Cerebral Cortex Advance Access originally published online on August 17, 2005
Cerebral Cortex 2006 16(5):688-695; doi:10.1093/cercor/bhj014
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Impact of Cortical Network Activity on Short-term Synaptic Depression
1 Instituto de Neurociencias de Alicante, Universidad Miguel Hernandez-CSIC, Apartado 18, 03550 San Juan de Alicante, Spain and 2 Centre de recherche ‘Cerveau et Cognition’, CNRS-Université Paul Sabatier.133, route de Narbonne. 31062 Toulouse Cedex, France
Correspondence should be addressed to M.V. Sanchez-Vives, Instituto de Neurociencias de Alicante, Universidad Miguel Hernández-CSIC, Campus de San Juan, Apartado 18, 03550 San Juan de Alicante, Spain. Email: mavi.sanchez{at}umh.es.
 |
Abstract |
|---|
 Top Abstract IntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Repetitive stimulation of synaptic connections in the cerebral cortex often induces short-term synaptic depression (STD), a property directly related to the probability of transmitter release and critical for the computational properties of the network. In order to explore how spontaneous activity in the network affects this property, we first studied STD in cortical slices that were either silent or that displayed spontaneous rhythmic slow oscillations resembling those recorded during slow wave sleep in vivo. STD was considerably reduced by the occurrence of spontaneous rhythmic activity in the cortical network. Once the rhythmic activity started, depression decreased over time in parallel with the duration and intensity of the ongoing activity until a plateau was reached. Thalamocortical and intracortical synaptic potentials studied in vivo also showed stronger depression in a silent than in an active cortical network, and the depression values in the active cortical network in vivo were indistinguishable from those found in active slices in vitro. We suggest that this phenomenon is due to the different steady states of the synapses in active and in silent networks.
Key Words: cortex • in vivo • plasticity • rhythmic activity • slow oscillations • spontaneous activity
|
Introduction |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Synaptic transmission between neocortical neurons often shows activity-dependent synaptic depression. Short-term synaptic depression (STD) is mainly attributed to depletion of a readily releasable vesicle pool that occurs with repetitive presynaptic activation (Zucker, 1989
; Dobrunz and Stevens, 1997) resulting in a decline in neurotransmitter release. Other mechanisms, such as feedback presynaptic inhibition and desensitization of postsynaptic receptors, may also participate (for a review, see Jones and Westbrook, 1996; see also Zucker and Regehr, 2002). A variety of STD rates (tens of milliseconds to seconds) have been described in the cerebral cortex in vitro (Thomson and Deuchars, 1994; Finlayson and Cynader, 1995; Gil et al., 1997; Tsodyks and Markram, 1997; Varela et al., 1997; Galarreta and Hestrin, 1998; Thomson et al., 2002). The decay of synaptic potential amplitude dependent on presynaptic firing frequency introduces nonlinearities between the input and ouput functions, deeply influencing cortical processing. By acting as a dynamic, input-specific gain control mechanism, STD may represent a crucial mechanism in neural coding (Abbott et al., 1997; Tsodyks and Markram, 1997). For these reasons, this particular form of cortical synaptic plasticity has been incorporated as a key mechanism in numerous computational models of cortical function. In particular, these model studies proposed that both thalamocortical and intracortical STD play a role in the adaptation of cortical responses to repetitive sensory stimulation (Todorov et al., 1997; Carandini et al., 1998; Chance et al., 1998; Adorjan et al., 1999a; Chung et al., 2002).
STD in vivo has also been reported in several studies (Castro-Alamancos and Connors, 1996; Chung et al., 2002; Fuentealba et al., 2004), and some indicate that it may be less pronounced than in vitro (Kang et al., 1991; Sanchez-Vives et al., 1998; Boudreau and Ferster, 2003). This difference between in vivo and in vitro values of synaptic depression may be due to several factors, among them differences in ionic environment or on the existence of spontaneous activity in the brain in situ.
Here we have explored how an inherent property of the cortical circuit in vivo, ongoing spontaneous activity, affects synaptic depression. To do this we used both silent and rhythmically active cortical slices, which generate activity closely resembling the one during slow wave sleep (Sanchez-Vives and McCormick, 2000). Furthermore, we examined STD in thalamocortical and intracortical synaptic connections in vivo in relationship to the spontaneous activity level, that was eventually manipulated by varying the depth of anesthesia. We conclude that ongoing activity in the network reduces synaptic depression.
|
Materials and Methods |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Slices Preparation
The methods for preparing cortical slices were similar to those described previously (Sanchez-Vives and McCormick, 2000). Briefly, cortical slices were prepared from 2- to 6-month-old ferrets of either sex that were deeply anesthetized with sodium pentobarbital (40 mg/kg) and decapitated. Four hundred-micrometer-thick coronal slices of the visual cortex were cut on a vibratome. A modification of the technique developed by (Aghajanian and Rasmussen, 1989) was used to increase tissue viability. After preparation, slices were placed in an interface-style recording chamber (Fine Sciences Tools, Foster City, CA) and bathed in what we refer to as ‘classical’ artificial cerebrospinal fluid (ACSF), containing (in mM): NaCl, 124; KCl, 2.5; MgSO4, 2; NaHPO4, 1.25; CaCl2, 2; NaHCO3, 26; and dextrose, 10, and aerated with 95% O2, 5% CO2 to a final pH of 7.4. Bath temperature was maintained at 34–35°C. Intracellular recordings were initiated after 2 h of recovery. In order to induce spontaneous rhythmic activity, the solution was switched to ‘modified’ ACSF containing (in mM): NaCl, 124; KCl, 3.5; MgSO4, 1; NaHPO4, 1.25; CaCl2, 1–1.2; NaHCO3, 26; and dextrose, 10.
