Download Gamma Oscillations in the Hippocampus

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PHYSIOLOGY 25: 319 –329, 2010; doi:10.1152/physiol.00021.2010
Gamma Oscillations in the Hippocampus
Gamma oscillations are thought to temporally link the activity of distributed
cells. We discuss mechanisms of gamma oscillations in the hippocampus and
Laura Lee Colgin and
Edvard I. Moser
Kavli Institute for Systems Neuroscience and Centre for the
Biology of Memory, MTFS, Norwegian University of Science and
Technology, Trondheim, Norway
[email protected]
review evidence supporting a functional role for such oscillations in several key
hippocampal operations, including cell grouping, dynamic routing, and memory. We propose that memory encoding and retrieval are coordinated by
different frequencies of hippocampal gamma oscillations and suggest how
transitions between slow and fast gamma may occur.
1548-9213/10 ©2010 Int. Union Physiol. Sci./Am. Physiol. Soc.
with each theta cycle providing a discrete unit for
sensory information processing in the brain (see
Ref. 44 for a review).
The second type of synchronization mechanism
seen in the hippocampus during alert behaviors is
the relatively fast gamma oscillation (⬃25–140 Hz).
Gamma oscillations in the hippocampus exhibit
their largest amplitude when they are nested
within the slower theta oscillations (5, 11, 49, 77).
Although the two types of oscillatory activity often
co-occur, hippocampal theta and gamma rhythms
appear to be independently generated (48, 77). Unlike theta rhythms, which remain relatively stable
throughout active behaviors, gamma oscillations
occur in bursts at particular times within the theta
cycle (5, 12, 14, 74, 77) and have been proposed to
select particular cell assemblies for processing at
those times (37, 38, 51, 68). Because of their high
frequency, gamma oscillations are ideally suited
for operations that require neuronal coordination
on a time scale that is beyond the range of conscious perception. This type of fast coordination
may be needed during many fundamental operations of the hippocampus, including rapidly selecting inputs, grouping neurons into functional
ensembles, retrieving memories needed to correctly perform a previously learned task, and determining which aspects of an experience will later
be remembered. All of these processes likely involve not only activating selected cell ensembles
but also filtering out unnecessary inputs. Consistent with this idea, gamma oscillations in hippocampal LFP recordings are not associated with
gamma-related firing in all principal neurons but
rather only with a particular subset of neurons at a
given time (14, 16, 68).
In this review, we will summarize evidence
showing that gamma oscillations synchronize the
activity of select ensembles of cells during many
functions of the hippocampus. We will first describe results elucidating the origins and mechanisms of gamma generation in the hippocampus
and discuss the functional significance of these
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Many cognitive operations require dynamic coordination of activity across distributed groups of
neurons. Several mechanisms exist for this purpose,
but one of the best understood is synchronization
of neuronal activity by oscillations. Oscillations
can be readily studied using local field potential
(LFP) recording techniques. LFPs are measured extracellularly and, for the most part, reflect the spatial integration of voltages generated by currents
flowing in and out of the dendrites of many neurons within an area. When postsynaptic activity
across many cells is periodically synchronized, oscillations appear in LFP recordings. Widespread
use of LFP recording techniques over the last several decades has provided a great deal of evidence
suggesting that oscillations are not merely an epiphenomenon but are instead important for temporal coordination of neural activity on a relatively
fast time scale.
In the hippocampus, a brain region critically
involved in encoding, storage, and retrieval of
memory (75), two main types of oscillations synchronize neuronal activity during active waking
behaviors. These two types of oscillations are
termed theta and gamma rhythms, and their distinctive temporal properties fit well with different
coordination functions. The theta rhythm is a large
amplitude, relatively slow (4 –12 Hz), and highly
regular rhythm that plays an important role in
spatial and episodic memory processing (see Ref.
10 for a review). Theta rhythms in the hippocampus correlate with theta in many hippocampal
efferent and afferent structures, including the entorhinal cortex (54), septum (59), amygdala (66),
parasubiculum (30), striatum (18), and prefrontal
cortex (40). Synchronized theta oscillations are
well suited for connecting widespread networks of
neurons due to their ⬃100- to 200-ms-wide period
that can tolerate long conduction delays. Hippocampal theta rhythms correlate with intake of
sensory information during movements such as
whisking and sniffing in rats and may temporally
segment samples of stimuli from the environment,
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results. Experiments supporting a critical functional role for gamma oscillations in several key
operations of the hippocampus will then be reviewed. To conclude, we will introduce novel hypotheses regarding the functional relevance of
hippocampal gamma oscillations and suggest a
number of unresolved questions for future testing.
