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BACHELOR THESIS
Episodic and semantic memory
Theoretical and empirical issues and an introduction to the State Trace
Analysis
Name:
Ian MacCorquodale
Student No.
5686822
Supervisor:
David Neville
Date:
20-06-2011
Index
Abstract
2
1 Introducing the dissociation
3
1.1 The history of the episodic–semantic dissociation
4
2 Memory
6
2.1 Episodic memory
6
2.2 Semantic memory
8
3 Episodic and Semantic memory
10
3.1 Functional interactions
10
3.2 Models of memory
12
4 Conclusion
14
5 Research proposal
16
5.1 State-Trace Analysis
16
5.2 Proposal for episodic-semantic distinction application
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5.3 Simulated data
22
Literature
23
1
Abstract
Human memory is too complex and too large to be studied or referred to as if it were
one single mechanism. Over the years progress has been made in understanding
memory by dividing it into multiple components that can be studied separately.
According to Tulving (1972) the general knowledge a person possesses about the
world not tied to a particular personal experience is called Semantic memory. In
contrast, Episodic memory relates to events in their specific context of time and place.
A crucial question remains: are episodic and semantic memories functionally
dissociated or are they expressions of one underlying system? The application of a
statistical technique called State-trace analysis could further clarify the episodicsemantic distinction and lead to re-appraisal of how memory models should be
formulated and tested.
2
1. Introducing the dissociation
From the moment we are born we are exposed to an enormous amount of information.
All the information we gather throughout our lifetime is said to be stored in our
memory. We can form memories almost instantaneously, and some of these last a
lifetime. A life without memory is unthinkable. When you try to remember the first
time you rode a bicycle as a child, you can picture yourself on the bicycle again as in
some kind of mental time travel. However when someone asks you how many wheels
a regular bicycle is equipped with, you “know” the answer right away without having
to actively picture it or even think about it. There seems to be a difference between
remembering and knowing when it comes to human memory.
In 1972, Endel Tulving proposed
that explicit long-term memory
consists of two types: Semantic
and Episodic. He defined episodic
memory as “a system that receives
A model of long-term memory
and stores information about
temporally dated episodes or events, and temporal-spatial relations among them”
(Tulving, 1984, p.223). In contrast, “Semantic memory is the memory necessary for
the use of language. It’s a mental thesaurus, organized knowledge a person possesses
about words and other verbal symbols, their meaning and referents, about
relationships among them, about rules, formulas, and algorithms for the manipulations
of these symbols, concepts, and relations.” (Tulving, 1972, p.386). The actualization
of episodic information is typically deliberate, often requires conscious effort, and is
informally termed “remembering,” while that of semantic information is usually
automatic, and is often referred to as “knowing”. (Tulving, 1984). In other words,
Tulving proposed a distinction between an autobiographical memory of personal
events, and a memory that applies to our store of culturally shared general knowledge
about the world and facts detached from autobiographical reference. Despite the
plausibility of this distinction research has yet to provide conclusive evidence that
these two systems are functionally separate.
Researchers in a number of areas, including neuropsychology, animal
learning, and cognitive psychology, have stated that it is useful to investigate the
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existence of multiple memory systems because it allows one to distinguish between
two forms of memory that intuitively seem different phenomena. Methodologically
research has focused on identifying dissociations between the two memory systems:
finding manipulations and tasks that have different effects on each of the systems.
When one variable has different effects on two tasks a dissociation is shown. These
dissociations lend support to the hypothesis of multi memory systems. Over the years
progress has been made in understanding memory by dividing it into multiple
components that can be studied separately. For example, distinctions have been
proposed that are now widely accepted, such as the short-term and long-term memory
distinction.
However, a crucial question remains: are episodic and semantic memories
functionally dissociated or are they expressions of one underlying system? For over
20 years a number of studies have adduced both empirical and theoretical arguments
in favour of either the former or the latter hypothesis. For this paper a critical review
of past and recent studies will be given in order to propose a clear taxonomy of the
effects and of the theoretical models, which dissociate episodic and semantic memory.