Animal Preparation for In Vivo Recording
Intracellular recordings in vivo from the primary visual cortex of cats were obtained following the methodology that we have previously described (Sanchez-Vives et al., 2000). In short, adult cats were anesthetized with ketamine (12–15 mg/kg, i.m.) and xylazine (1 mg/kg, i.m.), and then mounted in a stereotaxic frame. A craniotomy (3–4 mm wide) was made overlying the representation of the area centralis of area 17. To minimize pulsation arising from the heartbeat and respiration, a cisternal drainage and a bilateral pneumothorax were performed, and the animal was suspended by the rib cage to the stereotaxic frame. During recording, anesthesia was maintained with continuous i.v. infusion of propofol (5 mg/kg/h) and sufentanyl (4 µg/kg/h). The animal was paralyzed with norcuron (induction 0.3 mg/kg; maintenance 60 µg/kg/h) and artificially ventilated. The heart rate, expiratory CO2 concentration, rectal temperature and blood O2 concentration were monitored throughout the experiment and maintained at 140–180 bpm, 3–4%, 37–38°C and >95%, respectively. The EEG and the absence of reaction to noxious stimuli were regularly checked to insure an adequate depth of anesthesia. After the recording session, the animal was given a lethal injection of sodium pentobarbital.
Ferrets and cats were cared for and used in accordance with the Spanish regulatory laws (BOE 256; October 25, 1990), which comply with the EU guidelines on protection of vertebrates used for experimentation (Strasbourg, March 18, 1986).
Recordings and Stimulation
Sharp intracellular recording electrodes were formed on a Sutter Instruments (Novato, CA) P-97 micropipette puller from medium-walled glass and beveled to final resistances of 50–100 M
. Micropipettes were filled with 2 M KAc. Recordings were digitized, acquired and analyzed using a data acquisition interface and software from Cambridge Electronic Design (Cambridge, UK). Electrical stimulation (0.1 ms, 10–300 µA) was delivered by means of a WPI A-360 stimulus isolation unit (Sarasota, FL) that prevents electrode polarization. In vitro, a concentric bipolar stimulating electrode (FHC, Bowdoinham, ME) was placed in layer 4 and the postsynaptic neurons recorded in layer 2/3. In vivo thalamocortical (t.c.) or intracortical (i.c.) fibers were stimulated with bipolar electrodes made of sharpened tungsten wires. The eyes were focused onto a tangent screen at 114 cm using corrective, gas permeable contact lenses. The position of the area centralis and optic discs was localized by retroprojection. Receptive fields location was determined with a handheld projector. The electrode placed in the LGN was first used as a recording electrode and re-located following the coordinates in (Sanderson, 1971) until the local receptive fields were centered on the fovea and overlapped with the ones from the recorded cortical neurons. Once in place, it was used for t.c. stimulation. I.c. stimulation was delivered at 500–1500 µm from the intracellularly recorded neuron. Both in vivo and in vitro, and both in t.c. and i.c., the intensity of the stimulation was adjusted to achieve a stable PSP amplitude, which at the population level ranged between 2 and 7 mV. Only monosynaptic connections were included, the criteria being: reliably evoked synaptic potentials (no failures) of constant amplitude and shape and with a constant latency (jitter < 1 ms) of 1.5–3 ms. The latency to peak was between 2.8 and 6.7 ms. To confirm that the PSPs were excitatory, their amplitude were often examined at different membrane potentials. However, since we cannot rule out a possible participation of reversed IPSPs, we refer to the synaptic response to as PSPs. During stimulation protocols aimed at examining STD, neurons were hyperpolarized to –80 ± 2 mV to prevent action potentials firing. Repetitive stimulation was delivered at 5, 10 and 20 Hz for 20 s.
Analysis
Amplitude of PSPs was measured at the peak. For 18 neurons recorded in vitro we confirmed that the measurements of PSP's slope and the amplitude were significantly correlated (P < 0.0001; 200 measurements). The control PSP amplitude was the result of averaging 12 PSPs given at 0.2 Hz prior each period of high frequency stimulation. In vitro, the absolute values of control PSPs' amplitudes were: 4.4 ± 1.3 mV for ‘classical’ ACSF; 4.4 ± 2.1 mV for ‘modified’ solution, silent; and 4.2 ± 1.3 mV in ‘modified’ solution, active. These values should not be used to evaluate amplitude of PSPs in different ionic solutions, since the intensity of stimulation was adjusted at the beginning of each intracellular recording and then kept constant throughout the recording. However, in five neurons that underwent through the three conditions (silent cortex in ‘classical’ and ‘modified’ ACSF) and active, oscillatory cortex, no significant (P < 0.05) differences were observed between amplitude of the PSPs evoked in the different conditions, and this observation has been discussed (see below). No statistically significant correlation (correlation coefficient R = 0.09; P = 0.5) was found between the amplitude of PSPs and the degree of STD. In the results, all the values that are presented have been normalized to the control PSP amplitude. In all the cases 2–6 trials (repetitions of the same stimulation protocol) were averaged for each frequency of stimulation, to account for the distortions imposed by the existence of spontaneous activity.
