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The Journal of Neuroscience, 2001, 21:RC131:1-5
RAPID COMMUNICATION
Synchronous Activity in the Hippocampus and Nucleus Accumbens
In Vivo
Yukiori
Goto and
Patricio
O'Donnell
Center for Neuropharmacology and Neuroscience, Albany Medical
College, Albany, New York 12208
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ABSTRACT |
The hippocampus is one of the brain regions involved in cognitive
functions, including learning and memory. Extensive studies have
unveiled how information is processed within this system. However, the
mechanisms by which hippocampal activity is translated into action
remain unsolved. One important target of hippocampal projections is the
nucleus accumbens, which has been described as the motivation-to-action
interface. Previous experiments indicate that these projections can
control information processing in this region by setting neurons into a
depolarized state. Here, we report that membrane potential transitions
in nucleus accumbens neurons are correlated with electrical activity in
the ventral hippocampus, suggesting that hippocampal neural activity
can determine ensembles of active accumbens neurons.
Key words:
nucleus accumbens; hippocampus; electrophysiology; schizophrenia; membrane potential states; in vivo
intracellular recordings
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INTRODUCTION |
The
hippocampus, a brain region involved in cognitive functions
(Zola-Morgan et al., 1986 ; Muller et al., 1996), projects extensively
to the nucleus accumbens (NAcc) (Kelley and Domesick, 1982), a brain
region at the "limbic-motor interface" (Mogenson et al., 1980).
Previous experiments have suggested that these projections can control
information processing in the NAcc by setting NAcc neurons into a
depolarized state (O'Donnell and Grace, 1995). The electrical activity
of NAcc and dorsal striatal medium spiny neurons is characterized by
periodical shifts from a very negative resting membrane potential (DOWN
state) to a more depolarized (UP) state (Wilson, 1993; O'Donnell and
Grace, 1995), which depends on excitatory synaptic inputs (Wilson,
1993; O'Donnell and Grace, 1995). Transection or stimulation of the
fimbria-fornix, the fiber system carrying hippocampal afferents to the
NAcc, resulted in disappearance or induction, respectively, of the UP
state in NAcc neurons (O'Donnell and Grace, 1995). Furthermore,
recordings in slices do not yield neurons with a bistable membrane
potential (O'Donnell and Grace, 1993). Because activation of inputs
from the prefrontal cortex (PFC) can evoke action potentials in NAcc medium spiny neurons only during the UP membrane potential state, it
has been hypothesized that hippocampal afferents gate PFC-NAcc information flow by setting NAcc neurons into this depolarized state.
Such a gating mechanism may define the ensemble of neurons appropriate
to be active in a given context (O'Donnell, 1999), and its alteration
may be responsible for pathophysiological changes in psychiatric
disorders, such as schizophrenia (O'Donnell and Grace, 1998).
A prediction that arises from this model is that electrical activity in
the ventral hippocampus would be synchronized with UP states in NAcc
neurons. For example, in hippocampal CA1 and ventral subicular (vSub)
regions, local field potentials show periodical sharp potential shifts
(sharp waves and accompanying high-frequency oscillation, or ripples)
during sleep or awake resting conditions (Buzsáki, 1986; Ylinen
et al., 1995). Sharp waves in the CA1 region are induced by synchronous
discharge of CA3 neurons, resulting in depolarization of CA1 pyramidal
neurons (Buzsáki, 1986). Therefore, outputs of such synchronous
activity in the hippocampus may be the driving force of NAcc membrane
potential fluctuations. To test this hypothesis, we performed in
vivo intracellular recordings from NAcc medium spiny neurons
simultaneously with local field potential recordings from the ventral hippocampus.
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MATERIALS AND METHODS |
Animals. Simultaneous in vivo
intracellular and local field potential recordings were performed from
25 neurons in 19 rats. Male adult Sprague Dawley rats (230-400 gm)
were obtained from Taconic Farms (Germantown, NY). All experimental
procedures were performed according to the United States Public Health
Service Guide for the Care and Use of Laboratory Animals and
approved by the Albany Medical College Institutional Animal Care and
Use Committee. Rats were initially anesthetized with chloral hydrate (400 mg/kg, i.p.), followed by continuous supplemental anesthesia (chloral hydrate, 24-30 mg/hr) during the recording session via a
cannula inserted intraperitoneally.
Recordings. Intracellular and extracellular electrodes were
made from 1 mm outer diameter Omegadot borosilicate glass tubing (World
Precision Instruments, Sarasota, FL) pulled with a P-97 Flaming-Brown puller (Sutter Instruments, Novato, CA). Intracellular electrodes (resistance of 46-103 M ) were filled with 2 M potassium acetate and 2% Neurobiotin.
