Aristotle (350BC) contended that "…other animals (as
well as man) have memory, but, of all that we are acquainted with, none,
we venture to say, except man, shares in the faculty of recollection."
Here Aristotle distinguishes "memory," as an elementary matching of
current sensations to impressions from prior experience, from the
capacity for reminiscence, as the ability to mentally reconstruct past
experiences. Jumping to current times, Tulving (1983, 2002)
characterized animals as having the capacity for acquiring semantic
knowledge, but claimed that episodic recollection "… has evolved only
once, and in only one species, although other species would benefit from
it as much as do humans." Neither Aristotle nor Tulving employed
experimental evidence in support of their claims, but several other
contemporary researchers have, with indecisive results, such that there
is currently no consensus on whether animals have the capacity for
recollection (reviewed in Clayton, Bussey, & Dickinson, 2003; Clayton,
Bussey, Emery, & Dickinson, 2003; Hampson & Schwartz, 2004; see also
Roberts, 2005). This literature will not be critiqued again here.
Instead, I will argue simply that the issue of recollection in animals
can be addressed. Those who define recollection as accessible to
consciousness and available to declarative or explicit expression will
not find solace in this review. However, those who define recollection
in terms of the organization of its contents have generated a vigorous
area of study that is addressing the question.
Here I will present one perspective on that approach.
First I will consider how we might define recollection in terms of
features of memory that can be assessed in animals as well as humans,
and in doing so introduce three fundamental features of recollection
that can be examined across species. I will then introduce the
cortical-hippocampal system that supports recollection in humans,
focusing on the role of the hippocampus. I will consider evidence, using
examples primarily from experiments in my own laboratory, indicating
that animals exhibit each of the defining features of recollection, that
the hippocampus is critical to these features of recollection in
animals, and that neurons in the hippocampus encode information that
support these features of recollection. I will briefly discuss the often
emphasized role of the hippocampus in spatial function in animals,
offering a view on how the data on spatial navigation and memory can be
reconciled with a more general role for the hippocampus in recollection.
Finally, I will consider the anatomical organization of the hippocampus
and associated cortical areas, and the functions of these areas, in
several species. The following considerations are based on recent and
more extensive reviews covering each of these issues (Eichenbaum, 2004;
Eichenbaum, Fortin, Ergorul, Wright, & Agster, 2005; Manns & Eichenbaum,
2005, 2006; Eichenbaum, Yonelinas, & Ranganath, 2006), combined here to
address the question of whether recollection is a cognitive function
that is conserved across mammalian species.
Importantly, I will not present data from a large
number of animal species, as might be expected by some in a
comprehensive comparative review. Instead I will focus on a few highly
domesticated species of rodents, and a few non-human primate species
that have been the subject of extensive behavioral and neurobiological
investigations, and I make no apology for this focus. My aim is to
identify fundamental features of recollection that can, at least in
principle, be studied in any species and to identify the brain circuitry
that supports common features of recollection in mammals. Indeed,
because there is an extensive literature on these issues in laboratory
rodents and monkeys, one can make conclusions that are generalizable to
a variety of tests of memory function and different kinds of
investigations on the relevant brain areas. I would predict that the
same features of recollection and analogous roles of the same brain
areas can be identified in less studied, non-domesticated species and
that the interpretations offered here will be relevant to the natural
use of memory in their specialized habitats.
The Brain System that Supports Recollection
The brain system that supports recollection involves
a network of widespread cortical association areas and structures in the
medial temporal lobe (Eichenbaum, 1999). The cortical areas involve
components of the prefrontal cortex, as well as structures of the
diencephalon, that mediate working memory, effortful retrieval, source
monitoring, and other processing that contribute critically to cognitive
functions essential to recollection (e.g., Aggleton & Brown, 2006;
Henson, Shallice, Josephs, & Dolan, 1999; Yonelinas, Otten, Shaw, &
Rugg, 2005). Also, areas of the parietal and temporal cortex are
involved in complex perceptual processing essential to configuration of
the conceptual contents of information that is the subject of
recollection (e.g., Uncapher, Otten, & Rugg, 2006). Projections from
these areas strongly converge onto the medial temporal lobe, which also
sends strong projections back to these cortical areas, suggesting a
central role in organizing or extending the persistence of cortical
representations. Damage to the medial temporal area, including the
hippocampus and surrounding parahippocampal cortical areas, results in a
profound deficit in encoding information in a way that is subsequently
subject to recollection (for review, see Eichenbaum & Cohen, 2001).
Furthermore, unlike the cortical areas of this system, the role of the
medial temporal lobe is fully selective to memory. Therefore, this
review will focus specifically on the components of the medial temporal
lobe, and in particular on the hippocampus.
What is Recollection?
I will begin the discussion by considering the
distinction between a vivid recollection and something less, a sense of
familiarity with a particular person or object. We have all been in the
situation where we meet someone who seems slightly or perhaps highly
familiar but we cannot recall who they are or why we know them.
Sometimes, we just give up and say, "Don’t I know you?". Alternatively,
that embarrassment is sometimes avoided when a clue or sufficient mental
searching helps us suddenly retrieve the name, where we met before, and
the circumstances of the meeting. Familiarity is rapid and defined in
terms of the strength of the match of a cue to a stored memory template.
It is an isolated ability to identify a current stimulus (a person or
object) as previously experienced. Recollection is typically slower and
is defined by the number of associations retrieved and the organization
of the memory obtained. Thus, recollections typically include not only
the item sought in memory but also the spatial and temporal context of
the experience in which the item was previously encountered.
Furthermore, our most vivid recollections involve replaying an entire
episode in which we met the person, and that memory might lead to
remembering additional encounters. These considerations tell us that
familiarity and recollection differ both in the dynamics of memory
retrieval and in the contents of what is retrieved. These properties of
recollection will be the subject of the comparative analysis presented
here.
The Role of the Hippocampus in Recollection and Familiarity
As the incident described above suggests, one of the
ways familiarity and recollection are distinguished is by their
retrieval dynamics. Familiarity occurs quickly and is graded in
strength. Items from our past can generate a slight sense of familiarity
or an intensely held belief that we have experienced them before. By
contrast, recollection is qualitative. Its goodness is characterized by
the number of associations we retrieve, and we tend to retrieve each one
in an all-or-none fashion. How can these properties be dissociated in
the performance of human and animal subjects?
