Perceptual activity ends with
the identification and categorization of the distal stimulus. Every act of perception is an
act of categorization (paraphrasing Bruner),
and memory provides the conceptual knowledge that permits
categorization to occur. But the relations between
perception and memory are more extensive than that:
Accordingly, a theory of social cognition must go beyond perception to describe the processes by which social memories are encoded, the structure of the memory trace, and the operations by which social knowledge is retrieved (Hastie & Carlson, 1980; Kihlstrom & Hastie, 1997).
By way of background,
let us consider some theories of object recognition in the
nonsocial domain (Humphreys & Bruce, 1989; Roth &
Bruce, 1995; Palmer, 1999).
A highly influential theory of visual perception is that of David Marr (1982), who distinguished among three distinct levels of analysis:
Marr also offered a theory of the early stages of image processing -- that is, how the retinal image is processed by early stages of the visual system.
You get the idea.
An extension of Marr's theory,
is the Recognition-by-Components (RBC) theory proposed
by Biederman (1987; Biederman & Gerhardstein, 1993).
RBC employs a more extensive list of primitives, not just
cylinders, known as geons, which is a highly generalized
set of 36 3-dimensional shapes, out of which pretty much any
conceivable object can be constructed. Think of
Legos! (Though there area some exceptions, which is a
problem for the theory.)
Two important points
about Biederman's very popular theory.
Face Recognition
But
first, let's pause to consider the fact that we don't all look
alike. While that may seem
obvious, it's been argued that most other animals
seem to look very much like each
other, and seem to recognize
each other as individuals via other sensory
modalities, such as smell or vocalization.
Michael J. Sheehan, a postdoctoral fellow at
UCB, has proposed (Nature Communications, 09/16/2014) that the reason we're
individually recognizable, on the basis of
such visual features as the distance
between the eyes, or the width of the
nose, has its basis in evolution. It's not
clear how, as Sheehan proposes, human
social structure drove the evolution of
facial distinctiveness; it might have been
the other way around, that the fact that we're so distinctive forced us to develop
certain uniquely human social
structures. But still,
evolutionary pressures tend to make
individual species members more alike
over time; but in this case, they
seem to have made us more different, at
least with respect to
faces. in
any event, we really do all look
different. Anthropometric
measurements on a sample of US Army personnel confirm that facial
traits are much more variable than
other human traits, such as the length
of the arm and the length of the leg;
and they are less strongly
intercorrelated with each
other, too.
Studies of Face Perception and Recognition
And first, let's consider
some elementary phenomena of face-recognition.
Young et al. (1985) asked subjects to keep a diary in which they recorded errors, or at least difficulties, in recognizing familiar faces. They found that particular errors were especially common.
Anyway, on the basis
of findings such as these, Bruce and Young
proposed a formal model of face recognition which has become
widely accepted. the model assumes
that there are separate systems (or modules) for various
aspects of face perception: identifying a face (which is the
primary concern of the model), analyzing emotional
expressions (a la
Ekman), analyzing facial speech (i.e., lip-reading), and directed visual
processing (e.g., examining someone's teeth for stray bits of
spinach).
Sticking with the process of face recognition:
The model provides a pretty
good account of the major phenomena of face recognition.
That doesn't mean that the B&Y model is
perfect. But it remains the best model
we have, which is why it's been so widely
embraced by other theorists.
Bruce and Young
are clear about the explicit parallels between face
recognition and other forms of recognition -- object
recognition and word recognition. In each case,
processing follows a route from the early stages of visual processing to
recognition units, then an identity unit (itself connected to
other, related semantic knowledge), then a
name code, and finally the naming response. But the
modules performing
these perceptual tasks are different.
We generally think of face recognition as a universal ability,
and prosopagnosia as a neurological condition affecting only
patients with certain forms of brain damage. However, individual
differences in face recognition may vary along a wide continuum
(Russell, Nakayama, & Duchaine, Psychonomic Bulletin &
Review, 2009). Even in the absence of demonstrable
brain damage, some people are so bad at face recognition that they
appear to have a "developmental", perhaps congenital and
inherited, form of prosopagnosia. Others, whom Russell et
al. call "super-recognizers", have an extraordinary ability to
recognize faces from different angles and in different
contexts. These individual differences are often assessed
employing the Cambridge Face Memory Test.
Broadly speaking, memory
comes in two broad forms (Winograd, 1975; Anderson,
1976):
Declarative
knowledge consists of factual statements about the world --
past, present, and, for that matter, the future. All declarative knowledge can
be represented by sentence-like propositions,
consisting of a subject, an object, and the
relation between them. The general format for a
proposition is The subject verbed the object.
Declarative knowledge can be represented in two ways:
The most popular theoretical model for memory
consists of an associative network with concepts
represented by nodes, and associative links representing the
relations between them. In an alternative
representational format, propositions themselves are
represented by nodes, associatively linked to other nodes
representing the subject, object, and relation.