Origins and Cellular Mechanisms of
Hippocampal Gamma Oscillations
Entrainment by Two Oscillators
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Role of Inhibition
In a system that relies on fast temporal correlations
to link interactions among cells, the activity of
most cells in the network at any given time must be
suppressed because otherwise many cells would
fire near synchronously just by chance (87). In
accordance with this idea, many lines of evidence
point to the conclusion that the primary driving
force behind hippocampal gamma oscillations is
rhythmic inhibitory postsynaptic potentials (IPSPs)
in the pyramidal cells. In an early study, high correlations were consistently seen between interneuron spike
times and the phase of gamma oscillations, whereas
pyramidal cell firing was not consistently related to
gamma phase (11). A later study investigated intracellular recordings from CA1 and CA3 pyramidal
neurons during gamma oscillations in anesthetized rats to determine which intracellular currents
correlated with gamma oscillations in the field potentials (74). Intracellular gamma oscillations were
not immediately apparent, but intracellular injection of chloride ions induced gamma frequency
(25–50 Hz) depolarizing potentials in pyramidal
cells that were coherent with gamma oscillations in
the field (FIGURE 1). Because chloride injection at
resting potential converts IPSPs into depolarizing
responses, the results indicated that the gamma
oscillations reflect gamma frequency IPSPs in pyramidal cells. A later intracellular study using
urethane-anesthetized rats found that the amplitude of intracellular gamma oscillations recorded
in pyramidal cells was smallest in the range of the
chloride equilibrium potential (i.e., between ⫺60
and ⫺80 mV), and the phase of the intracellular
oscillations also reversed in this voltage range (62).
Thus the results from pyramidal cell intracellular
recording studies supported the conclusion that
gamma oscillations reflect rhythmic IPSPs in pyramidal cells.
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The results of several studies support the conclusion that there are two independent generators of
hippocampal gamma oscillations, one located in
the EC and another in CA3. A study conducted by
Bragin and colleagues (5) in behaving rats employed current source density (CSD) analyses of
hippocampal gamma activity and found the largest
estimated excitatory currents in the middle third of
the dentate gyrus molecular layer, i.e., the termination zone for medial entorhinal cortex (MEC)
projections. Furthermore, CSD profiles for dominant currents during gamma oscillations resembled CSD profiles for responses evoked by medial
perforant path stimulation, and lesions of the EC
caused these gamma-associated excitatory currents to virtually disappear. The average frequency
of the remaining gamma oscillations was lower in
lesioned animals than in control animals, and the
maximal gamma power shifted to CA1 with large
excitatory currents appearing in stratum radiatum,
a layer that receives CA3 projections. Additional
support for an entorhinal generator of hippocampal gamma oscillations was provided by CSD studies in partially decorticated, anesthetized guinea
pigs (13). In this study, large excitatory currents
associated with gamma oscillations were observed
in CA1 stratum lacunosum-moleculare, the target
area for perforant path fibers from the EC. The
gamma-associated currents were not disrupted by
knife cuts between CA3 and CA1 but were completely eliminated by lidocaine or tetrodotoxin injections to the EC. A more recent study in awake
behaving, non-lesioned rats further investigated
the driving forces behind hippocampal gamma oscillations (16). In this study, gamma oscillation
peaks were detected in EEG recordings, and gamma
cycle averages were constructed. Gamma peaks
were detected in two reference sites, the CA1 and
dentate gyrus cell body layers, and CSD maps were
constructed to estimate currents during gamma
oscillations in these regions. When CA1 was used
as the reference for detecting gamma, excitatory
currents were seen in CA3 and CA1 in the layers
that are targeted by CA3 projections. When the
dentate gyrus was chosen as the reference site,
gamma oscillations in the dentate gyrus were
coherent with gamma in CA1 stratum lacunosummoleculare, the layer that receives direct input
from EC. The authors concluded that there are two
generators of hippocampal gamma oscillations,
one in the dentate gyrus that depends on input
from EC and another that emerges in CA3 and
propagates to CA1. The two gamma oscillators
were reported to usually be independent but still
able to couple at times. A recent study suggested
that the two gamma generators may produce different frequencies of gamma oscillations in CA1
(14). Slow and fast gamma oscillations in CA1 were
entrained by CA3 and MEC, respectively, and
tended to occur on different phases of the underlying theta cycles. Taken together, the results of
these studies suggest that gamma oscillations in
the hippocampus are driven by CA3 inputs at some
times and by entorhinal inputs at other times.