The retrieval dynamics of recollection and
familiarity have been distinguished in humans by the analysis of
receiver operating characteristic (ROC) functions derived from
recognition memory performance (Yonelinas, 2001). In a typical
experiment, subjects study a list of words, then are tested for their
capacity to identify as "old" or "new" the same words plus a set of
words that were not studied. The resulting ROC analysis plots "hits,"
that is, correct identifications of old items, against "false alarms,"
incorrect identifications of new items as if they were old, across a
range of confidence levels. This analysis typically reveals an
asymmetric function characterized by an above-zero threshold of
recognition at the most conservative criterion (zero false alarm rate)
and thereafter a curvilinear performance function (Yonelinas, 2001;
Figure 1a). The positive Y-intercept is viewed as an index of the
recollection in the absence of measurable familiarity, whereas the
degree of curvature reflects familiarity as typical of a
signal-detection process (Macmillan & Creelman, 1991). Consistent with
this view, under different experimental demands that favor one of these
processes, the shape of the ROC curve takes on distinguishable functions
(Yonelinas, 2001). During performance that favors recollection, the ROC
curve highlights the threshold component of recognition with performance
at successively higher confidence levels characterized by a linear
function (Figure 1b). In contrast, during performance that favors
familiarity, the ROC curve is symmetrical and curvilinear (Figure 1c).
Figure 1. Signal detection
analyses of human recognition memory. A. Overall
recognition is characterized by an asymmetrical and
curvilinear function. Manipulations of the task demands
can divide those parameters. B. Performance that
emphasizes recollection is characterized by the
asymmetrical component and otherwise linear ROC. C.
Performance that emphasizes familiarity involves a
symmetrical and curvilinear ROC. Data from Yonelinas
(2001).
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Yonelinas et al. (2002) used ROC analysis to show
that mild hypoxia that causes damage largely confined to the hippocampus
resulted in a severe deficit in recollection but normal familiarity. The
distinction between impaired recollection and spared familiarity was
verified by measures of subjective experiences in recognition reflected
in "remember" versus "know" judgments by the same patients. In addition,
structural equation modeling methods used on a large sample of hypoxic
patients revealed that hypoxic severity predicted the degree to which
recollection, but not familiarity, was impaired. A similar pattern of
deficient recollection and preserved familiarity was reported in a
patient with relatively selective hippocampal atrophy related to
meningitis (Aggleton et al., 2005). These studies implicate the
hippocampus as playing a selective role in recollection.
However, other interpretations of the data on ROC
analyses in normal human subjects have led to the view that recollection
and familiarity reflect differences in strength of a single memory
function (Wixted & Stretch, 2004), and indeed many reports are mixed on
whether ROC curves are more consistent with single or dual processes in
recognition, suggesting that the dissociation of these processing
functions may be dependent on parameters of testing and assumptions in
the data analysis. In addition, another ROC study reported deficits in
both recollection and familiarity in hypoxic patients with identified
hippocampal damage (Wais, Wixted, Hopkins, & Squire, 2006), and several
other studies also reflect a mixture of results on whether the
hippocampus is selectively involved in recollection or involved in both
recollection and familiarity. Differences in the localization of damage
in different patients as well as differences in the task demands across
studies might account for the variability in results across these
studies. To address whether recollection and familiarity can be
distinguished in ROC functions by selective hippocampal damage, we
developed an ROC protocol for assessing recollection and familiarity in
rats and for examining the effects of highly selective experimental
lesions of the hippocampus.
Our recognition task exploited rats’ superb memory
capacities with odors (Fortin, Wright, & Eichenbaum, 2004). On each
daily test session, rats initially sampled 10 common household scents
mixed in with playground sand in a plastic cup containing a cereal
reward (Video 1). When each sample was presented the animal would dig
for the reward and incidentally smell the odor of the sand. Following a
30 minute memory delay, the same odors plus 10 additional odors were
presented one at a time in random order. On each recognition test, the
animal followed a non-match to sample rule such that it could dig in the
target odor to obtain a reward if the target was "new" (a non-match) or
could refrain from digging if the odor was "old" (a match) and instead
obtain a reward in an empty cup on the opposite end of the test chamber.
Initially animals were trained with short lists of odors, and the list
length was gradually increased to 10 items. In addition, in the final
phase of training and testing, a different response criterion was
encouraged for each daily session using a combination of variations in
the height of the test cup, making it more or less difficult to respond
to that cup, and manipulations of the reward magnitudes associated with
correct responses to the test and the unscented cup. Notably, the use of
a method for explicitly varying the animal’s bias is different from the
use of confidence judgments in experiments on recognition in humans
(Yonelinas, 2001); nevertheless, both methods successfully vary the
subject’s criterion along the full range required to compute ROC curves.
Figure 2. Performance of rats in
ROC analysis of recognition memory. Normal rats exhibit
an ROC curve similar to that supported by a combination
of recollection and familiarity. In contrast, rats with
selective hippocampal lesions perform as if recognition
is supported only by familiarity. Data from Fortin et
al. (2004).
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The ROC curve of intact control rats was asymmetric
(Figure 2), containing both a threshold component (above-zero
Y-intercept) and a strong curvilinear component. This pattern is
remarkably similar to the ROC of humans in verbal recognition
performance (Figure 1a), consistent with a combination of
recollection-like and familiarity-based components of recognition in
animals. To explore the role of the hippocampus in recollection,
subjects were subsequently divided into two groups matched on both
performance components, and one group received selective lesions of the
hippocampus whereas the other group received sham control operations.
After recovery, we again tested recognition performance at each response
criterion. The ROC of control rats continued to reflect both
recollection-like and familiarity components, whereas the ROC of animals
with selective hippocampal lesions was fully symmetrical and curvilinear
(Figure 2), characteristic of familiarity-based recognition in humans
(Figure 1c). To describe these patterns quantitatively, we calculated
indices of recollection and familiarity (Figure 2 insets). Whereas
familiarity remains normal in rats with hippocampal lesions,
recollection is severely impaired.
The overall level of performance (averaged across
biases) on the task is slightly worse in the hippocampal group (66%,
compared to 73% in controls). Given that any performance deficit would
be expected to result in an ROC closer to the diagonal (chance
performance; dashed line in Figure 2), it is possible that the
alteration in their ROC pattern resulting from the hippocampal lesion
reflect a generalized decline in memory. In order to compare the ROC of
hippocampal rats with the pattern of forgetting in normal animals, we
challenged the memory of control rats by increasing the memory delay to
75 minutes. This manipulation succeeded in reducing the overall level of
performance of control animals to 64%, equivalent to that of the
hippocampal rats. Yet, further testing of the controls showed that their
ROC continued to have an asymmetrical threshold component, as indicated
by an above-zero Y-intercept. Notably, the controls’ ROC was distinctly
more linear than that of both the hippocampal rats and the controls when
tested at the shorter memory delay. This pattern of performance suggests
that, in normal rats, familiarity fades more quickly than recollection,
similar to observations on humans (Yonelinas, 2002). Moreover,
comparison of the ROC curve in normal rats at the 75 minute delay versus
that of rats with hippocampal damage at the 30 minute delay emphasizes
the distinction between these two groups in their differential emphasis
on recollection and familiarity, respectively, even when the overall
levels of recognition success are equivalent.
