Sleep And Memory Consolidation

obviously has a great number of secondary effects on disposition, attention, and motivation—further complicating attempts to approach the problem experimentally.

Nevertheless, there are a number of intriguing observations consistent with a role for sleep-associated neuronal activity in memory consolidation. Work in this area has come primarily from Bruce McNaughton, Carol Barnes, Matt Wilson, Gyorgi Buzsaki, and their respective colleagues. These investigators have shown sleep-associated reproduction of specific patterns of hip-pocampal pyramidal neuron firing: firing patterns that mimic firing patterns that the animal had established while awake and learning. In other words, it appears that the hippocampus and cortex are "replaying" episodic events while asleep as part of a process of consolidation of memory. In addition, there are a number of correlative studies suggesting that loss of these types of replay episodes causes memory dysfunction.

On the other hand, in the human literature there is not as much support for the idea of a necessity for sleep per se in memory consolidation. For example, patients with specific types of brain lesions or on certain types of medication never sleep or have profound disruptions of their sleep pattern (see reference 37). There also are a few examples of individuals who spontaneously lose the desire to sleep and are essentially insomniac for their entire remaining lifetime. These phenomena do not lead to any profound memory disruption, dissociating sleep from memory formation. However, given the ambiguity in defining sleep, it certainly is possible that insomniac individuals may have certain sleeplike patterns of CNS activity that functionally substitute for the lack of sleep.

Obviously, resolution of the issue of the role of sleep in memory formation will require much additional study. At this point, however, it looks like the answer could be fascinating.

This is the fundamental quandary of the cognitive neurobiologist, and it shows up over and over again in the contemporary literature in experiments involving monitoring of cellular firing (or functional Magnetic Resonance Imaging (fMRI) signals) in real time in response to environmental stimulation. Where does sensory processing end and cognition begin? How does cellular firing get translated into an abstract construct in the brain? The real potential of beginning to answer these types of questions, which really are the modern reformulation of the philosophical mind-body problem that has intrigued mankind for millennia, is one of the best reasons I can think of to be particularly excited about being a neuroscientist in the contemporary era.

B. Time

The hippocampus is involved not only in processing of spatial information but also in what I will refer to, for lack of a better term, as processing temporal information. I do not necessarily mean that the hippocampus is involved in encoding time itself (which could also be true), but rather I am referring to the hippocampus being involved in temporally dependent learning such as trace associative conditioning and the ability to remember the order of events. Also, the hippocampus exhibits time- and experience-dependent alterations in its cellular firing properties. In this section, we will discuss a few examples of time-dependency of hippocampal function and information processing. We will start with an example of experience-dependent alterations in the behavior of hippocampal place cells as an example of changes in the hippocampus that occur with repeated environmental signals over time. In the next section, we will discuss the important role of the hippocampus in the formation of time-dependent associations, by and large using trace associative conditioning as our example.

We already discussed the impressive, rapid formation of hippocampal place fields when an animal is introduced into a new environment. These place fields are, of course, manifest as a burst of action potential firing in a CA1 pyramidal neuron when an animal enters a particular spatial location (or more precisely when an animal enters what it perceives to be a particular spatial location). What happens to place cell firing over time when the animal re-enters that same location? Are there time-dependent changes in place cell firing properties?

Recent work from the laboratories of Matt Wilson, Gyorgi Buzsaki, and Carol Barnes and Bruce McNaughton, along with several others, has given us clear answers to these two questions. There clearly are time-dependent changes in place cell firing properties that depend on the animal's experience (see Figure 9). Reentering the same place field repetitively over time leads to several pronounced effects on cellular firing patterns, at the level of the individual neuron. These changes are a clear example of experience-dependent changes in the firing properties of hippocampal pyramidal neurons, and, as described earlier, I use them to illustrate "time"-dependent information processing by the hippocampus.

Three specific examples of such cellular changes follow. One, with repeated reentry into the place field of a pyramidal neuron, there is an increase in the place cell's firing rate upon successive reexposure (11). Two, with reentry into a place field, there is a decrease in the latency of the time required for firing the first action potential in a place cell's burst of action potentials (11). Three, the extent of dendritic action potential attenuation decreases over time with experience in the place field (12, we will return to back-propagating action potentials in much more detail in later chapters). Thus, the first entry into a place sets up a hippocampal neuronal place field, but there are subsequent time- and experience-dependent changes in place cell action potential firing properties as well.