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Recordings from interneurons during gamma
oscillations further supported this conclusion. In
the study by Penttonen and colleagues mentioned
above (62), histologically verified basket cells burst
at theta frequency, with gamma-frequency (20 – 80
Hz) firing occurring within the bursts. Importantly,
the gamma-frequency firing of the basket cells was
phase locked to the gamma oscillations in the field,
suggesting that basket-cell firing directly contributes to gamma-associated IPSPs in pyramidal cells.
Basket cells predominantly innervate the cell body
and proximal dendritic region of pyramidal cells
and thus are well situated to potently inhibit the
pyramidal cell population. A more recent study of
Example recordings from CA1 during periods of spontaneously occurring theta-gamma oscillations are shown
under control conditions (A) and after addition of KCl to
the intracellular recording pipette (B). In each panel, intracellular recordings from pyramidal cells (1) appear
above simultaneously recorded extracellular field potentials (2). Note that intracellular gamma oscillations were
not apparent until after injection of chloride ions. Intracellular gamma oscillations elicited by chloride ions (indicated by arrow) coincided with gamma oscillations in
the extracellular recording and were largest in amplitude on a particular portion of the theta cycle. The arrowheads indicate the portion of the theta cycle when
intracellular gamma activity was substantially lower in
amplitude. Scale: 500 ms; 20 mV and 1 mV for intracellular and extracellular recordings, respectively. Figure is
adapted from Ref. 74.
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FIGURE 1. Gamma oscillations reflect inhibitory
postsynaptic potentials in pyramidal cells
interneuron firing during gamma oscillations in
anesthetized rats found that parvalbumin-expressing
basket cells were not strongly modulated by
gamma (81). However, various types of basket
cells, with different neurochemical characteristics,
are seen in the hippocampus (see Ref. 23 for a
review), and other classes of basket cells may participate in gamma oscillation generation. In the
study by Tukker and colleagues (81), juxtacellular
recordings were also made from several other
classes of hippocampal interneurons: O-LM cells,
axo-axonic cells, cholecystokinin-expressing cells,
and bistratified cells. Out of all of the interneuron
classes that were investigated, bistratified cells
showed the strongest gamma modulation, reliably
firing on the ascending phase of nearly every
gamma cycle. Bistratified interneurons receive input from CA3 and target the dendritic zones that
receive input from CA3 (i.e., strata oriens and radiatum), and thus they may participate in the generation of CA3-driven gamma oscillations in
particular. It is plausible to assume that the gamma
oscillations in the Tukker study were driven by the
CA3 generator because the recordings were performed in urethane-anesthetized animals (81), and
EC input to the hippocampus is reduced during
urethane anesthesia (91). Additionally, the average
frequency of gamma oscillations in this study was
⬃40 Hz, which falls within the frequency range of
gamma oscillations in CA1 that are coupled with
gamma from CA3 (14). In any case, the above results indicate that there are at least two different
types of interneurons that participate in the generation of gamma oscillations in the hippocampus.
If hippocampal gamma oscillations primarily reflect IPSPs in the pyramidal cells, the question
remains as to how gamma rhythmicity arises in the
interneurons. In a hippocampal slice model of
gamma oscillations, periodic firing emerged at ⬃40
Hz in networks of interconnected interneurons
(88). In this model, metabotropic glutamatergic
transmission, in the absence of ionotropic glutamatergic transmission, provided sufficient excitatory drive to the network of interneurons to bring
about IPSPs in intracellular recordings from CA1
pyramidal cells. In another slice study, ⬃40-Hz
oscillations were induced in CA3 and CA1 by infusion of cholinergic agonists (22). However, in this
preparation, the oscillations were completely abolished by AMPA receptor antagonists and were resistant to antagonists of metabotropic glutamate
receptors. The cholinergically induced oscillations
in CA3 were later shown to be generated by alternating cycles of AMPA receptor-mediated recurrent excitation followed by feedback inhibition
from perisomatic-targeting interneurons (33, 52).