These findings strongly suggest that rats exhibit two
distinct processes in recognition, one that is marked by a threshold
retrieval dynamic characteristic of episodic recollection in humans, and
another that follows a symmetrical and curvilinear processing function
characteristic of familiarity in humans. These observations suggest
comparable dual retrieval mechanisms underlying recognition in animals
and humans, and strongly support the notion that the hippocampus plays a
critical role only in the recollective processes that contribute to
recognition.
Fundamental Features of the Contents of Recollection
The above described experiment provides evidence
suggesting the retrieval dynamics of recollection are similar in animals
and humans. Further evidence suggesting conservation of recollective
function across species can be found in an examination of the contents
of recollected memories. Recollection in humans is highlighted by three
central features of its contents. First, when we move beyond a sense of
familiarity with a previously experienced stimulus, we recover
information about the context or source in which the stimulus was
experienced, most typically "where" and "when" an event occurred. This
aspect of recollection has been investigated in many studies of
recollection in humans, as well as animals. Second, vivid recollection
is also typically characterized by a "replay" of the sequence of events
that occurred in an experience. The capacity for mental replay has been
highlighted in Tulving’s (1983) account of episodic memory. Third,
recall of one memory often leads to the recollection of a larger set of
related memories. This indicates that recollection typically accesses
not just one isolated memory, but rather a network of memories.
Furthermore, these memories’ networks can be used to infer indirect and
novel relationships between elements of those memories, and we employ
these insights in a variety of creative ways. Do animals have the
capacity for all of these hallmark features of recollection? Which of
these features of recollection depends on the hippocampus? In the
following sections I will outline experimental studies we have pursued
to address these questions.
Memory for Where and When Events Occurred
Several investigators have argued that animals are
indeed capable of remembering the spatial and temporal context in which
they experienced specific stimuli (Clayton, Bussey, & Dickinson, 2003;
Day, Langston, & Morris, 2003). To further explore these aspects of
episodic memory, we developed a task that assesses memory for events
from a series of events that each involve the combination of an odor
("what"), the place in which it was experienced ("where"), and the order
in which the presentations occurred ("when"; Ergorul & Eichenbaum,
2004). On each of a series of events, rats sampled an odor in a unique
place along the periphery of a large open field (Figure 3a;
Video 2a).
Then, memory for the when those events occurred was tested by presenting
a choice between an arbitrarily selected pair of the odor cups in their
original locations (Video 2b). We identified the stimulus initially
approached and distinguished that response from the final choice in
which the rat dug for food. Over a series of shaping phases, rats were
trained to select the earlier presented odor of a pair randomly selected
from the series.
Figure 3. Performance of rats in
the "what-where-when" memory task. A. Example of a trial
in which rats initially sample a series of odors at
different locations then must select the earlier of two
of those stimuli. B. Normal rats perform better in their
final choice than the initial cup approached, and
perform poorly if no odor is present in the cups. C.
Animals with selective hippocampal damage perform at
chance in what-where-when memory and tend to first
approach the cup last rewarded. (Hippo = hippocampal
lesion)
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Rats performed well above chance (76.2% correct) in
their choices on the test phase, indicating that they can remember the
order of unique sequences of odors and places (Figure 3b). In addition,
we also found that rats first approached the correct stimulus at well
above chance level, indicating they remembered the sequence of places
where the cups were presented prior to perceiving information about the
odor at that location; importantly, separate tests showed that rats
cannot accurately judge the odor in a cup until they arrive within at
the edge of the cup. However, performance was not as accurate in the
first approach as it was in the final choice, suggesting that rats begin
by guessing the location of the earlier experienced cup, then confirm
this choice using the smell of the cup. This hypothesis was confirmed in
a control condition in which we presented the test cups without odors.
In this condition, performance of intact animals fell to chance,
indicating that when the selected location is not confirmed by the
associated odor, performance is disrupted (Figure 3b). This pattern of
results strongly suggests rats normally use a combination of "where" and
"what" information to judge "when" the events occurred.
To examine the role of the hippocampus, animals were
subsequently separated into matched groups, one of which received
selective hippocampal lesions. Subsequently, intact rats continued to
choose well on the standard "what-where-when" trials (Figure 3c). By
contrast, the performance of animals with hippocampal lesions was no
better than chance. In addition, whereas intact rats continued to
perform well on the initial approach, rats with hippocampal lesions
approached the correct choice less often than expected by chance.
Contrary to the strategy of normal rats and the reinforcement
contingency of the test phase, rats with hippocampal damage were
inclined to visit the more recently presented and rewarded place
rather than the earlier visited locus. This observation indicates an
intact spatial memory in rats with hippocampal damage, and this memory
was employed despite its maladaptive consequences.
These findings indicate that the hippocampus is
critical for effectively combining the "what," "when," and "where"
qualities of each experience to compose the retrieved memory. Normal
rats initially employ their memory of the places of presented cups and
approach the location of the earlier experience. Then they confirm the
presence of the correct odor in that location. Animals with hippocampal
damage fail on both aspects of this task and, instead, their behavior is
guided by another form of memory that leads to the incorrect first
approach. That they can initially approach the most recently rewarded
location indicated their spatial memory is intact. However, it appears
they are driven to approach the last rewarded cup rather than combine
the what-where-when cues to select the earlier event.
Memory for the Order of Events Within a Unique Experience
In addition to memory for the spatial and temporal
context of distinct events, a vivid recollection often involves
recalling the flow of events within a single experience. To investigate
the memory for the order of events in a unique experience, we developed
a behavioral protocol that assesses memory for episodes composed of a
unique sequence of olfactory stimuli presented to the animal as it
remains in its cage (Fortin, Agster, & Eichenbaum, 2002; see also
Kesner, Gilbert, & Barua, 2002). In addition, our design allowed us to
directly compare memory for the sequential order of odor events with
recognition of the odors in the list independent of memory for their
order. On each trial, rats were presented with a series of five odors,
selected randomly from a large pool of common household scents. Memory
for each series was subsequently probed by a choice test where the
animal was reinforced for selecting the earlier of two of the odors that
had appeared in the series. For example, the rat might be initially
presented with odors A then B then C then D then E. Following the delay,
two non-adjacent odors, e.g., B and D, were presented, and the animal
would be rewarded for selecting odor that appeared earlier (in this
case, B). On each trial, any pair of non-adjacent odors might be
presented as the probe, so the animal had to remember the entire
sequence in order to perform well throughout the testing session.
Figure 4. Performance of rats in
memory for the order of events in a unique episode. On
trial types where performance on order and item memory
are matched in intact rats and rats with hippocampal
damage, rats with hippocampal lesions are impaired in
order memory but not item memory. (Hippo = hippocampal
lesion) Data from Fortin et al. (2002).