Extracellular electrodes (impedance of 3-8 M measured at 2 kHz)
were filled with 2 M NaCl and 2% Pontamine Sky
blue. Intracellular electrodes were lowered into the NAcc
[anteroposterior (AP), bregma +1.4 to +2.0 mm; lateral, 1.0-2.0 mm;
vertical,  5.8 to 8.4 mm] and extracellular electrodes into the
ipsilateral CA1 (AP, bregma 6.0 mm; lateral, 5.3 mm; vertical, 7.8
mm) or vSub (AP, bregma 6.3 mm; lateral, 5.2 mm; vertical, 7.0 mm).
Once intracellular electrodes yielded stable recordings, simultaneous
baseline recordings were performed for 5 min. Only neurons showing at
least 50 mV resting membrane potential and 40 mV spike amplitude
measured from threshold were analyzed and included in the study. All
data were stored using custom-made software (Neuroscope) and
analyzed off-line.
Histology. After completion of the experiments,
extracellular recording sites were marked by ejection of Pontamine Sky
blue. Neurobiotin was injected into the intracellularly recorded
neurons by passing positive current (1.0 nA, 200 msec pulses at 2 Hz) for at least 5 min. Animals were killed by a lethal dose of
pentobarbital (100 mg/kg) and transcardially perfused with ice-cold
saline, followed by 4% paraformaldehyde. Brains were removed from the skull, cryoprotected in 30% sucrose, and sectioned using a freezing microtome. Serial 50-µm-thick sections were cut coronally. Either dye
markers or neurons were identified and localized according to the atlas
of Paxinos and Watson (1998).
Cross-correlation analysis. Cross-correlograms were
constructed based on the methods described previously (Perkel et al., 1967). The cross-correlation strength,
Sccr, was defined as:
where Nc is the number of
potential shifts detected simultaneously in intracellular and
extracellular recordings within a ±50 msec interval,
Nb is the chance level of coincident
events given by either shuffled cross-correlogram or baseline events, and Nmp and
Nlfp are the total number of events
within the time intervals analyzed. Normal distribution was assumed for
the histogram, and the significance of correlation was defined if the
peak exceeded three SDs (p < 0.013).
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RESULTS |
In vivo intracellular recordings were performed from 25 NAcc neurons, located in the core region. Seventeen of 25 (68%)
neurons showed a bistable membrane potential (Fig.
1a). The presence of UP and
DOWN membrane potential states was determined when a histogram of time
spent at different membrane potential values showed a bimodal
distribution fitting to a dual Gaussian curve (Fig. 1b). The
DOWN state, or resting membrane potential (O'Donnell and Grace, 1995),
was 78.1 ± 10.5 mV (mean ± SD), and the UP state was
66.8 ± 10.4 mV. Transitions to the UP state occurred at
0.55 ± 0.21 Hz. In all four bistable neurons injected with
Neurobiotin, histochemical procedures revealed that these were medium
spiny neurons (Fig. 1c).
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Figure 1.
NAcc medium spiny neurons show a bistable membrane
potential. a, Representative tracing from a neuron
alternating between the DOWN (73 mV) and UP (60 mV) membrane
potential states. b, Membrane potential distribution
histogram constructed from the recording shown in a. Two
peaks are observed, corresponding to the DOWN and UP membrane potential
states. The black line is a dual Gaussian curve to which
the histogram can be fitted (r2 = 0.95). c, Neurobiotin injection revealed that
recordings were obtained from medium spiny neurons.
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Local field potentials in the hippocampus, either CA1
(n = 6) or vSub (n = 7), were recorded
simultaneously with intracellular NAcc recordings from cells exhibiting
a bistable membrane potential. These local field potentials exhibited
large periodical negative shifts that occurred simultaneously with UP
membrane potential states in NAcc neurons in all pairs recorded
(n = 13) (Fig.
2a). Cross-correlograms
indicated that hippocampal field potential shifts and transitions to
the UP state in NAcc neurons occurred within <100 msec (Fig.
2b). Cross-correlation strength
(Sccr) was defined as the ratio
between coincident number of events and total number of events.
CA1-NAcc and vSub-NAcc recordings resulted in
Sccr of 0.27 ± 0.08 and
0.30 ± 0.07, respectively. These values were significantly higher
than the strength of shuffled cross-correlograms (0.05 ± 0.01 and
0.06 ± 0.01; paired t test; p < 0.00001 for both of them). Because there was no difference in the
strength and pattern of correlation between NAcc and CA1 or vSub, the
data were pooled. Half of the recordings obtained from the CA1 region exhibited ripples (n = 3), which were also synchronized
with UP states in NAcc medium spiny neurons (Fig. 2c).