Before this question can be more fully explored, it is necessary to define more
precisely the differences between the two proposed memory systems.
1.1 The history of the episodic-semantic dissociation
The dissociation Tulving proposed was not entirely a new one. In Confessions and
Enchiridion (cited by Herrmann 1982, from Augustine, 1955) in 410 BC, the
philosopher Augustine made a distinction between “things learned or intuited, and
principles” and “ images of things perceived and of feeling”. In 1890 The American
pioneering psychologist and philosopher William James defined memory as
pertaining to facts, or events. He also devoted one chapter of his famous work “the
Principles of Psychology” (James,1890 cited by Herrmanns 1982) to factual
knowledge and another chapter to memory of one’s past. Not much later, Wilhelm
Wundt (1896) distinguished between memory as used in cognition and memory as
used in recognition. In the field of psychiatry, Schactel (1947) proposed that memory
was practical, based on general knowledge, or autobiographical (Hermann, J, D,
1982).
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The first proposal that different neurological systems underlie long-term
memory phenomena was made by Eduard Claparede (1951). Based on observations
of amnesiacs, he discerned that patients could recall "passive associations or idea
reflexes" which he called marginal memories, even though they could have great
difficulty recalling events from their own pasts. These he called egocentric memories.
This observed distinction was later extended by Nielson (1958), who differentiated
between temporal amnesia, involving a loss of personal experiences, and categorical
amnesia, involving a loss of acquired facts (Crovitz, cited by Herrmann, J, D, 1982).
All together a total amnesia for episodic information with an unimpaired semantic
memory does suggest a dissociation between episodic and semantic memories.
In 1989, Tulving described an elaborate study of a patient called K.C. In a
motorcycle accident K.C. experienced severe brain damage to the frontal regions. As
a result of this damage he showed a complete loss of his own episodic memory.
Interestingly his semantic memory system seemed to work fine. Another well-known
case discovered by a neurosurgeon named William Scoville shows an opposite
dissociation. After performing surgery on a
patient called H.M. the patient completely
lost the ability to store new information. In
an attempt to cure H.M. of his epileptic
seizures he had sectioned parts of both the
left and right side of the patients
hippocampus. “Surgery had interfered with
Damage to these regions caused amnesia
in patients K.C and H.M.
the process of storing or retrieving new
memories but had
not touched previously stored memories” (Corkin, 2002).
It is clear that for a long time people from different scientific fields have
noticed the difference between the two types of memories. In this sense, Tulving’s
initial intent was to avoid confusion between episodic and semantic memory research.
In his 1972 article Tulving stated that “this distinction is not necessarily a functional
one, but merely for the convenience of communication”. This is because until then,
both phenomena were referred to as just one memory and researched as such. The
whole concept has undergone significant changes over the years. Later on in his work,
Tulving and other researchers explicitly assumed them to be functionally separate
systems, and directed their research accordingly. Tulving brought to light some of the
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substantial differences between episodic and semantic memory and in the next part I
will further elaborate on the functionally different properties held by each system.
2. Memory
2.1 Episodic memory
Our previous individual experiences help us determine who we are. All of our
preferences, dislikes and opinions that are a result of experiences we have had, and
influence the way we approach new situations. These episodic memories of events we
have experienced help guide our actions in the future and therefore it is important to
clarify all the characteristics of the episodic memory.
Along with Hans J. Markowitsch, Tulving explained the uniqueness of
episodic memory in their 1998 article; “Episodic memory is the only form of memory
that, at the time of retrieval, is oriented towards the past: Retrieval in episodic
memory means ‘‘mental time travel’’ through and to one’s past. All other forms of
memory, including semantic, declarative, and procedural memory, are, at retrieval,
oriented to the present” (Tulving and Markowitsch, 1998). Also, “The relation
between remembering and knowing is one of embeddedness: episodic remembering
always implies semantic knowing, whereas knowing does not imply remembering”.