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After training over many days, rats performed
sequential order judgments well above chance levels (Figure 4),
indicating they can remember the order of a sequence of events in unique
experiences. In order to examine the role of the hippocampus in memory
for the order of events in unique experiences, these subjects were
divided into two groups matched for performance, and animals in one
group were given selective hippocampal lesions whereas those in the
other group received sham operations. After recovery, all animals were
tested again on memory for the order of odors in unique odor sequences.
Intact rats continued to perform well whereas rats with hippocampal
lesions were severely impaired, performing no better than chance except
when the judgment was easiest (when the odors were first and last in the
series).
The same rats were then also tested on their ability
to recognize odors that were presented in the series. On each trial, a
series of five odors was presented in a format identical to that used in
the previous testing. Then, recognition was probed using a choice test
in which the animal was presented with one of the odors from the series
and another odor from the pool that was not in the series (in which food
was buried). For example, the rat might instead be presented with the
series A through E, then, following a delay, an odor selected randomly
from those initially sampled and an odor not presented in the sequence,
e.g., A and X, were presented. The rat would be rewarded for choosing X.
Both intact rats and rats with selective hippocampal damage acquired the
task rapidly, and there was no overall performance difference between
the groups in acquisition rate or final level of recognition performance
(Figure 4). Furthermore, in both groups, recognition scores were
consistently superior on probes involving odors that appeared later in
the series, suggesting some forgetting of items that had to be
remembered for a longer period and through more intervening items.
A potential confound in any study that employs time
as a critical dimension in episodic memory is that memories obtained at
different times are likely to differ in the strength of their memory
traces, due to the inherent decremental nature of memory traces. To what
extent could normal animals be using differences in the relative
strengths of memory traces for the odors to judge their sequential
order? The observation of a temporal gradient in recognition performance
by normal animals suggests that memories were in fact stronger for the
more recently presented items in each sequence. These differences in
trace strength potentially provide sufficient signals for the animals to
judge the order of their presentation. However, the observation of the
same temporal gradient of recognition performance in rats with
hippocampal damage indicated that they had normal access to the
differences in trace strengths for the odors. Yet these intact
trace-strength differences were not sufficient to support above chance
performance in the order probes. These considerations strongly suggest
that normal rats also could not utilize the relative strengths of
memories for the recently experienced odors, and instead based their
sequential order judgments directly on remembering the odor sequence.
The findings indicate that animals have the capacity to recollect the
flow of events in unique experiences and that the hippocampus plays a
critical role in this capacity.
Networking Memories
A third defining quality of recollection is our
capacity to bring to mind multiple related memories, that is, memories
that have common elements, and to make inferences from the information
contained in those memories. In order to examine the extent to which
animals can link memories that share common elements, we studied whether
rats can learn a set of odor problems that share elements, and then
tested whether they had integrated the memories into networks that
support inferential judgments. One experiment compared the ability of
normal rats and rats with selective damage to the hippocampus on their
ability to learn a set of paired associate problems that contained
common elements and to interleave the representations of these problems
in support of novel inferential judgments (Bunsey & Eichenbaum, 1996).
Animals were initially trained on two sets of overlapping odor paired
associates (e.g., A goes with B, B goes with C). Then the rats were
given probe tests to determine if they could infer the relationships
between items that were only indirectly associated through the common
elements (e.g., A goes with C?). Normal rats learned the paired
associates and showed strong transitivity in the probe tests (Figure 5).
Rats with selective hippocampal lesions also learned the pairs over
several trials but were severely impaired in the probes, showing no
evidence of transitivity.
Figure 5. Performance on the
associative transitivity task. Rats with hippocampal
lesions acquire the premise problems as readily as
intact rats. Intact rats demonstrate transitive
inference by a preference in the appropriate
indirectly related stimulus. In contrast, rats with
hippocampal lesions do not show transitivity,
indicating they have not represented the indirect
relations. (Hippo = hippocampal lesion) Data from
Bunsey & Eichenbaum (1996).
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In another experiment, rats learned a hierarchical
series of premises that involved odor choice judgments between
overlapping elements (e.g., A > B, B > C, C > D, D > E), then were
probed on the relationship between indirectly related items (e.g., B vs.
D?; Figure 6). Normal rats learned the series and showed robust
transitive inference on the probe tests. Rats with hippocampal damage
also learned each of the initial premises but failed to show
transitivity (Dusek & Eichenbaum, 1997). The combined findings from
these studies show that rats with hippocampal damage can learn even
complex associations, such as those embodied in the odor
paired-associates and conditional discriminations. However, without a
hippocampus, they do not interleave the distinct experiences by their
common elements to form a relational network that supports inferential
memory expression. Importantly, according to the present view, the
hippocampus does not compute or directly mediate transitive judgments.
Rather, the hippocampus supports the encoding and retrieval of
information about previous experiences on which cortical areas might
accomplish the critical judgment. One neocortical association area that
receives hippocampal outputs and is likely critical to inferential
judgments is the prefrontal cortex (Waltz et al., 1999).
Figure 6. Performance on the
transitive inference task involving hierarchical
relations. Rats with hippocampal lesions perform as
well as intact rats on the "inner" premise problems.
Intact rats demonstrate transitive inference by
selection of the stimulus higher in the series when
presented with a novel choice. In contrast, rats
with hippocampal lesions do not show transitivity,
indicating they have not represented the
hierarchical series. Data from Dusek & Eichenbaum
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Neural Representations that Support Recollection
Additional insights about the fundamental properties
of memory representation can be gained through the analysis of neural
activity patterns associated with the critical stimuli and behavioral
events that occur in animals performing memory tasks. These studies can
confirm the evidence from tests of brain damage by providing evidence of
normal coding of features of memory that are lost following selective
damage of the same brain areas. In addition, these studies can provide
insights about where and how particular types of information are encoded
within the circuitry of the hippocampus and associated brain structures.
Observations from rats, monkeys, and humans, accumulated across many
different behavioral protocols, show that hippocampal neuronal activity
reflects each of the three fundamental features of recollection
discussed above: representation of events as items in the context in
which they are experienced, representation of episodes as sequences of
events, and representation of common features of experiences that link
distinct memories into networks.
Events are represented as items in context
A wealth of studies have shown that hippocampal
neurons fire associated with the ongoing behavior and the context of
events as well as the animal’s location (Eichenbaum, 2004). The
combination of spatial and non-spatial features of events captured by
hippocampal neuronal activity is consistent with the view that the
hippocampus encodes many features of events and the places where they
occur. Two recent studies provide examples that highlight the rapid
associative coding of events and places by hippocampal neurons. In one
study rats were trained on an auditory fear conditioning task in which a
tone was paired with shock to produce conditioned freezing to subsequent
tone presentations (Moita, Moisis, Zhou, LeDoux, & Blair, 2003). Prior
to fear conditioning, few hippocampal cells were activated by the
auditory stimulus. Following pairings of tone presentations and shocks,
many cells fired briskly to the tone and did so only when the animal was
in a particular place where the cell had fired above baseline prior to
conditioning. Another study examined the firing properties of
hippocampal neurons in monkeys performing a task where they rapidly
learned new scene-location associations (Wirth et al., 2003). Just as
the monkeys acquired a new response to a location in the scene, neurons
in the hippocampus changed their firing patterns to become selective to
particular scenes.