In Figures 2, 3A,C, 4G and 5B we have represented a connecting curve between points called a B-spline, with the purpose of improving visualization of the data. The B-spline curve can be described by parametric equations P(t) = (x(t), y(t)) as t varies over a given range. The B-spline curve approximates the original data points without necessarily passing through them.
|
|
|
|
Differences in STD over time and under different conditions (Fig. 2; t.c. versus i.c. in Fig. 4) were estimated by analysis of covariance (ANCOVAR) after transforming the amplitude to a log scale. ANCOVAR was therefore used to carry out a regression analysis of the logarithm of the amplitude versus time for each condition, therefore allowing for the possibility that the slopes and intercepts vary between the different conditions. The null hypothesis is that they are all the same under the different conditions. A slope not different from 0 indicates absence of change in the amplitude over time.
For comparisons involving two different conditions or populations, a t-test was used. For both type of tests (ANCOVAR and t-test), differences are considered ‘significant’ at a P level of <0.05. Population data are given as mean ± SD.
|
Results |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
A first set of experiments was performed in adult ferret visual cortical slices prepared as previously described (Sanchez-Vives and McCormick, 2000
). Layer 2/3 neurons from the visual cortex were intracellularly recorded and monosynaptic potentials were evoked by electrical stimulation of layer 4 below the recording site. The occurrence of spontaneous slow rhythmic activity was controlled by the ionic composition of the ACSF. Cortical slices were silent (no spontaneous ongoing activity) when maintained in ‘classical’ ACSF (for composition see Materials and Methods). However, when the slice was bathed in a ‘modified’ ACSF that mimics the ionic concentrations in situ (Hansen, 1985; the same composition as the ‘classical’ ACSF except for 3.5 mM KCl, 1 mM MgSO4, 1–1.2 mM CaCl2) a slow rhythmic activity was spontaneously generated (Sanchez-Vives and McCormick, 2000; Fig. 1C). In order to study the effect that network activity had on STD, we measured the changes in the amplitude of synaptic potentials (PSPs) induced by high-frequency stimulation (5, 10, 20 Hz) of presynaptic axons in three different experimental conditions: (i) silent slices maintained in ‘classical ACSF’; (ii) silent slices maintained in ‘modified’ ACSF prior to the development of organized rhythmic activity; and (iii) slices with rhythmic oscillatory activity maintained in ‘modified’ ACSF for different periods of time.
|
Short-term Depression is Smaller in Active Than in Silent Cortical Slices
Figure 1 shows recordings from one neuron that underwent the three experimental conditions mentioned above. PSPs were evoked by repetitive stimulation at 10 Hz for a period of 20 s, and the first five and last two PSPs evoked by the train are displayed. The figure also shows the intracellular recordings (middle traces) and the concurrent multiunit activity in the vicinity of the intracellularly recorded neuron (bottom traces) when no stimulation was applied. It is noticeable that the same stimulus train produced less STD when there was ongoing activity in the network (Fig. 1C; depressed to 0.87 of the control amplitude) than when the network was silent (Fig. 1A,B; 0.33 and 0.54 of the control amplitude respectively). Slices that did not develop oscillatory activity in ‘modified’ ACSF — or during periods of recording before the oscillatory activity developed — were useful to differentiate the effect of changes in ionic concentrations from that of the spontaneous activity itself. As shown in Figure 1B, bathing the slice in the ionically ‘modified’ solution (in the absence of activity) also resulted in a decrease in STD but to a lesser extent. This is an expected effect due to the diminished Ca2+ in the solution and the subsequent decrease in the probability of release that characteristically reduces STD (Tsodyks and Markram, 1997; Varela et al., 1997; Zucker and Regehr, 2002; Crochet et al., 2005).
Less STD in the presence of spontaneous rhythmic activity in the network was a major finding in the population of neurons recorded in vitro. The study in vitro included a total of 44 neurons. The mean STD they exhibited was calculated for repetitive stimulation at 5, 10 and 20 Hz under the three aforementioned conditions (Fig. 2). All the changes in amplitude with repetitive stimulation were normalized, and this is how they are reported in this section and represented in the graphics.
For all stimulation frequencies there was less STD in active, oscillating slices than in silent slices (P < 0.02; ANCOVAR). During 5 Hz stimulation (Fig. 2A) there was no depression, and therefore no significant decay in the amplitude of the evoked synaptic potentials in oscillatory, active slices (ANCOVAR test; see Materials and Methods). In contrast, 5 Hz induced-STD in silent slices was significant, where it reached a final value (after 20 s of stimulation) of 0.71 ± 0.16 (Fig. 2A). Stimulation at 10 Hz (Fig. 2B) also induced a significantly larger STD in silent (0.43 ± 0.16 at 20 s) than in active slices (0.77 ± 0.27 at 20 s). STD induced by 5 and 10 Hz in silent slices (‘classical’ and ‘modified’ ACSF) (Fig. 2A,B), were not significantly different (t-test; P < 0.05). Finally, during 20 Hz presynaptic stimulation, the decay of the PSPs amplitude over time was significantly different in the three conditions (ANCOVAR; P < 0.05), with a faster-developing and more prominent depression in silent slices than in active ones; the exact values for each condition are represented in Figure 2C.