The mechanisms underlying this experience-dependent alteration in hip-pocampal pyramidal neuron properties is a subject of active investigation. In fact, we will return in later chapters to many details of the cellular and molecular mechanisms likely mediating these types of changes. For now, suffice it to say that intriguing mechanisms that could be contributing to these changes include activity-dependent changes in sodium or potassium channels in place cell neurons, changes in neuro-modulatory inputs (e.g acetylcholinergic or noradrenergic inputs) to the hippocampus, or activity-dependent synaptic plasticity within the hippocampus itself (12).

Memory for Real Time—Episodic Memory, Ordering, and the CS-US Interval

Experience-dependent changes in hip-pocampal place cell firing patterns only begin to scratch the surface of the involvement of the hippocampus in time-dependent encoding of information and temporal information processing. The hippocampus is necessary for a wide variety of different time-dependent learning tasks. I will briefly highlight a few examples here, but a common theme that is emerging in modern studies of hippocampal function is that the

FIGURE 9 Experience-dependent changes in place cell firing. (A) Histogram of the total firing rate at various distances from the place field center during the first and the last visitation to the same place in an environment (light curve, visit 1; solid curve, visit 17; bin width = 0.41 cm, which corresponds to the resolution of the position tracking camera). Firing rates increase as the animal approaches the place field center. Data and figure from Mehta et al. (11). (B) Activity-dependent attenuation in spike amplitude is reduced with experience. The average (± SE) amplitude attenuation during high-frequency bursts for a population of simultaneously recorded cells is shown on the left. The amplitude of the last spike in a burst is expressed as a fraction of the amplitude of the first spike and is plotted as a function of the number of spikes in the burst. The black line plots the average attenuation for the animal's first 4 minutes in the environment, and the gray line plots the attenuation for the animal's last 4 minutes. The amount of attenuation is reduced with experience. On the right, the average attenuation for bursts of three spikes for the first 4 minutes of exploration in a familiar environment are shown as black bars and for the last 4 minutes are shown as gray bars. A significant (*p < .05, t test) reduction in amplitude attenuation was seen in all data sets (n = 7). Data and figure reproduced with permission from Quirk, Blum, and Wilson (12).

hippocampus is involved in perceiving and encoding temporal relationships, storing memory traces for brief periods of time in associative learning, and indeed that the hippocampus is involved in "episodic" perception in general. Simply stated, the hippocampus appears to be integral to forming a coherent representation of a temporal series of events, corresponding to what we would refer to as a single episode of personal experience.

Obviously if the hippocampus is ultimately involved in mediating the storage of a complex set of individual experiences, forming a representation with the appropriate temporal ordering is key. In Houston, a typical example would be: the cross-walk light changed, I entered the street, the car almost ran me over; this is quite a different experience from any other sequencing of those three items. Recent exciting work by the laboratories of Howard Eichenbaum, Matt Wilson, and John Disterhoft have begun to demonstrate nicely that order-dependent hippocampal information processing is indeed occurring; furthermore, recent elegant work from these labs has begun to explore the cellular and molecular basis for this role.

Early studies in this area asked a simple question: do hippocampal lesions have a greater effect on memory paradigms that involve a time lag during learning? The answer to this question is clearly yes. For example, in one pioneering study, Chiba, Kesner, and Reynolds investigated memories for temporal ordering in rats, who were learning the specific order of presentation of two spatial locations (13). They found that the greater the time-lag between visits to the first site and the second site, the more susceptible the memory formation was to hippocampal lesions. Thus, the hippocampus is involved selectively in forming a memory of event orders when there is a longer intervening time between the first event and the second event.

More recent work (14) has shown that hippocampal lesions disrupt the ability of rats to learn the ordering of olfactory cues. For example, a rat with a hippocampal lesion will have a deficit in remembering the specific order: orange, lemon, winter-green. This is a very nice example of the role of the hippocampus in placing sensory stimuli in the appropriate temporal relationship with each other.

In additional recent studies from Howard Eichenbaum's group, recordings from the hippocampus in vivo in behaving animals has suggested that temporal factors can come into play in the firing of "place" cells. Howard's group has shown that place cells can fire selectively depending on the recent history of the animal (15). In this experiment, they trained rats to make alternating left-hand and right-hand turns as they repeatedly ran a T maze. An animal in the identical spot in a T maze can have a given place cell fire selectively depending on whether it is about to make a left-hand turn or a right-hand turn. These cells may be "intent" cells influencing what the animal will do next. Alternatively, they may be "recent history" cells because what the animal is about to do next depends on what it just finished doing. Regardless, this cell firing pattern clearly shows that "place" cells are not just place cells but something more complex, influenced by the animal's recent history.