Figure 7. Continuous
non-matching to sample task. On each trial an
odorous cup is placed in one of nine locations in an
open field. A reward is buried in the cup only if
the odor is different from (a non-match with) the
odor on the previous trial. |
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Figure 8. Incidence of
hippocampal neurons that encode odors, places where
odors were sampled, the match/non-match status of the
odor, or combinations of odor, place, and
match/non-match status. Data from Wood et al. (1999). |
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Additional studies have directly examined the extent
to which hippocampal neurons encode specific stimuli and places where
they occur by training subjects to perform the same memory judgments at
many locations in the environment. In one study, rats performed a task
in which they had to recognize any of nine olfactory cues when placed in
any of nine locations (Wood, Dudchenko, & Eichenbaum, 1999; Figure 7).
On each trial, the rat was rewarded when it responded to a cue that
differed from (was a non-match to) the immediately preceding stimulus.
Because the location of the discriminative stimuli was varied
systematically, cellular activity related to the stimuli and behavior
could be dissociated from that related to the animal’s location. Some
hippocampal cells encoded particular odor stimuli, others were activated
when the rat sampled any odor at a particular place, and yet others
fired associated with whether the odor matched or differed from the
previous cue (Figure 8). However, the largest subset of hippocampal
neurons fired only associated with a particular combination of the odor,
the place where it was sampled, and the match-non-match status of the
odor. In a similar task created for humans, Ekstrom et al. (2003)
recorded the activity of hippocampal neurons as people played a taxi
driver game, searching for passengers picked up and dropped off at
various locations in a virtual reality town. Some cells encoded
particular cues or fired as the subject traversed specific locations.
Also, many of these cells fired selectively when the subject viewed a
particular scene from a particular place or passed a location while
pursuing a particular goal.
Hippocampal cells that represent specific salient
objects in the context of a particular environment have also been
observed in studies of rats engaged in foraging (Gothard, Skaggs, Moore,
& McNaughton, 1996; Rivard, Lenck-Santini, Poucet, & Muller, 2004) and
place learning (Hollup, Molden, Donnett, Moser, & Moser, 2001) in open
fields. Furthermore, parallel evidence from functional imaging has shown
that the human hippocampus is selectively activated during association
of an item and the context in which it was experienced (e.g., Davachi,
Mitchell, & Wagner, 2003, Ranganath et al., 2003). Thus, in rats,
monkeys, and humans, a prevalent property of hippocampal firing patterns
involves the representation of unique associations of stimuli and their
significance, specific behaviors, and the places where these events
occurred.
Episodes are represented as sequences of events
Figure 9. Firing patterns of a
hippocampal neuron as a rat performs the T-maze
alternation task. A. Schematic diagram of the maze and
paths that compose left-turn (blue) and right-turn (red)
trials. Small circles indicate loci where rewards are
provided for correct alternation. B. The paths of the
rat on left-turn and right-turn trials are shown in
different shades of gray. The location of the rat when a
spike occurred is shown by blue dots. On left-turn
trials the cell fires robustly when the rat traverses
the middle of the stem. C. The location of the rat when
a spike occurred is shown by red dots. The cell fired
much less when the rat performed a right-turn trial. D.
Firing rates on left-turn and right-turn trials are
compared for four segments of the stem of the maze (see
black lines indicating segments of the maze in B and C). |
|
Figure 10. Hippocampal neurons
distinguish different types of episodes. Schematic of
the neural ensemble representations of left-turn
(yellow) and right-turn (blue) trials, and cells that
fire on both trial types (green). Individual ovals
indicate firing of single cells that represent discrete
events. A series of ovals of like color represent one
type of episode, and the combination of episodic
representations and linking cells (green) represent the
memory network. |
|
Another common observation across species and many
different behavioral protocols is that different hippocampal neurons
fire during each successive event that composes task performance. Some
cells are active during simple behaviors such as foraging for food
(e.g., Muller, Kubie, & Ranck, 1987) and learned behaviors directed at
relevant stimuli that have to be remembered (e.g., Hampson, Heyser, &
Deadwyler, 1993), and the firing patterns have been observed across a
broad range of learning protocols, from classical conditioning,
discrimination learning, and non-matching or matching to sample tasks to
a variety of spatial learning and memory tasks (for review, see
Eichenbaum, 2004). In each of these paradigms, a substantial proportion
of hippocampal neurons show time-locked activations associated with each
sequential event. Many of these cells show striking specificities
corresponding to particular combinations of stimuli, behaviors, and the
spatial location of the event.
These sequential firing patterns can be envisioned to
represent a series of events, and their places that compose a meaningful
episode, and the information contained in these representations, both
distinguishes and links related episodes. Consider, for example, a study
in which rats were trained on the classic spatial alternation task in a
modified T-maze (Wood, Dudchenko, Robitsek, & Eichenbaum, 2000).
Performance on this task requires that the animal distinguish left-turn
and right-turn episodes and that it remember the immediately preceding
episode to guide the choice on the current trial, and in that way, the
task is similar in demands to those of episodic memory (Figure 9;
Video
3). We found that hippocampal neurons encode each sequential behavioral
event and its locus within one type of episode, with most cells firing
only when the rat is performing within either the left-turn or the
right-turn type of episode. This was particularly evident for cells that
fired when the rat was on the "stem" of the maze, that is, when it
traversed the same locations on both types of trials (Figure 9). Indeed,
virtually all cells that fired when the rat was on the maze stem fired
differentially on left-turn versus right-turn trials. The majority of
cells showed strong selectivity, some firing almost exclusively as the
rat performed one of the trial types, suggesting they were part of the
representations of only one kind of episode. Other cells fired
substantially on both trial types, potentially providing a link between
left-turn and right-turn representations by the common places traversed
on both trial types. These findings indicated that separate ensembles of
neurons encoded the sequences of events that composed left-turn and
right-turn trials (Figure 10). Notably, there were also some cells that
fired similarly on both trial types; these might serve to link the two
types of episodes.
Functional imaging studies in humans have also
revealed hippocampal involvement in both spatial and non-spatial
sequence representation. Several studies have shown that the hippocampus
is active when people recall routes between specific start points and
goals, but not when subjects merely follow a set of cues through space
(Hartley, Maguire, Spiers, & Burgess, 2003). In addition, the
hippocampus is selectively activated when people learn sequences of
pictures (Kumaran & Maguire, 2006). Even greater hippocampal activation
is observed when subjects must disambiguate picture sequences that
overlap, parallel to our findings on hippocampal cells that disambiguate
spatial sequences (Wood et al., 2000).