Synaptic Depression In Vitro Correlates Inversely with the Degree of Ongoing Rhythmic Activity in the Network
The results presented above suggest that spontaneous ongoing activity in the network may induce a decrease in STD. In order to further explore this possibility, we first correlated the time course of the decrease in STD in active slices to the length of time during which the network had been active with oscillations. We averaged STD across time (Fig. 3A), whereby each value of STD corresponded to the depression at the end of 20 s of repetitive stimulation at 10 Hz. A total of 11 neurons were included, having been recorded in one, two or all three conditions (silent slice in ‘classical’ ACSF, silent slice in ‘modified’ ACSF and active slice in ‘modified’ ACSF) for different periods of time. The average STD in silent slices in ‘classical’ ACSF remained stationary in time and the mean was 0.37 (n = 7) of the normalized control amplitude. STD in neurons that were recorded in silent slices but in ‘modified’ ACSF (n = 4) also remained constant, regardless of the time (up to 110 min) after the solution change (Fig. 3A). The mean value of STD in this condition was 0.43 of the normalized amplitude, which was significantly larger than the one in ‘classical’ ACSF (t-test; P < 0.05) and therefore represents less STD. This observation demonstrates that there was a decrease in STD due to the ionic modification (‘modified’ ACSF), that remained constant once the new situation was stable. The next measures of STD were obtained following different periods of oscillatory activity in the slice, taking as zero the beginning of the organized rhythmic activity (Fig. 3A). Following 10 min of rhythmic activity, the normalized amplitude after the train was already increased to 0.59. There was a progressive decrease in STD over longer periods of activity in the network. For example, at 25 min the normalized amplitude was 0.64, and was 0.73 at 40 min (Fig. 3A). After 40 min of ongoing activity, the degree of depression reached a plateau value that remained constant up to 125 min of activity. Fifteen minutes after silencing the activity by returning to the ‘classical’ solution the original STD value was recovered (Fig. 3A). This result demonstrates that there was a close relation between the onset and development of rhythmic activity and the time course of the decrease in STD.
The relation between cortical network activity and STD was further tested by correlating the STD variation over time with the amount of network activity that occurred in the slice from the moment when spontaneous activity started. Network activity was quantified as the cumulative number of spikes (above a threshold of 2SD of the noise) recorded by a multiunit recording electrode placed in the close vicinity of the intracellularly recorded cell (Fig. 3B). There was a significant relationship (ANCOVAR, P < 0.0001) between amount of activity and decrease in STD until a plateau was reached, meaning that a further increase in activity did not induce a further decrease in STD, which remained constant.
Finally, to substantiate the relationship between decreases in STD and build up of spontaneous activity, we selected four cells: two of them were in slices with very low frequency oscillations (0.05–0.1 Hz) and the other two were in slices with higher (and more common) oscillatory frequencies (0.3–0.5 Hz), in all cases with upstates of similar durations (600 ms; Fig. 3C). Slices with higher frequency of oscillation had therefore more global activity for a given length of time. Time 0 represents the start of oscillatory activity in the slice. Over a period of 100 min, the rate of decrease of STD over time was faster for those synapses in more active slices with respect to those in less active slices. These results confirm that the amount of decrease in synaptic depression is related to the amount of ongoing spontaneous activity in the network.
Synaptic Depression in Thalamocortical and Intracortical Connections In Vivo
Forty-two in vivo intracellular recordings from neurons in the primary visual cortex of the cat were included in this study. Neurons were recorded through all layers and were electrophysiologically characterized according to criteria in (Nowak et al., 2003) as regular spiking (n = 29), chattering (n = 6), intrinsically bursting (n = 4) and fast spiking (n = 1), plus two unclassified cells. In general, the membrane potential of neurons recorded in vivo showed vigorous spontaneous synaptic activity (Figs 4C,D and 5A) that was often organized in slow (<1 Hz) oscillations, as previously reported (Steriade et al., 1993a,b; Pare et al., 1998; Lampl et al., 1999; Sanchez-Vives and McCormick, 2000; Steriade and Timofeev, 2003). Monosynaptic potentials were evoked by electrical stimulation of either thalamocortical (Fig. 4C) or intracortical (Fig. 4D) connections (see Materials and Methods). Thalamocortical (t.c.) connections were activated by electrical stimulation of the LGN (n = 21; latencies, 1.9 ± 0.4 ms; amplitudes, 5.2 ± 1.5 mV; Fig. 4A,C). The stimulating electrode was placed in an area of the LGN with neuronal receptive fields overlapping with the one from the recorded cortical neuron, therefore increasing the probability for monosynaptic connections (Reid and Alonso, 1995). Intracortical (i.c.) connections were activated by electrical stimulation applied in the vicinity (0.5–1.5 mm) of the intracellularly recorded neuron (n = 21; latencies, 1.9 ± 0.3 ms; amplitudes, 4.4 ± 1.9 mV; Fig. 4B,D). Repetitive electrical stimulation at frequencies of 5, 10 or 20 Hz for a period of 20 s induced decreases in the amplitude of the evoked thalamocortical (Fig. 4E) and intracortical (Fig. 4F) synaptic potentials that were larger for higher stimulation frequencies. No significant (P > 0.05) differences were found between the STD exhibited by the thalamocortical and intracortical connections (Fig. 4G).