In fact, it is intriguing to consider that a potential clue to this aspect of pyramidal neuron function was there in the very first description of place cells by O'Keefe and Dostrovsky. Place cells don't just fire depending on location, they also only fire when the animal is moving in a specific direction through the place field. Obviously an animal moving in one direction in a place field has had a different recent experience than when it crossed the same spot moving in the opposite direction. This is pure speculation, but interesting to consider as a possibility.

The most extensively studied example of hippocampal involvement in time-dependent information processing is trace associative conditioning. You will recall from the last chapter that in trace conditioning a time lag is introduced between the CS and the US, typically in the range of a few seconds to a few minutes. The most popular experimental model to study this is trace eye-blink conditioning, although trace cued fear conditioning has recently begun to be utilized as well. Hippocampal lesions of various sorts (anatomical, pharmacologic, molecular) lead to a loss of trace eye-blink or fear conditioning in animals up to and including the human (1, 16, 17). The time-dependent specificity of the involvement of the hippocampus is illustrated by the observation that delivery of the identical stimuli with no intervening time lag (unfortunately designated as

"delay" conditioning, although there is no delay between CS and US) is perfectly normal in hippocampal lesioned animals. Thus, the hippocampus is selectively involved in memory formation that incorporates a time-dependent component.

What is happening in the hippocampus during trace associative conditioning? This fascinating question is being explored at present, and at least a few answers are available. Hippocampal pyramidal neurons in area CA1 show large increases in their firing rates during the learning period, especially early in training when pyramidal neurons show increased firing in response to both the CS and the US (see Figure 10 and references 18 and 19 for more details). Thus it is possible that pyramidal neurons maintain a representation of the CS over time so that it can be associated with the US. Howard Eichenbaum has proposed a more sophisticated model, which he refers to as the episodic encoding model (20, 21). In this model, the hippocampus forms a temporal representation of a single event based on the specific order of firing of individual (or groups of) CA1 pyramidal neurons. Thus, the firing of ensembles of cells in a particular order would represent a specific episode in the animal's life, preserving the temporal relationships with fidelity. This type of information could then be used in the storage of a learned relationship between two stimuli separated in time. Overall, while the circuit properties underlying the role of the hippocampus in temporal information processing are still unclear at this time, new insights have been gained, and much effort is being devoted to this problem.

If the circuitry is unclear, the cellular and molecular mechanisms are even more

Time CS US

FIGURE 10 Increased hippocampal neuron firing during trace eye-blink conditioning. Average peri-event histograms (10 ms bins) for pyramidal cell response profile recorded from rabbits during trace conditioning. Action potentials (spikes) from each cell were summed across a single training session, then averaged across cells. The duration of the histogram is 3750 ms, and the duration of the baseline period prior to CS onset is 1000 ms. Of all tested pyramidal cells, 7.4% display this type of response profile. Data and figure reproduced with permission from McEchron, Weible, and Disterhoft (19).

It is worth noting that many neocortical neurons exhibit this same type of firing pattern, that is, a residual increase in firing after the presentation of an environmental stimulus. This has been most extensively documented in neurons in the visual system. This is important to keep in mind because clearly the hippocampus is not the only area of the brain encoding temporal information.

Time CS US

FIGURE 10 Increased hippocampal neuron firing during trace eye-blink conditioning. Average peri-event histograms (10 ms bins) for pyramidal cell response profile recorded from rabbits during trace conditioning. Action potentials (spikes) from each cell were summed across a single training session, then averaged across cells. The duration of the histogram is 3750 ms, and the duration of the baseline period prior to CS onset is 1000 ms. Of all tested pyramidal cells, 7.4% display this type of response profile. Data and figure reproduced with permission from McEchron, Weible, and Disterhoft (19).

It is worth noting that many neocortical neurons exhibit this same type of firing pattern, that is, a residual increase in firing after the presentation of an environmental stimulus. This has been most extensively documented in neurons in the visual system. This is important to keep in mind because clearly the hippocampus is not the only area of the brain encoding temporal information.

mysterious. Tantalizing clues have emerged, however. For example, trace fear conditioning is dependent on N-methyl-D-aspartate (NMDA) receptor function in CA1 pyramidal neurons, as was recently demonstrated in a very sophisticated study using genetically engineered mice (17). John Disterhoft's lab has also shown that trace eye-blink conditioning results in increases in CA1 pyramidal neuron membrane excitability and an increase in synaptic efficacy at the connections between neurons in area CA3 and area CA1 (see reference 22 and Figure 11). The contributions of these specific mechanisms to the role of the hippocampus in temporal information processing will hopefully become more clear as work in this area continues.

