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1Department of Physiology and Biophysics, Georgetown University Medical Center, Washington, DC; and 2Department of Cell and Molecular Immunology, Medical School, Henan University, Kaifeng, China
Submitted 20 June 2006; accepted in final form 20 July 2006
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ABSTRACT |
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25 Hz. The activity can be reversibly blocked by 6-cyano-7-nitroquinoxalene-2,3-dione (CNQX). 2-amino-5-phosphonopentanoic acid (APV), and atropine but not by bicuculline, indicating polysynaptic excitatory mechanisms. Voltage-sensitive dye imaging showed high-amplitude oscillation signals in superficial and middle cortical layers. Spatiotemporally, the oscillations were organized as waves, propagating horizontally along cortical laminar. Each oscillation cycle was associated with one wave propagating in space. The waveforms were often different at different locations (e.g., extra cycles), suggesting the co-existence of multiple local oscillators. For different cycles, the waves often initiated at different locations, suggesting that local oscillators are competing to initiate each oscillation cycle. Overall our results suggest that this cortical network oscillation is organized at two levels: locally, oscillating neurons are tightly coupled to form local oscillators, and globally the coupling between local oscillators is weak, allowing abrupt spatial phase lags and propagating waves with multiple initiation sites. |
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INTRODUCTION |
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; Freeman and Barrie 2000; Gray and Singer 1989; Llinas and Ribary 1993; Murthy and Fetz 1996; Nicolelis et al. 1995; Steriade et al. 1993; Tank et al. 1994). Spatially organized oscillations may play a role in cortical processing such as sensory binding (Buzsaki et al. 2002; Eckhorn 1994; Engel et al. 1991; Gray et al. 1989), coding sensory information or experience (Bressler 1988; Chabaud et al. 2000; Freeman and Viana di Prisco 1986) and attention (Fries et al. 2001). Because all of these neuronal processes are distributed in large areas of the cortex, studying the spatiotemporal patterns of the cortical oscillations is important in the understanding of how population neuronal activity is organized during these processes.
Many network oscillations are spatiotemporally organized as propagating waves (aka "traveling waves") (Ermentrout and Kleinfeld 2001). Propagating waves have been observed during sensory processing including visual (Arieli et al. 1995, 1996; Prechtl et al. 1997, 2000; Senseman and Robbins 1999), somatosensory (Nicolelis et al. 1995; Petersen et al. 2003; Ferezou et al. 2006), and olfactory (Freeman and Barrie 2000; Lam et al. 2000, 2003; Friedrich and Korsching 1997). A possible mechanism for creating propagating waves is spatial distribution of phase gradient of coupled local oscillators (Cohen 1988; Ermentrout and Kleinfeld 2001; Kopell and Ermentrout 1986). In a distributed network such as neocortex, a local oscillator can be defined as a group of tightly coupled oscillating neurons. Between two local oscillators, the coupling is relatively weak, allowing large phase lags to occur. The existence of such cortical local oscillators has been suggested by multi-electrode recordings from turtle visual cortex (Prechtl et al. 2000). However, many basic questions regarding cortical local oscillators have not been explored, e.g., what is the physical size of a local oscillator (single column/multiple columns) and whether these local oscillators are dynamically organized during each cortical event. The first step to approach these questions would be to visualize local oscillators with voltage-sensitive dye imaging. During a network oscillation local oscillators may be identified when large and abrupt phase lags occur between neighboring areas.
We have previously imaged two types of 4–15-Hz oscillations (Bao and Wu 2003; Huang et al. 2004; Wu et al. 1999) and found phase variations between local areas (Bao and Wu 2003), suggesting the existence of local oscillators during these oscillations. However, large and abrupt phase lags were not seen, probably because the coupling among the local oscillators was too strong. We have also imaged an evoked oscillation of 20–80 Hz in neocortical slices (Wu et al. 2001). The oscillation can be recorded in local field potential, suggesting that oscillating neurons near the electrode tip formed tightly coupled local oscillators. However, the oscillation cannot be recorded by voltage-sensitive dye imaging, probably because the coupling on a local scale (under each optical detector) was too weak (Wu et al. 2001).