In
any
event, each node in memory is associatively linked to other
nodes representing related knowledge, and each proposition is
linked to related propositions, so that the associative
network represents all of the individual's knowledge.
For example, each element in the proposition The hippie
touched the debutante (Anderson, 1976) is linked to
other nodes representing our knowledge about hippies,
debutantes, and touching. When nodes representing the
elements of a proposition are activated by perception,
activation spreads to related nodes in the network. This
spreading activation serves as the basis for priming.
The facts
comprising declarative memory can be either episodic
or semantic in nature.
In principle, every episodic
memory consists of a number of elements, each represented by
one or more propositions:
In contrast with the autobiographical
knowledge of specific events and experiences that comprises episodic
memory, semantic memory holds abstract, context free
knowledge:
Given the basic empiricist position that (most) knowledge comes to us via experience, or reflections on experience, it is evident that semantic memory begins in episodic form. When you first learn that Columbus discovered America you also remember the circumstances under which you learned that fact. However, accumulated encounters with the fact will blur the episodic features, resulting in a generic memory that makes no reference to the circumstances under which it was acquired.
Similarly, all
procedural knowledge can be represented by productions
consisting of a goal, a condition, and an action
which will achieve the goal under the condition. The
general format for a production is IF (goal, condition)
THEN (action). Productions, too, can be linked to
each other in a larger network called a production system.
Procedural knowledge comes in two broad forms:
Individual productions are embedded in
larger production systems. In a production
system, execution of one production is the precondition for
executing another. Or, put another way, execution of
each production creates the conditions under which the next
production can be executed.
The rules and skills that
comprise procedural memory can be either cognitive or
motoric in nature:
According to a theory offered by J.R. Anderson, procedural memory starts out in declarative form -- that is, as a factual list of directions -- an algorithm, or "recipe" -- that can be consciously retrieved and deliberately executed by the user. Through repeated use, this knowledge structure undergoes proceduralization, a process analogous to knowledge compilation in a computer, that changes its representational format from declarative to procedural. At this point activation of nodes representing the goals and conditions of a production will automatically execute the action.
All these forms of memory are relevant to social cognition.
On the declarative side:
Although
models such as Bruce and Young's are viable accounts of face
recognition, the fact is that we're often pretty bad at
recognizing the faces of strangers. This is demonstrated
clearly by eyewitness identification in forensic settings, where
a witness or victim has to identify the perpetrator from a
lineup or photospread. If you think about it, eyewitness
identification is a paradigmatic example of episodic person
memory: the witness or victim encounters the perpetrator just
once, during the commission of a crime; and the question is
whether the former will recognize the latter at some subsequent
time. In fact, these days, the standard police procedure
for lineups or showups (using photospreads) is to ask the
witness two questions: (1) Have you ever seen any of these
individuals before?" (2) "And if so, where?". This
is exactly what episodic memory is all about: what happened, and
in what context.
True Story: I was once asked to testify for the defense, as an expert witness on memory, in a case in which several Puerto Rican men had been charged for armed robbery of a gas station in Chicago (illinois v Ciaramitaro, Cook County, 1985). The police theory was that the men were members of the Puerto Rican National Liberation Front, and had held up the gas station to raise money to support terrorist activities. The hearing was held in a fortified courtroom, shielded from spectators by bulletproof glass. During the initial investigation, the police had shown the gas station attendant a photospread including the suspects, and he had failed to identify any of them. But later, the police showed the attendant a new photospread, with the same suspects but different foils, and asked him if he had seen any of the faces before. The attendant immediately picked out the suspects, leading to their arrest. As an expert, my job was to testify that this was an inappropriate procedure, and that the repetition of the suspects' photos might have biased the attendant toward recognition. But before I could conclude my testimony, the judge interrupted the proceedings and asked the district attorney prosecuting the case, "They did what?". When the prosecutor admitted that this had, in fact, been the procedure, the judge dismissed the case immediately.
To take just one example of the problem: according to the Innocence Project, a large proportion -- up to 75% -- of criminal convictions subsequently vacated on the basis of DNA evidence had been based on eyewitness identification.
True Story: Donald Thomson, an Australian psychologist (and the Thomson of Tulving & Thomson, 1973) was once arrested on a charge of rape based n the victim's identification. Thomson's alibi was that, at the time of the attack, he was being interviewed on television, along with an assistant police commissioner. The detective who interrogated Thomson initially didn't believe him. It turned out that the victim had been watching TV right before her attack, and apparently confused Thomson's face with that of her perpetrator (Baddeley, 1990)..
Now, from
one point of view the unreliability of eyewitness identification
should surprise us. After all, picture recognition
is remarkably good.
Doubts
about eyewitness memory really began with a study by Loftus and
Palmer (1974) demonstrating the post-event misinformation
effect. That is leading questions like "How fast
were the cars going when they _____ each other?" -- where the
blank space was filled by verbs like hit or smashed,
biased observers' memories for, or judgments about, the event
they witnessed.
