grouping, complex patterns of phonological similarity effects, se-
quence learning, and much more. One could argue that the prob-
lem with these models is that they are so good that it is becoming
increasingly difficult to devise experiments to distinguish between
them. Nevertheless, these are all concrete models that can be
subject to empirical scrutiny. In contrast, there are no computa-
tional models based on activation of LTM. Before activation-based
models can be taken seriously they need to be clearly formulated
and to be shown to be competitive with existing computational
models.
STM must be able to represent multiple tokens. The spoken
sentence “Buffalo buffalo buffalo Buffalo buffalo” contains five
tokens of the same phonological word form ‘bfələυ. If you do
not know that a buffalo is a North American bison, that ‘to buffalo’
means ‘to confuse,’ and that there is a town called Buffalo, this
sentence will probably leave you completely buffaloed.
1
In fact,
even if you know all three of those it’s still hard to understand.
Nevertheless, if you hear this sentence it is very easy to repeat it
back—it’s just the same word repeated five times. If STM were
nothing more than the activated portion of LTM then a sentence or
list containing five repetitions of the same phonological word form
1
The sentence should be interpreted as indicating that bison who are
from the town of Buffalo confuse (buffalo) other bison from the town of
Buffalo. It is commonly used as an example of several different linguistic
phenomena and may have been generated independently by a number of
researchers. See http://www.cse.buffalo.edu/~rapaport/buffalobuffalo.html
999
SHORT-TERM MEMORY AND LONG-TERM MEMORY
could not be recalled. There would just be a single very strongly
activated representation of bfələυ.
This is an example of what Jackendoff (2002) called ‘the prob-
lem of two’ the cognitive system needs to be able to represent
multiple tokens of the same type.
2
Of course, it might be the case
that LTM contains multiple representations of the word ‘buffalo’
that can each be activated separately. But how many? Is it possible
to repeat the sentence “Buffalo buffalo Buffalo buffalo buffalo
buffalo Buffalo buffalo”?
3
Maybe LTM contains a whole herd of
buffalo? Possibly these sentences could be coded by a single LTM
representation with either five or eight units of activation. But what
about a list like “buffalo cowboy cowboy buffalo”? Could activa-
tion levels reliably differentiate between the lists “buffalo cowboy
cowboy buffalo” and “cowboy buffalo buffalo cowboy” so that
they could be recalled in the correct order? The idea that STM is
nothing more than activated LTM fails to provide a solution to ‘the
problem of two.’ Even the simple requirement to remember sen-
tences or lists containing two occurrences of the same type (word)
cannot be supported solely by activating LTM. In the memory
literature the importance of being able to represent multiple tokens
was highlighted by Potter (1993) in discussing what she called
“Very short-term conceptual memory.” She pointed out that ”It is
not enough just to activate the type representation of each word in
LTM; one must set up an episodic representation that includes a
token of each word type, tokens that are pointers to or copies of the
long-term representation of the words and their meanings” (p.
159). Note that the need to represent multiple tokens is not limited
to verbal processing. In the context of visual perception and
attention Kahneman and Treisman (1984) made a distinction be-
tween “episodic tokens and semantic types” (p. 55) in the devel-
opment of their concept of an object file. Theoretical accounts of
phenomena such repetition blindness (Kanwisher, 1987,1991) and
the attentional blink (Bowman & Wyble, 2007) also require a
distinction to be made between type and token representations.
Most computational models of STM have the ability to represent
multiple tokens. One straightforward way of achieving this can be
found in connectionist models of immediate serial recall that are
based on forming associations between item representations and
representations of list position (e.g., Burgess & Hitch, 1992;
Brown, Preece, & Hulme, 2000). The Burgess and Hitch model
was explicitly developed as a model of the articulatory loop
component of Baddeley and Hitch’s (1974) working memory
model. In their model a vector representing list position slowly
evolves so as to change slightly as each successive word is pre-
sented. At each position, the network learns an association be-
tween the position vector and the word. At recall, the states of the
position vector can be replayed and successive states of the vector
will tend to reactivate the word in the list associated with that
position. Because the same word can be associated with more than
one position, the model has no difficulty in remembering se-
quences where words are repeated. One might suggest that the
words that are activated must be in LTM and this could then be
construed as performing short-term storage by activating LTM.
However, the crucial point is that the model’s performance de-
pends entirely on the position-item association mechanism which
exists purely to perform short-term serially ordered recall. STM is
supported by a dedicated mechanism which exists in addition to
LTM. That mechanism is a STM store. Furthermore, in this par-
ticular model, the memory is encoded in the weights between the
position vector and the word representations and not by sustained
activation over LTM. This reminds us once again that although
there is a close relationship between LTM and STM, LTM cannot
do the job of supporting STM on its own. The problem of two
poses an insurmountable barrier to the idea that STM might be
supported simply by activating LTM. This holds regardless of the
content of STS. Exactly the same argument will apply to STM for
semantic information (Martin & Romani, 1994;Martin, Shelton, &
Yaffee, 1994;Shivde & Anderson, 2011) or visual information.
STM must contain structured representations. The ability
to represent multiple tokens is a basic prerequisite for a simple
passive STM system. However, this is not sufficient for a memory
store that could serve as a mental workspace for WM. A conse-
quence of being able to actively manipulate the contents of WM is
that this can create completely new structures which have never
been encountered before, which can themselves be manipulated.
By definition, this productivity cannot be captured simply by
activating preexisting representations (Logie, 2003;Logie & Della
Sala, 2003). In simple short-term verbal memory tasks the only
novelty is generally in the ordering or composition of the items to
be remembered. In contrast, WM has to have the capacity to store
a vast and unpredictable set of representations. There might be
some STM tasks that can be performed simply by activating
preexisting structures, but rarely will that be possible in a WM
task.