Along the line of effort for visualizing local oscillators in neocortex, we are searching for a cortical oscillation with strong coupling within a local oscillator and weak coupling between local oscillators. Here we report a discovery of an evoked network oscillation in neocortical slices with this feature. Voltage-sensitive dye imaging revealed high-amplitude oscillations, suggesting a strong local synchrony. At different locations the waveforms were different, suggesting weak coupling between local oscillators. In addition, different oscillation cycles often initiated from different locations, suggesting a competition between local oscillators to initiate each oscillation cycle. Our results suggest the oscillation is organized at two levels, locally neurons are more synchronized to form local oscillators but globally coupling between local oscillators is weak, allowing spatial distribution of phase lags and propagating waves.
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METHODS |
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Sprague-Dawley rats (n = 29) of both sexes from P21 to P32 were used in the experiments. Following National Institutes of Health guidelines, the animals were deeply anesthetized with halothane and decapitated. The whole brain was quickly removed and chilled in cold (0–4°C) slicing artificial cerebrospinal fluid (sACSF) for 90 s. The sACSF contained (in mM) 110 choline chloride, 2.5 KCl, 0.5 CaCl2, 7 MgSO4, 1.2 NaH2PO4, 25 NaHCO3, 20 dextrose, 10 sucrose, 1.3 L-ascorbic acid, and 2.4 Na pyruvate (modified from Hoffman and Johnston 1998), and the solution was bubbled with 95% O2-5% CO2. Coronal slices (400 µm thick) of the whole cortical hemisphere were cut in the sACSF at 0–4°C with a vibratome stage (752M Vibroslice, Campden Instruments, Sarasota, FL) and transferred into a holding chamber containing sACSF at 35°C (bubbled vigorously with 95% O2-5% CO2). After 30 min incubation at 35°C, the temperature was reduced to 26°C (room temperature). Then half of the sACSF in the holding chamber was replaced by normal ACSF [containing (in mM) 132 NaCl, 3 KCl, 2 CaCl2, 2 MgSO4, 1.25 NaH2PO4, 26 NaHCO3, and 10 dextrose]. The slices were then incubated in a combination of 1/2 sACSF and 1/2 ACSF for 2–3 h until transferred to a submerged chamber for recording. The slice was perfused with ACSF at a rate of >20 ml/min for 
40 min (30–31°C) in the submerged chamber before recording. In some experiments, the slices were cut horizontally, parallel to the cortical lamina (tangential slices) as described in our previous paper (Huang et al. 2004). These tangential slices were cut at 100 µm below the cortical surface and 500 µm thick, contained most of the layers II–III and part of layer IV. Due to the curvature of the cortex, the size of the tangential slices were limited to 4 x 6 mm2.
Voltage-sensitive dye imaging
The imaging apparatus and methods are described in detail in Jin et al. (2002). Briefly, the slices were stained for 60 min with ACSF containing 0.005–0.02 mg/ml of an oxonol dye, NK3630 (1st synthesized by R. Hildesheim and A. Grinvald as RH482; available from Nippon Kankoh-Shikiso Kenkyusho) [see Momose-Sato et al. (1999) for molecular structure]. After staining, the slices were washed in dye-free ACSF for 40 min before recording and perfused in ACSF during imaging experiments. Voltage-sensitive dye imaging was performed by a 124-element photodiode array (Centronics, Newbury Park, CA) or a 464-element photodiode array (WuTech instruments; www.wutech.com). The imaging devices allow us to measure small signals (10–5) at a fast (1,600 frame/s) imaging rate. Image of the tissue was projected by an objective of 5x (0.12 NA, dry lens, Zeiss) or 20x (0.5 NA, water immersion, Zeiss) to the diode array and each photodetector received light from an area of 0.33 x 0.33 mm2 (5x) or 0.08 x 0.08 mm2 (20x) of the cortical tissue, respectively, when the 124 array was used and 0.13 x 0.13 mm2 (5x) when the 464 array was used. The preparation was trans-illuminated by 705 ± 20 nm light and was only exposed to the illumination light during optical recording trials, for about 3 s/trial and <64 trials per slice. With this level of exposure, photodynamic damage and dye bleaching are not detectable (Jin et al. 2002). The voltage-sensitive dye signal of the oscillation was 10–4 (peak-to-peak) of the resting light intensity. Optical signal from each detector was individually amplified to 200x, low-pass filtered at 333 Hz, and then multiplexed and digitized at 12 bits and 1,600 samples/s per channel. A commercial version of 464-diode array is available as NeuroPDA from RedshirtImaging (www.redshirtimaging.com). Additional details about the imaging methods are discussed in Wu and Cohen (1993) and Jin et al. (2002).
