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Department of Physiology and Biophysics, Georgetown University, Washington DC, 20057-1421
Submitted 31 December 2002; accepted in final form 18 February 2003
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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8 Hz) oscillation in rat neocortical slices. The imaging
has large signal-to-noise ratio, allowing us to map the phase distribution
over the neocortical tissue during the oscillation. The oscillation was
organized as spontaneous epochs and each epoch was composed of a "first
spike," a "regular" period (with relatively stable frequency
and amplitude), and an "irregular" period (with variable frequency
and amplitude) of oscillations. During each cycle of the regular oscillation,
one wave of activation propagated horizontally (parallel to the cortical
lamina) across the cortical section at a velocity of 50 mm/s. Vertically
the activity was synchronized through all cortical layers. This pattern of one
propagating wave associated with one oscillation cycle was seen during all the
regular cycles. The oscillation frequency varied noticeably at two neighboring
horizontal locations (330 µm apart), suggesting that the oscillation is
locally organized and each local oscillator is about ≤300 µm wide
horizontally. During irregular oscillations, the spatiotemporal patterns were
complex and sometimes the vertical synchronization decomposed, suggesting a
de-coupling among local oscillators. Our data suggested that neocortical theta
oscillation is sustained by multiple local oscillators. The coupling regime
among the oscillators may determine the spatiotemporal pattern and switching
between propagating waves and irregular patterns. |
INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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) and rapid-eye movement sleep
(Jovet 1969;
Vanderwolf 1969), suggesting
that this activity may be related to spatial learning and memory deposition.
Neocortical theta activity has been observed in animal and human subjects
(Raghavachari et al. 2001;
Sarnthein et al. 1998) and may
play a role in spatial learning and working memory
(Lisman and Idiart 1995;
Raghavachari et al. 2001). In
vitro experiments indicate that at different phases of the oscillation, the
same input to the local circuit may lead to different synaptic modifications
(long-term potentiation or depression)
(Huerta and Lisman 1995). Thus
the phase distribution of the oscillation in the horizontal directions
(parallel to cortical lamina) must play a role in determining when, where, and
what synaptic modifications would occur in the cortical circuit.
The horizontal phase distribution over hippocampus was changing with
behavior (O'Keef and Recce 1993; Skaggs et
al. 1996), suggesting that cortical oscillators in CA3 and dentate
gyrus may also contribute to the horizontal phase organization
(Buzsaki 2002) in addition to
the subcortical pacemaker neurons in the medial septum-diagonal band of Broca
(Buzsaki et al. 1983;
Lee et al. 1994;
Leung 1984;
Stewart and Fox 1990).
In neocortex, theta waves have been recorded during behavioral and mental
tasks (Kahana et al. 1999;
Raghavachari et al. 2001);
however, almost nothing is known about the pace making and spatiotemporal
organization of these waves.
An in vitro cholinergic oscillation (7 Hz) can be generated in
neocortical slices by bath applying of carbachol and bicuculline
(Lukatch and MacIver 1997).
This in vitro oscillation may share a common mechanism with the theta activity
because applying these two agents together in vivo is sufficient to induce
theta oscillations when the hippocampus is deafferented from the medial septum
areas (Colom et al. 1991).
These two agents may induce the oscillation by mimicking cholinergic
depolarization (Benardo and Prince
1982; Cole and Nicoll
1984) and GABAergic disinhibition
(Bilkey and Goddard 1985) of
the assumed pacemakers. Under in vitro conditions, neocortical neurons do not
receive any innervation from subcortical pacemaker(s). Thus the pacemaking and
phase distribution must be organized by intrinsic neocortical oscillators.
In this report, we use voltage-sensitive dye (VSD) imaging to examine this in vitro neocortical oscillation. Pharmacologically generating the activity in brain slice allows us to exclude contributions from external (subcortical) pacemaker (s), allowing an analysis of how intracortical interactions organize the phase distribution.