Overall, these studies directly demonstrating changes in hippocampal pyramidal neuron firing in time-dependent associative learning are a beautiful example of cognitive processing of real time. They suggest that hippocampal pyramidal neurons encode the maintenance of a representation of a sensory stimulus, in the absence of any continued presentation of the stimulus itself.1 This representation functions to allow a subsequent association of that sensory input with a temporally removed, second sensory stimulus.

C. Multimodal Associations— The Hippocampus as a Generalized Association Machine and Multimodal Sensory Integrator

Even the earliest reports of place cells noted that they are multimodal sensory integrators. In an early study where O'Keefe began to investigate "why they fire where

1It is important to note that this may not take place entirely within the hippocampus. For example, a larger circuit of which the hippocampus is a part may carry out this function. Particularly appealing in this context is the possibility of reciprocal hippocampal-neocortical projections participating in a short-term memory store, given the variety of evidence demonstrating the maintained firing of cortical neurons in vivo after various sensory stimuli.

they fire," he trained rats in a T maze using four different external visual cues as the spatial landmarks (6). He then proceeded to query the animal's hippocampus by recording how place cell firing patterns changed when one or several of the spatial cues were removed. He found that some place cells used one or two of the cues as the relevant landmarks while the remainder of the landmarks were immaterial to their firing—a fairly straightforward result. However, he also observed some place cells that were triggered by any combination of any two landmarks. As far as these cells were concerned, landmarks A + B was equivalent to landmarks C + D was equivalent to A + C, and so on. Thus, two environments that were different from each other visually (A + B versus C + D, for example) were treated as equivalent as long as the animal had had the opportunity to previously learn that A, B, C, and D were always present in a consistent spatial relationship to each other. The place cell firing apparently had come to represent an abstraction, an integration of four spatial cues. Apparently any two cues were sufficient to allow the place cell (or something upstream of it) to reconstruct a representation of the entirety of the space.

More recent work has made clear the role of the hippocampus in general, and "place" (i.e., pyramidal) cells in particular, in multimodal sensory integration. Howard Eichenbaum and his collaborators have been leaders in this pursuit, and they have made many seminal observations in this area. Their findings have completely changed the way we look at the function of the hippocampus. In this next section, I will highlight two of the studies from Howard Eichenbaum and his co-workers that I consider to be landmarks in the field.

Eichenbaum's lab has used the four-arm radial maze in many studies (see Figure 7). The set-up in the basic version of the experiment is quite simple—there are four arms to the plus-shaped maze, and the maze is in a room with one unique visual

FIGURE 11 Increased connectivity in hippocampal pyramidal neurons with eye-blink conditioning. Hippocampal slices were prepared and physiologic responses monitored in vitro, using control animals and trace-conditioned animals. (A) Diagram showing rabbit hippocampal slices in vitro with placement of stimulating electrode (SE), and somatic (R1) and dendritic (R2) recording electrodes. To the right are representative field potentials (excitatory postsynaptic responses) from each type of recording one hour after conditioning. The following structures are also labeled: Schaffer collaterals (sc), perforant path (pp), dentate gyrus (DG), mossy fibers (mf), CA1 and CA3. (B) Effects of conditioning on Schaffer collateral evoked field potentials recorded in CA1. Means ± SE are given for trace-conditioned (1 hour, n = 9; 24 hour, n = 13), pseudoconditioned (1 hour, n = 9; 24 hour, n = 8), and naive (n = 7) animals for each stimulus intensity value. (a) Excitatory Postsynaptic Potential (EPSP) slope recorded in dendrites was greater in slices prepared from conditioned animals 1 hour after conditioning. (b) No significant differences in initial EPSP slope were seen between conditioning groups 24 hours after conditioning. No conditioning effect was seen in population spike amplitude input-output function 1 hour (c) or 24 hours (d) after conditioning; population spikes indicate action potential firing in the post-synaptic CA1 pyramidal neurons. Diagram and data reproduced with permission from Power, Thompson, Moyer, and Disterhoft (22).