Local field potential recordings
Tungsten epoxy-coated microelectrodes with tip resistance of 75 k
(FHC, Bowdoinham, ME) were used for stimulating and for recording local field potentials simultaneously with optical recordings. The field potential signals were amplified to 1,000x and band-pass filtered between 0.1 and 400 Hz by a Brownlee Precision 440 amplifier. During imaging experiments, the field potential was digitized simultaneously with voltage-sensitive dye signals at a rate of 1,600 Hz. In some experiments, the slices were not stained and imaging was not performed, the oscillations were only recorded by local field potential electrodes. The LFP signals were recorded by a tape recorder (InstruTech, Great Neck, NY) and digitized at 1,600 Hz off-line. The LFP signals in stained and unstained slices were undistinguishable, suggesting that staining and voltage-sensitive dye imaging did not contribute to the formation and sustaining of the oscillations.
Data analysis
The oscillation frequency was calculated by a program written in MatLab using the FFT function. The averaged frequency-power spectrum was obtained by adding the FFT of individual trials.
The optical data were analyzed using the program NeuroPlex (RedShirtImaging, LLC, Fairfield, CT) and displayed in the form of traces and pseudocolor images. To generate pseudocolor maps, the signals from each individual detector were normalized to their own maximum amplitude (peak = 1 and baseline/negative peak = 0), (Variable scaling in NeuroPlex). Then a scale of 16 colors was linearly assigned to the values between 0 and 1. The propagating velocity was calculated by dividing the distance between two locations by the time difference for a wave to reach these two locations.
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RESULTS |
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). After slicing, the sodium concentration was gradually restored while choline was removed over a period of several hours in the holding chamber. The oscillations were evoked in normal ACSF after choline was thoroughly washed out. During experiment, the slices were continuously perfused with choline free ACSF at 30–31°C in a submerged chamber. Field potential signals
The oscillation was evoked by a single electrical shock to cortical layers II–IV of slices from temporal cortex (area I–III, auditory cortex, Fig. 1A) or occipital cortex (visual areas). Local field potential signals can be recorded from cortical layers II–III at 2 mm lateral to the stimulation site (Fig. 1, A and B). A shock of moderate intensity (5 V x 0.25-ms pulse, 1.5 times of the field potential response threshold) was enough to trigger an epoch of oscillations (Fig. 1B). The oscillation epoch was an all-or-none event. Changing the stimulation intensity above the threshold did not alter the occurrence of the oscillation and the frequency, amplitude, or the number of cycles in the epoch. With an inter-stimuli-interval of 30 s, the oscillation can be reliably evoked for 4 h (68 slices from 29 animals). Each oscillation epoch started with a first spike and followed by 4–13 cycles of oscillations (Fig. 1, B and C). The first spike was more robust than the subsequent oscillation cycles. In a small fraction of trials, only the first spike was evoked and the subsequent oscillations failed to develop (data not shown). Although the number of cycles varied in different epochs (Fig. 1C), the oscillation frequency was stable with small trial-to-trial variations (Fig. 1D). The power spectrum (FFT) had a sharp frequency peak, and the frequency peaks from multiple epochs were clustered together (Fig. 1D). Sharp frequency peaks and small trial-to-trial variations suggest a stable organization of oscillating neurons near the electrode tip. However, the organization was only stable for a short time, 4–13 cycles (Fig. 1C).