It gathered steam with a series of analyses showing a surprisingly low correlation between accuracy and confidence in eyewitness identification.
Eyewitness
identification is one area where empirical research, in both the
laboratory and the field, has had a major impact on practical
application. For example, Lindsay and Wells (American
Psychologist, 1993) and others argued that sequential
lineups, in which witnesses must make individual decisions about
each target, were superior to the classic simultaneous lineup,
in which witnesses viewed all the targets at the same
time. The sequential procedure significantly reduced the
rate of false identifications, without substantially affecting
correct identifications (Wells et al., Psychological, Public
Policy, & Law, 2011). More recently, however,
the simultaneous method has come back into favor, based on a
form of signal-detection analysis (Gronlund et al, Current
Directions in Psychological Science, 2014; American
Psychologist, 2015). It turns out that the
sequential method makes witnesses less likely to identify anyone,
and this spuriously inflates the accuracy of any identifications
that are made. Employing a variant on signal detection
theory, they found that simultaneous presentation yields higher
accuracy levels than sequential presentation -- and that
confidence and accuracy are correlated after all.
After reviewing the empirical research, the National Academy of Sciences made recommendations concerning the proper handling of eyewitness testimony (Identifying the Culprit: Assessing Eyewitness Identification, 2014). For example, it recommends that jurors be cautioned that confident identifications are not necessarily accurate ones. However, they didn't make specific recommendations on simultaneous vs. spontaneous presentations.
Still, in
the present context, the bottom line of this research is that
eyewitness identifications are a lot more accurate than we
originally thought they were. This, in turn, is
commensurate with what is known about picture recognition in
nonsocial domains.
Person memory consists of a person's factual knowledge about some other person -- his or her general traits and attitudes, and his or her specific behaviors and experiences. Thus, person memory consists of a mix of episodic and semantic memories.
In general, person memory is studied with variants of the classic verbal-learning paradigm employed in the study of memory since the time of Ebbinghaus (1885). The only difference is that instead of describing a list of words, the items committed to memory describe a person.
Interestingly, when subjects study a list
of facts about a person in order to form an impression of that
person's personality, they remember the facts better than if
they studied them in anticipation of a later memory test.
Viewed from the
perspective of a generic associative-network model of memory,
person memory can be represented by a node representing each
individual person, linked to nodes representing facts about
that person. As we accumulate knowledge about the
person, additional links are created.
This structure is illustrated
by a classic experiment on the fan effect by Anderson
(1974). Anderson asked his subjects to learn simple
facts about people and locations, such as:
Note that from just these four
sentences, we have learned:
The subjects memorized such
sentences to a criterion of perfect recall. Then
Anderson conducted a recognition test in which subjects were
asked to verify whether they had studied various sentences:
Subjects
rarely
made mistakes on this task, but Anderson was more interested
in their response latencies, which varied according to the
number of facts that they had learned about various people and
locations. The more facts the subjects knew, about
either people or locations, the longer it took them to verify
any particular fact. Anderson called this outcome the
paradox of knowledge: the more you know about a subject,
the harder it is to retrieve any particular item of
information about it. The fan effect is an excellent
demonstration of inter-item interference in memory, but in the
present context it is most important for what it tells us
about how knowledge is represented in memory, and how it is
retrieved.
An interesting
problem occurs when with respect to individuation and
reference. Suppose you learn a set of facts about one
person, James Bartlett (e.g., that he rescued the
kitten), and then another set of facts about another person, The
Lawyer (e.g., that he caused the accident). Then
you learn that James Bartlett and The Lawyer
are one and the same person. Whatever you learned about
James Bartlett you also now know about The Lawyer, and
vice-versa. How is this situation represented in memory,
so that you can know that James Bartlett caused the accident
(which, of course, he did)?
One possibility is that the
two representations remain separate -- one for James Bartlett,
and one for The Lawyer. Under these conditions, we
wouldn't know that James Bartlett caused the accident, because
there is no connection between the two nodes. But we do
know this fact, so this representation can't be right.
Another possibility is that
all the knowledge about The Lawyer is linked
directly to James Bartlett, including the fact that James
Bartlett is a lawyer, and vice-versa. This permits us to
know directly that James Bartlett is the lawyer caused the
accident.
Yet a third possibility is that when we learn that James Bartlett is the lawyer, we establish a new link between the James Bartlett node and the Lawyer node. This permits us to know by inference that James Bartlett caused the accident.
In a classic study of person memory,
Anderson and Hastie (1974) used a sentence-verification
paradigm to show that response latencies for inferential
sentences were longer than those for non-inferential
sentences, but only for subjects who learned later
that James Bartlett was the lawyer. Apparently, there
are three links between the node representing James Bartlett
and the node representing the fact that he
caused the accident: And because it takes time to
trace down each of these links (that's
the implication of the fan effect), it takes longer to
verify an inferential fact.
Apparently, if we know the reference -- that James Bartlett is the lawyer -- at the outset, we build a knowledge structure around a single node representing everything we know about the person.