Since this system is context sensitive, both encoding and retrieval phases process
events in relation to their time and space. This aspect has been formulated by
Thompson and Tulving in 1970 as the notion of encoding specificity. Research has
shown that when a list of words was presented with sound in the background
(instrumental music or white noise), then recall tested 48 hr later was better and
forgetting was less if the acoustic background was re-instated rather than changed or
removed. If learning occurred with quiet background conditions, recall performance
was the same whether testing took place with quiet, music, or white noise in the
background (Smith, 1985). Previous studies by Godden and Baddeley (1975) found
similar results by showing that divers recalled words better when the recall condition
matched the original learning environment, either underwater or on land. Apart from
these external contextual differences, internal contexts like emotions or mood also
influence our memory of information. Our memory of information is better if we are
in the same mood we were in when we where encoding the information (Blaney,
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1986). Another study where people learned information while they were drunk or
sober showed that memory was better when these people were in the same
psychological state at recall. Those who studied drunk performed better in the test if
they took it whilst being drunk (Goodwin et al., 1969). A common method for
measuring the episodic memory is the Recognition Task. During the study phase of
this test participants have to asses how familiar a word is. During the test phase
participants have to decide whether or not a word has been shown before during the
study phase. What is used for analysis is the proportion of words that were correctly
recognized.
According to Tulving episodic memory differs from semantic memory by the
way the memory is encoded. Episodic memories are filled with contextual properties
such as emotions and location because they are part of this type of memory. What is
stored in the episodic memory is not just the words presented to the subject under
water, but the entire event. Episodic memories contain information on how these
memories were created. In contrast the semantic memory is less sensitive to
contextual influences during retrieval because these contextual factors are not stored
in the semantic memory. However there is a problem with this statement because
often very little is known about the specific context wherein for example someone has
learned what a bicycle is. This makes it very difficult to examine whether the
semantic memory is actually less context-dependent.
Another important difference between episodic and semantic memory is that
the episodic memory is more subject to forgetting, more vulnerable, than semantic
memory (McKoon & Ratcliff, 1986). The episodic memory system cannot hold on to
all attended information forever. Over time we lose access to many memories of our
specific past experiences, but the general knowledge that is extracted from those
experiences often stays with us in the form of semantic information.
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2.2 Semantic memory
The general knowledge a person possesses about the world not tied to a particular
personal experience is called semantic memory. Literally translated “memory for
meaning”. Semantic memory is quite different from episodic memory in the sense that
contextual information encoded at the time of learning is lost. An example of
semantic memory would be a discussion you have with someone in which the other
person mentions owning a bicycle. Rather than visualizing a specific episodic
memory of a bicycle, you can access the semantic definition of a bicycle instantly to
understand what the other person is talking about. In contrast to episodic memories,
all the information is free from context and only an abstract form of information is
stored which can be used in novel situations. Without this semantic memory, every
time you would see a pencil on a desk you would have to determine its function.
An important characteristic of the semantic memory is the organized structure it
possesses. Remembering one particular fact brings related facts closer to
consciousness. This facilitation of related concepts is called “spreading activation”.
Collins and Quillian (1969) viewed the structure of the semantic memory as a
network. Within this network each
concept is represented as a node.
Each of these concept nodes are linked
together by pathways of associations
between concepts. This explains why
related concepts are facilitated when a
A network model of memory
organization (Collins & Loftus 1972)
particular concept is activated. For
example, when you read the
word “boat” its mental representation becomes activated and therefore activates
all the nodes connected to it like “sea” or “water”.
Another important feature of semantic memory is the accessibility of the
information. Retrieving information from semantic memory is said to be fully
automatic and will cost no effort. Retrieving episodic information on the other hand is
said to be a process that does require effort and is not automatic. As seen in the
previous example about spreading activation, whenever a word is presented it is the
meaning of this word that is immediately activated and not a specific event related to
the word.
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The organization of semantic memory appears to be much more structured and free
from error in comparison to the episodic memory. The information stored in the
episodic memory is more prone to error due to the loose structure it possesses, and the
information is easier to be lost because it applies only to one single specific event. In
semantic memory, the information is often learned in a better way and less vulnerable
to forgetting because it is embedded in rich cognitive structures. However semantic
memory retrieval is not entirely free of error either.