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Before optical recording, the slices were stained with voltage-sensitive dye NK 3630. Local field potential recordings from stained and unstained slices did not noticeably differ in the amplitude, frequency, and the number of oscillation cycles. Optical recording was done with a trans-illumination arrangement, and absorption of the stained tissue through the light path was measured. The optical signal at 705 ± 10 nm (on one side of the absorption peak of cortical tissue stained with NK 3630) (Momose-Sato et al. 1999; Jin et al. 2002) had both slow and fast components after the stimulus (Fig. 2, trace 2). The slow component was independent of the illumination wavelength (Fig. 2, trace 3), indicating that it was an "intrinsic" optical signal or activity-related light scattering due to cell swelling and shrinkage in the extracellular space (Jin et al. 2002; MacVicar 2000; Sato et al. 1997). The fast component had a reversed polarity at 670 nm (data not shown), indicating that it was a voltage-sensitive dye signal, associated with membrane potential changes from the neurons stained with the voltage-sensitive dye (Jin et al. 2002; Ross et al. 1977). At 705 nm, the amplitude of the voltage-sensitive dye signal for the first spike was 5.2 ± 0.4 x 10–4 (n = 143 trials from 7 slices) of resting light intensity. The intrinsic optical signal was 8.6 ± 1.0 x 10–4 (n = 16 trials from 1 slice).
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Laminar distribution of the oscillation
Voltage-sensitive dye imaging revealed that the oscillations had large amplitude in superficial and middle cortical layers. Using a 20x microscope objective, we imaged the oscillations with 100 detectors in a field of view of 1 mm in diameter over the middle and deep layers of the cortex (Fig. 3, left). Along the vertical axis from layers II–III to VI, there were 12 rows of optical detectors. The first spike was seen in all cortical layers. The amplitude of the subsequent oscillation cycles, however, decreased in the deep layers of the cortex (Fig. 3, right). The amplitude reduction in deep layers was disproportional between the first spike and the subsequent oscillation cycles (Fig. 3, right). In tangential slices containing only layers II–IV, oscillations occur normally (example traces shown in Fig. 7B), suggesting that the oscillations can be sustained without deep layers.
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Associated with each oscillation cycle a wave propagated horizontally (parallel to cortical laminar) in coronal slices (Fig. 4, right). The propagation velocity was 0.045 ± 0.008 m/s (measured from 23 trials in slices from 2 animals). This velocity was slower than axonal conductance in cortex, suggesting that the wave was mediated by multiple synapses in the local circuit.
The propagation direction during different oscillation cycles was not fixed. Figure 4 shows two example trials recorded optically in the same tissue. The first trial had four cycles (Fig. 4, top traces, cycles 1–3 and s) following the first spike (f). Cycles 1–3 reached detector A earlier than detector B, indicating that all propagated from medial to lateral (last cycle s had low-amplitude and direction was indeterminate). The second trial was recorded a few seconds later and had five cycles after the first spike (Fig. 4, bottom traces). In this trial, the first spike and the first two cycles of oscillation had the same propagation direction from medial to lateral, as in the first trial. But in the third cycle (s), the wave appeared simultaneously on both detectors and the subsequent two cycles (r1 and r2) had a reversed propagation direction. Change in propagation direction was seen in many optically recorded trials (further examined below), suggesting that different oscillation cycles started at different locations.
Initiation foci of the waves
To explain why different oscillation cycles often had different propagating directions, we examined oscillations with a 464-element diode array with higher spatial resolution (128 µm diam/detector). This high spatial resolution allowed us to more accurately locate the initiation site of the propagating wave associated with each oscillation cycle. In all trials recorded optically, the first spike always started at the location of stimulating electrode. The following oscillation cycles initiated at different locations. In the example shown in Fig. 5, there were seven oscillation cycles after the first spike. The first spike initiated at the location of the stimulating electrode (Fig. 5, black cross in 1st top row image) and propagated across the slice. Two oscillation cycles, 3 and 7, initiated from two different locations (Fig. 5, black crosses in middle and bottom row images) and propagated in a concentric pattern surrounding their initiation foci. Thus the variation in propagation directions shown in Fig. 4 can be explained as two cycles starting from different locations.