The hippocampus encodes events that can link related memories
In virtually all the studies described above, some
hippocampal neurons encode features that are common among different
experiences – these representations could provide links between distinct
memories. For example, in Moita and colleagues’ (2003) study of auditory
fear conditioning, some cells only fired to a tone when the animal was
in a particular place, whereas others fired associated with the tone
wherever it was presented across trials. In the Wood et al. (1999) study
on odor recognition memory, some cells showed striking associative
coding of odors, whereas their match/non-match status, and places, other
cells fired associated with one of those features across different
trials. Some cells fired during a particular phase of the approach
towards any stimulus cup, while others fired differentially as the rat
sampled a particular odor, regardless of its location or match-non-match
status. Yet other cells fired only when the rat sampled the odor at a
particular place, regardless of the odor or its status. Still, other
cells fired differentially associated with the match and nonmatch status
of the odor, regardless of the odor or where it was sampled. Similarly,
in Ekstrom and colleagues’ (2003) study on humans performing a virtual
navigation task, whereas some hippocampal neurons fired associated with
combinations of views, goals, and places, other cells fired when
subjects viewed particular scenes, occupied particular locations, or had
particular goals in findings passengers or locations for drop off. Also,
in Rivard and colleagues’ (2004) study of rats exploring objects in open
fields, some cells fired selectively associated with an object in one
environment, while others fired associated with the same object across
environments.
The notion that these cells might reflect the linking
of important features across experiences and the abstraction of common
information was highlighted in recent studies on monkeys and humans.
Hampson, Pons, Stanford, and Deadwyler (2004) trained monkeys on
matching to sample problems then probed the nature of the representation
of stimuli by recording from hippocampal cells when the animals were
shown novel stimuli that shared features with the trained cues. They
found many hippocampal neurons that encoded meaningful categories of
stimulus features and appeared to employ these representations to
recognize the same features across many situations. Kreiman, Koch, and
Fried (2000) characterized hippocampal firing patterns in humans during
presentations of a variety of visual stimuli. They reported a
substantial number of hippocampal neurons that fired when the subject
viewed specific categories of material, e.g., faces, famous people,
animals, scenes, and houses, across many exemplars of each. A subsequent
study showed that some hippocampal neurons are activated as a subject
views any of a variety of different images of a particular person,
suggesting these cells could link the recollection of many specific
memories related to that person (Quiroga, Reddy, Kreiman, Koch, & Fried,
2005).
This combination of findings across species provides
compelling evidence for the notion that some hippocampal cells represent
common features among the various episodes that could serve to link
memories obtained in separate experiences. Furthermore, recent
functional imaging studies have associated activation of the hippocampus
in humans to the performance of transitive inference tasks similar to
those described above as dependent on the hippocampus in animals. In one
study, subjects learned overlapping paired associations between faces
and houses or direct face-face associations (Preston, Shrager,
Dudukovic, & Gabrieli, 2004). The hippocampus was selectively activated
when people identified the indirect associations between faces that were
paired with the same house as compared with direct face-face
associations. In another study, subjects were trained on the task which
involves a hierarchical series of judgments (A > B, B > C, C > D, D > E)
or a series of non-overlapping judgments (K > L, M > N, O > P, Q > R;
Heckers, Zalezak, Weiss, Ditman, & Titone, 2004). The hippocampus was
activated when subjects performed transitive judgments as compared to
novel judgments between items taken from the non-overlapping pairs.
Under some circumstances, it may be possible to indirectly relate items
without a memory network (O’Reilly & Rudy, 2001; Van Elzakker, O’Reilly,
& Rudy, 2003), but the above described results provide compelling
evidence that the hippocampus is indeed involved in binding related
memories and in using these memories to make novel inferential
judgments.
Summing up the physiological data
These various observations are consistent with the
notion that hippocampal neurons in animals and humans represent the
kinds of information that underlie recollection. Hippocampal neurons
encode attended stimuli and behavioral actions in the context in which
they occur. These representations are created for each series of events
that compose a behavioral episode across a broad range of behavioral
protocols and encode features of events that are shared across distinct
experiences that can link memories.
Spatial Functions of the Hippocampus
So far this review has touched only briefly on the
role of the hippocampus in spatial cognition and memory. Yet a wealth of
studies have shown that the hippocampus plays an essential role in a
variety of forms of spatial learning and memory in laboratory mice and
rats, monkeys, and humans, as well as several other undomesticated
species including fish, reptiles, bats, and a variety of avian and
rodent species (e.g., Hampton & Shettleworth, 1996; Vargas, Petruso, &
Bingman, 2004). Also, several studies have compared hippocampal anatomy
within closely related species of rodents, birds, and bats, as well as
humans with different occupations, providing fascinating evidence that
hippocampal size is related to greater use of space in natural habitats
(e.g., Pleskcheva et al., 2000; Safi & Dechmann, 2005; Jacobs, Gaulin,
Sherry, & Hoffman, 1990; Jacobs & Spencer, 1994; Lucas, Brodin, de Kort,
& Clayton, 2004; Maguire, Woollett, & Spiers, 2006).
Many of these studies have been interpreted as
supporting the notion that the hippocampus is selectively involved in
spatial cognition and, in particular, in the creation and use of
cognitive maps (Bingman, Ioale, Casini, & Bagnoli, 1988; Sherry, Jacobs,
& Gaulin, 1992; Salas, Broglio, & Rodriguez, 2003; Jacobs & Schenk,
2003). However, this interpretation is challenged by several of the
studies outlined above that demonstrate a critical role for the
hippocampus in a variety of non-spatial memory tasks. Here I will take
the view that a deeper understanding of hippocampal function in spatial
cognition and memory can be had by altering the focus away from
comparing spatial and non-spatial tasks, and instead focus on the
fundamental demands of spatial tasks that may have led to the evolution
of the hippocampus and its functions in both spatial and non-spatial
memory (Sherry & Shacter, 1987).
In particular, I suggest that the cognitive demands
of spatial memory tasks put a heavy demand on the three fundamental
features of recollection that were examined above. Many natural and
laboratory spatial memory tasks involve remembering where important
objects are located (e.g., food caching in birds). This demand of
spatial memory is a particularly strong and common example of the
general feature of recollection involving memory for items in the
(spatial) context of prior experience. Other laboratory and natural
spatial tasks involve remembering routes through the environment taken
to find rewards or escape locations. Memories for routes provide a
particularly strong example of the general feature of recollection
involving memory for sequences of events, in this case events extended
through space as well as time (e.g., the T-maze alternation study
described above; Wood et al., 2000; for an example in humans see Shelton
& Gabrieli, 2002). Yet other laboratory tasks (e.g., the Morris water
maze) and many natural situations require animals to learn multiple
spatial memories and interleave those memories to form a general
representation of space that can be used to navigate from novel starting
points (e.g., Eichenbaum, Stewart, & Morris, 1990). The networking of
spatial memories and application of spatial networks (cognitive maps) in
inferring novel routes (navigation) is a particularly good example of
the general feature of recollection as based on linking related memories
and employing the generated memory networks to make inferences from
memory.