In brain slices, the sensitivity of VSD imaging was high
(Jin et al. 2002), allowing a
simultaneously measurement from 50 to 100 locations over an area of 4 mm
in diameter. The advantage of optical recordings over an electrode array is
that VSD imaging measures the transmembrane potentials of the neuronal
population and thus the phase gradient caused by current source/sink pairs in
the tissue is ignored, and only the phase in the membrane potential
oscillation is measured. Our results show that the oscillation is organized as
propagating waves. Local (330 µm) phase variations suggest that the
propagation wave may be composed of coupled local oscillators.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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Sprague-Dawley rats (n = 20) of both sexes from P28 to P35 were used. The animals were deeply anesthetized with halothane and quickly decapitated. The whole brain was chilled in cold (0–4°C) artificial cerebrospinal fluid [ACSF, containing (in mM) 132 NaCl, 3 KCl, 2 CaCl2, 2 MgSO4, 1.25 NaH2PO4, 26 NaHCO3, and 10 dextrose and saturated with 95% O2-5% CO2] and coronal slices (450 µm thick) including occipital areas (Bregma –3 to –5 mm) were cut and transferred to a holding chamber for >60 min (at 22°C) before the next procedure.
VSD imaging
The imaging apparatus and methods are described in detail by Wu and Cohen
(1993) and Jin et al.
(2002). Briefly, the slices
were stained with ACSF containing 0.005–0.02 mg/ml of an oxonol dye,
NK3630 [first synthesized by R. Hildesheim and A. Grinvald as RH482; available
from Nippon Kankoh-Shikiso Kenkyusho, Japan) (see Momose-Sato et al.
(1999) for molecular
structure], for 30–60 min (22°C). During staining, the dye solution
was gently bubbled with 95% O2-5% CO2. The stained
slices were then perfused in dye-free ACSF in a submerge chamber at
28–32°C during imaging experiments. A 124-element photodiode array
system was used for the imaging. The preparation was
trans-illuminated by 705 ± 20 nm light for the imaging. The
illumination was only applied during recording trials (8–32 s each
trial, >20 trials for each slice), and the exposure (light intensity and
illumination time) did not cause detectable bleaching or phototoxicity
(Jin et al. 2002). An
objective of x5 (0.12 NA, Zeiss) was used to form the image on the diode
array. Each photo-detector received light from an area of 330 x 330
µm2 of the cortical tissue. With trans-illumination,
neurons through the entire thickness of the slice (450 µm) contributed
equally to the signal. The resting light intensity was 109
photons/ms per detector and the VSD signal of the oscillation was
10–4 (peak-to-peak) of the resting light
intensity. The signal was AC coupled at 0.1 Hz, amplified 200 times, low-pass
filtered at 333 Hz, and then digitized at 1,000 frames/s with a 12-bit
accuracy.
Local field potential recordings
Tungsten microelectrodes (epoxylite-coated, FHC, Bowdoinham, ME) with tip
resistance of 75 k
were used for sampling local field potentials.
The electrode was carefully placed into the tissue so that the tissue
surrounding the electrode produced normal VSD signals. The field potential
signals were amplified x1,000 and band-pass filtered at 0.1–400 Hz
(by a Brownlee Precision 440 amplifier) and digitized at 1,000 Hz
simultaneously with the VSD signals.
Data analysis and display
The optical data were analyzed using the program NeuroPlex (RedShirtImaging, LLC, Fairfield, CT). Data were displayed in the form of traces for numerical analysis and pseudocolor images for visualizing the spatiotemporal patterns. To generate pseudocolor maps, we normalized the signals from each individual detector to their own maximum amplitude (peak = 1 and baseline/negative peak = 0). Then a scale of 16 colors was linearly assigned to the values between 0 and 1 (Variable scaling in NeuroPlex). The pseudocolor maps were displayed as "contour" maps using the CONTOUR function provided by IDL (Interactive Data Language, Research Systems, Boulder, CO) and used by NeuroPlex.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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When neocortical slices were perfused with 100 µM carbachol and 10 µM
bicuculline at 28–32°C, oscillations at theta frequencies
(5–14 Hz) occurred in the occipital area of the slice
(Fig. 1) in agreement with the
results obtained by Lukatch and MacIver
(1997). These oscillations can
be distinguished from epileptiform spikes in the same tissue: epileptiform
spikes had high-amplitude (1 mV) and low-repetition frequency
(0.5–1.5 Hz), whereas theta oscillations had a low-amplitude (0.5
mV) and high frequency (5–14 Hz)
(Kowalczyk et al. 2001).
