spike frequency adaptation is developmentally regulated in substantia nigra pars compacta...
TRANSCRIPT
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Neuroscience 192 (2011) 1–10
SPIKE FREQUENCY ADAPTATION IS DEVELOPMENTALLYREGULATED IN SUBSTANTIA NIGRA PARS COMPACTA
DOPAMINERGIC NEURONSM. VANDECASTEELE, J.-M. DENIAU AND L. VENANCE*
Laboratory of Dynamics and Pathophysiology of Neuronal Networks,CIRB, INSERM-U1050, CNRS-UMR7241, Collège de France, Paris,France
Abstract—Dopaminergic neurons of the substantia nigra parscompacta play a key role in the modulation of basal gangliaand provide a reward-related teaching signal essential for ad-aptative motor control. They are generally considered as a ho-mogenous population despite several chemical and electro-physiological heterogeneities, which could underlie differentpreferential patterns of activity and/or different roles. Usingwhole-cell patch-clamp recordings in juvenile rat brain slices,we observed that the evoked activity of dopaminergic neuronsdisplays variable spike frequency adaptation patterns. The in-tensity of spike frequency adaptation decreased during post-natal development. The adaptation was associated with an in-crease in the initial firing frequency due to faster kinetics of theafterhyperpolarization component of the spike. Adaptation wasenhanced when small conductance calcium-activated potas-sium (SK) channels were blocked with bath application ofapamine. Lastly, spike frequency adaptation of the evoked dis-charge was associated with more irregularity in the spontane-ous firing pattern. Altogether these results show a developmen-tal heterogeneity and electrophysiological maturation of sub-stantia nigra dopaminergic neurons. © 2011 IBRO. Published byElsevier Ltd. All rights reserved.
Key words: dopaminergic neuron, substantia nigra pars com-pacta, SK current, spike frequency adaptation, post-natal de-velopment, in vitro electrophysiology.
The substantia nigra pars compacta (SNc) constitutes themain modulatory nucleus of basal ganglia, a network ofsubcortical nuclei involved in procedural learning and mo-tor habit formation (Gerfen, 1992; Graybiel, 1995, 2005;Yin and Knowlton, 2006). Dopaminergic neurons compos-ing SNc mainly project to the dorsal striatum, the majorinput nucleus of basal ganglia. In striatum, dopamine po-tently modulates the processing of corticostriatal informa-tion (Reynolds and Wickens, 2002; Arbuthnott and Wick-ens, 2007), contributing to the formation of sensory-motorlinkages allowing selection of adapted motor behavior inresponse to environmental cues. The consequence of the
*Corresponding author. Tel: �33-1-44-27-12-26; fax: �33-1-44-27-12-60.-mail address: [email protected] (L. Venance).bbreviations: AHP, afterhyperpolarization; AP, action potential;
AHP, fast afterhyperpolarization; Ffinal, final instantaneous firing fre-quency; Finit, initial instantaneous firing frequency; Ih, hyperpolariza-tion-activated depolarizing current; ISI, interspike interval; SFA, spike
frequency adaptation; SK, small conductance calcium-activated potas-sium; SNc, substantia nigra pars compacta.0306-4522/11 $ - see front matter © 2011 IBRO. Published by Elsevier Ltd. All righdoi:10.1016/j.neuroscience.2011.07.017
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degeneration of nigrostriatal dopaminergic neurons, lead-ing to Parkinson’s disease, highlights their crucial impor-tance in striatal cognitive and motor functions.
Nigrostriatal dopaminergic neurons display differentmodes of discharge: single-spike firing associated with alow dopamine release supporting a permanent tune-up ofthe striatal network, and a phasic firing leading to peaks ofdopamine release, coding for a predictive reward valueand attention to salient environmental events (Gonon,1988; Venton et al., 2003; Schultz, 2004; Redgrave andGurney, 2006). Moreover, single-spike firing varies frompacemaker-like to highly irregular activity (Tepper et al.,1990; Hyland et al., 2002). The knowledge of the mecha-nisms controlling these dopaminergic neuron activity pat-terns is fundamental to understand the spatiotemporalproperties of striatal dopamine release and its functionalconsequences. These mechanisms include dopaminergicmembrane properties, local interactions and afferents(Grace and Bunney, 1984a,b; Pucak and Grace, 1994;Overton and Clark, 1997; Grillner and Mercuri, 2002;Komendantov and Canavier, 2002; Floresco et al., 2003),which might not be homogenous across the dopaminergicpopulation. Indeed, dopaminergic neurons display severalheterogeneities concerning electrophysiological character-istics (Gu et al., 1992; Hajós and Greenfield, 1993; Neuhoffet al., 2002), connectivity and local interactions (Fallon andMoore, 1978; Grace and Onn, 1989; Gauthier et al., 1999;Vandecasteele et al., 2005, 2007, 2008), and expressionof receptors, channels and peptides (Seroogy et al., 1988;Chen et al., 2001; Vandecasteele et al., 2006). Such het-erogeneities might therefore underlie different dopaminer-gic neuron discharge properties.