There is also evidence that gap junctions between interneurons increase the power of gamma oscillations by
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Functions of Gamma Oscillations in
the Hippocampus
Dynamic Grouping
It has long been known that gamma oscillations
emerge in sensory cortices in response to sensory
stimulation (1, 67). Interest in gamma oscillations
increased in the 1980s when researchers began to
suspect that gamma oscillations in sensory cortices
offered a possible solution to the so-called “binding problem.” Complex stimuli are broken down
during sensory processing, with spatially disparate
cells coding different aspects of the stimuli (e.g.,
color, shape, direction of motion, etc.). The binding problem is the question of how the brain puts
these pieces back together to end up with a coherent perceptual experience (see Ref. 86 for a review).
In 1989, experimental evidence was obtained in
Wolf Singer’s laboratory, suggesting that gamma
oscillations provided the precise temporal synchrony necessary for binding distributed cells involved in coding various aspects of a particular
stimulus. Gamma synchronized firing was recorded across neurons in separate columns of primary visual cortex when cells responded to
different aspects of the same stimulus, a single
light bar simultaneously passing through the different receptive fields of the neurons (31). When
two separate and independent light bars were
passed through the receptive fields, the same cells
responded but did not show gamma synchronized
firing. These results were widely interpreted as an
indication that neurons that respond to the same
sensory object synchronize their firing at gamma
frequency and additionally that neurons that are
activated by different objects in the sensory space
do not show synchronized firing. The original experiments were conducted using anesthetized animals, but the general hypothesis has since been
supported by subsequent studies using different
experimental paradigms in awake animals (e.g.,
Refs. 26, 46, 47, but see also Ref. 69). The results
obtained from this line of research suggested a
neural mechanism for how the brain integrates
and segregates neural activity into functional neuronal ensembles during perceptual processing.
As the relationship between gamma synchronization
and perception was studied further, work from Robert
Desimone’s laboratory revealed that gamma oscillations were also important for selecting which visual
inputs would be processed in higher visual areas. They
found that when animals attended to one of two stimuli
in the visual field, phase synchronization was enhanced
between LFP gamma oscillations and spikes from neurons in cortical area V4 only when the stimulus inside
the neurons’ receptive field was being attended to but
not when it acted as a distracter to be ignored (25).
They concluded that gamma synchronization of
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rapidly spreading and enhancing inhibition (9).
These results suggest that gamma rhythmic firing
of hippocampal interneurons may be activated and
enhanced by a variety of different mechanisms.
The influence of excitatory inputs during hippocampal gamma oscillations remains less clear.
The firing patterns of ⬃30 –50% of hippocampal
pyramidal cells are significantly phase-locked to
gamma in behaving animals (14, 16, 68). The gammaassociated pyramidal cell firing in CA3 is likely
required for the feed-forward inhibition that is believed to entrain gamma oscillations in CA1 (14,
16). Still, on a given gamma cycle in recordings
from the pyramidal cell body layer, the probability
of place-cell firing is at least an order of magnitude
lower than the probability of interneuron firing
(16), and a much higher percentage of interneurons (⬃75–100%) fire phase-locked to gamma oscillations than do pyramidal cells (14, 16, 68).
Furthermore, an intracellular recording study
revealed that gamma-associated inhibitory postsynaptic currents in anesthetized rats were approximately five times larger than gamma-associated
excitatory postsynaptic currents (2). Taken together, the above findings support the conclusion
that gamma oscillations exert a largely inhibitory
influence on the pyramidal cell population.