Variable binding. To hold structured representations of ob-
jects or scenes the system must also be able to perform variable
binding (see van der Velde & de Kamps, 2006, for review). For
example, consider how we might maintain a coherent representa-
tion of a sentence such as “The young boy saw the boy who was
singing.” Here the problem is not simply representing the order of
the words, or even that there are two tokens of the word boy, but
appreciating that there are two different boys, one of whom is
singing and one of whom is young. It’s necessary to both represent
multiple tokens and the bindings between each of those tokens and
other components of the sentence. However, this cannot be
achieved solely by coactivating and associating existing represen-
tations (as assumed by Cowan & Chen, 2008). This can be appre-
ciated by considering the simple case of forming associations
between AB, BC, and CA. Associating these three pairs will
necessarily form associations between all items in the triple ABC.
It will therefore be impossible to determine whether what has been
learned was AB, BC, and CA, or ABC. What is needed are
additional representation of the individual conjunctions (e.g., cre-
ating an ‘AB’ node in a connectionist network). In STM this could
be achieved by variable binding. That is, STM would contain a set
of variables to which arbitrary representations could be assigned.
For example, x(A, B), y(B, C) would construct bound
representations assigned to the variables xand y. This process may
or may not activate representations in LTM, but, for the reasons
already given, it should not form direct associations between A and
B or between B and C. This might seem to present a severe
problem for Oberauer’s three state model shown in Figure 1D.
2
The same argument applies even if ‘Buffalo’ and ‘buffalo’ are assumed
to activate separate semantic representations and therefore correspond to
different types as there will still be multiple tokens of the those types.
3
See https://en.wikipedia.org/wiki/Buffalo_buffalo_Buffalo_buffalo_
buffalo_buffalo_Buffalo_buffalo for interpretation.
1000 NORRIS
Oberauer depicts his model as having three concentric regions—
activated LTM, the direct access region, and the focus of attention,
all of which select a different subset of LTM representations
(shown by the lines and nodes). However, while the diagram and
the term region imply that the direct access region is simply a
subset of activated LTM, the operations taking place within the
direct access region involve much more than activation. According
to Oberauer “the region of direct access is a mechanism for
establishing and holding temporary bindings between contents. . .
. By supporting arbitrary bindings between virtually any content
with any context, this system enables the compositionality of
thought that many theorists regard as a hallmark of human cogni-
tion (Fodor & Pylyshyn, 1988): we can create an unlimited number
of different ideas by freely combining content elements into new
structures.” (Oberauer, 2009, p. 53). The direct access region is
therefore much more than just an activated region of LTM. It must
have all of the computational machinery needed to support all
aspects of higher cognition, and to have the same functionality as
the central executive and episodic buffer components of the Bad-
deley and Hitch WM model. As with Cowan’s model, it is not
clear whether activated LTM alone plays an essential part in the
model’s operation, or in its ability to retain information over the
short-term. The fact that Oberauer’s model needs to be supple-
mented with a binding mechanism reinforces the argument that a
model of STM needs more than just activated LTM to make it
work. Indeed, the big challenge for any model that might be based
purely on activation of LTM would be to make it work.
Visual STM. The case for STM as activated LTM has been
advanced predominantly in the domain of verbal STM. Perhaps
this is because some verbal STM tasks might be seen as simply
requiring the participant to remember a collection of familiar
words, which might be achieved simply by activating existing
representations. As we have seen though, the need to remember
words in sequence demands that words be bound to positions.
However, it has long been appreciated that perception of visual
objects depends on forming structured representations that bind
together features such as shape, color and location (Kahneman &
Treisman, 1984;Marr, 1982;Pylyshyn, 1989,2001). Not surpris-
ingly, the notion that STM might simply be activated LTM has
been less influential here. Combinations of visual features can
produce completely novel visual objects that cannot possibly have
preexisting representation in LTM. Nevertheless, configurations of
complex objects can be stored in STM. Even an image as simple
as an array of randomly placed identical dots cannot be represented
just by activating the appropriate number of dots. The dots must
each be individuated and bound to a unique spatial location.
Indeed, the change detection task used in many studies of visual
STM (e.g., Luck & Vogel, 1997) requires participants to judge
whether an object (such as a colored square) in a particular
location has changed color. There may well be other objects of the
same color in other locations. The task can only be performed by
binding colors to locations. The task of remembering a spatial
sequence presents even more of a challenge for activation ac-
counts. The Corsi block task (Corsi, 1973) requires participants to
touch a series of blocks in the same order as the experimenter had
done. Here there is no need to remember the spatial location of the
blocks, as they remain in view; instead, the participant must
remember the binding between the location of the blocks and their
order.
In the neuroimaging literature on visual STM many of the data
are consistent with what the ‘sensory recruitment’ hypothesis (Lee
& Baker, 2016;Serences, Ester, Vogel, & Awh, 2009). This
suggests that maintenance of information in visual STM is
achieved by recruitment of the same neural mechanisms that are
engaged in encoding that information. That is, information in STM
is stored in perceptual areas and not in those areas involved in
LTM. The sensory recruitment hypothesis is supported by data
showing that information maintained in visual STM can be de-
coded from brain regions known to be involved in visual percep-
tion (Harrison & Tong, 2009;Serences et al., 2009). Information
maintained in visual STM can also be decoded from regions of
parietal cortex (Bettencourt & Xu, 2016;Christophel, Hebart, &
Haynes, 2012;Sprague, Ester, & Serences, 2014;Sprague et al.,
2016) similar to those that that have been found to be active in
verbal STM. However, at the moment it is far from clear how the
neuroimaging data can be mapped onto cognitive models of visual
STM. For example, some have argued that there is more than one
visual STM. Basing his argument primarily on neuropsychological
data Logie (2003), has suggested that there may be one store for
spatial layout, and one that supports the ability to manipulate
mental images, and to retain dynamic information such as se-
quences.