We then examined whether oscillation cycles were initiated from a few preferred foci. In one slice, we have imaged 352 oscillation cycles and identified the initiation focus for each cycle. The initiation foci were defined as the location of the optical detector with earliest onset time (the time at which signal reached half of the maximum amplitude). We found that the majority of the initiation foci were distributed in the upper and middle layers of the Te III area (Fig. 6A, right). Many cycles started from a few locations, indicating there were preferred initiation foci. Figure 6B shows the initiation foci for four example trials. In all four trials, the first spike was initiated at the location of stimulation (F). Subsequent oscillation cycles after the first spike were initiated at different locations, apparently in a random sequence for each epoch. The phenomenon of multiple initiation foci may be explained as a result of multiple local oscillators in the tissue. These local oscillators have similar frequency and compete to initiate each propagating wave. The existence of multiple local oscillators is also supported by evidence that the waveforms at different locations are significantly different (2 examples shown in the next section).
Multiple local oscillations
Imaging revealed a large variation in the waveform at different locations. Figure 7 shows two examples from slices sectioned in coronal and tangential planes. In both preparations, the waveforms at different locations were different. In the example shown in Fig. 7A, the duration of the oscillations were similar in all locations, but two extra cycles were seen on detector 2 after the first spike (trace 2, arrowhead). Similarly, on detector 4 an extra cycle was seen at the end of the oscillation epoch (trace 4 arrowhead). Trials with waveform variations were often seen in recordings with high spatial resolution (51%, n = 130 trials using the 464 array).
In tangential slices, the spatial variation in waveforms can be examined in the horizontal plane. Again a single shock evoked oscillations in a large area (marked by dashed line on the Fig. 7B, left), but within the area, individual detectors show different numbers of cycles and phases (Fig. 7B, traces 1–4). The spatial average of the entire oscillating area (160 detectors, marked by dashed line in Fig. 7B, left) showed a net depolarization with small oscillations (Fig. 7B, bottom), indicating that the oscillations were not synchronized over space. On the other hand, the local oscillators were not completely independent as indicated by the propagating waves accompanying each oscillation cycle (if the oscillators were independent, then there would be no propagating waves). Movies from two examples, one from a coronal slice and another from a tangential slice, are presented as supplement movies 1 and 2 to demonstrate the irregularities of the propagating waves.
Pharmacological manipulations
The oscillation in this report only occurs in slices pretreated with choline and choline needs to be thoroughly washed out before the oscillations can be triggered. Slices prepared by another method, using sucrose to replace NaCl (Sanchez-Vives and McCormick 2000), did not show this evoked oscillation. Apparently, choline modifies the local cortical circuits during slicing and subsequent incubation when sodium concentration was restored.
Synaptic mechanisms of the oscillation were explored with agonists and antagonists of common neurotransmitters. Figure 8 summarizes the effects of blocking major neocortical synapses. Antagonists to the N-methyl-D-aspartate (NMDA) subtype glutamate receptors, 2-amino-5-phosphonopentanoic acid (APV) reversibly blocked the oscillation (Fig. 8A). Increasing the concentration of Mg2+ in the ACSF, from normal 2 to 3–4 mM also reversibly blocked the oscillation (Fig. 8B). In high-Mg2+ media, it became more difficult to evoke the oscillation with the same stimulation intensity, and the failure rate of evoking the oscillation become higher (Fig. 8B, middle). Blocking AMPA subtype receptors by their antagonist 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX) also blocked the oscillations (Fig. 8C). Perfusing with GABAA receptor antagonist bicuculline did not block the oscillations. The amplitude of the first spike and the number of oscillation cycles increased with bicuculline (Figs. 2, trace 4, and 8D). Manipulating muscarinic cholinergic receptors also affected the oscillations. The oscillations were sensitive to muscarinic receptor antagonist atropine (completely blocked in 10 µM, Fig. 8E). Carbachol, a muscarinic/nicotinic receptor agonist, also blocked the oscillations at a low concentration (10 µM, Fig. 8F). In contrast, nicotinic receptor antagonist methyllycaconitine (100 nM) had no apparent effect on the oscillation (neither enhancing nor blocking, data not shown).