A word of caution is that much of what is known
about the role of interneurons in the generation of
hippocampal gamma oscillations may pertain specifically to slow (⬃25–50 Hz) gamma oscillations
arising from CA3 (14). Connectivity between the
entorhinal cortex and the hippocampus is greatly
reduced in most hippocampal slice preparations,
meaning that evidence from in vitro models may
only be relevant for CA3-entrained gamma oscillations. In line with this conclusion, gamma oscillations in slices exhibit a peak frequency (⬃40 Hz;
Refs. 22, 88) that falls within the frequency range of
CA3-entrained slow gamma oscillations in CA1
(14). Moreover, some intracellular studies of gamma
mechanisms in vivo have been performed in
urethane-anesthetized animals (62, 81), and, as
discussed above, the perforant path input to the
hippocampus is attenuated during urethane anesthesia (91). In agreement with these observations,
an earlier study found that urethane anesthesia
produced gamma power increases in the 25- to
50-Hz range and decreases in the 50- to 100-Hz
range (11). The former frequency range matches
the frequency of CA3-coupled slow gamma oscillations in CA1, and the latter overlaps with the
frequency band of fast gamma oscillations in CA1
that are coherent with gamma in MEC (14). Recent
developments in intracellular recording techniques in awake animals (34) may pave the way for
future studies to differentiate the mechanisms involved in EC- vs. CA3-driven gamma oscillations.
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Dynamic Routing
Recently, Pascal Fries suggested another hypothesis of gamma oscillation function, “neuronal communication through neuronal coherence” (24),
which describes a mechanism for how synchronized gamma oscillations facilitate transmission of
information from one level of processing to the
next. Gamma oscillations, like neural oscillations
in general, consist of alternating periods of higher
excitability and periods of higher inhibition. Thus,
when gamma oscillations between a “sending”
neuronal group and a “receiving” neuronal group
are synchronized, their periods of high excitability
coincide, and this leads to more effective communication between the regions. Experimental evidence
supporting this hypothesis was later obtained from
simultaneous paired recordings across visual cortical
areas in cats and monkeys during presentation of
visual stimuli (90). The authors found that gamma
power correlations in the paired recordings were
high during trials when gamma oscillations between
the regions were classified as having a “good” phase
relationship (i.e., phase difference close to the mean
phase difference across trials). Gamma power correlations were low during trials when gamma oscillations between the regions had a “bad” phase
relationship (i.e., out of phase with the mean). This
study provided experimental evidence for the idea
that synchronized gamma oscillations promote interregional communication during transmission of
sensory information.
The hypothesis that synchronized gamma oscillations facilitate communication between brain regions has recently been supported by findings in
the hippocampal network. These findings further
suggest that the frequency of gamma oscillations
plays a critical role in routing the flow of information in the hippocampal network. In a study in
freely behaving rats, different frequencies of
gamma oscillations were shown to synchronize
CA1 with two of its main sources of input, CA3 and
MEC (14). Specifically, slow gamma oscillations in
CA1 were coupled with slow gamma in CA3, and
fast gamma oscillations in CA1 were coherent with
fast gamma in MEC (FIGURE 2). A significantly
higher proportion of CA3 cells were phase locked
to slow gamma oscillations in CA1 than to fast
gamma oscillations in CA1, suggesting that CA3
was communicating with CA1 more effectively
during slow gamma oscillations. A substantial proportion of cells in layer III of the MEC were phase
locked to fast gamma oscillations in CA1, but none
were phase locked to CA1 slow gamma, suggesting
that MEC was transmitting its signals to CA1 more
effectively during fast gamma. Slow and fast
gamma oscillations preferentially occurred at
significantly different phases of theta in CA1,
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neurons activated by attention to stimuli leads to a
very powerful output because the spikes from these
cells converge at the next stage of visual processing at
roughly the same time. In this way, the synchronous
cells, and not the asynchronous cells, will most effectively activate the downstream neurons (see Ref. 24
for a review). Subsequent results showing that enhanced power of gamma oscillations and gamma
synchrony of spikes in V4 were associated with increased reaction times in a change detection task
supported this conclusion (89). This neural mechanism likely allows the brain to select the most behaviorally relevant stimuli for processing downstream,
while at the same time ensuring that noisy and irrelevant stimuli are filtered out.
Gamma synchronization of neurons could also
mediate attentional selection processes in the hippocampus. Selecting the environmental cues that are
important for performing hippocampal-dependent
tasks and ignoring extraneous cues that are taskirrelevant requires attention (21, 57) and thus likely
activates attentional selection mechanisms involving
gamma oscillations in the cortex (described above,
and see also Ref. 24). Gamma-facilitated transfer of
inputs related to the task-relevant cues would provide an excitatory advantage to the hippocampal
cells involved in coding these cues, enabling them to
be activated more reliably. In support of this idea,
place cell discharges are more reliable when animals
are trained to attend to a particular set of environmental cues (21, 43, 61). It is possible that this increased reliability is brought about by gamma
oscillations because in one of these studies place cell
spikes became phase-locked to gamma oscillations
after animals learned to attend to the relevant stimuli
(57). Considering that attention largely determines
which experiences will be remembered (see Refs. 43,
56 for a review), cell selection by gamma oscillations
likely also plays a major role in regulating the information that will be retained in long-term storage.