Synaptic Depression In Vivo in a Silent versus an Active Cortical Network
Although synaptic and suprathreshold spontaneous activity in vivo was usually intense under propofol/sufentanil anesthesia there was a certain variation among recordings (Fig. 5A), probably related to the depth of the anesthesia. In order to silence the cortical network, we induced an even deeper anesthesia by administrating 1–2 ml of a barbiturate (thiopental, 8 mg/ml i.v.). We quantified the amount of ongoing synaptic activity by calculating the SD of the distribution of membrane potential values (Pare et al., 1998; Fig. 5A; see Materials and Methods). The resulting values of SD ranged between 0.15 and 3.75 (n = 42 recordings). We considered activity as low when the SD was below the median of the SD distribution (0.62; n = 21) and as high when it was above (n = 21). Out of the 21 cases with low activity, 11 were recordings in the presence of added barbiturate and 10 corresponded to low spontaneous activity with the usual anesthetic (see Materials and Methods). In some cases, another form of short-term synaptic plasticity, facilitation, occurred during the first 3 s of the high frequency stimulation. No difference related to the activity level was found in the number of neurons that showed facilitation. Thus, for an stimulation of 10 Hz, 6 out of 20 neurons recorded in a silent cortex showed facilitation, while 7 out of 21 recorded in the active cortex did. It is interesting that the time course of facilitation was different (P < 0.05) between both (silent and active) conditions, such that it peaked earlier in the silent cortex (1.8 s) than in the active cortex (2.8 s). The facilitation in both groups was to an amplitude of 121%. Facilitation was found more often in the intracortical (42.8%) than in the thalamocortical (20%) connections.
Short-term depression was found to differ considerably depending on the level of ongoing activity in the cortex in vivo. Population data for repetitive electrical stimulation at 10 Hz in high versus low activity are shown in Figure 5B. STD for thalamocortical and intracortical did not differ significantly, neither in the active (Fig. 4G), nor in the silent (not shown) cortical network. For this reason results from both connections were pooled in one single group. Analysis of covariance then revealed that there was significantly more STD in the silent than in the active cortex (P < 0.001; Fig 5B).
The impact of ongoing synaptic activity on STD is summarized in Figure 5C. At the end of 20 s of 10 Hz stimulation, short-term depression was very similar in silent or low activity cortical networks both in vitro and in vivo (gray columns). The level of depression was also indistinguishable in the oscillating cortical slice and in the active in vivo cortex. Altogether, we can conclude that short-term depression is consistently stronger in a silent than in an active network.
|
Discussion |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Here we have demonstrated that STD of synaptic potentials in the cerebral cortex varies as a function of the spontaneous ongoing activity in the network. We found an inverse correlation over time between the development of slow rhythmic activity in a previously silent cortical slice and the degree of synaptic depression induced by repetitive stimulation, until a plateau of minimal depression was reached. These variation in STD depending on network activity results in less depression in an active than in a silent in vitro cortical network. These findings are in agreement with our results in the anesthetized preparation in vivo, where both thalamocortical and intracortical connections display lesser depression in an active than in a silent cortical or, rather, thalamocortical network.
In vitro studies often report a large STD in most of the connections examined, thalamocortical (Gil et al., 1997; Beierlein and Connors, 2002), as well as for most of the intracortical connections between excitatory neurons (Finlayson and Cynader, 1995; Thomson, 1997; Tsodyks and Markram, 1997; Varela et al., 1997; Galarreta and Hestrin, 1998). Although there are reports indicating synaptic depression of the thalamocortical connection in vivo (Chung et al., 2002), several in vivo studies have reported weak STD, and eventually a replacement of STD by facilitation (Kang et al., 1991; Sanchez-Vives et al., 1998; Boudreau and Ferster, 2003). There are several explanations for these differences between in vivo and in vitro synaptic depression (Sanchez-Vives et al., 1999), including neuronal ionic environment, with lower Ca2+ and Mg2+ and higher K+ in vivo (Hansen, 1985) than those typically used in in vitro studies. Other factors are animal age, since younger animals (commonly used in in vitro studies) have stronger STD (Varela et al., 1997; Angulo et al., 1999; Reyes and Sakmann, 1999), and the existence of neuromodulators in vivo (see below). In the current study we have explored the effect of the presence of ongoing activity in the network, a factor that seems to be important in determining differences in STD in different preparations. We cannot rule out that interactions between postsynaptic neurons could play some role in the reported STD. Although reduced [Ca2+]o should have resulted in a reduced PSP amplitude (Katz and Miledi, 1967; Tsodyks and Markram, 1997), we found no significant difference between the PSPs in the neurons that went through the three conditions (silent cortex in ‘classical’ and ‘modified’ ACSF, and spontaneously active slices). A possible explanation is that the decrease of the PSP amplitude expected from the lowered [Ca2+]o was compensated for by the concomitant lowering of [Mg2+]o (Volgushev et al., 1995). In addition, increasing [K+]o and lowering [Ca2+]o may have resulted in higher excitability of the network, with more axons recruited at the same stimulus intensity. Therefore our results do not imply that unitary PSPs would not have a smaller amplitude in the ‘in vivo like’ or ‘modified’ ACSF. For the rest of the neurons included in the study, possible changes in amplitude of PSPs due to ionic differences could not be evaluated since the intensity of stimulation was adjusted at the beginning of each intracellular recording (see Materials and Methods). However, we did not observe sistematic differences in the intensities that were required to evoke PSPs of similar amplitude.