Staining with the dye did not change the frequency, duration, or the amplitude
of the theta oscillations recorded by the local field potential electrode
(data not shown). During VSD imaging, only a moderate illumination intensity
was used so that bleaching and photodynamic damage (resulting from high
illumination intensity, Jin et al.
2002) were not detectable.
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In cortical layer II–III, oscillations both in local field potential
and optical signal were highly correlated in the same voxel (330 x 330
x 450 µm3, Fig.
1, middle, top 2 traces). However, in local field
recordings there were harmonic frequency components
(Fig. 1, right). Local
field potential signal has a continuous phase shift from Layers II–III
to VI and opposite phases occurred in between superficial and deep layers
(data not shown) (but see Fig. 7 of
Lukatch and MacIver 1997).
This phase reversal was not seen in the VSD recordings during most oscillation
cycles (14 slices from 10 animals, 1 recording from layer V was shown in
Fig. 1, middle, bottom
trace, other examples are in Figs.
3B, and
5, C3, C5, and
D3; an exception shown in Fig.
6B). This difference between electrodes and optical
recordings demonstrated that VSD and field potential recordings measured
different aspects of the neuronal activity. VSD signal is a population sum of
transmembrane potential; Local field potential represents the local current
density; the phase shift and polarity reversal indicate a current sink/source
pair located in the cortical column
(Lukatch and MacIver 1997).
This phase shift is not present in the membrane potential oscillations. The
phase map of VSD imaging correlates with the phase distribution in the
membrane potential over the neuronal population without the interference of
current source/sink pairs resulting from the geometrical arrangement of the
neurons.
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Oscillation epoch
This oscillation was organized in epochs. The epochs started spontaneously
or could be triggered by an electrical stimulation (e.g., 0.5 V x 0.1
ms). In local field recordings, each epoch was composed of a large first spike
(Fig. 2B), a period of
"regular" cycles (relatively stable frequency and amplitude)
followed by a period of "irregular" cycles (with variable
frequency and amplitude, Fig.
2B). These three components were seen in all epochs, from
five slices of five animals, with 300 spontaneous epochs recorded from
each slice by a local field potential electrode. When a large area of tissue
was imaged optically, the three components could be more clearly characterized
by their spatiotemporal patterns. When recorded with a single electrode from
one point, there was no apparent activity before the first spike. With imaging
we found that occasionally (2 of 47 epochs recorded optically, from 14 slices
of 10 animals) the first spike was preceded by a local oscillation (Figs.
2C, 1, and
5C, 1). The first
spike occurred as an excitation wave propagating across the tissue. After the
first spike, the periodic activation spread to the whole field of view
(Fig. 2C, image 1) and
the frequency and amplitude became relatively stable
(Fig. 2C, images 2 and
3). Each oscillation cycle was associated with one activation wave (comparing
the traces and the image of Figs.
2C, image 2, and
3A). This one-cycle
one-wave pattern was seen during the entire course of the oscillation. The
oscillation frequency decreased from cycle to cycle (Figs.
2C, image 3, and
Fig. 4D), and later
the reoccurrence of the waves gradually became infrequent and
"irregular", as the initiation site and propagating velocity
varied in different cycles (Fig.
2C, images 5–7). The first cycle in
Fig. 2C, image 5,
started simultaneously on several detectors and propagated in the two opposite
directions with different velocity. The second cycle in
Fig. 2C, image 5,
started from the bottom section and propagated up (a reversed direction as
that in Fig. 2C,
images 2–4). Complex patterns, such as collision and reflection of the
waves also occurred: The first cycle in
Fig. 2C, image 6, was
initiated at the center of the tissue and propagates in both directions.
Apparently the activity reflected at the edge of the field of view, and the
reflected waves propagated back and collided in the center, forming an
"O" pattern. Irregular periods were observed following regular
cycles in all 47 epochs examined optically (14 slices from 10 animals). Other
examples of irregular oscillations were documented in Figs.