But when we only learn the reference later, we establish a link between two separate nodes representing, respectively, what we know about James Bartlett and what we know about The Lawyer. The extra link takes time to traverse, leading to the longer response latencies in the "reference after" condition.
So now, within the framework of a generic associative-network model of memory, we have some idea of what person memory looks like -- that is, how our knowledge about a person is represented in memory.
A great deal of research on
person memory has been devoted to studying the effects of
general beliefs and expectations, collectively known as
cognitive schemata, on memory for specific facts about
a person. Bartlett (1932) famously proposed that memory
favors schema-congruent information, but subsequent research
yielded conflicting results.
Technically, the word schema has a Greek root, and so its proper plural is schemata. However, the word has been Anglicized, and so you will often see the plural schemas instead. If you are really lucky, you will stumble on the occasional use of the word schematas as the plural for schema. Apparently, the writer didn't want to take any chances -- sort of like the kind of person who wears both a belt and suspenders to keep up his pants.
Hastie
& Kumar (1979) combined
the verbal-learning paradigm with Asch's impression-formation
paradigm. Subjects first studied an ensemble of traits
describing some person, in order to induce a schema for that
person (Judy is smart and sophisticated). Then
they studied a list of that person's specific behaviors.
Hastie & Kumar varied the mix of behaviors across conditions:
Subsequent recall testing showed that
schema-relevant items were remembered better than
schema-irrelevant items. But among the schema-relevant
items, schema-inco
ngruent items were remembered even better
than schema-congruent ones.
The findings of the Hastie & Kumar experiment illustrate the schematic processing principle of memory: the memorability of an event depends on its relationship to pre-existing schemata.
Hastie (1980, 1981) proposed a
two-process explanation for schema-dependency:
In order to test
this explanation, Hastie (1984) conducted an experiment in
which the trait ensemble was followed by a list of
schema-congruent and schema-incongruent items.
Recall testing
yielded the schematic processing effect, as expected.
However, in a second experiment Hastie asked subjects to
perform a sentence-continuation task: after each item, they
were supposed to continue it with either an explanation of the
event, an elaboration of the event, or the sequel to the
event. On a later recall test, items (whether
schema-congruent or schema-incongruent) in the explanation
condition were recalled better than those in the elaboration
or sequel condition. So, it's not schema-incongruency per
se that yields better memory: it's the explanatory
activity that schema-incongruency instigates.
Thomas Srull (1981) offered a
somewhat different explanation for schema-dependency, within
the framework of a generic associative-network model of
memory. He pro
posed
that nodes representing individual episodes are linked to a
node representing the person, in the usual way. Then,
connections among nodes are produced by virtue of processing
at the time of encoding -- such as explaining
schema-incongruent items in light of the schema.
However, nodes representing schema-incongruent items are
associatively linked both to each other and to nodes
representing schema-congruent items as
well.
In his experiment,
Srull, like Hastie & Kumar, varied the
mix of behaviors: 12 schema-congruent,
12 schema-neutral (or schema-irrelevant),
and either 0, 6, or 12 schema-incongruent
behaviors. Testing recall,
Srull obtained the usual schema-dependency effect.
Schema-relevant items were recalled better than
schema-irrelevant items, and schema-incongruent items were
recalled better than schema-congruent items.
Then, Srull employed a
sentence-verification procedure, not unlike that which had
been used by Anderson & Hastie (1974), to examine priming
effects on recognition memory.
Srull compared
response latencies to verify schema-congruent, incongruent,
and -irrelevant items, depending on the immediately preceding
item. Compared to a baseline provided by processing of
schema-irrelevant items served as a baseline.
Schema-congruent items primed responses to schema-incongruent
items, while schema-incongruent items primed both
schema-congruent and schema-incongruent items;
schema-irrelevant items didn't prime anything. These
results are consistent with Srull's hypothesis, that
schema-incongruent items are linked to each other and to
schema-congruent items, but that schema-congruent items are
not directly linked to each other.
Srull's
model shows how
behavioral episodes are represented in person memory, and
presumably more abstract, generic trait information is
represented the same way -- as nodes representing traits
linked to a central node representing the person.
However, there is another possibility: given that traits are
categories of behaviors, it is possible that traits organize
behavioral episodes in memory -- that is, that nodes
representing traits are linked to nodes representing the
behaviors that exemplify or instantiate them.
Category Clustering
In
fact, there is a long tradition in the study of nonsocial
memory which supports the idea that abstract categories
organize more concrete information in memory. For
example, if subjects study a list of words, some of which are
instances of various conceptual categories, their recall will
tend to be organized by category - a phenomenon called category
clustering.
In the early 1950s, as one of the
earliest shots in the "cognitive revolution" in the study of
human learning and memory, Bousfield and his associates showed
that category clustering increased over trials, just as recall
itself did. This is consistent with the organization
principle in memory processing.