In 1981 Erickson and Mattson investigated a phenomenon called the semantic
illusion. In their study, people were required to answer a set of questions, four of
which contained semantic anomalies, such as “How many animals of each kind did
Moses take on the ark?” Participants were told that they had the option to say “don’t
know” if they did not know the answer or “wrong” if the question had something
wrong with it. The researchers discovered that as many as 80% of their participants
failed to detect the error that was hidden in the sentence even though they did know
that it was Noah, and not Moses, who took the animals on the ark (Erickson &
Mattson, 1981). They attribute this phenomenon to inappropriate activation of
information in semantic memory. Similar language components such as similar names
can cause information to be accessed in an inaccurate way, which can subsequently
lead to such mistakes.
In summary, episodic memory is more subject to forgetting and more
vulnerable in comparison to semantic memory. The information in semantic memory
can be inappropriately activated due to overlapping lexical information. Both
semantic and episodic memory systems appear to be not entirely free from error. In
the next part I will closely look at whether there are more functional properties that
are shared by the two systems. Secondly, I will cover the empirical evidence
supporting a multiple systems view.
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3. Episodic and semantic memory
3.1 Functional interactions
There appear to be numerous and distinct differences between episodic and semantic
memory characteristics. However, before assuming that these observed differences in
fact imply functionally separate memory systems, I will discuss some arguments
opposing the episodic-semantic distinction.
Some investigators, including Tulving, have adopted the functional distinction
position, while others have embraced a single-store view of long-term memory. Two
researchers by the names of Anderson and Ross explained in their 1980 article that;
“there are two kinds of empirical results that are particularly diagnostic in evaluating
the semantic-episodic distinction. One is whether similar memory effects are obtained
in experiments on episodic as in experiments on semantic memory. Similar effects
would be evidence that the two types of knowledge obeyed similar functional laws and
would be evidence against a functional distinction” (Anderson and Ross, 1980). In
their article they discuss the observed similar effects for the two memory systems and
the transfer from episodic memory to semantic memory as two types of empirical
evidence against a separation between the memory systems. The purpose of their
article was to question whether there is any functional difference between the memory
that stores semantic knowledge and the memory that stores episodic knowledge. In
order to do so they wanted to find out if the time to retrieve semantic information
could be affected by the prior learning of episodic information. In other words, does
the learning of episodic material interfere with the retrieval of semantic? They argued
that if this were the case it would indicate that the same processes are at work in both
semantic and episodic memory. Another argument that would imply the functional
separation of the two systems is the transfer of information. According to this view,
episodic memory is not stored in the semantic memory, therefore suggesting that the
two systems are functionally separate.
McKoon and Ratcliff (1979) proposed arguments against a functional
distinction by explaining that a functional separation of semantic and episodic stores
can be concluded only when evidence shows that semantic or episodic information is
independently accessible. To examine whether semantic information is independently
accessible from episodic information they used a prototypical lexical decision task. In
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a lexical decision task subjects are presented with a string of letters on a computer
screen and have to decide as fast as they can whether the string of letters form a word
or not. In this task the response time is essential. When a word is presented shortly
before the target word the response time is affected. Meyer and Schvaneveldt (1976)
found that the response to confirm whether the presented word is actually an existing
word was faster if the word preceding target word, called the prime, is semantically
related to the target word. For example, response time will be faster when the prime
word flower is shown shortly before the target word blossom. If the word bread is
used as a prime word this should not lead to a faster response. This effect is called
associative priming. As explained before, the highly structured organization of
semantic memory is the explanation for this effect. The semantic network where each
concept is represented as a node and is linked with other nodes causes activation of
one node to spread the activation through these links to the related nodes. Because the
word pairs in former studies were all well learned semantic associations, McKoon and
Ratcliff were interested in the question whether this effect would still occur with
newly learned word pairs and thus invoke the episodic memory.