Copies or pointers? In Atkinson and Shiffrin’s modal model
the store is a box that you put things in. But what do you put in the
box? This was never explicitly specified. In their 1966 paper they
suggested that the item “that is placed in the buffer may be
considered to be an amount of information which is sufficient to
allow emission of the correct response” (p. 3). One way to achieve
this is to store a copy of a representation of the input. For example,
in the WM model the primary responsibility for storage of verbal
information falls on the articulatory loop, which stores copies of
phonological representations. Alternatively, instead of storing cop-
ies, one might store pointers to representations stored elsewhere.
Either would be sufficient to allow emission of the correct re-
sponse.
The possibility that an STS might be based on pointers rather
than copies has a number of interesting implications. If the pointers
address representations in LTS then this would greatly complicate
the relationship between STS and LTS. However, pointers might
also operate within the bounds of a self-contained modality-
specific STS. As we will see, the advantage of this option is that
it can make very efficient use of the available storage capacity. Far
from blurring the lines between STS and LTS, consideration of
how a pointer system might work actually reinforces the case for
modality-specific short-term stores.
Perhaps the simplest possible model of an STS is Conrad’s
(1965) slot model—STS would contain a number of slots, and each
slot would contain a copy of an item to be remembered. But what
does it mean to store a copy? Exactly what is it that’s copied into
memory? In principle, when trying to remember ‘dog,’ we could
store a copy of everything we know about the word ‘dog.’ That
might seem excessive. More plausibly, we might store only a
subset of the information held in LTM; perhaps a phonological
representation of ‘dog.’
An alternative to storing copies of objects is to store pointers to
representations elsewhere. As every programmer knows, it is usu-
ally much more efficient to manipulate pointers than to copy entire
data structures. In computing terms a pointer is the address of a
1001
SHORT-TERM MEMORY AND LONG-TERM MEMORY
location in memory where information is stored. The great advan-
tage of using pointers is that the pointers generally take up much
less storage than the data they point to, and they eliminate the need
to copy the data. For example, if the data objects were lexical
representations of words, any list of words could be represented
economically by a list of pointers to those objects. The STS storage
requirements would remain the same no matter how complicated
the lexical representations were. Importantly, STS could represent
multiple tokens by having more than one pointer index the same
type representation (the same word in LTS). Thus, if the capacity
of STS happened to be five pointers, it would be possible to retain
the identity and order of any five objects.
It is worth bearing in mind that it is possible to write two
programs to perform the same computations that differ solely in
terms of whether they rely on copying data or manipulating point-
ers. Indeed, programming languages differ in terms of whether
they perform assignment by copying data or pointers. In C, a
b copies the data in bto a. In Python, ab sets ato point to
the same data as b. If one were to write two superficially identical
programs, one in C and one in Python, they would produce the
same output, but the underlying operation of the programs would
be different.
Some of the confusion seen in the neuroimaging literature might
come from an assumption that a distinct STS would hold repre-
sentations copied from LTM, and that therefore LTM should not
be activated while that information is being retained in STM.
Interestingly, in computational models of STM, what is stored is
generally more akin to a pointer than a copy. In the Burgess and
Hitch model the weights between position vectors and word vec-
tors act as pointers to a single representation of a word. There is no
need to have multiple copies of a word.
Pointers, address space, and efficiency of storage. Although
it is tempting to think that memory capacity might be determined
by the number of available pointers, not all pointers are created
equal. The amount of memory required to store a pointer will vary
as a function of the number of objects that the pointer can poten-
tially address. In an early 8-bit computer an 8-bit pointer could
only address one of 256 memory locations. A 16-bit pointer could
address one of 65536 locations. How large a pointer might be
necessary in order to address any possible representation that
might be stored in LTM? Let’s pretend that a 32-bit pointer would
be sufficient as that could address any one of 4.3 10
9
represen-
tations (on the assumption that each representation corresponds to
a single address). But an 8-bit pointer would be more than suffi-
cient to index the set of phonemes in a language. With a memory
capacity of 32 bits it would therefore be possible to store pointers
to 4 phonemes, or just a single pointer to any object in LTM—
which might be a phoneme. There’s a simple trade-off. For a given
memory capacity it is possible to store pointers to either a large
number of items selected from a small set, or a smaller number of
items selected from a larger set. This has implications for how best
to make efficient use of available memory capacity. Imagine that
there is some set of computations in language comprehension that
only requires manipulation of phonemes. If those computations
can be performed in a dedicated speech store that only needs to
reference speech representations, then the total memory require-
ment (in bits) will be much less than if those same computations
have to be performed in a general purpose system that has the
potential to reference all possible representations in LTM. Note
that a specialized store could be made even more efficient if it
could take into account the redundancies of the language to con-
struct a compressed representation. One estimate is that each
phoneme in English phoneme could be coded by as few as 3 bits
(Stilp, 2011). That is, a dedicated store might be able to store as
much as 10 times as many phonemes in a given capacity than a
general-purpose store. Note that the amount of data compression
possible will depend how much context can be taken into account
(Shannon, 1951). Nevertheless, a dedicated store that incorporated
knowledge of say, syllables,
4
or the phoneme transition probabil-
ities of English, could make far more effective use of storage than
one that had to rely on pointers to LTM. One point in favor of a
phonological store like that in the WM model is therefore that it
would make very efficient use of available memory capacity.
Note, however, that if we used an 8-bit pointer to represent
phonemes in a phonological store, that pointer could not make
direct contact with phonological representations in LTM on its
own. If LTM had, say, a 32-bit address space, an 8-bit pointer
could only address a subset of that space. A simple solution would
be that a modality-specific store could add a bit pattern to the
modality-specific pointer that would serve to select the relevant
subset of LTM representations. In our simple example, the pho-
nological store would pad out the 8-bit pointers to 32-bits with an
extra 24 bits that effectively say “I’m a phonological representa-
tion” and ensure that the 8-bit pointer can address the correct part
of LTM. In the brain, if phonological representations in LTM
were, in a sense, stored close together, then connections from
phonological STM could target specifically those representations.