In this study, we found similar levels of synaptic depression in both thalamocortical and intracortical connections in vivo that varied depending on network activity (Fig. 4G). In vitro studies, on the other hand, describe thalamocortical inputs as showing more STD and paired-pulse depression than intracortical connections (Stratford et al., 1996; Gil et al., 1997). The larger STD exhibited by thalamocortical connections could be attributed to the larger number of release sites and the greater probability of release exhibited by these synapses (Gil et al., 1999). Several differences between the reported in vitro studies and our own could contribute to the discrepancy of this result, such as the cortical area, the animal species and age, the ionic environment or the definition of depression, since we compared depression after 5–20 s of stimulation at high frequencies, while others (Gil et al., 1997) referred to paired pulse depression. On the other hand, the existence of ongoing activity in the in vivo brain has probably affected the steady state of the synaptic connections and altered their plasticity. Finally, in vivo there are neuromodulators that vary with brain states, and these can regulate glutamatergic and gabaergic synaptic transmission (McCormick, 1992; Gil et al., 1997).
One functional consequence of the results presented here is that ongoing spontaneous activity in vivo would permanently maintain synapses in a state of relative depression. Supporting this, there is evidence showing that an increased tonic firing of thalamocortical neurons during activated states decreases the efficacy of thalamocortical bursts to activate the cortex (Swadlow and Gusev, 2001) and that sensory responses are modulated by behavioural states (Fanselow and Nicolelis, 1999). Depending on the level of spontaneous activity, synaptic depression might contribute in different degrees to the dynamic adjustment of the cortical responses to sensory stimulation. One characteristic of sensory responses is adaptation with repetitive stimulation. An example is adaptation to contrast, which has been examined extensively in visual cortex and has been hypothesized to result from synaptic depression of thalamocortical and/or intracortical pathways (Finlayson and Cynader, 1995; Todorov et al., 1997; Carandini et al., 1998; Chance et al., 1998; Adorjan et al., 1999b). According to these results, the role of synaptic depression on adaptation would vary depending on the previous history of firing on the network. Tonically depressed synapses in activated brain states could have other roles such as to allow a more accurate spatial (Castro-Alamancos and Oldford, 2002; Chung et al., 2002) and temporal (Castro-Alamancos, 2002) representations of the sensory inputs.
Synaptic strength has been found to be modulated in the long term depending on the ongoing activity in the network by homeostatic synaptic scaling (Turrigiano et al., 1998; Gil and Amitai, 2000; Desai et al., 2002). Recent studies (Wang et al., 2004) find that in low [Ca2+]o, low activity increases the probability of release, therefore increasing short-term depression in the neuromuscular junction. Through synaptic scaling, network activity may also be regulating information processing in the adult cortex in vivo. Our data in the active slices and in the anesthetized animal suggest that activity causes short-term tuning of synaptic plasticity. Higher rates of activity in the alert state should induce a different steady state in cortical synapses, and therefore affect cortical processing.
|
Acknowledgments |
|---|
We thank M. Slater for his help in the data analysis, D.A. McCormick and J. Bullier for their participation on in vivo preliminary experiments, and A. Compte for helpful discussions. This work has been sponsored by Human Frontiers Science Program Organization and MCYT (BFI2002-03643) to M.V.S.-V. L.G.N. was supported by the CNRS and by the Ministry of Foreign Affairs (Egide, ‘Picasso’ travel grant). R.R. was supported in part by a fellowship CSIC-Bancaja.
|
References |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Abbott LF, Varela JA, Sen K, Nelson SB (1997) Synaptic depression and cortical gain control. Science 275:221–224.
Adorjan P, Levitt JB, Lund JS, Obermayer K (1999a) A model for the intracortical origin of orientation preference and tuning in macaque striate cortex. Vis Neurosci 16:303–318.[CrossRef][Web of Science][Medline]
Adorjan P, Piepenbrock C, Obermayer K (1999b) Contrast adaptation and infomax in visual cortical neurons. Rev Neurosci 10:181–200.[Web of Science][Medline]
Aghajanian GK, Rasmussen K (1989) Intracellular studies in the facial nucleus illustrating a simple new method for obtaining viable motoneurons in adult rat brain slices. Synapse 3:331–338.[CrossRef][Web of Science][Medline]
Angulo MC, Staiger JF, Rossier J, Audinat E (1999) Developmental synaptic changes increase the range of integrative capabilities of an identified excitatory neocortical connection. J Neurosci 19:1566–1576.
Beierlein M, Connors BW (2002) Short-term dynamics of thalamocortical and intracortical synapses onto layer 6 neurons in neocortex. J Neurophysiol 88:1924–1932.