Recent theoretical work has proposed a winnertake-all mechanism to explain how gamma oscillations could regulate cell selection in the
hippocampus (17). In the model, each gamma cycle evokes inhibitory postsynaptic potentials in the
pyramidal cells, consistent with experimental data
described above (74). This inhibition strongly suppresses spikes from the pyramidal cell population.
As the inhibitory potentials decay, the pyramidal
cells with the most excitatory input at that time
will be the first cells to fire. These cells trigger feedback inhibition in the other pyramidal
cells within a few milliseconds so that the
less-excited cells quickly lose their chance to fire.
This mechanism can differentiate cells with only
small differences in levels of excitation and may
contribute to selection of hippocampal neurons
during attentional states.
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Memory Encoding
If gamma oscillations play a role in selection of
inputs during memory formation in the hippocampus, as hypothesized above, then there should be a
link between hippocampal gamma oscillations and
memory encoding processes. Indeed, a number of
recent studies point to the conclusion that hippocampal gamma oscillations facilitate effective
memory encoding. In intracranial recordings from
human subjects asked to remember lists of random
words, increased gamma power in the hippocampus during encoding of individual words was correlated with a high probability that a word would
be subsequently recalled (64, 65). In another study
involving intracranial recordings from patients
who were asked to memorize word lists, gamma
synchronization was significantly higher between
EEG recordings from hippocampus and rhinal cortices during encoding of words that were later remembered compared with words that were later
FIGURE 2. Dynamic routing of inputs by slow and fast gamma oscillations
A: example recordings of slow (top) and fast (bottom) gamma oscillations, overlying theta oscillations, in CA1. B: coherence
spectra for example pairs of CA3-CA1 local field potential recordings (top) and MEC-CA1 local field potential recordings
(bottom). Note that CA3 and CA1 are more coherent in the slow gamma frequency range (⬍60 Hz) and that MEC and CA1
are more coherent in the fast gamma frequency range (⬎60 Hz). C: schematic illustrating how slow and fast gamma oscillations route different inputs. Slow gamma is maximal on the descending portion of the theta wave and serves to synchronize
CA1 with slow gamma-mediated inputs arriving from CA3. Fast gamma peaks near the theta trough and synchronizes CA1
with MEC input transmitted by fast gamma waves. Figure is adapted from Ref. 14.
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consistent with earlier results showing that excitatory currents from CA3 and EC are maximal at
different phases of theta (6, 35, 42). Segregation
of CA3 and EC inputs to the hippocampus may
be critical for preventing interference from previously learned associations during encoding of
new associations (35), and gamma oscillations
may play a role in this segregation of inputs by
facilitating transfer of information from one region while filtering out inputs from the other.
The above results point to the conclusion that
different frequencies of gamma oscillations serve
to dynamically route information transfer to CA1
and further suggest that gamma-mediated routing of inputs is regulated by underlying theta
oscillations. Gamma-modulated activity may
also be induced in other brain areas at particular
phases of hippocampal theta oscillations, and
this may serve to facilitate communication between the hippocampus and structures such as
the striatum and the prefrontal cortex (72, 80).
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Memory Retrieval
It is also possible that gamma oscillations are required to link the distributed cells that represent a
memory episode during memory retrieval processes in the hippocampus. In line with this idea,
several studies have provided evidence supporting
a role for hippocampal gamma oscillations during
memory retrieval. In a recent study, local field potentials were recorded as rats learned to perform a
delayed spatial alternation task in which they were
required on each trial to retrieve information about
the trajectory they traversed on the previous trial to
decide which way to turn to receive a reward (55).
Increases in gamma coherence between CA3 and
CA1 and in gamma power in CA1 were observed on
the center arm, the region that the rats traversed
after the delay and before the turning choice point.
This was thought to be the region where memory
retrieval processes were engaged, and thus the authors proposed that gamma oscillations facilitate
transfer of retrieved memories from CA3 to CA1.