In their experiment subjects were taught pairs of words that were not highly
associated semantically before the experiment. The association resulting from the
newly learned word pairs is called episodic association. Again they used the lexical
decision task to examine the amount of priming. Their experiment showed about the
same size of priming effects in lexical decision between newly learned word pair
associates as in the task with well-learned semantic associations. McKoon and
Ratcliff regarded this finding as evidence for the interaction between episodic and
semantic information in a standard semantic memory task. This interaction would not
be expected under the assumption that the memory systems are independently
accessible. Thus, such an effect argues against a functional separation of episodic and
semantic memory systems.
Durgunoglu and Neely (1987) also found episodic priming effects in a lexical
decision task but only when a certain amount of requirements were met. Typically,
Carroll and Kirsner (1982) did not find any episodic priming effects in their study.
However, in their experiment they presented the two novel words together and the
lexical decision had to be made when the two words were again presented together.
This indicates that priming as an effect is very sensitive to the variations in
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experimental procedures and therefore not conclusive evidence against a functional
separation.
Many researchers have tried to find evidence that provides an answer to the
question whether the episodic and semantic memory systems are functionally
separate. Often the question is answered with more questions leading to an
inconclusive discussion. The formulation of ideas and questions about memory
systems in mathematical form, thereby the creation of formal models of memory,
assumptions and predictions can be investigated more accurately, therefore providing
novel explanations for previous findings alike. At this point the episodic-semantic
distinction looks like a descriptive list of features. The simple labelling of effects as
episodic or semantic does not provide a theoretical explanation but merely a
categorization. The construction of a model for human memory provides a rigorous
way to test theories against empirical data. In the next part several models will be
described in order to give a clear overview of semantic-episodic memory models.
3.2 Models of memory
In 1976, John Anderson proposed a general theory of cognition that focuses on
memory processes called the ACT (Adaptive Control of Thought) theory. In his most
recent version of this theory, the ACT* model (1983) there is no functional distinction
between episodic and semantic information regarding storage or retrieval. It is
essentially viewed as one big memory. According to this model, all information,
episodic and semantic is stored together in a propositional network similar to the
semantic network theory discussed earlier and long-term memory is represented by a
network with connected conceptual nodes. The difference is that the network nodes
have a continuously altering strength of activation. In other words, if node A has an
associative link to node B, activation will spread through the link from A to B with
the load of activation of node B being determined by the strength of the link. One
important difference between the semantic network theory and the ACT model is the
introduction of token nodes. These nodes differ from the so-called type nodes that
resemble the nodes in the former semantic model. Token nodes refer to specific
events. For example, a “bicycle” type node stands for bicycles in general, but a
“bicycle” token node stands for one specific bicycle like “the one across the street”.
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Through the network structure and the spreading activation mechanism the ACT
Theory provides an explanation for the associative priming effects found
experimentally. However this single memory system model cannot provide an
explanation for the variety of results found in episodic priming experiments.
A model that proposes separate storage mechanisms is the SAM (Search of
Associative Memory) model proposed by Raaijmakers and Shiffrin (1981). During
storage, information is represented in memory images that contain associative and
contextual information. According to the model the act of remembering is the endresult of a matching process between the information of the cue and the information
of the memory trace. That is why in SAM, when any two items simultaneously
occupy the memory the strength of their association is incremented. Thus, items that
are presented in pairs more often are more strongly associated. In this model
information is also associated with the specific context, and the strength of that
association is determined by how long each item is presented in the context.
Memories consist of a set of associations between items in memory and between
items and contexts and of a parallel mechanism combining episodic and semantic
memory information.
Like the ACT* model, the MINERVA 2 model by Hintzman (1986) is also a
multiple trace model. One of the main goals of this model was to explain memory for
individual experiences (episodic memory) and memory for abstract concepts
(semantic memory) within one single system. The notable difference between the
former two models is that the MINERVA 2 model assumes that a new memory trace,
called an echo is formed that composes of all the activated memory traces.