5 and
6 and discussed in the related
sections.
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Propagating waves
During the regular oscillation period, VSD imaging revealed a localized activation associated with each oscillation cycle (e.g., Fig. 3A, pseudocolor images). The activated area had a columnar shape, perpendicular to the cortical laminae. The width of the active area (the area with signal >50% of the peak) was 400 ± 220 µm (n = 15). This activated area propagated continuously in the horizontal direction across the entire occipital cortex. "Propagating waves" were defined as one such activation wave correlated with one oscillation cycle (1-cycle 1-wave). The mean propagation velocity was 55 ± 21 mm/s (54 measurements from 54 waves in 3 slices). The horizontal propagation direction was the same (from medial to lateral, Figs. 2 and 5) during regular cycles.
During propagating waves, the activation of the neuronal population was more synchronized in the vertical (columnar) direction. Figure 3B shows the time difference for the VSD signal to reach its maximum at two neighboring detectors (named "peak-time difference" in this report). In the horizontal direction, the peak-time difference is centered around 6 ms, resulting from the propagation delay. In the vertical direction, the peak-time difference is centered around 0 ms. The shape of the distribution histogram in the vertical direction (red envelope in Fig. 3B) was also taller and thinner than that of the horizontal direction, indicating a better synchronization along the columnar direction than in the horizontal direction (also see Fig. 5C, 2 and 3). Because of this vertical synchronization, the propagating wave had a columnar shape in the activity maps (Fig. 3A, bottom).
Local frequency
Local oscillation frequency was examined on a spatial scale of 330
µm. In Fig. 3B, the
peak time difference at two horizontal neighboring locations had variations as
large as ±20 ms, suggesting a wide range of frequency variations within
a 330-µm distance. Figure
4A shows the peak time difference of two neighboring
detectors (330 µm apart, horizontally arranged in layer II–III,
Fig. 4B) in
consecutive cycles of a regular period of oscillation. The overall propagation
direction was the same for all the cycles. The peak-time difference changed
from cycle to cycle, from positive to negative values. In 14 slices (47
epochs) imaged optically, we found 11 detector pairs with continuous changing
of local frequency (Fig.
4C, blue and black), whereas others have apparent random
fluctuations (Fig. 4C,
red). The continuous cycle-to-cycle change suggests that the local frequency
variations were not randomly distributed nor caused by noises. Because the
overall oscillation frequency declined with time
(Fig. 4D), if in one
location the frequency declined faster than its neighbors, continued peak-time
variations would occur. This suggests that the frequency at two neighboring
locations were at least partially controlled by two local oscillators. The
local oscillators would have a size similar to or smaller than 330 x 330
µm2—the area of tissue imaged onto one optical
detector.
Much larger local frequency variations were seen during irregular cycles where the oscillation at two neighboring locations can switch from phase advance to phase delay in one cycle. The irregular patterns were analyzed below to demonstrate that the horizontal coupling regime could break and local oscillators could activate independently.
Irregular oscillations
Examples of irregular oscillations from four different slices were shown in Fig. 5. In all the examples, propagating wave occurred before the irregular patterns, indicating that a coupling regime for regular propagating waves existed in all preparations, and this regime could degrade during the course of the epoch and dynamically change into other coupling patterns. The following irregular patterns were seen in the 14 slices we examined: 1) dynamic reversal of propagating direction. The waves changed from the "\" to "/" shaped patterns in different cycles (Fig. 5A, images 1 and 3). When propagation direction changed, the phase relationship reversed in all neighboring locations; 2) wave collision. Two waves propagated in opposite directions and collided in the middle, forming a ">" pattern (1st 4 cycles in image 2 of Fig. 5A); 3) wave initiated in the center and propagated in two directions, forming a "<" pattern (1st cycle in image 4 of Fig. 5C); 4) possible reflection of the wave occurred outside the field of view, forming a "V" shaped pattern (image 4 of Fig. 5B); and 5) interruption of a propagating wave. In some cycles, the wave did not propagated through the entire tissue (image 2 of Fig. 5, A and B).