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DISCUSSION |
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Synchrony of oscillating neurons on local scale
Voltage-sensitive dye imaging provides a useful tool for examining the spatiotemporal patterns of oscillations in cortical network. The amplitude of the voltage-sensitive dye signal can be used to estimate the fraction of neurons synchronized in a local oscillating population. The voltage-sensitive dye signal is linearly correlated to transmembrane potentials (Ross et al. 1977), and the sensitivity of the voltage-sensitive dye is comparable to local field potential microelectrodes in measuring cortical population neuronal activities (Jin et al. 2002). In our absorption dye measurement, all neurons "seen" by each optical detector contributed relatively equally to the voltage-sensitive dye signal, thus the amplitude of the voltage-sensitive dye signal reflects a net sum of the membrane potential fluctuation of all neurons under each detector. Large voltage-sensitive dye signals of the oscillations (Figs. 2–7) indicate that a large fraction of oscillating neurons is synchronized on a local scale, under each optical detector. The density of cortical neurons was estimated to be 100,000 neurons/ mm3 (Douglas and Martin 1991), and the tissue volume projected onto each optical detector (of the 128 array) contains 5,000 neurons. During an all-or-none epileptiform event under bicuculline disinhibition (aka. interictal-like spike), 80% of the neurons are activated (Wu et al. 2001). Trace 4 of Fig. 2 shows that with bicuculline the amplitude of the first spike is similar to that of interictal-like spikes and that the first spike is about three times larger than other oscillation cycles. Thus we estimate that 30% of the local population is synchronized during the oscillations. Intrinsic optical signals were about twice as large in the presence of bicuculline as that in normal ACSF, consistent with the estimation that a smaller fraction of neurons is synchronized during oscillations than during an all-or-none epileptiform event (traces 3 and 4 of Fig. 2).
Local oscillators
As mentioned in the preceding text, large voltage-sensitive dye signals indicate synchrony among the oscillating neurons on a local scale under each detector. Strong local synchrony was also suggested by the fact that the oscillation had a sharp frequency peak and the peak was robust from trial to trial.
If at two locations the oscillation waveforms are different, there must be two or more clusters of synchronized oscillating neurons (local oscillators). Different oscillating waveforms were often observed at different locations (Fig. 7), indicating that multiple local oscillators co-exist simultaneously at different locations. However, with the present data, we do not know if there is a sharp boundary between two neighboring local oscillators. This oscillation has another feature that different oscillation cycles often initiate from different locations (Figs. 5 and 6). Such switching of initiation sites also suggests the existence of multiple local oscillators. The oscillators may have a similar frequency and a weak coupling between each other. At the beginning of each oscillation cycle, the oscillators compete and the one with the earliest phase becomes the pacemaker to lead the wave. As a result, the propagation path has large cycle-to-cycle variations (Figs. 4 and 5 and supplemental movies1 ).