Consistent with the organization principle, some theorists have proposed a structure of person memory in which "trait nodes" fan out from "person nodes", and that specific "behavior nodes" fan out from the trait nodes, has been very popular. Certainly it is a highly rational way to organize person memory. Accordingly, some investigators have tried to demonstrate that person memory is, indeed, organized by traits.
Certainly,
person
memory is organized by person. In one
experiment, Ostrom et al. (1981) had subjects study five
sentences each about 5 familiar people (e.g.,. Clint
Eastwood is an actor) and about 5 unfamiliar people
(e.g., Clark Patterson is a comedian). The 50
sentences were randomized at presentation, but Ostrom et al.
found that subjects' recall tended to be organized by person
-- e.g., they recalled several Clint Eastwood facts before
recalling several Clark Patterson facts, etc.
But is recall of facts about a single
individual person organized by that person's
traits? In one study, Hamilton, Leirer, & Katz
(1979) had subjects study a list of 16 sentences, 4 each
describing a person's socially desirable, intelligent,
athletic, and religious behaviors. As expected,
recall was better under impression-formation instructions
compared to a memory set. But although the level of
category clustering was significantly greater than zero, it
was not very high in absolute terms.
In
a similar study, Hamilton, Katz, &
Leirer (1979) gave subjects 8 study-test trials, instead of
only one or two, as in the previous study. Recall grew
appreciably over the 8 trials, but clustering remained at
rather low levels. Although Hamilton et al. claimed
these two studies as evidence for trait-based organization of
person memory, which they are, kindasorta, it has to be said
that there wasn't much trait-based organization in evidence.
Further
doubt was cast on the organizational
hypothesis by a study by Smith & Kihlstrom (1987), which
used Norman's (1968) set of Big Five traits as stimulus
materials. After 5 study-test trials, there was very
little evidence of category clustering -- especially compared
to a standard experiment of the type performed by Bousfield
and his associates, using nouns instead of trait adjectives as
stimulus materials.
Even more doubt was cast by an experiment
by Dabady, Bell, & Kihlstrom (1992) which used sentences
describing specific behaviors related to the Big Five, instead
of trait adjectives, as stimulus materials. The
sentences were presented either randomly, or blocked by
trait.
Blocked
presentation yielded slightly
worse recall than random presentation, suggesting that
subjects didn't capitalize on the traits to organize their
memories. And category clustering was at very low levels,
approaching zero.
Priming of Behaviors by Traits
The coup de
gras to the organization hypothesis was administered by
a series of studies performed by Klein, Loftus, and their
colleagues. In one experiment, Klein and Loftus (1992)
presented a list of 20 behaviors, 4 instances of each of 5
traits (athletic, intelligent, honest, religious, and
sociable) under three different conditions (impression
formation, memorization, and category clustering).
There was some evidence of category clustering in
the impression and memorization conditions, as in Hamilton's
studies, but the level of clustering was much less than that
observed when subjects were actually
asked to sort the behaviors into the appropriate trait
categories.
A second study, by Klein, Loftus, et al.
(1992), capitalized on priming, as in the earlier study by
Srull. If trait nodes are interposed between person
nodes and episode nodes, then activating the trait nodes
should prime retrieval of trait-related behavioral
episodes. Klein et al. first asked their subjects to
rate their own mothers on a list of trait adjectives.
Then, in the experimenter proper, the subjects were presented
with the trait terms and asked to perform one of three tasks:
If traits organize memory, then rating a
trait for its descriptiveness should prime retrieval of
trait-related behaviors. As it turned out, there was no
priming for traits that were highly descriptive of the
subjects' mothers: response latencies in the recall task were
no shorter when it was preceded by the describe task than when
it was preceded by the define task.
For traits that were less descriptive of
their mothers, however, there was such priming. Klein et
al. concluded that highly descriptive traits are represented
independently of trait-related behaviors. In order to
account for the priming effect observed with less-descriptive
traits, Klein et al suggested that these trait judgments are
based on the retrieval of exemplary behaviors. In
effect, then, in the case of less-descriptive traits, it is
the retrieval of exemplary behaviors, not retrieval of the
trait itself, that is responsible for priming the retrieval of
other exemplary behaviors.
Episodic and Semantic Self-Knowledge in Amnesia
Neuropsychological evidence
converges on the conclusion that knowledge
of traits is represented independently of knowledge of
behaviors. Patients suffering the amnesic syndrome
following damage to the hippocampus and the medial portions
of the temporal lobe cannot remember "post-morbid"
events that happened after their brain
damage occurred. This means that they lose
autobiographical memory. Yet they do retain semantic
knowledge of themselves, in terms of their personality traits.
Actually, there
are two temporal (time-related) forms of amnesia:
So, despite his total lack of episodic memory, K.C. nevertheless had fairly accurate semantic self-knowledge, of what he was like as a person. Yes, it would have been interesting if Tulving had also assessed K.C.'s knowledge of his premorbid personality, but Tulving didn't do that.