FIGURE 11 Increased connectivity in hippocampal pyramidal neurons with eye-blink conditioning. Hippocampal slices were prepared and physiologic responses monitored in vitro, using control animals and trace-conditioned animals. (A) Diagram showing rabbit hippocampal slices in vitro with placement of stimulating electrode (SE), and somatic (R1) and dendritic (R2) recording electrodes. To the right are representative field potentials (excitatory postsynaptic responses) from each type of recording one hour after conditioning. The following structures are also labeled: Schaffer collaterals (sc), perforant path (pp), dentate gyrus (DG), mossy fibers (mf), CA1 and CA3. (B) Effects of conditioning on Schaffer collateral evoked field potentials recorded in CA1. Means ± SE are given for trace-conditioned (1 hour, n = 9; 24 hour, n = 13), pseudoconditioned (1 hour, n = 9; 24 hour, n = 8), and naive (n = 7) animals for each stimulus intensity value. (a) Excitatory Postsynaptic Potential (EPSP) slope recorded in dendrites was greater in slices prepared from conditioned animals 1 hour after conditioning. (b) No significant differences in initial EPSP slope were seen between conditioning groups 24 hours after conditioning. No conditioning effect was seen in population spike amplitude input-output function 1 hour (c) or 24 hours (d) after conditioning; population spikes indicate action potential firing in the post-synaptic CA1 pyramidal neurons. Diagram and data reproduced with permission from Power, Thompson, Moyer, and Disterhoft (22).

cue on each wall. The animal learns to use the spatial cues to navigate to food rewards in the maze. Firing patterns for hippocam-pal place cells recapitulate what we described previously—they fire dependent upon the animal's location in space relative to the distal visual cues. In addition, as expected, they are direction-dependent; that is, they fire selectively when the animal is moving either outward into an arm or inward back toward the center of the maze.

What happens when you have local cues within the arms of the maze? Eichenbaum's group addressed this question by preparing their four-arm maze with distinct visual, olfactory, and tactile cues in each of the four arms, in addition to the four distal visual cues on the wall (23, 24; see Figure 12). When they train their animals in this maze, they find cells that fire selectively dependent upon the texture of the floor and the olfactory cues that are present. If there are cells in the hippocampus that fire in response to distal visual cues and also cells that fire in response to local cues, are they

FIGURE 12 Four-arm radial maze with local and distal cues. The four-arm radial maze set-up used in the experiments such as those performed by Tanila et al. (7, 24; see text and Figure 13) is used to assess effects of manipulation of local and distal cues. Local cues are coverings of the arms that give a set of visual, tactile, and olfactory cues distinct form the other arms. The distal cues are objects on each wall surrounding the maze. Reproduced with permission from Tanila, Sipila, Shapiro, and Eichenbaum (7).

FIGURE 12 Four-arm radial maze with local and distal cues. The four-arm radial maze set-up used in the experiments such as those performed by Tanila et al. (7, 24; see text and Figure 13) is used to assess effects of manipulation of local and distal cues. Local cues are coverings of the arms that give a set of visual, tactile, and olfactory cues distinct form the other arms. The distal cues are objects on each wall surrounding the maze. Reproduced with permission from Tanila, Sipila, Shapiro, and Eichenbaum (7).

mutually exclusive? The answer is no—in fact, there are individual cells that fire in response to both local cues and distal cues when they are presented separately. Moreover, there are some cells that fire only when all the cues are presented together. Their firing depends on the simultaneous presence of all the various cues. This latter finding suggests that these cells are firing in response to (or in order to produce) an aggregate representation of all the cues!

Finally, we come to the piece de resistance— what happens to these multimodal cells, cells that respond to both local cues and distal cues, if you change the relationship of the local cues to the distal cues? Eichenbaum and his colleagues did a clever manipulation where they asked that question: the "double rotation" experiment (Figure 13). They trained animals in a multicue maze that contained both local cues and distal visual cues and then rotated the visual cues 90° counterclockwise and the local cues 90° clockwise. When the animal is placed back in the manipulated maze what happens to the firing of the cells? The firing of some cells tracks the visual cues, as expected of place cells. The firing of other cells tracks the local olfactory, tactile, and visual cues—sort of a variant of the classic place cell. However, there are some single cells that track both the local and distal cues. They continue to fire when the animal is in a particular arm of the maze with specific local cues, and fire in a different arm of the maze that is in the original orientation relative to the distal visual cues. Thus, hippocampal pyramidal neuron firing can track local cues, can track distal cues, or can track both independently. In the latter case the cell appears to encode an A + B + C + D representation as discussed earlier, where either A + B or C + D is sufficient to trigger firing. In this case, it is even more complex because the different cues are nonequivalent; that is, some are distal visual cues and some are local tactile and olfactory cues.