In this study, we have investigated the spiking patternof SNc dopaminergic neurons recorded by patch-clamp inrat brain slices. We have observed variable spike fre-quency adaptation (SFA) patterns (from regular spiking toadapting) among dopaminergic neurons. The intensity ofSFA decreases along development towards regular spik-ing patterns. Analysis of the spike trains components re-vealed that SFA is caused by faster afterhyperpolarization(AHP) kinetics in the first action potentials (APs) of thetrain. Consistently, SFA pattern was accentuated whensmall conductance calcium-activated potassium (SK)channels were blocked with bath application of apamine.Lastly, these spiking patterns observed during evoked ac-tivity were found to correlate with differences in the regu-
larity of spontaneous tonic activity.ts reserved.
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EXPERIMENTAL PROCEDURES
In vitro slice preparation
Coronal brain slices were prepared from Sprague–Dawley rats ofboth sexes (postnatal days 6–17). Animals were killed by decap-itation, in accordance with local Ethical Committee and EU guide-lines (directive 86/609/EEC). Brain slices (330 �m) were cut usinga vibrating microslicer (Leica VT1000S, Nussloch, Germany).Slices were subsequently incubated 45 min at 34 °C, in an extra-cellular solution containing (mM): 125 NaCl, 2.5 KCl, 25 glucose,25 NaHCO3, 1.25 NaH2PO4, 2 CaCl2, 1 MgCl2 and 1 pyruvic acidsodium salt) bubbled with 95% O2 and 5% CO2 before electro-
physiological recordings.
Electrophysiological recordings
Whole-cell recordings were performed, as previously described(Vandecasteele et al., 2005, 2008), using borosilicate glass pi-pettes containing (mM): 105 K-gluconate, 30 KCl, 10 HEPES, 10phosphocreatine, 4 ATP-Mg, 0.3 GTP-Na, 0.3 EGTA (adjusted topH 7.35 with KOH), or 0.1 EGTA when indicated. The compositionof the extracellular solution was (mM): 125 NaCl, 2.5 KCl, 25glucose, 25 NaHCO3, 1.25 NaH2PO4, 2 CaCl2, 1 MgCl2, 10 �Mpyruvic acid (sodium salt) bubbled with 95% O2 and 5% CO2. Allecordings were performed at 34 °C using a temperature controlystem (Luigs and Neumann, Ratingen, Germany) and slicesere continuously superfused at 2–3 ml/min with the extracellularolution. Neurons were identified using infrared-differential inter-erence contrast microscopy with CCD camera (Hamamatsu2400-07; Hamamatsu, Japan). Signals were amplified using anPC10-2 amplifier (HEKA Elektronik, Lambrecht, Germany). Cur-
ent-clamp recordings were filtered at 2.5 kHz and sampled at 5Hz while voltage-clamp recordings were filtered at 5 kHz andampled at 10 kHz using the program Pulse-8.65 (HEKA Elek-ronik). All chemicals were purchased from Sigma (St-Quentin,rance).