Watch Tulving Interview Patient K.C. on
YouTube
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With these sorts
of results in hand, we can draw some conclusions about the
representation of persons in memory:
The kinds of memory models discussed so far
are known as symbolist and declarativist
in nature.
These models are, by far, the most popular in both cognitive psychology and social cognition. But they do not exhaust the possibilities, and some theorists have proposed alternative architectures for both nonsocial and social memory.
Some of these models are proceduralist in nature, because at least some knowledge is represented procedurally, as production systems, rather than declaratively, as propositions. Rather than encoding all person memory in propositional form, at least some aspects of person memory are not encoded at all, but rather are computed as needed, on line, by executing various productions.
Among the most prominent such models in
person memory is one proposed by Smith (1984), in which
behaviors are represented declaratively, as in the Srull-Wyer
model, but traits are not represented at all. Instead,
trait information is computed as needed by productions that take
the following form (very roughly):
A model like this underlies Bem's self-perception theory of attitudes, which holds that people do not actually hold attitudes about various objects and issues. Instead, when asked their attitudes, they infer what their attitudes must be, based on their perception (and memory) of their own behavior.
The declarativist and
proceduralist views of person memory are both "symbolic "
models of knowledge representation, in which items of
knowledge are represented symbolically, as propositions or
productions, located at nodes in an associative network.
An alternative view, known as connectionism, dispenses
with the idea that knowledge is represented at discrete nodes
in an associative network. Instead, it asserts that
knowledge is represented as a pattern of activation
across all the elements of a network.
So, two different pieces of knowledge, such as Judy attended the symphony concert and James Bartlett rescued the kitten are not associated with different nodes in a network, but instead are represented by the same nodes -- that is, by the same processing elements. They simply differ in the pattern of activation in the associative pathways connecting the processing elements.
Connectionist models are sometimes called parallel distributed processing (PDP) models, because all the elements are activated simultaneously (instead of a more serial view in which activation takes time to spread from one node to another), and because knowledge is distributed across the entire network (instead of being associated with discrete nodes). They are also called parallel constraint satisfaction models, because the pattern of activation in the network is constrained by both the inputs and the outputs to the network. In the domain of social cognition, Kunda & Thagard (1996) offered a connectionist, "parallel constraint satisfaction" model of impression formation that is based on a generic connectionist model of memory.
Connectionist models are sometimes
favored over symbolic processing models because they are more
"neurally plausible" models of how memory must be represented in
the brain. To understand this claim, we finish with a
discussion of the neural representation of person memory.
At the abstract level of cognitive theory, person memories can be viewed as nodes representing a person, his or her characteristics, and his or her behaviors, all linked together by associative links and embedded in a wider associative network of memories. But what is person memory like at the neural level?
An Exchange About NodesAt a seminar once, long ago and far away, a famous cognitive psychologist was giving a presentation on his associative-network model of memory. In the audience was a famous cognitive neuroscientist, who asked the following question:
To which the cognitive psychologist replied:
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The easiest answer is that the every memory is represented by a single neuron, or perhaps a small cluster of neurons, located in a particular part of the brain, and that person memories are no exception to this rule. Thus, the nodes in associative-network models of person memory, like those discussed here, have their neural counterparts in distinct (clusters of neurons).
Early research by Wilder
Penfield (1954), a Canadian neurologist, suggested that this
is indeed the case. In the process of diagnosing and
treating cases of epilepsy, Penfield would stimulate various
areas of the brain with a small electrical current delivered
through a micro-electrode implanted in the brain. This
procedure does not hurt, because the cortex does not contain
afferent neurons, and patients remain awake while it was
performed. Accordingly, Penfield asked patients what
they experienced when he stimulated them in various
places. Sometimes they reported experiencing specific
sensory memories, such as an image of a relative or the sound
of someone speaking. This finding was controversial:
Penfield had no way to check the accuracy of the memories, and
it may be that what he stimulated were better described as
"images" than as memories of specific events. In any
event, the finding suggested that there were specific neural
sites, perhaps a cluster of adjacent neurons, representing
specific memories in the brain.
However,
evidence
contradicting Penfield's conclusions was provided by Karl
Lashley (1950), a neuroscientist who conducted a "search for
the engram", or biological memory trace, for his entire
career. Lashley's method was to teach an animal a
task, ablate some portion of cerebral cortex, and then observe
the effects of the lesion on learned task performance.
Thus, if performance was impaired when some portion of the
brain was lesioned, Lashley could infer that the learning was
represented at that brain site. After 30 years of
research, Lashley reported that his efforts had been entirely
unsuccessful. Brain lesions disrupted performance, of
course. But the amount of disruption was proportional to
the amount of the cortex destroyed, regardless of the
particular location of the lesion.
Lashley's Law of Mass Action states that any specific memory is part of an extensive organization of other memories. Therefore, individual memories are represented by neurons that are distributed widely across the cortex. It is not possible to isolate particular memories in particular bundles of neurons, so it is not possible to destroy memories by specific lesions.