All of these multiple trace models propose that information is stored
separately. Two models in particular propose that information is stored in a
distributed fashion: the Theory of Distributed Associative Memory (TODAM) by
Murdoch (1982), and the Composite Holographic Associative Retrieval Model
(CHARM) by Eich (1982). In these models, associative information is stored as a
memory trace in the form of a convolution of the two item memory trace vectors, and
both item and associative information are then represented as traces distributed across
a set of shared memory elements.
Mathematical models can describe memory in a more precise way than verbal
descriptions. The network model by Collins and Loftus neatly describes the structure
of memory while the other models discussed focus in particular on the processes and
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on the retrieval mechanisms. When it comes to the episodic-semantic distinction a
satisfactory conclusion has yet to be provided. In order to provide a unified model of
long-term memory, it is a necessity to know whether semantic and episodic memory
rely on a single underlying system. So far, no conclusive evidence has reached the
surface. What is specifically called for is conclusive statistical data able to state
whether one or two systems underlie episodic and semantic memory.
4. Conclusion
The theoretical work of Tulving (e.g., 1972, 1984) has opened the field of memory to
extensive empirical investigation. The heuristic value of the episodic vs. semantic
distinction for classifying types of information or experimental manipulations is quite
apparent (Tulving, 1985). Still, the crucial question remains, whether this dichotomy
accurately reflects the way the human brain actually processes information. Still today
there are researchers embracing either the two-store model or the single-store model
of long-term memory.
When the ability to form new autobiographical memories is lost but the old
memories are intact, one could say that the episodic memory system is damaged and
the semantic memory system remained intact. One could call this evidence for the
operation of dual processes. In other words, something is changed that affects one
process but not the other. A limitation with data from lesion studies, however, is that
it gives information only concerning whether the specific damaged region is somehow
necessary for task performance. Plus, evidence that different tasks are sub-served by
different brain regions does not immediately imply functionally different systems.
Willingham and Goedert (2001) clarify this example with an analogy: “One could
draw an analogy to a computer hard drive: If two Microsoft Word documents occupy
different parts of a computer’s hard drive, does that indicate that there is a
fundamental difference between them? No, because the representation format and the
processes (i.e., software) need to interpret that the two files are the same, despite their
different “anatomic loci.” By the same token, Microsoft Word and Microsoft Excel
documents would be considered different, even if they occupied neighboring or even
interleaved portions of the hard drive, because they use different formats and because
different processes are required to interpret them. We could apply the same logic to
memory. Anatomic separability is not enough. There must be a difference between
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the representations at a cognitive level of description to draw the conclusion that they
are truly different and represent separate memory systems. It is becoming increasingly
clear that complex cognitive and memory processes rely on the integrity of extended
networks of brain regions rather than on the workings of individual regions.
The reliance on dissociations in the episodic-semantic distinction is therefore
problematic. Hintzman (1984) pointed out that when one variable shows different
effects on two tasks this is viewed as dissociation. However, when variables are found
that have one effect on semantic- and a different effect on episodic memory, there is
nothing that predicted which way around the dissociation should have occurred. This
way every dissociating result would count as evidence for the proposed distinction.
Dissociation says nothing about causation.
As for the results found in patients suffering from brain damage, David Horner
pointed out that “among the experiments that have demonstrated dissociation of
episodic and semantic memory, many of the results can be explained without
invoking the existence of separate memory systems” (Horner, 1990). This is because
many semantic memory tasks, like word recognition, require the subject to recall well
learned information, a type of information preceding brain damage that has been often
repeated, well consolidated and over-learned.
With the crucial question still unanswered, with researchers still apposing
either the multi-store model or the single-store model of long-term memory, statetrace analysis can clear the sky and provide researchers with clear and concluding
evidence concerning the underlying memory systems.
To give a concrete example of how state-trace analysis can be fruitfully
applied to memory research, in the next section I will provide a proposal for an
experiment.
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5 Research proposal
5.1 State-Trace Analysis
In 1979, Donald Bamber developed a method of testing simple theories of causation
which he called State-Trace Analysis. A theoretical structure is a model proposed to
explain empirical observations and the purpose of state-trace analysis is to test the
validity of these theoretical structures by analyzing the state traces, which appear as
curves in the accompanying plots.