Data analysis
Off-line analysis was performed using PulseFit-8.65 (HEKA Elek-tronik) and Igor Pro (Wavemetrics, Lake Oswego, OR, USA). Allresults were expressed as mean�standard error of mean andstatistical significance was assessed using the Student t-test, orthe nonparametric Mann–Whitney test when appropriate, at thesignificance level (P) indicated. AP threshold was measured asfollows: dopaminergic neurons were first clamped to �60 mV andsuccessive depolarization steps (10 pA steps) were applied untilthe first AP, on which the threshold was then measured. Inputresistance was calculated from the steady state of voltage re-sponses obtained after injecting a hyperpolarizing current (�10pA; 1 s duration). Sag amplitude was measured from voltageresponses obtained after injecting a hyperpolarizing current (�90pA; 1 s duration, cell being previously held at �60 mV), betweenthe potential at sag peak (closed square or triangle in Fig. 2A) andthe potential at steady state (open square or triangle in Fig. 2A).Spike duration was measured between the onset of the spike andthe equipotential point during the repolarization phase. Fast afte-rhyperpolarization (fAHP) amplitude was taken between this lastpoint and the trough of the AHP. The slow AHP was definedbetween the trough of the AHP and the next point equipotential tothe onset of the spike. SFA was calculated for each cell using theformula: SFA ratio�Finit/Ffinal, where Finit is the initial instanta-eous spike frequency (1/first interspike interval) and Ffinal is the
instantaneous frequency calculated from the last interspike inter-val. A neuron exhibiting no SFA (Finit�Ffinal) and one showingadaptation would have an SFA ratio of 1 and �1, respectively(Venance and Glowinski, 2003). For each neuron, the adaptationratio was estimated for a depolarizing stimulation of �40 pA above
spike threshold during 1 s.Biocytin filling and immunohistochemistry
Biocytin (Sigma) 5 mg/ml was dissolved in the pipette solution andcells were filled during at least 45 min of recording. Subsequently,slices were fixed overnight in 2% paraformaldehyde at 4 °C.Biocytin-filled cells were visualized using the avidin-HRP reaction(ABC Elite peroxidase kit; Vector Laboratories, Burlingame, CA,USA) according to the instructions of the manufacturer, or strepta-vidin-alexa488 (Invitrogen, Carlsbad, CA, USA), incubated 2 h atRT. Tyrosine hydroxylase immunostaining was performed by in-cubation of the slices in a 1/400 diluted mouse anti-(tyrosinehydroxylase) monoclonal antibody (Chemicon International, Te-mecula, CA, USA) overnight at 4 °C. Goat anti-rabbit secondaryantibody, coupled to TRITC (Southern Biotechnology, Birming-ham, AL, USA) was incubated at dilution 1/200 for 2 h at roomtemperature.
RESULTS
Dopaminergic neurons of the SNc (n�155), recorded bywhole-cell patch-clamp at 34 °C in coronal rat brain slices(P6-22) were identified by their morphological and electro-physiological characteristics (Fig. 1A) (Vandecasteele etal., 2005, 2008). Briefly, dopaminergic neurons displayedan hyperpolarization-activated depolarizing current (Ih cur-rent) (�21.1�2.0 mV in response to a current injection of�90 pA during 1 s) followed by a depolarizing rebound atthe stimulus offset (11.3�1.0 mV), a depolarized firingthreshold (�36.4�0.4 mV), a long duration AP (5.6�0.1ms) followed by a pronounced AHP (18.7�0.8 mV), and aslow regular spontaneous firing activity (3.7�0.4 Hz)(measured from 39 neurons). In a subset of experiments(n�11), dopaminergic phenotype of recorded neurons wasconfirmed by double immunohistochemistry staining forbiocytin injected through the recording pipette and tyrosinehydroxylase (Fig. 1B).
Spike frequency adaptation among dopaminergicneurons
Close analysis of the evoked AP firing during application ofdepolarizing current steps revealed heterogeneity in spikefrequency patterns. For each neuron, the adaptation ratiowas estimated as the ratio of the initial over the finalinstantaneous frequencies for a depolarizing stimulation of�40 pA above spike threshold during 1 s. The SFA ratiovalues in a dopaminergic population (Fig. 1C) did notexhibit a Gaussian distribution, but continuously variedfrom more regular to more adapting patterns. It should benoted that neurons exhibited a constant SFA ratio duringrepetitive depolarization. Since the SFA ratio distributiondid not display obvious bimodality, the choice of an SFAratio threshold for classifying the neurons in each categorywould be arbitrary. Therefore, for most of the analysis weused either correlations of the SFA ratio with the parameterstudied, or else, we compared subsets of 15 highly adapt-ing (SFA ratio�2.5) vs. 15 clearly regular spiking (SFAratio�1.02) dopaminergic neurons.