From this viewpoint, many examples of spatial
learning and memory in nature are especially demanding on all three of
the fundamental properties of recollective memory. Thus, it should come
as no surprise that the hippocampus is important for spatial memory
across many species, that hippocampal neuronal activity reflects the
encoding of spatial location along with other features of events
(Eichenbaum, Dudchencko, Wood, Shapiro, & Tanila, 1999), and that
hippocampal size relates to the high spatial memory demands for animals
with larger or more complex habitats or greater demands for use of
spatial memory in their everyday lives.
Towards a Comparative Functional Organization of the Hippocampal Memory System
Figure 11. A putative functional organization of
the hippocampal memory system. The scheme highlights
parallel pathways for object and context information
that are combined in CA3 to represent object-in-context
and to link memories, and in CA1 to represent sequences
of events. |
|
A consideration of the anatomical organization of the
major circuitry involving the hippocampus and neocortex provides further
insights into basic mechanisms that underlie recollection across diverse
species. In primates, the hippocampus receives an enormous variety of
information from virtually every cortical association area, and this
information is funneled into the hippocampus via the parahippocampal
region, which is subdivided into the perirhinal cortex, the
parahippocampal cortex, and entorhinal cortex (Figure 11). The cortical
outputs of hippocampal processing involve feedback connections from the
hippocampus successively back to the entorhinal cortex, then the
perirhinal and parahippocampal cortex, and finally, neocortical areas
from which the inputs to the hippocampus originated (Amaral & Witter,
1995). To what extent is the organization of this system similar in
mammalian species?
The internal circuitry of the hippocampus itself is
largely conserved across mammalian species (Manns & Eichenbaum, 2007).
The subdivisions of the hippocampus are connected by a serial,
unidirectional path, starting with the dentate gyrus, and continuing
through CA3, then CA1, and then the subiculum. Furthermore, anatomical
details involving several topographical and parallel organizations are
highly similar in species including rats, cats, and monkeys, as well as
other species (see Amaral & Witter, 1995 and Witter, Wouterlood, Naber,
& Van Haeften, 2000 for reviews). There is also considerable
conservation of the areas of the parahippocampal region. The perirhinal,
parahippocampal (called postrhinal cortex in rats), and entorhinal
subdivisions of the parahippocampal region are similar in
cytoarchitecture in rats, mice, and monkeys, and the connectivity among
these areas is also remarkably similar (Burwell, Witter, & Amaral,
1995). In contrast to the conservation of hippocampal and
parahippocampal circuitry, the neocortical regions that are the ultimate
origin of hippocampal inputs differ substantially from species to
species. For example, there are numerous dissimilarities in the
neocortex that reflect general differences between small-brained and
big-brained mammals, such as cortical size, laminar stratification, and
number of polymodal association areas (Krubitzer & Kaas, 2005; Manns &
Eichenbaum, 2007). Furthermore, the extent of cortical areas devoted to
a particular sensory modality also varies substantially between species.
Despite major species differences in the neocortex,
the organization of cortical inputs to the hippocampus is remarkably
similar in rodents and primates. Across species, most of the neocortical
input to the perirhinal cortex comes from association areas that process
unimodal sensory information about qualities of objects (i.e., "what"
information), whereas most of the neocortical input to the
parahippocampal cortex comes from areas that process polymodal spatial
("where") information (Suzuki & Amaral, 1994; Burwell et al., 1995).
There are connections between the perirhinal cortex and parahippocampal
cortex, but the "what" and "where" streams of processing remain largely
segregated as the perirhinal cortex projects primarily to the lateral
entorhinal area whereas the parahippocampal cortex projects mainly to
the medial entorhinal area. Similarly, there are some connections
between the entorhinal areas, but the "what" and "where" information
streams mainly converge within the hippocampus. These anatomical
considerations suggest a functional organization of the flow of
information into and out of the hippocampus. Here I will outline some of
the functional differences between components of the parahippocampal
region and subfields of the hippocampus leading to a working hypothesis
about how the phenomena of recollection emerge from the organization of
hippocampal pathways.
Perirhinal cortex and lateral entorhinal area
Substantial evidence indicates that neurons in the
perirhinal cortex and lateral entorhinal cortex are involved in the
representation of individual perceptual stimuli. Electrophysiological
studies on monkeys and rats performing simple recognition tasks have
identified three general types of responses (Brown & Xiang, 1998; Suzuki
& Eichenbaum, 2000). First, many cells in these areas exhibit selective
tuning to memory cues such as odors or visual stimuli. Second, some
cells maintain firing in a stimulus-specific fashion during a memory
delay, indicating the persistence of a stimulus representation. Third,
many cells have enhanced or suppressed responses to stimuli when they
re-appear in a recognition test, indicating involvement in the
recognition judgment. Similarly, in humans, among all areas within the
medial temporal lobe, the perirhinal area selectively shows suppressed
responses to familiar stimuli (Henson, Cansino, Herron, Robb, & Rugg,
2003). Complementary studies in animals with damage to the perirhinal
cortex indicate that this area may be critical to memory for individual
stimuli in the delayed non-matching to sample task in rats (Mumby &
Pinel, 1994; Otto & Eichenbaum, 1992) and monkeys (Suzuki, Zola-Morgan,
Squire, & Amaral, 1993). These and other data have led several
investigators to the view that the perirhinal cortex is specialized for
identifying the memory strength of individual stimuli (e.g., Brown &
Aggleton, 2001; Henson et al., 2003; Aggleton, Kyd, & Bilkey, 2004).
Parahippocampal cortex and medial entorhinal area
The parahippocampal cortex and medial entorhinal area
may be specialized for processing spatial context. Whereas perirhinal
and lateral entorhinal neurons have poor spatial coding properties,
parahippocampal and medial entorhinal neurons show strong spatial coding
(Burwell & Hafeman, 2003; Hargreaves, Rao, Lee, & Knierim, 2005).
Furthermore, the immediate early gene fos is activated in the perirhinal
cortex by novel visual cues, but fos is activated in the postrhinal
cortex by a spatial re-arrangement of the cues (Wan, Aggleton, & Brown,
1999). In addition, whereas object recognition is impaired following
perirhinal damage, object-location recognition is deficient following
parahippocampal cortex damage in rats (Gaffan, Healey, & Eacott, 2004)
and monkeys (Alvarado & Bachevalier, 2005). Similarly, perirhinal cortex
damage results in greater impairment in memory for object pairings
whereas parahippocampal cortex lesions results in greater impairment in
memory for the context in which an object was presented (Norman &
Eacott, 2005). Parallel findings from functional imaging studies in
humans have dissociated object processing in perirhinal cortex from
spatial processing in the parahippocampal cortex (Pihlajamaki et al.,
2004). Furthermore, whereas perirhinal cortex is activated in
association with the memory strength of specific stimuli (Henson et al.,
2003), the parahippocampal cortex is activated during recall of spatial
and non-spatial context (Ranganath et al., 2003; Bar & Aminoff, 2003).