The same reasoning holds even if what is stored are copies.
Efficiency will be greatest if only the minimum amount of infor-
mation required is copied into the store. Although the pointer
argument is made from a purely computational perspective, an
analogous argument can be made from the perspective of neural
economy (Bullmore & Sporns, 2012). If some computations in-
volve a restricted set of processes and representations, then the
neurons responsible for those computations should be strongly
interconnected and physically adjacent so as to minimize expen-
sive long-range connections.
All of these arguments will apply equally well to any system
that implements the same functionality as pointers. For example, in
a connectionist model relying on weighted connections between
nodes, the greater the number of representations that can be stored,
the more nodes and connections will be required.
Pointers and single-store models. Proponents of single store
models have also invoked the idea of pointers. In arguing that
working memory is a state of activated long-term memory Ruch-
kin et al. (2003) say that “Prefrontal cortex provides the attentional
pointer system for maintaining activation in the appropriate pos-
terior processing systems.” (abstract). That is, there is an atten-
tional pointer system that takes care of all of the processing
operations that are needed by an STS, whereas the representations
that are being retained exist only in activated LTM. Ruchkin et al.
do not specify exactly what is meant by an attentional pointer
system, nor by activation. However, adding a pointer system to
4
Simply coding the input in terms of syllables rather than phonemes
(allowing for the fact that there are many more syllables than phonemes)
can reduce the requirements to between 3 and 4 bits per phoneme.
1002 NORRIS
activated LTM at least has the potential to overcome the funda-
mental barrier that undermines simple activation models - the
problem of two. But exactly how does such a model differ from
one that posits separate short- and long-term stores? The pointer
system functions as a store and must necessarily be responsible for
representing multiple tokens and serial order. The claim seems to
be predominantly one about neural implementation or localization
rather than function; the pointers are in prefrontal cortex and the
representations are in posterior systems. As I have already argued,
pointers will generally provide the most efficient way to represent
multiple tokens and to manipulate information in STM. However,
there are also efficiency gains to be had by restricting pointers to
operate on representations held within a local STS rather than
using a single pointer system that can address all of LTM. How-
ever, apart from the efficiency argument, a greater concern is that,
under this view, the basic behavioral phenomena that motivated
the WM model remain unexplained. A pointer-based store that
could address any representation in LTM would have no reason to
be modality-specific - the pointers could equally well address
phonological, semantic, or even visual representations. So why
does verbal STM seem to be primarily based on a phonological
code, and why does phonological coding of visual input appear to
be eliminated by articulatory suppression? Why would the pointers
point to purely phonological representations if they could equally
well point to lexical representations?
Ruchkin et al. say that “findings of multiple, modality-
specialized short-term stores are fully compatible with the position
that short-term memory corresponds to activated long-term mem-
ory representations, given that long-term memory involves multi-
ple, modality-specialized stores.” (p. 712). However, the behav-
ioral data show that the qualitative behavior of the different stores
is different. At the very least they have different time-courses. If
short-term retention is controlled by a single pointer system, then
all short-term storage should have the same time-course.
Most of the data that Ruchkin et al. martial in support of their
view come from electrophysiology. However, in common with the
neuroimaging data reviewed above, this is entirely correlational
and shows only that, during STM tasks, there is neural activity in
brain regions usually associated with LTM or perceptual pro-
cesses. We have already seen that, according to a multistore view,
LTM and perceptual regions should also be activated, so finding
correlated activation does not tell us whether that activation plays
a causal role in retention. The only data we have that speaks
directly to that question is the data from STM patients.
Ruchkin et al.’s position makes it clear that we should not view
the question of whether there are distinct long-term and short-term
stores as being a simple dichotomy. There is a very large space of
possible models. The simplest possible model might seem to be
Atkinson and Shiffrin’s modal model, but even there the STS
could contain copies, or could contain pointers. In most cases these
two alternatives would produce indistinguishable behavior. Point-
ers might address representations in LTM, or representation in
modality-specific stores. A short-term phonological store might
operate with pointers to representations held within that store
itself. Additionally, it might be a specifically mnemonic store, or
parasitic on processes responsible for perception or speech pro-
duction.
An additional layer of complexity arises when we consider how
any of these memory systems might be implemented in the brain.
For example, if there is an STS containing copies of information in
LTM, will the binding between the two sets of representations
elicit neural activity? Or, to put it the other way around, what does
neural activity tell us about the computations involved? More
fundamentally, what is the mechanism of neural binding underly-
ing STM? The space of possibilities grows even larger when we
move from just considering STM to thinking about working mem-
ory and how to manipulate representations and coordinate them
across different modalities. Note that I have referred to a system
holding pointers to LTM as an STS even though the representa-
tions are in LTM. If there is a system where the STS contains
pointers to LTM, should we really call this a STS, or is it just a
pointer system? My own inclination is to stick with the term STS,
as the pointers are doing all of the hard work. They also control the
capacity of STM—more pointers means greater capacity.
Summary. When reading many of the papers cited here it is
easy to form the impression that there is a clearly formulated
model of memory in which STM is simply the activated portion of
LTM. No such theory exists. This should not really come as a
surprise as such a model would founder on the problem of two.