At about the same time, D.O. Hebb, a pioneering neuroscientist, argued that memories were represented by reverberating patterns of neural activity distributed widely over cerebral cortex. Hebb's suggestion was taken up by others, like Karl Pribram, another neuroscientific pioneer, who postulated that memory was represented by a hologram, in which information about the whole object was represented in each of its parts.
Connectionist models are inspired, in part, by both Lashley's Law of Mass action and Hebb's reverberating-network model of memory.
Still,
Penfield's vision held some attraction for some
neuroscientists, who continued to insist that individual
memories were represented by the activity of single neurons,
or at most small clusters of neurons, at specific locations in
cortex.
Problems with
Penfield's clinical studies aside, early advances in
understanding the neural basis of perception led support to
the localist views of representation.
Nobody, including Lettvin and Barlow themselves, took any of this all that seriously, and neuroscientific doctrine has emphasized distributed representations of the sort envisioned by Lashley and Hebb.
Until recently.
A serendipitous finding, ingeniously pursued by a group of investigators at UCLA and Cal Tech, has suggested that there might be something to the idea of a "grandmother neuron" after all (Quian Quiroga, Reddy, Kreiman, Koch, & Fried, Nature, Vol. 425, pp. 1102-1107, June 23, 2005; see also "Brain Cells for Grandmother" by Quian Quiroga, Fried, and Koch, Scientific American, 02/2013)).
These
investigators
worked with eight patients with intractable epilepsy. In
order to localize the source of the patients' seizures, they
implanted micro-electrodes in various portions of the
patients' medial temporal lobes (the hippocampus, amygdala,
entorhinal cortex, and parahippocampal cortex). Each
micro-electrode consisted of 8 active leads and a reference
lead. They then recorded responses from each lead to
visual stimulation -- pictures of people, objects, animals,
and landmarks selected on the basis of pre-experimental
interviews with the patients.
In one patient, the investigators
identified a single unit (i.e., a single lead of a single
electrode, corresponding either to a single neuron or to a
very small, dense cluster of neurons), located in the left
posterior hippocampus, that responded to a picture of Jennifer
Aniston, an actress who starred in a popular television
series, Friends. (A response was defined very
conservatively as an activity spike of magnitude greater than
5 standard deviations above baseline, consistently occurring
within 1 second of stimulus presentation). That unit did
not respond to any other stimuli tested. The
investigators quickly located other pictures of Aniston,
including pictures of her with Brad Pitt, to which she was
once (and famously) married. The same unit responded to
all the pictures of the actress -- except those in which she
was pictured with Pitt!
Similarly, a
single unit in the right anterior hippocampus of another
patient responded consistently and specifically to pictures of
another actress, Halle Berry (who won an Academy Award for her
starring role in Monsters' Ball). Interestingly,
this unit also responded to a line-drawing of Berry, to a
picture of Berry dressed as Catwoman (for her starring role in
the unfortunate film of the same name), and even to the
spelling of her name, H-A-L-L-E--B-E-R-R-Y (unfortunately, the
investigators didn't think of doing this when they were
working with the "Jennifer Aniston" patient -- remember, they
were flying by the seat of their pants, doing this research
under the time constraints of a clinical assessment).
The fact that the unit responded to Berry's name, as well as
to her picture, and to pictures of Berry in her (in)famous
role as Catwoman, suggests that the unit represents the
abstract concept of "Halle Berry", not merely some
configuration of physical stimuli.
As another example, yet a third patient
revealed a multi-unit (i.e., two or more leads of a single
electrode, evidently corresponding to a somewhat larger
cluster of neurons) in the left anterior hippocampus that
responded specifically, if not quite as distinctively, to
pictures of the Sydney Opera House. This same unit also
responded to the letter string SYDNEY OPERA HOUSE. It
also responded to a picture of the Baha'i Temple -- but then
again, in preliminary testing this patient had misidentified
the Temple as the Opera House! So again, as with the
Halle Berry neuron, the multi-unit is responding to the
abstract concept of the Sydney Opera House, not to any
particular configuration of physical features.
Across the 8 patients, Quian Quiroga et al. tested 993 units, 343 single units and 650 multi-units, and found 132 units (14%) that responded to 1 or more test pictures. When they found a responsive unit, they then tested it with 3 to 8 variants of the test pictures. A total of 51 of these 132 units yielded evidence of an invariant representation of people, landmarks, animals, or food items. In each case, the invariant representation was abstract, in that the unit responded to different views of the object, to line drawings as well as photographs, and to names as well as pictures.
So maybe there is a
"grandmother neuron" after all! This research -- which,
remember, was performed in a clinical context and thus may
have lacked some desirable controls -- identified sparse
neural representations of particular people (landmarks, etc.),
in which only a very small number of units is active during
stimulus presentation.
Moving away for a moment from strictly social memory, Quian Quiroga and his colleagues have proposed that the same principle applies to concepts in general, not just to faces and places. That is to say, concepts like tree and surfboard are also "sparsely" represented in the brain, as a discrete cluster of relatively few (meaning hundreds or thousands) of adjacent neurons (Quian Quiroga, Nature Reviews Neuroscience, 2012).