More complex patterns may be explained by the combination of the preceding patterns, such as the X-shaped pattern (image 4 of Fig. 5D), which can be explained as a combination of a collision and then the collision point initiating a new wave. The "O" shaped pattern (image 6 of Fig. 2C) can be explained as a combination of center initiation, reflections at both edges and then a collision at the center.
Vertical de-synchronization
As described before (Fig. 3, A and B), during propagating waves, the synchronization along cortical columns was better than that of horizontal (along the cortical laminae). Vertical synchronization also persevered during most irregular cycles when regular waves were disrupted (Fig. 5, C, 3 and 5, and D, 3). However, in the 14 slices we examined optically, we found two irregular periods where superficial and deep layers did not activate together. In one example during some irregular cycles, the activations in deep layers did not reach superficial layers (Fig. 5D, 5). In another slice (Fig. 6), the amplitude in layer II-III significantly reduced in some irregular cycles (Fig. 6A). Before these irregular cycles there was a period (Fig. 6A, x) in which superficial and deep layers showed an alternating activation. These examples suggest that superficial and deep layers of the same column may activate independently during the oscillation. However, vertical de-synchronization was much less frequently observed, suggesting that the coupling in the vertical direction is stronger that of the horizontal direction.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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In this report we found that the in vitro cholinergic oscillation was
organized as propagating waves. The oscillation has a one-cycle one-wave
characteristic (Fig. 3); that
is, each oscillation cycle is associated with one propagating wave. This
characteristic was seen in the N-methyl-D-aspartate (NMDA)
7- to 10-Hz oscillation (Wu et al.
1999). The NMDA waves can be blocked by
2-amino-5-phosphonopentanoic acid (AP5)
(Wu et al. 1999), but the
cholinergic waves in this report were not blocked by AP5 (data not shown, see
also Lukatch and MacIver
1997), suggesting that these propagating waves can be generated by
more than one polysynaptic mechanisms. The propagating waves during the two
oscillations had a similar velocity of 20–60 mm/s, slower than axonal
conductance, suggesting both are mediated by polysynaptic local circuitry.
Propagating waves during oscillations were also observed in intact brains
from turtle visual cortex (10–20 Hz)
(Prechtl et al. 1997;
Senseman and Robbins 1999) and
olfactory bulb (5–30 Hz) (Lam et al.
2000) in response to natural sensory stimulation. In turtle visual
cortex, the propagation waves also had a one-cycle one-wave characteristic but
their spatial pattern was much more complex
(Prechtl et al. 1997).
Oscillations of different frequencies happened at the same time and travel in
different directions (Prechtl et al.
1997). In intact cortex there are two horizontal dimensions that
allow variations in many directions. In brain slices there is only one
horizontal dimension and therefore only two possible propagation directions.
Reversal in the propagation was observed in this cholinergic oscillation
(e.g., Figs. 2C, 5,
and 5A, 3) and also in
the NMDA oscillations (7–10 Hz) where the horizontal direction reversed
dynamically in different cycles (Fig. 7 of
Wu et al. 1999). This dynamic
change of propagation direction further suggests that the activation of the
cortical neuron population is dynamically organized during the
oscillation.
Coupled local oscillators and propagating waves
Our data suggest that the frequency of the oscillation may be determined by
locally organized oscillators. Coupled local oscillators were also proposed
during the evoked oscillations in turtle visual cortex
(Prechtl et al. 2000).
Mathematical models showed that propagating waves might emerge in a network of
coupled oscillators with proper frequency gradient or coupling intensity
(Ermentrout and Kopell 1984,
1994;
Kopell 1988). In our data, the
coupling intensity seemed to be variable in each epoch: During regular cycles,
the phase relationship is less variable, suggesting a stronger coupling;
during the irregular cycles following the regular period, the phase
relationship was more variable suggesting a weaker coupling. In all slices, we
found regular and irregular waves occurred in the same tissue, suggesting that
the coupling intensity is controlled by dynamic factors of the local circuits
because the anatomical connectivity did not change within seconds. However,
anatomical connectivity may still play a role: in an examination of the
waveforms in different cortical areas, Lukatch and MacIver
(1997) reported irregular
waveforms were often seen in somatosensory areas while regular oscillations
were mostly seen in occipital and entorhinal cortices, suggesting different
cortical areas may have different background coupling strengths.