Studies demonstrating that memory retrieval requires intact projections from CA3 to CA1 are in
accord with this conclusion (29, 58, 76, 78). In
another study, CA3 place cell representations of
possible future trajectories were activated when
animals paused at a choice point (39). These activations may have reflected memory retrieval
processes during prospective coding and were associated with strong gamma oscillations that were
not seen during other pauses, suggesting another
possible link between gamma oscillations and
memory retrieval. In a later study, the amplitude of
slow gamma (30 – 60 Hz) oscillations in CA3 increased as animals learned to accurately perform a
task that involved retrieval of learned associations
between items and contexts (79). In another study,
CA1 place cell firing in mice was phase locked to
slow (20 – 60 Hz) gamma oscillations only when
mice had to suppress odor cues and retrieve a
stable representation of the visuospatial environment to receive a reward (57). Gradual increases in
gamma power were also seen as the animals
learned to correctly perform the task. It is interesting to note that the gamma reported in the Tort
et al. (79) and Muzzio et al. (57) studies was in the
slow gamma frequency range. Both slow gamma
oscillations (14) and memory retrieval (55) are associated with increased gamma coherence between CA3 and CA1, raising the possibility that
slow gamma oscillations promote the CA3-CA1
communication that leads to successful memory
retrieval.
The timing of slow gamma may work better for
memory retrieval than memory encoding. In a
study of spike-timing-dependent plasticity in hippocampal synapses, postsynaptic spikes occurring
more than 20 ms after the onset of EPSPs in the
postsynaptic cell were not effective at eliciting synaptic changes (4). This suggests that repetitive activation carried to CA1 by slow gamma oscillations
(with a period of ⬃25 ms) would be outside of the
optimal time range for effectively inducing longterm potentiation. Thus slow gamma oscillations
may be fast enough to link distributed cells during
memory retrieval yet also slow enough to avoid
re-encoding of previously stored memories.
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forgotten (20). In a later study of neural activity and
gamma oscillations in monkey hippocampus, coherence between spiking activity and local field
potentials was higher in the gamma band during
encoding of stimuli that were later well recognized
compared with stimuli that were poorly recognized
(41). As in the human studies, gamma power in the
local field potentials was also significantly enhanced during encoding of stimuli that were well
remembered later.
In accord with the hypothesized link between
hippocampal gamma oscillations and memory encoding, we recently suggested that fast gamma
synchronization between MEC and CA1 may facilitate memory encoding. Fast gamma oscillations in
CA1 are coherent with fast gamma oscillations in
layer III of MEC (14), the layer that provides direct
input to CA1. The direct MEC projection to CA1
conveys information about the animal’s current
position in the environment (7, 8, 28, 32). Thus it is
possible that fast gamma oscillations transmit information about environmental stimuli from the
EC to the hippocampus for encoding.
There is a plausible mechanism for how the timing of fast gamma oscillations would make them
particularly well suited for memory encoding. Consider a scenario in which a depolarizing input is
carried to a particular cell by fast gamma, and the
same cell is activated again ⬃10 –15 ms later on the
next excitatory phase of fast gamma, this time
leading to spiking. In this hypothetical scenario,
the timing of the initial depolarization and the
subsequent spiking would lead to long-term potentiation because of spike-timing-dependent plasticity in hippocampal neurons (4). This may explain
why high frequencies of gamma oscillations may be
ideal for transferring information about ongoing experiences from the entorhinal cortex to the hippocampus during memory encoding.
Working Memory
Several studies have suggested that hippocampal
gamma oscillations play an important role in working memory, defined as the short-term internal
maintenance of information that is required for
impending decisions or actions but no longer
present in the external environment (19, 27). In
a study of intracranial recordings from human
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Representations of Spatial Sequences
Gamma oscillations in the hippocampus may also
be important for representing movement trajectories. A recent study in rats found a distinct class of
pyramidal cells in CA1 that fires phase locked to
the trough of gamma cycles (“TroPyr” cells; Ref.