Double

Standard Rotation

FIGURE 13 Double rotation four-arm maze experiment. In this experiment, the four local cues were rotated 90° to the left as the distal cues were rotated 90° to the right. The responses of four simultaneously recorded cells (cells 1-4) are shown here before and after the double rotation of the cues. Data and figure reproduced with permission from Tanila, Shapiro, and Eichenbaum (24). Copyright © 1997 John Wiley and Sons, Inc.

FIGURE 13 Double rotation four-arm maze experiment. In this experiment, the four local cues were rotated 90° to the left as the distal cues were rotated 90° to the right. The responses of four simultaneously recorded cells (cells 1-4) are shown here before and after the double rotation of the cues. Data and figure reproduced with permission from Tanila, Shapiro, and Eichenbaum (24). Copyright © 1997 John Wiley and Sons, Inc.

FIGURE 14 Continuous odor-guided non-matching to sample. This diagram outlines an experiment to assess the ability of the animal to distinguish a matching or non-matching stimulus. The animals must determine if the second smell that they experience is the same or different than the first, if the third is the same or different than the second and so on. In this example, Test 1 has Odor A; Test 2 has Odor B, a non-match. Test 3 also has Odor B so the third is a match to the second. Only non-matches contain a food reward.

FIGURE 14 Continuous odor-guided non-matching to sample. This diagram outlines an experiment to assess the ability of the animal to distinguish a matching or non-matching stimulus. The animals must determine if the second smell that they experience is the same or different than the first, if the third is the same or different than the second and so on. In this example, Test 1 has Odor A; Test 2 has Odor B, a non-match. Test 3 also has Odor B so the third is a match to the second. Only non-matches contain a food reward.

Thus we have seen our first example of the fact that "place cell" is really a misnomer. Hippocampal pyramidal neurons are place cells, but they also can be texture cells and olfactory cells, and they also can be place + texture + olfactory cells. In the next experiment I will describe, Howard Eichenbaum's lab went on to show that the world of the hippocampal pyramidal neuron is even more complex than that. Hippocampal pyramidal neurons are multimodal association cells that are involved in encoding a wide variety of contingencies and relationships.

In preparing to do their experiment, Howard and his colleagues Emma Wood and Paul Dudchenko first trained rats in a contingency task—a task with the accurate but cumbersome descriptor "continuous odor-guided non-matching to sample" (25). One aspect of the task is that rats learn that small cups filled with sand sometimes have food rewards in them. Moreover, each sand cup has one of nine odor cues mixed in with it, spicy smells such as thyme and paprika. How does a rat know if a specific sand cup has food buried in it or not? The sand cups are presented sequentially, and if the smell of the cup presented is different from the previous one, then the rat knows there is food buried in the new cup. Thus, continuous (presented sequentially) odor-guided (smell of the cup) non-matching (different) to sample (from the previous one). In presenting many odors in a row, the investigators were also careful to vary the order of presentation so that sequences of odors could not be used to predict the food—in other words, only the odor presented immediately before could be used to predict the food reward.

After rats learned this fundamental contingency, an additional layer of complexity was added that was irrelevant to the rats, but of fundamental import to the rattesters (see Figure 14). The food cups were presented to the rats randomly at one of nine different locations in an open field surrounded by spatial cues (can you say place cell?). The positions of placement in the matrix were carefully controlled so that this variable did not allow prediction of the presence or absence of the food reward.

In considering the entirety of the task, then, a number of different individual components can be identified. The rats at any given time will be in a particular place. At some times they will be approaching the location of the new food cup, as they move from one place to the next. When they smell the new cup they will be sensing the odor. After sensing the new odor, they will ascertain whether it is a match/nonmatch to the previous odor.