Comparison with other in vitro oscillations
In addition to the oscillation in this report, seven other kinds of oscillatory activity have been described in rat neocortical and hippocampal slices (I–VII, Table 1). Five of them, I—V, have been examined with voltage-sensitive dye imaging or an electrode array. The oscillation in this report is organized as propagating waves with a pattern of one oscillation cycle associating with one wave propagating in space (1-cycle-1-wave). The one-cycle-one-wave pattern was also observed during oscillation types I (Wu et al. 1999), III (Bao and Wu 2003; Huang et al. 2004), and V (Kim et al. 1995). In contrast, oscillation type II was synchronized over space and did not appear as propagating waves (Fig. 3 of Mann et al. 2005). Compared with oscillation types I and III, the oscillation in this report had larger variations from cycle to cycle and more frequent switching of wave initiation sites, suggesting a weaker spatial coupling. The 20- to 80-Hz oscillations (type IV) can be seen in local field potential recordings, suggesting a certain level of local synchrony in the oscillating population. However, the oscillations cannot be seen in the voltage-sensitive dye signals (Wu et al. 2001), suggesting that each small volume of tissue projected onto one optical detector contains multiple local oscillators. A spatial average of 160 detectors during the oscillation in this report can also create a mostly nonoscillatory waveform (Fig. 7B, right, bottom trace), consistent with the idea that a mixture of loosely coupled local oscillations results in a nonsynchronized waveform.
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Propagating waves
Propagating waves have been seen in cortical neuronal networks during both excitatory and oscillatory events. Excitatory waves in brain tissue have been examined extensively (Albowitz and Kuhnt 1995; Chervin et al. 1988; Demir et al. 1998; Fleidervish et al. 1998; Golomb and Amitai 1997; Grinvald et al. 1984; Miyakawa et al. 2003; Tanifuji et al. 1994; Tsau et al. 1998; Wu et al. 2001). GABAergic inhibition is important for controlling the propagation of excitatory waves (Chagnac-Amitai and Connors 1989; Golomb and Ermentrout 2002; Miles et al. 1988; Traub et al. 1987; Wadman and Gutnick 1993). When GABAA receptors are blocked with bicuculline, the excitation wave propagates at 0.14 m/s in hippocampal slices (Miles et al. 1988) and 0.08 m/s (Chervin et al. 1988) to 0.13 m/s (Wu et al. 2001) in neocortical slices. These excitatory waves are much faster than the oscillatory waves in this report.
Propagating waves also occur during oscillatory events. Spatial phase distribution among coupled oscillators is a mechanism for generating propagating waves (Ermentrout and Kleinfeld 2001; Osan and Ermentrout 2001). Experimentally distinguishing local oscillators in neuronal populations may be difficult if coupling over space is so strong that it diminishes the spatial phase shift between local oscillators. For example, carbachol-induced oscillations in hippocampal slices (type II, Table 1) do not propagate (Fig. 3 of Mann et al. 2005), making it impossible to visualize individual oscillators. Carbachol-induced oscillations in neocortical slices (type III, Table 1) do propagate, but evidence for the existence of local oscillators can only be found indirectly (Bao and Wu 2003). The oscillation in this report provides an example where spatial coupling is weak enough to identify local oscillators but strong enough to form propagating waves (Fig. 5, supplemental movies 1 and 2).
In the intact brain, propagating waves have been observed during oscillations evoked by natural sensory input (Dorries and Kauer 2000; Freeman and Barrie 2000; Lam et al. 2000; Prechtl et al. 1997, 2000; Senseman and Robbins 1999). The one-wave-one-cycle pattern was also found in vivo by voltage-sensitive dye imaging (Lam et al. 2003; Prechtl et al. 1997). Our analysis in this report suggests that complex wave patterns (as that seen in vivo, Lam et al. 2003) may be a result of weakly coupled local oscillations.
In conclusion, our results showed that the oscillation we have described here has two levels of spatiotemporal organization. On a local scale, a fraction of oscillating neurons is synchronized to form local oscillators, resulting in large-amplitude voltage-sensitive dye signals. On a global scale, the coupling between local oscillators is weak, resulting in variations of waveforms and propagating paths. Further experiments are needed to examine the size of the local oscillators and the factors controlling the spatial coupling on both local and global scales.
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GRANTS |
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
1 The online version of this article contains supplemental data.
Address for reprint requests and other correspondence: J.-Y. Wu, Georgetown University, The Research Building, WP26, 3900 Reservoir Rd. NW, Washington, DC 20057 (E-mail: wuj{at}georgetown.edu)
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