Any model of STM must have some additional mechanisms be-
yond simple activation. There must be mechanisms to control the
activation, to store multiple tokens, to recall those tokens in the
correct order, and to create novel structured representations that
cannot yet be in LTM. Only then could such a model begin to
compete with existing computational models of STM developed
within a multistore framework. However, those additional mech-
anisms would effectively amount to a dedicated STS. In a system
relying on storing pointers in a STS, STM would indeed depend on
LTM representations, but all of the heavy lifting would be done by
processes outside of LTM itself. The theories of Cowan and
Oberauer, which have often been cited as models where STM
depends on activated LTM, have additional mechanisms to support
binding and serial recall. Indeed, serial recall should probably be
seen as the natural task to investigate the relation between verbal
STM and LTM. A simpler task where there is no need to represent
order might conceivably be performed largely using LTM. Recall-
ing the words “buffalo cowboy cowboy buffalo” in the correct
order requires a memory for multiple tokens, but judging that the
list contains the word “cowboy” does not. It is also important to
bear in mind that factors such as phonological similarity can have
different effects on memory for order information and item infor-
mation. Although phonological similarity generally has a detri-
mental effect on recall of order, it can have a beneficial effect on
item memory (Fallon et al., 1999;Gathercole, Gardiner, & Gregg,
1982;Gupta, Lipinski, & Aktunc, 2005).
Although we can be sure that an activation-based single store
model will not work, representations in LTM have an important
role to play in assisting STM. One of the big questions here is
whether that assistance takes the form of a continuous interaction
between LTM and STM during retention, or a redintegration
process operating only at recall. Note that if activation from LTM
is assumed to improve retention of order, that source of activation
needs its own ordering and binding mechanism. An even bigger
question though is “What is stored in STM?”. The primary options
are copies and pointers. But copies of what, and pointers to what?
It is clear that what is stored in the phonological store of the
Working Memory model are copies of speech-based representa-
tions. However, in the Burgess and Hitch model which is intended
1003
SHORT-TERM MEMORY AND LONG-TERM MEMORY
as an implementation of the phonological store, the weights can be
thought of as pointers.
Interestingly, the computational properties of this model would
remain unchanged if it were assumed that the item representations
that were pointed to were in LTM rather than a separate STS. That
is, the change would simply be in terms of how the models were
described or interpreted, or how they might be implemented in the
brain, not in terms of how they worked. As noted earlier though,
there are advantages to using pointers within a dedicated STS.
Using pointers to local representations can make economical use
of storage. It could also minimize the need for information to be
transferred between different brain regions. This would be advan-
tageous given that most of the connections within the brain are
local. Together, these engineering constraints make a case for
expecting the existence of modality specific stores. That is, while
it may seem more parsimonious to have a single store, it may be
more complicated to build one.
In experimental psychology, much of the progress in under-
standing STM has followed from the development of computa-
tional models. Before the advent of computational theories the
Working Memory model had no proper account of how serial
recall was actually performed, even though much of the data that
motivated the model came from the serial recall task. However,
models such as those of Burgess and Hitch (1992), and Page and
Norris (1998b) are implementations of the phonological store
component of the WM model. Those models can simulate a wide
range of data form serial recall. Theories making claims that STM
is supported by activated LTM need to rise to the same challenge.
This is not simply a matter of requiring them to simulate the data,
the models need to be specified in more detail to even begin
understand what claims about activated LTM actually mean.
I have concentrated primarily on one possible class of single-
store model, those relying solely on activation. Might it be possible
to produce more complex single-store models that wouldn’t fall
foul of the problem of two? The pointer-based models of the form
proposed by Ruchkin et al. could represent multiple tokens, but
only by adding extra mechanism that serves all of the functions of
an STS. However, such a model still faces the seemingly insur-
mountable challenge of accounting for the neuropsychological
data from STM patients. Ruchkin et al. tried to downplay the
significance of the neuropsychological data by suggesting that
patients with deficits in phonological STM deficits “should be
indicative of impairments in establishing long-term memories for
those representations” (p. 711). In other words, this is an attempt
to turn the argument presented earlier on its head. The problem
phonological STM patients have in long-term learning of novel
words is not because they have poor STM but because they have
trouble establishing phonological representations in LTM. Given
that the claim is that STM is supported by activated LTM, it is not
clear why a problem in establishing new representations should
prevent those representations from being activated—which should
be all that’s necessary to hold information in STM. According to
the Ruchkin et al. view, language comprehension should also
depend on activation of phonological representations in STM.
However, STM patients have good comprehension abilities, sug-
gesting that they have no problems in activating those representa-
tions. Furthermore, the patients’ primary STM deficit is in remem-
bering sequences of familiar items such as words or digits. This
should not place any demands on establishing new representations
in LTM. Additionally, these patients definitely can establish new
representations of verbal material in LTM because they have little
trouble with paired-associate learning.
More recently, Surprenant and Neath (2009) also presented a
case for a single store model. They mounted a spirited attack on
nine lines of argument that have been used to support the distinc-
tion between STM and LTM. Number nine concerned data from
patients with intact STM but impaired LTM, but they offered no
explanation of how data from STM patients might be accounted
for in a single store model.
5
Conclusions
The primary argument advanced here is that any STM system
must be able to store complex representational structures that have
never been encountered before, whether this be novel sequences of
words, or novel combinations of visual features. By definition,
such representations cannot already exist in LTM, and therefore
cannot be stored simply by activating LTM. The most basic
requirement for any memory system is to be able to store multiple
tokens of the same type. This is essential for even a simple STM
task such as serial recall. If LTM is a store of type representations,
STM cannot function simply by activating LTM types. Of course,
it is possible to argue that LTM has many representations of a
given type, but this would be grossly inefficient as it would imply
that all representations in LTM are extensively duplicated. The
standard solution is to allow memory to either contain multiple
copies of representations, which ensures that only those represen-
tations being retained at the moment are duplicated, or to contain
pointers to the representations of single types in LTM; the same
representation in LTM can be pointed to by multiple pointers in
STM. However, simple pointers from STM to LTM are not suf-
ficient to solve the binding problem. There must also be provision
for the construction and storage of more complex representations,
and this must involve something equivalent to variable binding.
Whatever is going on when we store information in STM is far
more elaborate than activating LTM, or putting copies in boxes.