What happens if, like Wood, Dudchenko, and Eichenbaum, you are able to record pyramidal neuron firing in the animals' hippocampi while they perform this task? If you were in this enviable position you would find that hippocampal pyramidal neurons exhibit an amazing array of sophisticated firing patterns (Figure 15). Some cells fire selectively only when the animal is approaching a food cup, regardless of where it is (Figure 15D). Perhaps they are encoding that the animal is about to have to make a decision about the content of the cup. Or perhaps they encode some abstract representation of the food cup itself. Some cells respond selectively to specific odors only (Figure 15A). Some cells fire selectively depending on whether the odor matches or doesn't match the previous odor, regardless of the odor being presented or where it is (Figure 15C). Perhaps they are reward/no reward cells, or perhaps they are contingency cells. Thus, specific hippocampal pyramidal neurons can be considered odor cells, or approach cells, or match/non-match cells—an amazing array of possibilities.

Not surprisingly, some cells are simply place cells (Figure 15B). However, some cells are specific place + odor cells, firing at only one place in the matrix and only upon the presentation of a specific odor. Some cells are place + match/nonmatch cells. Finally, a few cells were even so specialized as to be place + odor + match/nonmatch cells. Just think about it! These cells will fire only in a specific place in response to a specific odor and only if it does not match the previous odor. These cells appear to encode complex, multimodal associations among locations, sensory stimuli, and recent history—a significant step up from "place" cells.

These findings from Eichenbaum's lab fundamentally change the way we should think about the hippocampus. Pyramidal neurons are sensory integration cells. They are involved in making sophisticated associations and correlations of sensory stimuli with specific places, in the context of the animal's prior history.

Overall, the wide variety of studies we discussed in this section, which used in vivo recording techniques in the behaving animal, suggest an amazingly complex involvement of the hippocampus in sensory processing—suggesting its involvement in cognitive processing of space, time, and relationships.

Finally, these experiments illustrate the power of, but also the important caveat for, the "measure" experiment when studying the behaving animal. Measuring things in vivo is quite powerful because you can ascertain that specific things are happening as the animal learns. However, there also is the limitation that the interpretation of the data may be limited by our own lack of discernment of what is going on in the animal's brain. Cells that in previous studies had been characterized as "place" cells likely were encoding information much more sophisticated than the experimenters realized. The interpretation of data in a behavioral "measure" experiment may fall short simply because the experimenter has not fully appreciated everything that is happening with the animal's cognitive processing.

Our interpretation is limited by what we think we are asking the animal to do, based on our own thinking about the task when we design the experiment. However, the animal may be learning many things about its environment, and about what is happening to it, that are not apparent to us. These learning events will result in real

FIGURE 15 Task related firing patterns of hippocampal pyramidal neurons. Panels A-C in this figure show the firing rate in 1-second analysis period for each trial type (M = match; NM = non-match), cup location (P1-P9), and odor (O1-O9) for three different types of cells: (A) an odor cell (odor, F(8,74) = 8.59, P < .0001; trial type, F(1,74) = 0.04, not significant (NS); cup location F(874) = 1.03, NS; odor x trial type, F(874) = 1.74, NS); (B) a location cell (cup location, F(8 74) = 8.60; P <.0001; odor, F(8,74) = 0.84, NS; trial type F(1,74) = 2.76, NS; odor x trial type F(8,74) = 1.14, NS; cup x trial type, F(8,74) = 1.58, NS); (C) , a match cell (trial type, F(1,74) = 22.95, P < .0001; odor, F(874) = 1.42, NS; location, F(8 74) = 1.17, NS; odor x trial type, F(8 74) = 0.68, NS; location x trial type, F(8 74) = 1.20, NS). Panel d shows firing rates (200 ms bins) for 3 second period when the rat approached each cup position (P1-P9), and averaged across all positions (all P) for an approach cell (trial period, t(1,107) = 10.77, P < .001; trial type, F(174) = 0.06, NS; odor F(8,74) = 0.47, NS; Location F(8,74) = 1.42, NS; Odor x trial type, F(8,74) = 0.96, NS; location xtrial type, F(874) = 1.00, NS). Each panel also shows the waveform of the cell recorded on each tetrode channel and a raster display of firing patterns time-locked to the end of the odor sample period. Data, figure, and figure legend reproduced from Wood, Dudchenko, and Eichenbaum (25).