Figure 1: Idealized state-trace plots.
Each data point represents the average proportion correct
(from Newell & Dunn, 2008).
Bamber explains a state trace as a plot graph showing the co-variation of two
dependent variables. Multiple process models are often advanced on the basis of
dissociations in data and the main advantage of such an analysis is that “State trace
analysis can be used to evaluate conceptualizations of single- and multi-dimensional
theoretical structures, independent of preconceptions or assumptions about the nature
of the proposed processes and without using the flawed logic of dissociations”. “The
crucial diagnostic feature of this plot concerns whether or not, across a set of
experimental conditions, the data fall on a single, monotonically increasing (or
decreasing) curve” (Newell & Dunn, 2008). So, if the performance measured by two
tasks depends on the same underlying dimension, the relevant data should fall on a
monotonically increasing curve in the state-trace plot as seen in Figure 1 (a). If on the
other hand, more than one underlying dimension is required to account for the data, a
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two dimensional state-trace plot would be expected, reflecting the involvement of two
systems during task performance (Figure 1, b).
So far, state-trace analysis has already been successfully applied in other
experiments: by Dunn (2008) on the Dimensionality of the Remember-Know task and
by Loftus, Oberg and Dillon (2004) on the Face Inversion Effect. In particular the
latter study investigated the finding that inversion disproportionately affects face
recognition, thereby suggesting that faces are encoded in a different way compared to
other stimuli types. When Loftus et al. tested this effect using state-trace analysis,
they initially found evidence for a one-dimensional encoding of unfamiliar faces.
However, when they tested for encoding of familiar faces they found evidence for a
two-dimensional system.
As shown in the study by Loftus et al. and argued by Newell and Dunn, the
role of dissociations should be replaced by state-trace analysis because the latter
approach is founded on logical principles and overcomes the flaws of dissociation
logic. The application of this statistical technique could finally shed light on the
episodic-semantic distinction and lead to re-appraisal of how memory models have to
be formulated and tested.
5.2 Proposal for episodic-semantic distinction
State-trace analysis (Bamber, 1979), which has also been called dimensional
analysis (Loftus, Oberg & Dillon, 2004) can be applied to examine whether there is
one or more processes underlying episodic and semantic memory. Considering the
results from studies on patients with brain damage it is safe to say that more than one
cognitive process is involved in memory functioning. To investigate whether a
dissociation between episodic and semantic memory can be made I propose a state
trace analysis experiment. I will first give an example of how the analysis can be
applied and follow with a proposal.
Newell and Dunn (2008) use the example of a category learning experiment
because, much like the semantic-episodic distinction, it is a debate whether a singleor a multi-process explanation best accounts for the results.
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In this hypothetical experiment participants are divided into four groups. Two of these
groups are trained in a “procedural task” that is assumed to be learned without tapping
into the working memory. The other two groups are given a “declarative task” which
is assumed to involve the working memory system. Before the first test, one out of
each of the two groups is required to perform a concurrent working memory task
during the training phase. Figure 2 (a) shows a uni-dimensional model for the
relationship between the independent and dependent variables. The two factors,
number of training trials and the working memory load show the effect on the
underlying dimension. This underlying dimension is responsible for the performance
of the two tasks. Figure 2 (b) shows a model with a second underlying dimension only
influencing the task that claims to require involvement of the working memory.
Figure 2 (a)
Figure 2 (b)
Now, performances on the two tasks are plotted against
each other for both working memory conditions; load
versus no load. Each point in this plot represents the
average proportion of correct responses of the training
trials. As explained before, if performance on a task
depends upon two dimensions, the resulting state-trace
will not be a monotonic curve (figure 3).
Figure 3
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Dimension factor
According to Heathcote & Prince (2009) State-trace analysis is most easily
explained with reference to a state-trace plot. “A scatterplot showing the covariation
of two factors, a state factor and a dimensional factor. The state factor defines the
axes of the plot. Each point on the plot is defined by a pair of dependent variable
values, one for each level of the state factor”. The causal variables which are
manipulated to differentially influence the latent configurable dimension is the
dimension factor.