The important question is not simply whether there are separate
short-term and long-term stores, but what is stored in STM. If
STM contains pointers, the information capacity of STM will
depend on the address space—the wider the range of LTM repre-
sentations that can be stored in STM (pointed to) the more bits will
be required to hold those pointers. This provides an additional
motivation for modality-specific stores of the form incorporated
into Baddeley and Hitch’s working memory model. If some set of
computations only need access to a limited range of information
that has to be stored temporarily (say phonological information)
then it will be more memory-efficient to process that information
in a store that is specialized to hold only that kind of information.
The suggestion that STM might be nothing more than activated
LTM may have the merit of parsimony, but it simply doesn’t work.
A simple activation process would be unable to solve the problem
of two, or to store novel representations. It follows that any model
that places an emphasis on storage by activated LTM must be
supplemented by some additional mechanism that can represent
multiple tokens serial order. That mechanism must be able to
5
See Thorn and Page (2009) for a more detailed rebuttal of the Supre-
nant and Neath arguments.
1004 NORRIS
perform the variable-binding operation required to construct novel
representations. That additional mechanism would then amount to
what has conventionally been thought of as a short-term store. In
fact, the resulting model would look very much like existing
computational models of STM. Some may still prefer to describe
this by saying that STM is activated LTM. If they make it clear that
there must be some additional mechanism, and explain how that
mechanism operates, at least we’ll know what they mean.
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Received March 31, 2016
Revision received December 8, 2016
Accepted April 16, 2017
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1009
SHORT-TERM MEMORY AND LONG-TERM MEMORY
... In this study, the VI3DM presented compiled information comprising life-like digital 3D models with marked relations, attachments, and features, which simplified the processing of visuo-spatial information and helped learners conceptualise the anatomical facts. According to the cognitive load theory, unnecessary cognitive load can be eliminated or reduced by optimally designing learning resources (Craik, 2014;De Jong, 2010;Norris, 2017;Smith et al., 2014;Sweller et al., 1998) and VI3DM reduce distraction, which increases the mental capacity of the learner's cognitive system to transform information to memory (Craik, 2014;De Jong, 2010;Norris, 2017;Sweller et al., 1998). Participants from the experimental group struggled and required more time learning the digital 3D models in the first learning session because most learners were using digital 3D technology for the first time. ...
... In this study, the VI3DM presented compiled information comprising life-like digital 3D models with marked relations, attachments, and features, which simplified the processing of visuo-spatial information and helped learners conceptualise the anatomical facts. According to the cognitive load theory, unnecessary cognitive load can be eliminated or reduced by optimally designing learning resources (Craik, 2014;De Jong, 2010;Norris, 2017;Smith et al., 2014;Sweller et al., 1998) and VI3DM reduce distraction, which increases the mental capacity of the learner's cognitive system to transform information to memory (Craik, 2014;De Jong, 2010;Norris, 2017;Sweller et al., 1998). Participants from the experimental group struggled and required more time learning the digital 3D models in the first learning session because most learners were using digital 3D technology for the first time. ...
... STM has a longer processing time (a few seconds or a few minutes). Unlike sense memory, which works unconsciously, STM allows people to repeatedly and consciously recall facts and events (Norris, 2017). Working memory is a special kind of STM. ...
... However, based on existing research, the differences between working memory and STM are still not clear (Aben et al., 2012). LTM is the memory that has been stored in the brain for a long time (Norris, 2017). LTM can be divided into two categories: declarative memory and non-declarative memory. ...
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This study aimed to identify and compare the EEG activities associated with semantic and episodic memory retrieval during creative processes. Episodic and semantic memory induction studies were conducted and EEG was used to collect data. The results showed that (i) Episodic and semantic memory retrieval are related to the frontal lobe area; (ii) Semantic memory retrieval is evoked more swiftly compared with episodic memory retrieval (ii) Prior to episodic memory retrieval, semantic memory retrieval is evoked first.
... Recent years have seen a flowering of research on how information is transferred from working memory (WM), a temporary system that can hold a limited amount of information Cowan, 2001) in mind for ongoing cognitive operations , to episodic long-term memory (LTM), a more permanent repository with seemingly unlimited capacity (Brady et al., 2008) for storing memories of events occurring in specific times and places (Tulving, 1983(Tulving, , 2002. The relation between WM and LTM has a rich history in cognitive psychology, dating back to the seminal work of Atkinson and Shiffrin (1968), and has been the topic of intense scientific debate (Cowan, 2019;Norris, 2017). Some theorists view WM and LTM as distinctly separate memory systems (Logie et al., 2009;Shallice & Warrington, 1970;Shimi & Logie, 2019), some adopt a unitary approach according to which there are not separate WM and LTM systems (Brown et al., 2007;McElree, 2006;Nairne, 2002;Surprenant & Neath, 2009), and others view WM as a temporarily activated subset of LTM (Cowan, 1988(Cowan, , 2019Morey et al., 2013;Oberauer, 2002). ...
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Limitations in one’s capacity to encode information in working memory (WM) constrain later access to that information in long-term memory (LTM). The present study examined whether these WM constraints on episodic LTM are limited to specific representations of past episodes or also extend to gist representations. Across three experiments, young adult partici- pants (n = 40 per experiment) studied objects in set sizes of two or six items, either sequentially (Experiments 1a and 1b) or simultaneously (Experiment 2). They then completed old/new recognition tests immediately after each sequence (WM tests). After a long study phase, participants completed LTM conjoint recognition tests, featuring old but untested items from the WM phase, lures that were similar to studied items at gist but not specific levels of representation, and new items unrelated to studied items at both specific and gist levels of representation. Results showed that LTM estimates of specific and gist memory representations from a multinomial-processing-tree model were reduced for items encoded under supra-capacity set sizes (six items) relative to within-capacity set sizes (two items). These results suggest that WM encoding capacity limitations constrain episodic LTM at both specific and gist levels of representation, at least for visual objects. The ability to retrieve from LTM each type of representation for a visual item is contingent on the degree to which the item could be encoded in WM.