Ripples were defined as oscillations of >100 Hz (Buzsáki, 1986;
Ylinen et al., 1995). An association was found between the location of
NAcc neurons intracellularly recorded and their cross-correlation
strength with hippocampal activity.
Sccr values were higher for NAcc
neurons located more medial and dorsal, in the medial core territory
(Fig. 2e). Neurons located in the lateral core exhibited
lower Sccr with hippocampal activity.
A statistically significant association was found between
Sccr and the mediolateral location of
the NAcc neurons (nonparametric Spearman rank order correlation;
r = 0.554; p < 0.05).
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Figure 2.
Membrane potential shifts in NAcc neurons occur
simultaneously with hippocampal field potentials. a,
Representative traces of simultaneous recordings from the NAcc and
hippocampus. Top, Local field potential recorded from
vSub showing periodical negative potential shifts; the dashed
line indicates 0 µV. Bottom, Intracellular
recording from an NAcc neuron showing a bistable membrane potential
with UP events occurring synchronously with hippocampal field potential
shifts; the dashed line indicates the DOWN state.
Low-pass filter (<50 Hz) was applied to both traces to show only slow
waveform components. b, Top,
Cross-correlogram created from the recording shown in a.
Bin width is 100 msec, and the dashed lines indicate
three SDs. A significant peak is observed at time point 0. Bottom, Shuffled cross-correlogram between
nonsimultaneous time epochs of each recording does not reveal a peak.
c, Example of simultaneous recordings indicating the
correlation between hippocampal ripples recorded in CA1 and UP state
transitions in an NAcc neuron. The inset shows one of
the ripples at a faster time scale. High-pass filter (>50 Hz) was
applied to the local field potential to eliminate slow potential
shifts. d, Diagrams illustrating the locations of
intracellular and local field potential recordings in the NAcc and
hippocampus. e, The cross-correlation strength
(Sccr) between UP state transitions
in an NAcc neuron, and onset of hippocampal local field potential
shifts was plotted against the location of intracellularly recorded
NAcc neurons on three two-dimensional grayscale maps. These maps were
constructed from 13 pairs by plotting Sccr
values in a 50 × 50 point matrix. The remaining
Sccr values were determined by weighted
least-squares estimation. Axes refer to coordinates in
millimeters relative to bregma
(Rostral-Caudal), midline
(Medial-Lateral), and brain surface
(Dorsal-Ventral).
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In addition to the hippocampal input, the NAcc receives excitatory
afferents from the PFC (Phillipson and Griffiths, 1985). In a previous
study, PFC stimulation failed to evoke transitions to the UP state in
NAcc neurons (O'Donnell and Grace, 1995). It was then predicted that
simultaneous recordings of intracellular NAcc activity and PFC local
field potentials would yield a lower degree of cross-correlation
compared with NAcc-hippocampus recordings. Although PFC local field
potentials also exhibited slow negative potential shifts, they were not
well correlated with transitions to the UP state in NAcc neurons
(n = 4) (Fig.
3a). Cross-correlograms showed
significant peaks in only two of four pairs (Fig. 3b). Comparison of correlation strengths among PFC-NAcc, shuffled
PFC-NAcc, and hippocampus-NAcc pairs indicates that the
cross-correlation between PFC local field potentials and NAcc membrane
potential shifts was weaker than the cross-correlation between
hippocampal local field potentials and NAcc membrane potential
transitions (ANOVA; F(2,30) = 41.1;
p < 5.0 × 10 7)
(Fig. 3c).
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Figure 3.
Membrane potential state transitions in NAcc
neurons are correlated more weakly with prefrontal cortical local field
potentials. a, PFC local field potential
(top) acquired simultaneously with an intracellular
recording from an NAcc neuron (bottom). The
dashed lines indicate 0 µV and the DOWN state in
extracellular and intracellular recordings, respectively. Black
arrows indicate PFC potential shifts that are not simultaneous
with membrane potential transitions in the NAcc neuron.
b, Cross-correlograms showed significant peaks in some
cases (left); in others, the peak did not reach
significant values (right). c, Comparison
of cross-correlation strength among NAcc-PFC, control (shuffled
NAcc-PFC), and NAcc-hippocampus pairs of recordings. A post
hoc Newman-Keuls test was used for the comparison between each
pair. d, Locations of intracellular recordings in the
NAcc and local field potential recordings in the PFC.