Hippocampus
Compelling support for differentiation of functions
associated with recollection come from within-study dissociations that
reveal activation of the perirhinal cortex, selectively associated with
familiarity and activity in the hippocampus as well as parahippocampal
cortex, was selectively associated with recollection (Daselaar, Fleck, &
Cabeza, 2006; Davachi & Wagner, 2002; Davachi et al., 2003; Ranganath et
al., 2003). These and many other results summarized in a recent review
suggest a functional dissociation between the perirhinal cortex, where
activation changes are consistently associated with familiarity, and the
hippocampus and parahippocampal cortex, where activation changes are
consistently associated with recollection (Eichenbaum et al., 2006). An
outstanding question in these studies is whether the parahippocampal
cortex and hippocampus play different roles in recollection. In
particular, the above described findings on parahippocampal activation
associated with viewing of spatial scenes suggests the possibility that
this area is activated during recollection because recall involves
retrieval of spatial contextual information. By contrast, the
hippocampus may be activated associated with the combination of item and
context information.
CA1 versus CA3
Several recent studies have suggested that subregions
of the hippocampus may play distinct roles in memory. A particularly
striking contrast comes from a comparison between two studies by Kesner
and colleagues (Gilbert & Kesner, 2003; Kesner, Hunsaker, & Gilbert,
2005). In one experiment, normal rats learned associations between a
particular object or odor and their locations in specific places in an
open field. On each trial, one of two objects (differentiated by visual
or olfactory cues) was placed at one of two locations on a large open
field. If object A was in place one, a reward could be found underneath.
Similarly, if object B was in place two a reward could be obtained by
displacing the object. However, no reward was available if either object
was presented in the alternate location. Normal animals improved in
performance across days, as reflected in differentiating their latencies
to approach object in rewarded vs. non-rewarded locations. Selective
lesions of CA3 completely blocked acquisition of object-place
associations, whereas CA1 lesions had no effect. In contrast, the
opposite pattern of results was found in another study were rats were
taught associations between an object and an odor that were separated by
a short delay. The animals learned that if object A was presented before
the delay, then a cup of sand would contain a food reward if it was
scented with odor 1 (but not with odor 2). Conversely, if object B was
presented first, then a cup of sand would contain a food reward if it
was scented with odor 2 (but not odor 1). Memory was measured by a
briefer latency to approach the scented cup on rewarded pairings (A-1
and B-2) than on non-rewarded pairings (A-2 and B-1). In normal rats,
the latency to approach rewarded cups gradually decreased over daily
training sessions, at about the same rate as observed in the previous
object-place association study. In contrast, rats with selective CA1
lesions showed no sign of acquiring the associations between temporally
separated objects, whereas rats with CA3 lesions acquired the task just
as rapidly as normal animals. These results, and other similar findings
(Kesner et al., 2005), are consistent with the possibility that CA3 is
specialized for the representation of items in the (spatial) context in
which they are experienced, whereas CA1 is specialized for
representation of the order of events that are separated in time (Manns
& Eichenbaum, 2005).
A Species-General Model of Hippocampal Function in Recollection
The diverse lines of evidence reviewed above suggest
that recollection and familiarity are functionally dissociable
processes, and that different components of the hippocampal system make
distinct contributions to recognition memory. Evidence from
neuropsychological, functional imaging, and neurophysiological studies
of rats, monkeys, and humans indicate a distinct role for the
hippocampus in recollection and not familiarity. The parahippocampal
cortex also contributes to recollection, via the representation and
retrieval of contextual (especially spatial) information, whereas the
perirhinal cortex contributes to and is necessary for familiarity-based
recognition.
These findings are consistent with the
anatomically-guided hypothesis about the functional organization of the
hippocampal system presented in Figure 11 and suggest mechanisms by
which the anatomical components of this system interact in support of
the phenomenology of recollection (Figure 12). Following experience with
a stimulus, the perirhinal and lateral entorhinal areas may match a
memory cue to a stored template of the stimulus, reflected in suppressed
activation that signals familiarity. Outputs from perirhinal and lateral
entorhinal areas back to neocortical areas may be sufficient to generate
the sense of familiarity without participation of the hippocampus. In
addition, during the initial experience, information about the
to-be-remembered stimulus, processed by the perirhinal and lateral
entorhinal areas, and about the spatial and possibly non-spatial context
of the stimulus, processed by the parahippocampal and medial entorhinal
areas, converge in the hippocampus. During subsequent retrieval,
presentation of the cue may drive the recovery of object-context
representations in the hippocampus that, via back projections,
regenerates a representation of the contextual associations in
parahippocampal and medial entorhinal areas, which cascades that
information back to neocortical areas that originally processed the item
and contextual information. This processing pathway may constitute the
subjective experience of recollection.
Figure 12. Hypothetical
scheme for encoding and retrieval. (PRC = perirhinal
cortex; PHC = parahippocampal cortex; LEA = lateral
entorhinal area; MEA = medial entorhinal area) |
|
Conclusions
This forgoing overview suggests that the
phenomenology of recollection consists of the capacity to recover
information about a memory that is not present at the time of testing.
That information includes arbitrary associations and the context of a
prior event with the cue, information about flow of events that occurred
in the prior episode, and links to related memories. Notably animals as
well as humans exhibit the capacity to retrieve all these forms of
information derived from memory cues. Also, in animals, as in humans,
the capacities to remember context, order, and related memories each
depend on hippocampal function. Correspondingly, across species, neurons
in the hippocampus encode the kinds of information that support these
features of recollective memory. The demands for these fundamental
features of recollective memory are especially evident in spatial memory
performance observed across a broad variety of species. Finally, the
anatomical findings and data about functional components of hippocampal
circuitry are remarkably similar across mammalian species and suggest a
functional organization of cortical-hippocampal pathways from which
these features of recollection emerge. Because these pathways, and their
particular functional roles in memory, are the same in various animal
species and humans, there exists no reason to postulate a difference in
the outcome of these interactions. That is, there is no reason to
postulate a species difference in the capability of recollective
experience, although the specific contents of memories may differ
substantially because of species differences in cortical
specializations. The impressive convergence of data and theory on the
behavioral features of recollection and on hippocampal system
organization and function offer a preliminary account of conscious
recollection that involves both an evolutionary continuity and a
mechanistic explanation.
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