In thalamic slices, the propagating patterns of spindle waves also have
similar irregular patterns, such as collisions, multiple initiation points,
and local waves (Kim et al.
1995). Other kinds of one-dimensional propagating waves formed by
coupled oscillators have been suggested in developing chicken spinal cord
(O'Donovan et al. 1998) and in
the lamprey spinal cord during fictive swimming
(Mellen et al. 1995;
Rand et al. 1988). Coupled
local oscillations may have complex behaviors (e.g.,
Davidenko et al. 1992).
However, all the variety of propagating patterns observed (Figs.
2,
5, and
6) can be explained by the
variations in the initiation site, collisions, and phase advance/delay between
two neighboring locations.
Size of local oscillators
The optical signal originates from the change in transmembrane potential of
neurons (Ross et al. 1977).
Our signal is the averaged transmembrane potentials of many neurons. The
estimated neuronal density in neocortical tissue is 100,000
neuron/mm3 (Douglas and Martin
1990). In the cortical tissue projected to one optical detector
(330 x 330 x 450 µm3), there were 5,000
neurons. To detect the oscillation optically, a fraction of these neurons must
change their membrane potential synchronously. Frequency fluctuations
(Fig. 3) suggested that the
size of the local oscillator is comparable to or less than the volume of the
tissue (330 x 330 x 400 µm3) projected onto one
optical detector. Thus we estimate that the local oscillator during this
cholinergic oscillation is organized with thousands of at least partially
synchronized neurons.
During an evoked 20- to 80-Hz oscillation in cortical slices (Fig. 7 of
Wu et al. 2001), the
oscillation only appears on a field potential electrode but is not detectable
optically from the same tissue, suggesting that the size of the local
oscillator is substantially smaller than the volume of the tissue projected
onto one optical detector. Another oscillation, a NMDA-mediated 7- to 10-Hz
oscillation (Fig. 3 of Wu et al.
1999), can be detected optically, suggesting that it has larger
local oscillators, similar to that of the cholinergic oscillation in this
report.
Propagating velocity
The propagation velocity of excitation waves in neocortex has been measured
during different population events (Bal et
al. 1995; Chervin et al.
1988; Demir et al.
1999; Fleidervish et al.
1998; Golomb and Amitai
1997; Tanifuji et al.
1994; Tsau et al.
1998; Wu et al.
1999,
2001). GABAergic inhibition
was proposed to be an important factor for controlling the propagating
velocity of an excitation wave (Golomb and Ermentrout 2000). When the
GABAergic network is intact, the propagation velocity of the evoked gamma
oscillation is 10 mm/s (Wu et al.
2001). After blocking GABAA receptors with bicuculline,
the propagation velocity increased to 130 mm/s
(Wu et al. 2001). Here we show
that in the presence of carbachol and bicuculline, the propagation velocity
was much slower than that of adding bicuculline alone. We speculate that
carbachol might modify the network to form localized oscillators and that the
slow propagation wave may be due to network localization and the phase lags
between neighboring oscillators.
Conclusions
Our results suggest that propagating waves during neocortical oscillations
are organized by coupled local oscillators. Each oscillator is a population
unit, composed of thousands of neurons. Variation in the coupling strength may
contribute to the spatiotemporal dynamics of the waves. A number of questions
remain. What defines a population oscillator? What determines the coupling
strength? Finally, do similar oscillations also occur in vivo? The wavelengths
of the propagating waves were small (4 mm,
Figs. 3). It might be difficult
for scalp electroencephalgraphy to reach such a high spatial resolution
(Ferree and Clay 2000) and
detect waves with such small wavelengths. Additional experiments will be
needed to address these questions.
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ACKNOWLEDGMENTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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This work was supported by National Institute of Neurological Disorders and Stroke Grant NS-36477 and a Whitehall Foundation grant.
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FOOTNOTES |
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Address for reprint requests: J.-Y. Wu, Georgetown University, Rm 247, Basic Science Building, 3900 Reservoir Rd. NW, Washington, DC 20057 (E-mail: wuj{at}georgetown.edu).
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