No significant difference was found in current-voltagerelationships (Fig. 2A), whether measured at the sag peakor at the steady state, for subsets of dopaminergic neuronschosen at each end of the SFA continuum (SFA ra-
tio�1.02, n�15 vs. SFA ratio�2.5, n�15). The input re-
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sistance of individual dopaminergic neurons (406�15 M�,n�122 neurones) was not significantly (P�0.1, Spear-man’s rank test) correlated to their SFA ratio (Fig. 2B). Thissuggests a lack of relationship between the SFA ratio andpassive membrane properties. Furthermore, the rheo-bases were not significantly different (�37�8 pA in neu-rons with SFA�1.02, �33�7 pA in neurons with SFA�2.5,n�15 in each group), indicating that the difference in ad-aptation patterns did not result from differences in excit-ability. The depolarization-activated hyperpolarizing cur-rent Ih current is also involved in dopaminergic neuronspike firing regulation, at least in a subset of dopaminergicneurons (Seutin et al., 2001; Neuhoff et al., 2002). How-ever, the absence of correlation observed between Ih am-plitude (evoked by a �90 pA, 1 s hyperpolarizing stimula-tion) and SFA ratio (P�0.05) (Fig. 2C) suggests that Ih isnot involved in dopaminergic neuron SFA. Lastly, wetested lowering the EGTA concentration in the intracellularsolution to 0.1 mM (Wolfart et al., 2001). Similar distribu-tion of SFA ratio was observed (Fig. 2D). Neurons re-corded in both conditions displayed similar mean SFAratios (1.62�0.06 in 0.3 mM EGTA vs. 1.62�0.2 in 0.1 mM
Fig. 1. Evoked activity in dopaminergic neurons display various spdopaminergic neurons. Typical responses of dopaminergic neuronsImmunohistochemical identification of dopaminergic neurons: identithydroxylase, a specific marker of dopaminergic neurons (red), and bioratios among dopaminergic neurons (n�128) display a non-gaussian dreader is referred to the Web version of this article.
EGTA), and their median SFA ratios were not statistically t
different (1.49 vs. 1.28, respectively, P�0.24, Mann–Whit-ney test).
SFA patterns along post-natal development
As dopaminergic neurons undergo an electrophysiologicalmaturation during the first post-natal weeks (Tepper et al.,1990; Mangin et al., 2002), we investigated the evolution ofSFA during post-natal development. The distribution ofdopaminergic neuron SFA ratio according to the age of theanimals (Fig. 3A) showed that the adapting pattern wasover-represented for rats younger than P12. A separatenalysis of P6-11 and P12-22 animals (Fig. 3B) revealed thatlder rats displayed a Gaussian distribution of dopaminer-ic neuron SFA ratio centered around 1.08, with only 14%f neurons displaying an SFA ratio over 1.5 (5 out of 37eurons), while in younger animals SFA ratio values werecattered between 0.8 and 4.1, and 63% of neurons (57ut of 91 neurons) displayed an SFA ratio higher than 1.5.he difference of proportions of neurons with an SFA ratiover 1.5 between the two age groups was statisticallyignificant (P�0.0001, Fischer’s exact test). In addition,
uency adaptation patterns. (A) Electrophysiological identification ofnt injections (�90 to �40 pA), displaying variable SFA ratios. (B)rded cells was confirmed by double immunoreactivity for tyrosineted through the patch pipette (green). (C) Spike frequency adaptation
n. For interpretation of the references to color in this figure legend, the
ike freqto curre
y of recocytin injec
he mean SFA ratio in P12-22 animals was 50% higher than
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M. Vandecasteele et al. / Neuroscience 192 (2011) 1–104
the SFA ratio observed in younger animals (1.79�0.07,n�91, vs. 1.19�0.05, n�37, respectively, P�0.0001). Al-though the P11-12 limit is a choice based on the distributionin Fig. 3, the comparison of these two age groups showsan evolution of the SFA patterns, suggesting that dopami-nergic neurons mature towards more regular spiking pat-terns.
SFA is underlied by differences in sAHP kinetics
SFA can reflect either an increase of the initial instanta-neous frequency (Finit), or a decrease of the final instan-taneous frequency (Ffinal). Correlation analysis of Finit andSFA ratio, and of Ffinal and SFA ratio (Fig. 4A) showed that
FA ratio linearly increased with Finit, (r2�0.76, P�0.0001,n�121) but was poorly correlated to Ffinal (r2�0.05,
�0.01, n�121). Therefore, SFA arises from a highernstantaneous firing frequency, which decreases along therain down to a final value that is similar to that of regulareurons.