FIGURE 15 Task related firing patterns of hippocampal pyramidal neurons. Panels A-C in this figure show the firing rate in 1-second analysis period for each trial type (M = match; NM = non-match), cup location (P1-P9), and odor (O1-O9) for three different types of cells: (A) an odor cell (odor, F(8,74) = 8.59, P < .0001; trial type, F(1,74) = 0.04, not significant (NS); cup location F(874) = 1.03, NS; odor x trial type, F(874) = 1.74, NS); (B) a location cell (cup location, F(8 74) = 8.60; P <.0001; odor, F(8,74) = 0.84, NS; trial type F(1,74) = 2.76, NS; odor x trial type F(8,74) = 1.14, NS; cup x trial type, F(8,74) = 1.58, NS); (C) , a match cell (trial type, F(1,74) = 22.95, P < .0001; odor, F(874) = 1.42, NS; location, F(8 74) = 1.17, NS; odor x trial type, F(8 74) = 0.68, NS; location x trial type, F(8 74) = 1.20, NS). Panel d shows firing rates (200 ms bins) for 3 second period when the rat approached each cup position (P1-P9), and averaged across all positions (all P) for an approach cell (trial period, t(1,107) = 10.77, P < .001; trial type, F(174) = 0.06, NS; odor F(8,74) = 0.47, NS; Location F(8,74) = 1.42, NS; Odor x trial type, F(8,74) = 0.96, NS; location xtrial type, F(874) = 1.00, NS). Each panel also shows the waveform of the cell recorded on each tetrode channel and a raster display of firing patterns time-locked to the end of the odor sample period. Data, figure, and figure legend reproduced from Wood, Dudchenko, and Eichenbaum (25).

biological signals that we may misinterpret or underinterpret due to our inherent inability to perceive the environment in the same way as the experimental subject.

D. The Hippocampus is also Required for Memory Consolidation

Consolidation is the general term for the process by which memories are rendered stable and lasting (see references 21, 26, and 27). Its existence as a phenomenon has been reliably demonstrated by many investigators using many different learning paradigms over a span of four decades. Despite its long history of investigation, however, the process is quite mysterious. For example, it is not clear if consolidation is a process whereby a short-term memory is rendered long-lasting (i.e., a process of serial conversion of short-term to long-term memory), or if short-term and longer-term memories of a given event are consolidated entirely separately.

A few things are clear, however. Consolidation clearly is not a unitary process. There are consolidation processes that subserve different types of learning (explicit versus implicit, for example) and that, at a minimum, utilize different brain areas. There also are distinct consolidation processes for short-term, intermediate-term, and long-term memories that probably are different—we will return to this in the last chapter of the book. There also is a clear distinction between consolidation of memory versus storage of memory. Brain lesions to specific areas can lead to a selective disruption of consolidation of new memories without affecting storage and recall of old memories The classic studies illustrating this distinction involve patient "H.M." The story of H.M. has been told, retold, and analyzed repeatedly in the learning and memory literature, so I will only briefly review the case here. The first studies of H.M. and his memory deficits are landmarks in the field and helped unequivocally establish the existence of memory consolidation as a distinct process (2, 28, 29).

H.M. is (he is still alive at this writing) an unfortunate victim of human neurosurgical experimentation. H.M. initially presented in the early 1950s with epilepsy that was effectively untreatable by any of the drugs or procedures of the day. His seizures were profound and debilitating. His physicians hypothesized that his seizures originated in the hippocampus, a known and common locus of seizure generation. A neurosurgeon named William Scoville performed a bilateral medial temporal lobe resection on his patient in an admittedly desperate attempt to control the seizures. This procedure removed most of H.M.'s hippocampi on both sides along with the adjacent cortical tissue, and the amygdala (see reference 29 and Figure 16).

This iatrogenic lesion partially treated the epilepsy and essentially completely destroyed H.M.'s capacity for long-term memory consolidation. H.M.'s prior memories are mostly intact for his lifetime up to several years predating the surgery. However, since the time of the surgery, H.M. has been essentially completely unable to form any new long-lasting memories. He has been living a minute-to-minute existence for the last 49 years. His only new memories are of facts to which he has been exhaustively exposed and re-exposed. Testing of H.M. has unambiguously demonstrated the existence of consolidation processes in human memory. He has preservation and stability of a large number of pre-existing memories and a clear capacity to recall them consistently. What he does not have is the capacity to make any new memories that last for more than a few seconds without continuous rehearsal.

There has been a general tendency to ascribe this deficit to loss of the hippocampus, which is consistent with a wide variety

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Eliminating Stress and Anxiety From Your Life

Eliminating Stress and Anxiety From Your Life

It seems like you hear it all the time from nearly every one you know I'm SO stressed out!? Pressures abound in this world today. Those pressures cause stress and anxiety, and often we are ill-equipped to deal with those stressors that trigger anxiety and other feelings that can make us sick. Literally, sick.

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