... There is an ongoing debate regarding whether WM and LTM represent distinct memory systems or if there exists a single memory system responsible for both short-and long-term storage (for a current view on this debate, see, for instance, Cowan, 2019;Norris, 2017). One prominent theory supporting the latter perspective is the Embedded-Processes Model (Cowan, 1999(Cowan, , 2019. ...
... The transformation of short-term to long-term memory is essential for the development of long-term memory elements in artificial neural networks. 68 The modulation of optical input stimulation parameters such as optical pulse duration, pulse number, and pulse intensity affect the conversion process. We measured the optical pulse durationdependent EPSC by varying the pulse duration from 1 s to 5 s, as depicted in Fig. 6(a). ...
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In recent times, there has been a growing interest in the development of light-stimulated artificial synapses for applications related to artificial intelligence. Low operating voltage, low energy consumption, less noise, high transmission rate, and high operating speed make artificial synaptic organic field-effect transistors (OFET) suitable candidates for future artificial complex neural network development. In this work, we demonstrate human cognitive activities through the utilization of water-soluble gelatin biopolymer gated poly(2,5-bis(3-alkylthiophen-2-yl)) thieno [3,2-b] thiophene [PBTTT-C14] synaptic OFETs. The devices exhibit basic neurobiological phenomena including excitatory post-synaptic current (EPSC), pair-pulse facilitation (PPF), short-term plasticity (STP), long-term plasticity (LTP), STP to LTP conversion, and learning-forgetting-memorizing (LFM) nature similar to the human brain. The photo-response parameters such as photoresponsivity, detectivity, and the photo and dark current ratio are estimated for the better realization of the photo synapses. The OFETs exhibit commendable photoresponsivity of 11.10 mA W⁻¹, high detectivity of 8.55 × 10⁸ Jones, and the photo to dark current ratio of 654. Moreover, these photo synaptic OFETs imitate the human emotion-tuneable and the mood-swing-influencing (MSI) memory and learning behavior. Further, We also demonstrate the implementation of the ‘OR’ logic gate under the stimulation of two different wavelengths by utilizing these OFETs. Additionally, we replicate Pavlov's dog experiment to explain the associative learning nature of the OFETs. The OFETs exhibit a fairly low energy consumption of ∼89 nJ per optical event to perform basic neurobiological activities which facilitates the development of complex artificial neural networks with minimal energy consumption.
... Several studies have shown that STM supports information previously encountered as memory [3]. It can also act as a system with limited capacity that can represent information after the individual has no sensory input. ...
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Short-term memory (STM) temporarily stores sensory events, movements, and cognitive information. Several studies have shown that STM can store previously encountered information as memory. Studies show that as age increases, the STM of the individual decreases; however, there is no precise age division for when the decay of STM occurs. In this study, a method of short-term visual memorization of a random sequence of numbers has been used to study the correlation between age and STM, and the age of decay of STM. The result of this study has shown a significant difference in the number of digits recalled between the age groups 1-12 and 65 and above and age groups 13-17 and 65 and above.Similarly, age groups 1-12 and 18-64 differed significantly. We conclude that the increase in age correlates negatively with short-term memory, where the STM and the ability to recall short items decrease as age increases. Potential genetic and physiological mechanisms of the negative correlation between age and STM are discussed.
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The long-term fate of to-be-remembered information depends in part on the conditions of initial learning, including mental operations engaged via working memory. However, the mechanistic role of working memory (WM) processes in subsequent episodic memory (EM) remains unclear. Does re-exposure to word-pairs during WM recognition testing improve EM for those associations? Are benefits from WM re-exposure greater after an opportunity for retrieval practice compared to mere re-exposure to the memoranda? These questions are addressed in three experiments (N = 460) designed to assess whether WM-based recognition testing benefits long-term associative memory relative to WM-based restudying. Our results show null or negative benefits of WM recognition testing minutes later when initial WM accuracy was not considered. An EM benefit of WM recognition testing only emerges when the analyses are limited to pairs responded to correctly during WM. However, even when compared with accurate WM recognition, restudying can lead to similar associative EM benefits in specific experimental conditions. Taken together, the present results suggest that while WM re-exposure to studied pairs is beneficial to long-term associative memory, successful retrieval on initial tests may be a necessary but insufficient condition for the emergence of a “WM-based testing effect.” We consider these results in relation to several hypotheses proposed to explain the testing effect in long-term memory (LTM). In view of empirical parallels with the LTM testing effect, we propose that similar processes influence the benefits of practice tests administered within the canonical boundaries of WM, suggesting continuities in memory over the short and long term.
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To account for the large demands on working memory during text comprehension and expert performance, the traditional models of working memory involving temporary storage must be extended to include working memory based on storage in long-term memory. In the proposed theoretical framework cognitive processes are viewed as a sequence of stable states representing end products of processing. In skilled activities, acquired memory skills allow these end products to be stored in long-term memory and kept directly accessible by means of retrieval cues in short-term memory, as proposed by skilled memory theory. These theoretical claims are supported by a review of evidence on memory in text comprehension and expert performance in such domains as mental calculation, medical diagnosis, and chess.
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One explanation of the correlation often observed between working-memory span scores and reading comprehension is that individuals differ in level of activation available for long-term memory units. Two experiments used the fan manipulation to test this idea. In Experiment 1, high- and low-working-memory Ss learned a set of unrelated sentences varying in the number of shared concepts (fan) and then performed speeded recognition for those sentences. Low-working-memory Ss showed a larger increase in recognition time as fan increased. When the slope of the fan effect was partialed out of the relationship between working-memory span and verbal abilities, the relationship was reduced to nonsignificance. In Experiment 2, Ss learned thematically related sentences that varied in fan. Low-span Ss showed the positive fan effect typically found with thematically unrelated sentences, whereas high-span Ss showed a negative fan effect. The results are discussed in terms of a general capacity theory.