Boudreau CE, Ferster D (2003) Synaptic depression in thalamocortical synapses of the cat visual cortex. Soc Neurosci Abstr 484.11.
Carandini M, Movshon JA, Ferster D (1998) Pattern adaptation and cross-orientation interactions in the primary visual cortex. Neuropharmacology 37:501–511.[CrossRef][Web of Science][Medline]
Castro-Alamancos MA (2002) Different temporal processing of sensory inputs in the rat thalamus during quiescent and information processing states in vivo. J Physiol (Lond) 539:567–578.
Castro-Alamancos MA, Connors BW (1996) Spatiotemporal properties of short-term plasticity sensorimotor thalamocortical pathways of the rat. J Neurosci 16:2767–2779.
Castro-Alamancos MA, Oldford E (2002) Cortical sensory suppression during arousal is due to the activity-dependent depression of thalamocortical synapses. J Physiol (Lond) 541:319–331.
Chance FS, Nelson SB, Abbott LF (1998) Synaptic depression and the temporal response characteristics of V1 cells. J Neurosci 18:4785–4799.
Chung S, Li X, Nelson SB (2002) Short-term depression at thalamocortical synapses contributes to rapid adaptation of cortical sensory responses in vivo. Neuron 34:437–446.[CrossRef][Web of Science][Medline]
Crochet S, Chauvette S, Boucetta S, Timofeev I (2005) Modulation of synaptic transmission in neocortex by network activities. Eur J Neurosci 21:1030–1044.[CrossRef][Web of Science][Medline]
Desai NS, Cudmore RH, Nelson SB, Turrigiano GG (2002) Critical periods for experience-dependent synaptic scaling in visual cortex. Nat Neurosci 5:783–789.[Web of Science][Medline]
Dobrunz LE, Stevens CF (1997) Heterogeneity of release probability, facilitation, and depletion at central synapses. Neuron 18:995–1008.[CrossRef][Web of Science][Medline]
Fanselow EE, Nicolelis MA (1999) Behavioral modulation of tactile responses in the rat somatosensory system. J Neurosci 19:7603–7616.
Finlayson PG, Cynader MS (1995) Synaptic depression in visual cortex tissue slices: an in vitro model for cortical neuron adaptation. Exp Brain Res 106:145–155.[Web of Science][Medline]
Fuentealba P, Crochet S, Timofeev I, Steriade M (2004) Synaptic interactions between thalamic and cortical inputs onto cortical neurons in vivo. J Neurophysiol 91:1990–1998.
Galarreta M, Hestrin S (1998) Frequency-dependent synaptic depression and the balance of excitation and inhibition in the neocortex. Nat Neurosci 1:587–594.[CrossRef][Web of Science][Medline]
Gil Z, Amitai Y (2000) Evidence for proportional synaptic scaling in neocortex of intact animals. Neuroreport 11:4027–4031.[Web of Science][Medline]
Gil Z, Connors BW, Amitai Y (1997) Differential regulation of neocortical synapses by neuromodulators and activity. Neuron 19:679–686.[CrossRef][Web of Science][Medline]
Gil Z, Connors BW, Amitai Y (1999) Efficacy of thalamocortical and intracortical synaptic connections: quanta, innervation, and reliability. Neuron 23:385–397.[CrossRef][Web of Science][Medline]
Hansen AJ (1985) Effect of anoxia on ion distribution in the brain. Physiol Rev 65:101–148.
Jones MV, Westbrook GL (1996) The impact of receptor desensitization on fast synaptic transmission. Trends Neurosci 19:96–101.[CrossRef][Web of Science][Medline]
Kang Y, Endo K, Araki T (1991) Differential connections by intracortical axon collaterals among pyramidal tract cells in the cat motor cortex. J Physiol 435:243–256.
Katz B, Miledi R (1967) Ionic requirements of synaptic transmitter release. Nature 215:651.[CrossRef][Medline]
Lampl I, Reichova I, Ferster D (1999) Synchronous membrane potential fluctuations in neurons of the cat visual cortex. Neuron 22:361–374.[CrossRef][Web of Science][Medline]
McCormick DA (1992) Neurotransmitter actions in the thalamus and cerebral cortex and their role in neuromodulation of thalamocortical activity. Prog Neurobiol 39:337–388.[CrossRef][Web of Science][Medline]
Nowak LG, Azouz R, Sanchez-Vives MV, Gray CM, McCormick DA (2003) Electrophysiological classes of cat primary visual cortical neurons in vivo as revealed by quantitative analyses. J Neurophysiol 89:1541–1566.
Pare D, Shink E, Gaudreau H, Destexhe A, Lang EJ (1998) Impact of spontaneous synaptic activity on the resting properties of cat neocortical pyramidal neurons in vivo. J Neurophysiol 79:1450–1460.
Reid RC, Alonso JM (1995) Specificity of monosynaptic connections from thalamus to visual cortex. Nature 378:281–284.[CrossRef][Medline]
Reyes A, Sakmann B (1999) Developmental switch in the short-term modification of unitary EPSPs evoked in layer 2/3 and layer 5 pyramidal neurons of rat neocortex. J Neurosci 19:3827–3835.