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DISCUSSION |
Hippocampal local field potentials were tightly correlated with
transitions to the UP state in NAcc neurons, suggesting that hippocampal inputs are important for the onset of UP membrane potential
states in NAcc neurons. In contrast, the correlation between PFC local
field potentials and NAcc UP transitions was weak. Such difference
between excitatory inputs to the NAcc is consistent with previous
anatomical and physiological findings. Five to 10% of hippocampal
terminals in the NAcc contact cell bodies or proximal dendrites,
whereas PFC axons are exclusively observed at distal dendrites
(Meredith et al., 1990). This anatomical arrangement would result in
hippocampal afferents having a stronger input on somatic membrane
potential in NAcc neurons. Indeed, our finding of a cross-correlation
strength between NAcc neurons and hippocampal local field potentials
higher than that of NAcc-PFC pairs indicate that the PFC-NAcc
projection is less important in driving the UP state than the
hippocampal projections. Furthermore, the NAcc-hippocampal
cross-correlation strength was higher when NAcc neurons were recorded
from the medial aspect of the NAcc core. This may reflect the ventral
hippocampus projecting primarily to the medial NAcc (Groenewegen et
al., 1999).
UP and DOWN membrane potential states can be affected by the anesthetic
agent used. Because the UP state is dependent on excitatory synaptic
inputs, it cannot be seen in the presence of GABA-enhancing agents,
such as barbiturates. On the other hand, these plateau depolarizations
have been observed in chloral hydrate- or urethane-anesthetized animals
(Wilson, 1993; O'Donnell and Grace, 1995) and even in locally
anesthetized animals (Wilson and Groves, 1981).
Increasing attention is being paid to the role of neuronal ensembles in
CNS information processing. Synchronous activity defining neural
ensembles has been observed in the striatum (Jog et al., 1999),
cerebellum (Thier et al., 2000), motor cortex (Laubach et al., 2000),
PFC (Schoenbaum and Eichenbaum, 1995), and hippocampus (Deadwyler et
al., 1996). These studies focused on spike firing in a population of
simultaneously recorded neurons in behaving animals. Subthreshold
membrane potential variations, however, were not considered. Because
the UP membrane potential state brings NAcc neurons very close to their
firing threshold, UP events can be seen as periods during which neurons
are in a "ready-to-fire" state. Therefore, it would be important to
consider the membrane potential states in the definition of active
neuronal ensembles in systems exhibiting these oscillations
(O'Donnell, 1999). Indeed, synchronous bistable membrane potential
fluctuations in pairs of neurons have been reported recently in the
dorsal striatum (Stern et al., 1998) and visual cortex (Lampl et al.,
1999).
The results presented here support the idea of the hippocampal output
gating corticostriatal information flow in the NAcc. The synchrony
reported here is likely to be the result of hippocampal activity
driving NAcc UP membrane potential states (O'Donnell and Grace, 1995).
Thus, the activity of hippocampal neural ensembles may determine the
ensembles of NAcc neurons that are appropriate to be set in the UP
state, according to contextual cues (Fig. 4). This mechanism may provide a basis
for the incorporation of hippocampal functions into motor planning and
attentional mechanisms within the ventral basal ganglia circuits.
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Figure 4.
Hypothetical model of hippocampal gating of
PFC-NAcc information transmission. Each circle
indicates subsets of neurons. Different contextual information
(C1-C3) activates specific ensembles of ventral
hippocampal neurons, which, in turn, shape ensembles of NAcc neurons
defined as those in the UP state. Ensembles of active neurons in
hippocampus (e.g., place fields) should be directly reflected on
ensembles of NAcc neurons shaped by synchronous UP states because of
parallel projections from the subiculum (Naber et al., 1997). Inputs
from the PFC converging with the hippocampal-driven UP state in NAcc
neurons can elicit specific responses (R1-R3) according
to such contextual information from the hippocampus.
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FOOTNOTES |
Received Sept. 27, 2000; revised Dec. 4, 2000; accepted Dec. 6, 2000.
This work was supported by United States Public Health Service Grant
MH57683. We thank Barbara L. Lewis for her excellent technical
assistance, Drs. Stanley D. Glick and Min Zhou for comments on this
manuscript, and Brian Lowry (University of Pittsburgh, Pittsburgh, PA)
for developing and providing the software used for data acquisition and
analysis (Neuroscope).
Correspondence should be addressed to Patricio O'Donnell, Albany
Medical College (MC-136), Center for Neuropharmacology and Neuroscience, 47 New Scotland Avenue, Albany, NY 12208. E-mail: odonnep{at}mail.amc.edu.
This article is published in
The Journal of Neuroscience, Rapid Communications Section,
which publishes brief, peer-reviewed papers online, not in print. Rapid
Communications are posted online approximately one month earlier than
they would appear if printed. They are listed in the Table of Contents
of the next open issue of JNeurosci. Cite this article as:
JNeurosci, 2001, 21:RC131 (1-5). The
publication date is the date of posting online at
www.jneurosci.org.
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TOP
ABSTRACT
INTRODUCTION