68). This class of place cells exhibited clear theta
phase precession, a phenomenon that is thought
to provide a temporal code for spatial sequences
(53, 60, 73). The TroPyr class of place cells was
separated from another group of cells, termed
“RisPyr,” which fired on the rising phase of gamma
oscillations. RisPyr cells did not show normal theta
phase precession when gamma oscillations were
present. Interestingly, fast gamma-modulated
place cells fire on the fast gamma trough and are a
largely separate population from slow gammamodulated cells, which fire on the ascending phase
of slow gamma (14). Thus fast and slow gammamodulated place cells may correspond to the TroPyr and RisPyr classes of cells, respectively, in the
Senior et al. study (68). The firing properties of
TroPyr gamma-modulated cells indicate that they
may link codes for discrete places on each gamma
cycle and thereby encode temporal sequences during theta phase precession, as has been suggested
previously (50). If TroPyr cells and fast gammamodulated cells correspond to the same class of
place cells, it may suggest that fast gamma
326
PHYSIOLOGY • Volume 25 • October 2010 • www.physiologyonline.org
oscillations help maintain the temporal code for
spatial sequences during theta phase precession.
Transitions Between Different
Gamma Mechanisms
It is reasonable to assume that different mechanisms exist for hippocampal gamma oscillations
that are employed for distinct purposes such as
memory encoding and memory retrieval. We hypothesized that synchronization of CA3 and CA1
during slow gamma oscillations and synchronization of MEC and CA1 during fast gamma oscillations selectively promote retrieval and encoding,
respectively. However, it remains unclear what
causes the transition between the different synchronization mechanisms.
Perhaps the most parsimonious explanation of
how gamma mechanisms could transition is that
different interneurons are recruited by different
inputs during different functions. Diverse classes
of interneurons can be characterized by their distinct pattern of inputs, outputs, and firing patterns
during hippocampal oscillations (see Ref. 45 for a
review). It is possible that the interneuron circuits
activated by CA3 inputs generate oscillations at
lower frequencies than do the interneuron circuits
activated by EC inputs. However, for the sample of
interneurons recorded in the pyramidal cell body
layers of the hippocampus in the Colgin et al. study
(14), the majority were phase locked to both slow
and fast gamma oscillations in CA1. It is possible
that other types of interneurons with soma in other
layers participate selectively in one or the other
gamma subtype, but still the finding that so many
interneurons participate in both types of gamma
suggests that there is likely another mechanism
involved in transitioning the network from one
gamma state to the other.
A recent study has suggested a novel mechanism
for how changes in gamma coherence across
regions could be regulated (2). In CA3, large variations in gamma oscillation amplitude and frequency were observed, as has been reported previously
(5, 14). However, the Atallah and Scanziani study
(2) additionally reported that the instantaneous
frequency of a gamma cycle could be predicted
based on the amplitude of the preceding gamma
cycle. Specifically, a particularly large amplitude
gamma cycle was likely to be followed by a slow
gamma cycle. Correlated increases in both excitatory and inhibitory synaptic currents in CA3 pyramidal cells were involved in the large amplitude
gamma cycle. This effect may lead to a situation
where a very large gamma cycle, involving increased excitation of CA3 pyramidal cells and interneurons, triggers a transition to slow gamma
oscillations in the hippocampal network. Examples
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epileptics, the power of gamma oscillations in the
hippocampus increased with increasing working
memory load (83). Another recent study using similar techniques found enhancement of the coupling between theta phase and gamma power in
the hippocampus during the maintenance period
of a working memory task (3). Working memory
processes rely on a distributed network of brain
regions, including the hippocampus and the prefrontal cortex (19, 27, 63). Thus gamma-related
working memory effects in the hippocampus may
involve gamma synchronization with other regions
involved in working memory operations, including
the prefrontal cortex. A recent study showed that
prefrontal neurons synchronized their activity at
gamma frequencies (⬃30 Hz) as monkeys remembered two objects during a brief delay period in a
short-term memory task (71). During working
memory, the hippocampus and prefrontal cortex
show enhanced theta coherence (40), and prefrontal cortex neurons fire phase locked to hippocampal theta rhythms (36, 40, 70). Considering that the
amplitude of gamma oscillations in the prefrontal
cortex is modulated by the phase of theta oscillations in the hippocampus (72), it is plausible to
hypothesize that gamma oscillations may also be
involved in the coupling between prefrontal cortex
and hippocampus during working memory.
REVIEWS
gamma synchrony, such as schizophrenia (see Ref.
82 for a review). 䡲
No conflicts of interest, financial or otherwise, are declared by the author(s).
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