Of course, this evidence for localization of content contradicts the distributionist assumptions that have guided cognitive neuroscience for 50 years. Further research is obviously required to straighten this out, but maybe there's no contradiction between distributionist and locationist views after all. After all, according to Barlow's (1972) psychophysical linking principle,
Whenever two stimuli can be distinguished reliably... the physiological messages they cause in some single neuron would enable them to be distinguished with equal or greater reliability.
In other words, even in a distributed memory representation, there has to be some neuron that responds invariantly to various representations of the same concept. Neural representations of knowledge may be distributed widely over cortex, but these neural nets may come together in single units.
But wait a minute -- we're talking about the cerebral cortex, and the data from Quian Quiroga et al. came from the hippocampus and other subcortical structures. Note, however, that the hippocampus is crucial for memory: it was the destruction of his hippocampus that rendered H.M. amnesic. Nobody thinks that memories are stored in the hippocampus -- it's just too small for that purpose. But one prominent theory of the hippocampus is that it performs a kind of indexing function, relating memories to each other that are located in the cortex. Accordingly, maybe Quian Quiroga didn't exactly tap into their patient's whole knowledge representation of Halle Berry -- but instead, hit on the neural index card that locates all that information.
Note: This whole issue was battled out in the pages of Psychological Review (2009-2010) -- naturally, inconclusively.
A
special case of person memory is autobiographical
memory (ABM) -- that is, a real person's memories for
his own actions and experiences, which occurred in the
ordinary course of everyday living. Episodic memory, as
studied with variations on the verbal-learning paradigm, is
explicitly intended as a laboratory analogue of
autobiographical memory: each list, and each word on a list,
constitutes a discrete event, with a unique location in space
and time. ABM is episodic memory, as opposed to semantic
memory or procedural knowledge, but ABM isn't just
episodic memory -- there's more to it than a list of items
studied at particular places and particular times (Kihlstrom,
2009).
Another familiar phenomenon of emotional
memory is the flashbulb memory, in which subjects
remember the circumstances under which they first learned about
a surprising, consequential, affect-laden event. For
members of the "baby-boom" generation, a classic example is the
assassination of President John F. Kennedy. For younger
individuals, as well as boomers, other familiar examples are the
space shuttle Challenger disaster of 1986 and the terror attacks
of September 11, 2001.
For more on autobiographical memory, including
an extensive discussion of flashbulb memories, see the lecture
supplement on "The Self".
So far, we've followed the traditional paradigms of psychology and cognitive science, and discussed social memory as it exists inside the heads of individuals. But social memories seem to exist at the level of the group as well as the level of the individual -- for example, in the monuments and memorials that we erect to commemorate various individuals and events. These, too, are social memories -- they are ways for entire societies, not just individuals, to remember things that are important to them.
For example:
Maybe what they mean is that they know these events happened, as matters of historical fact. But maybe these memories really exist, as something like personal recollections, but at a level that extends beyond the individual, and to the group(s) of which the individual is a member.
The formal study of collective memory begins with Maurice Halbwachs (1877-1945), who was a student of both Henri Bergson, a pioneering French psychologist, and Emile Durkheim, a pioneering French sociologist. Bergson was particularly interested in individual consciousness, particularly as it was manifested in memory. Durkheim, for his part, was interested in collective consciousness, and in the proposition (which is axiomatic for sociologists) that groups had special properties that were not reducible to the properties of the individuals in them.
Putting these two themes together, Halbwachs articulated a concept of collective memory:
"The individual calls recollections to mind by relying on the frameworks of social memory.... There are surely many facts, and many details..., that the individual would forget if others did not keep their memory alive for him. But, on the other hand, society can live only if there is sufficient unity of outlooks among the individuals and groups comprising it.... [T]he necessity by which people must enclose themselves in limited groups... is opposed to the social need for unity.... This is why society tends to erase from its memory all that might separate individuals, or that might distance groups from each other. It is also why society, in each period rearranges its recollections in such a way as to adjust them to the variable conditions of its equilibrium."
For Halbwachs, collective memories are more than merely the sum of individuals' memories. They represent the integration of personal pasts into a common past. However, as the sociologist Lewis Coser points out, collective memory is not the memory of a group mind. Minds exist in individuals, and not somewhere in the space between or above them.
"While the collective memory endures and draws strength from its base in a coherent body of people, it is individuals as group members who remember."
Collective memories are shared within groups and institutions, as individuals draw on the group context to remember and reconstruct the past. Halbwachs went so far as to argue that all individual memories are collective, in the sense that "We are never alone". The only exception, perhaps, is our memories of our dreams -- but even dreams are largely remembered to the extent that we share them with others.
In his work, Halbwachs
analyzed a number of examples of what he called the
social frameworks of memory:
This page last modified 01/17/2017.