Sanchez-Vives MV, McCormick DA (2000) Cellular and network mechanisms of rhythmic recurrent activity in neocortex. Nat Neurosci 3:1027–1034.[CrossRef][Web of Science][Medline]
Sanchez-Vives MV, Nowak LG, McCormick DA (1998) Is synaptic depression prevalent in vivo and does it contribute to contrast adaptation? Soc Neurosci Abstr 24:896.
Sanchez-Vives MV, Nowak LG, McCormick DA (1999) Why might cortical synaptic depression be lesser in vivo than in vitro? Soc Neurosci Abstr 25:2191.
Sanchez-Vives MV, Nowak LG, McCormick DA (2000) Membrane mechanisms underlying contrast adaptation in cat area 17 in vivo. J Neurosci 20:4267–4285.
Sanderson KJ (1971) The projection of the visual field to the lateral geniculate and medial interlaminar nuclei in the cat. J Comp Neurol 143:101–108.[CrossRef][Web of Science][Medline]
Steriade M, Timofeev I (2003) Neuronal plasticity in thalamocortical networks during sleep and waking oscillations. Neuron 37:563–576.[CrossRef][Web of Science][Medline]
Steriade M, Nunez A, Amzica F (1993a) Intracellular analysis of relations between the slow (<1 Hz) neocortical oscillation and other sleep rhythms of the electroencephalogram. J Neurosci 13:3266–3283.[Abstract]
Steriade M, Nunez A, Amzica F (1993b) A novel slow (<1 Hz) oscillation of neocortical neurons in vivo: depolarizing and hyperpolarizing components. J Neurosci 13:3252–3265.[Abstract]
Stratford KJ, Tarczy-Hornoch K, Martin KA, Bannister NJ, Jack JJ (1996) Excitatory synaptic inputs to spiny stellate cells in cat visual cortex. Nature 382:258–261.[CrossRef][Medline]
Swadlow HA, Gusev AG (2001) The impact of ‘bursting’ thalamic impulses at a neocortical synapse. Nat Neurosci 4:402–408.[CrossRef][Web of Science][Medline]
Thomson AM (1997) Activity-dependent properties of synaptic transmission at two classes of connections made by rat neocortical pyramidal axons in vitro. J Physiol 502:131–147.
Thomson AM, Deuchars J (1994) Temporal and spatial properties of local circuits in neocortex. Trends Neurosci 17:119–126.[CrossRef][Web of Science][Medline]
Thomson AM, West DC, Wang Y, Bannister AP (2002) Synaptic connections and small circuits involving excitatory and inhibitory neurons in layers 2–5 of adult rat and cat neocortex: triple intracellular recordings and biocytin labelling in vitro. Cereb Cortex 12:936–953.
Todorov EV, Sapas AG, Somers DC, Nelson SB (1997) Modeling visual cortical contrast adaptation effects. In: Computational neuroscience, trends in research (Bower JM, ed.), pp. 525–531. Kluwer Academic.
Tsodyks MV, Markram H (1997) The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability. Proc Natl Acad Sci USA 94:719–723.
Turrigiano GG, Leslie KR, Desai NS, Rutherford LC, Nelson SB (1998) Activity-dependent scaling of quantal amplitude in neocortical neurons. Nature 391:892–896.[CrossRef][Medline]
Varela JA, Sen K, Gibson J, Fost J, Abbott LF, Nelson SB (1997) A quantitative description of short-term plasticity at excitatory synapses in layer 2/3 of rat primary visual cortex. J Neurosci 17:7926–7940.
Volgushev M, Voronin LL, Chistiakova M, Artola A, Singer W (1995) All-or-none excitatory postsynaptic potentials in the rat visual cortex. Eur J Neurosci 7:1751–1760.[CrossRef][Web of Science][Medline]
Wang X, Engisch KL, Li Y, Pinter MJ, Cope t.c., Rich MM (2004) Decreased synaptic activity shifts the calcium dependence of release at the mammalian neuromuscular junction in vivo. J Neurosci 24:10687–10692.
Zucker RS (1989) Short-term synaptic plasticity. Annu Rev Neurosci 12:13–31.[CrossRef][Web of Science][Medline]
Zucker RS, Regehr WG (2002) Short-term synaptic plasticity. Annu Rev Physiol 64:355–405.[CrossRef][Web of Science][Medline]
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  J. A. M. Lorteije, S. I. Rusu, C. Kushmerick, and J. G. G. Borst Reliability and Precision of the Mouse Calyx of Held Synapse J. Neurosci., November 4, 2009; 29(44): 13770 - 13784. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. R. Stoelzel, Y. Bereshpolova, A. G. Gusev, and H. A. Swadlow The Impact of an LGNd Impulse on the Awake Visual Cortex: Synaptic Dynamics and the Sustained/Transient Distinction J. Neurosci., May 7, 2008; 28(19): 5018 - 5028. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. I. Chelaru and V. Dragoi Asymmetric Synaptic Depression in Cortical Networks Cereb Cortex, April 1, 2008; 18(4): 771 - 788. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Hasenstaub, R. N. S. Sachdev, and D. A. McCormick State Changes Rapidly Modulate Cortical Neuronal Responsiveness J. Neurosci., September 5, 2007; 27(36): 9607 - 9622. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||