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Repetition blindness (Kanwisher, 1986, 1987) has been defined as the failure to detect or recall repetitions of words presented in rapid serial visual presentation (RSVP). The experiments presented here suggest that repetition blindness (RB) is a more general visual phenomenon, and examine its relationship to feature integration theory (Treisman & Gelade, 1980). Experiment 1 shows RB for letters distributed through space, time, or both. Experiment 2 demonstrates RB for repeated colors in RSVP lists. In Experiments 3 and 4, RB was found for repeated letters and colors in spatial arrays. Experiment 5 provides evidence that the mental representations of discrete objects (called “visual tokens” here) that are necessary to detect visual repetitions (Kanwisher, 1987) are the same as the “object files” (Kahneman & Treisman, 1984) in which visual features are conjoined. In Experiment 6, repetition blindness for the second occurrence of a repeated letter resulted only when the first occurrence was attended to. The overall results suggest that a general dissociation between types and tokens in visual information processing can account for both repetition blindness and illusory conjunctions.
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A theory of the way working memory capacity constrains comprehension is proposed. The theory proposes that both processing and storage are mediated by activation and that the total amount of activation available in working memory varies among individuals. Individual differences in working memory capacity for language can account for qualitative and quantitative differences among college-age adults in several aspects of language comprehension. One aspect is syntactic modularity: The larger capacity of some individuals permits interaction among syntactic and pragmatic information, so that their syntactic processes are not informationally encapsulated. Another aspect is syntactic ambiguity: The larger capacity of some individuals permits them to maintain multiple interpretations. The theory is instantiated as a production system model in which the amount of activation available to the model affects how it adapts to the transient computational and storage demands that occur in comprehension.
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Participants memorized briefly presented sets of digits, a subset of which had to be accessed as input for arithmetic tasks (the active set), whereas another subset had to be remembered independently of the concurrent task (the passive set). Latencies for arithmetic operations were a function of the setsize of active but not passive sets. Object-switch costs were observed when successive operations were applied to different digits within an active set. Participants took 2 s to encode a passive set so that it did not affect processing latencies (Experiment 2). The results support a model distinguishing 3 states of representations in working memory: the activated part of long-term memory, a capacity limited region of direct access, and a focus of attention.
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Abstract Three patients with semantic dementia, involving progressive deterioration of semantic memory, performed immediate serial recall of short sequences of familiar words. On the basis of their performance in other tasks of word comprehension and production, the stimuli were selected individually for each patient as either known or unknown words. All patients showed a marked advantage in recall of known as compared to familiar but now unknown words. Errors consisted primarily of incorrect combinations of correct phoneme sequences in the stimulus string, with a large number of errors preserving onsethime syllable structure (e.g., mint, rug reproduced as "rint, mug"). Discussion focuses on the implication of these errors for the structure of phonological representations, and in particular on a hypothesis that meaning plays a crucial role in binding the elements of phonological word forms.
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Since the 196Os, there has been controversy as to whether long-term learning might depend on some form of temporary short-term storage. Evidence that patients with grossly impaired memory span might show normal learning was, however, particularly problematic for such views. We reexamine the question by studying the learning capacity of a patient, P.V., with a very pure deficit in short-term memory. A series of experiments compare her learning capacity with that of matched controls. The fast experiment shows that her capacity to learn pairs of meaningful words is within the normal range. A second experiment examines her capacity to learn to associate a familiar word with an unfamiliar item from another language. With auditory presentation she is completely unable to perform this task. Further studies show that when visual presentation is used she shows evidence of learning, but is clearly impaired. It is suggested that short-term phonological storage is important for learning unfamiliar verbal material, but is not essential for forming associations between meaningful items that are already known. Implications for the possible role of a phonological short-term store in the acquisition of vocabulary by children are discussed. 0 1988 Academic During the 196O.q evidence for separate long-and short-term memory stores began to accumulate. This evidence led to a number of models, the most influential of which was the "modal model" of Atkinson and Shiffrin (1968). This assumed that information was fed from a series of sensory buffers into a limited capacity short-term store, which in turn fed information into and out of a much larger capacity long-term store. Learning was assumed to involve transfer of information from the short-term to the long-term store, with the probability of long-term learning being a function of the time spent by the relevant item in the short-term store. By the early 1970s evidence that did not fit into the modal model was begin
Book
Available again, an influential book that offers a framework for understanding visual perception and considers fundamental questions about the brain and its functions. David Marr's posthumously published Vision (1982) influenced a generation of brain and cognitive scientists, inspiring many to enter the field. In Vision, Marr describes a general framework for understanding visual perception and touches on broader questions about how the brain and its functions can be studied and understood. Researchers from a range of brain and cognitive sciences have long valued Marr's creativity, intellectual power, and ability to integrate insights and data from neuroscience, psychology, and computation. This MIT Press edition makes Marr's influential work available to a new generation of students and scientists. In Marr's framework, the process of vision constructs a set of representations, starting from a description of the input image and culminating with a description of three-dimensional objects in the surrounding environment. A central theme, and one that has had far-reaching influence in both neuroscience and cognitive science, is the notion of different levels of analysis—in Marr's framework, the computational level, the algorithmic level, and the hardware implementation level. Now, thirty years later, the main problems that occupied Marr remain fundamental open problems in the study of perception. Vision provides inspiration for the continuing efforts to integrate knowledge from cognition and computation to understand vision and the brain.
Article
Two experiments are described which demonstrate a long-term memory contribution to memory span. In the first experiment nonwords were used because they lack a long-term memory representation. Memory span was lower for nonwords than words and in both cases a linear function related recall to speech rate for items of differing spoken durations. The function for nonwords had an equivalent slope (interpreted as reflecting a contribution from a subvocal rehearsal process) but a lower intercept (interpreted as reflecting a contribution from a long-term memory component). The second experiment compared the spans for Italian and English words. The span was lower for Italian words than for English words, due to a depression in the intercept of the recall-speech rate function, but learning the English translations of these words increased subjects' memory span for them.