For the proposed state trace I will use the following manipulations that
correspond to the three factors needed in state trace. As the dimension factors I
suggest the use of two memory tasks. The lexical decision task which is assumed to
rely heavily on semantic information and the recognition task that relies on episodic
information. A prototypical recognition task consists of a study- relax- and test phase.
During the study phase participants have to assess how familiar a presented word is
according to their opinion on a numerical scale ranging from 1 to 5. During the relax
phase of about 5 minutes a simple computer game should be used to clear the working
memory. It is of importance the game does not interfere with the previous task
meaning there should be no words involved. A puzzle video game like Tetris would
fit that description seeing it involves only sequences of shapes which have to be
manipulated to form lines. During the test phase participants have to decide whether a
presented word has been seen before during the study phase or not. What is of interest
in this task is the level of accuracy. Meaning the proportion of correctly assigned
words that indeed where shown during the study phase.
In the lexical decision task a string of letters will be shown and participants have to
decide as quickly as possible whether the presented word exists or should be
classified as a non-word. The time it takes for a participant to classify a word as either
existing or non-existing is of interest.
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State factor
The manipulation used as state factor in both tasks should be word frequency.
Meaning how frequently a word is used in a specific language. Two lists of words
have to be composed. One with high-frequently used words and one with lowfrequently used words.
Trace factor
The third manipulation called the trace factor that should be applied in both tasks
should be repetition: the amount of times a word is presented during the tasks.
Multiple levels can be composed in this manipulation. For instance one level wherein
a word is shown only once and a level wherein a word is shown as many as five
times.
Now, in the lexical decision task the assumption is that reaction times
decrease when words are more frequently used in language compared to words that
are less frequently used because familiar words are easier recognized as being a word
or a non-word. This effect should not be of influence on the recognition task because
no matter how frequently a word is used you have to be able to asses whether the
word has been shown before or not. It can even be more confusing because the words
are more familiar at general and therefore lead to a poorer performance.
If declarative memory consists of one dimension, the effects on performance of the
lexical decision task and performance on the recognition task would be the same. But
if multiple dimensions are involved in declarative memory the reaction times on the
recognition task will be decreasing for high frequency words and performance will be
higher on the lexical decision task. The proposed model should consequently look like
the one in Figure 4(a) and 4(b).
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Figure 4(a)
Figure 4(b)
If performance on the task depends upon two systems, two different traces should
appear in the box plot showing different monotonic curves, since list length only
affects the episodic system and therefore performance on the recognition task. If
however one monotonic curve appears, the conclusion should be made that the
episodic and semantic memory tap into the same system, showing no differentiating
effects for the two tasks. Based on previous studies, frequency is assumed to have a
differential effect on memory systems. The higher the frequency, the better the
performance for semantic memory. The higher the frequency, the lower the
performance for episodic memory.
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5.3 Simulated data
By simulating data from 20 subjects divided over the conditions high and low
frequency items with 300 items per condition, the following plot (Figure 5) shows a
uni-dimensional and a bi-dimensional model. As explained before the semantic
memory will be measured with reaction times on the lexical decision task and the
accuracy level on the recognition task will measure the episodic memory. However
for this plot I simulated accuracy instead of reaction time which for the purpose of
merely illustrating the plot is of no importance. Performance on both tasks are
simulated. Each of the observations is generated according to a general linear model.
A non-parametric measure of statistical dependence (Spearman’s Rho) between the
two variables high- and low frequency curves is also shown.
Figure 5
The uni-dimensional model shows one monotonic curve implicating that both the
lexical decision task and the recognition task performances are based on the same
dimension. The bi-dimensional model shows two separate monotonic curves
expressing that both tasks depend on separate dimensions.
The state trace analysis has been successfully applied in previous experiments
and could provide a large contribution to memory research. Along with the data
derived from the analysis, these findings could bring researchers a step closer to
unravelling the mysteries of the human memory by providing statistical evidence of
underlying processes.
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