We analyzed the parameters that could explain the
Fig. 2. Spike frequency adaptation is independent from passive memmarkers) and at the steady state (closed markers) in dopaminergic neuDifferences are not significant. The inset shows where the sag peakinjection of a �10 pA, 1 s current in a dopaminergic neuron maintainircles represent individual neurons (n�122). (C) The amplitude ofopaminergic neuron maintained at �60 mV) displays no correlationopaminergic neurons recorded in 0.1 mM intracellular EGTA (n�27
ecorded in 0.3 mM EGTA (n�128, grey bars).
ecreasing firing frequency along the spike train. Indeed,
his increase in interspike interval duration could resultrom an increased AHP duration (due either to an in-reased amplitude or to slower kinetics), or to an elevationf the spike threshold at the end of the spike train.
We measured these characteristics for the first and theast interspike interval in 30 dopaminergic neurons, chosent each end of the SFA continuum (SFA ratio�1.02, n�15
vs. SFA ratio�2.5, n�15). Superimposition of the first andthe last spike of the train in an example of regular (SFAratio�1.0) and adapting (SFA ratio�2.9) showed that thespike and the AHP kinetics were constant in the regular butnot in the adapting neuron cell (Fig. 4B1). It should benoted that the waveform of the last spike of the train wassimilar in both cells (Fig. 4B2). Quantitative analysis ofAHP parameters (Fig. 4C) showed that the duration of thetwo AHP components (fast, hyperpolarizing component:fAHP, and slow, repolarizing component: sAHP) during thefirst interspike interval was significantly reduced in neuronswith an SFA ratio�2.5, compared to those with an SFAratio�1.02. During the spike train, fAHP and sAHP dura-
operties or Ih. (A) I–V relationships measured at the sag peak (openSFA ratio�2.5 (squares) vs. neurons with SFA ratio�1.02 (triangles).
ady state were measured. (B) The input resistance (measured after0 mV) is not correlated to the spike frequency adaptation ratio. Openduced sag (measured after injection of a �90 pA, 1 s current in a
adaptation ratio. Circles represent individual neurons (n�100). (D)distribution of their adaptation ratio (open bars) similar to neurons
brane prrons withand ste
ed at �6the Ih-inwith the
tions increased significantly in more adapting neurons,
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M. Vandecasteele et al. / Neuroscience 192 (2011) 1–10 5
reaching values similar to those of more regular spikingneurons for the last interspike interval. This increase infAHP and sAHP duration was due both to an increase intheir amplitude and to a decrease in the absolute value oftheir slope. Lastly, the increase in fAHP and sAHP ampli-tude was not caused by an elevation of the spike threshold,which was similar for the first and the last interspike inter-val. Besides, it should be noted that parameters measuredfor the last interspike interval did not display any significantdifference between the two patterns. Altogether, theseresults show that SFA in dopaminergic neurons is due tochanges in the AHP characteristics of the first AP of thetrain.
Dopaminergic neurons AHP largely depends on the SKcurrent (Wolfart et al., 2001; Wolfart and Roeper, 2002;Waroux et al., 2005). We investigated the involvement ofthis current in SFA by bath application of the selective SKblocker, apamine (100–300 nM). SFA ratio was signifi-cantly increased (�116�65%, P�0.05 Wilcoxon’s pairedtest, n�7 dopaminergic neurons) when SK currents wereblocked by apamine treatment (Fig. 5A, B). Therefore, SKcurrent appears to counteract the SFA phenomenon,which is consistent with their involvement in the regularityof dopaminergic neuron spontaneous discharge (Wolfart etal., 2001; Waroux et al., 2005). The intensity of the SKcurrent results from the density of SK channel expression,as well as the calcium influx that activates them. We there-
Fig. 3. Spike frequency adaptation decreases along post-natal devel-opment. (A) The adaptation ratio of dopaminergic neurons (n�128) isplotted against the age of the animal. Dashed line indicates meanvalues for P6-11 and P12-22 rats. (B) Adaptation ratio distribution in P6-11
(grey bars) and P12-22 rats (open bars). The dashed line indicates theaussian fit for P12-22 rats.
fore wondered whether the difference in AHP and SFA c
were due to either or both hypothesis. To analyze AHPcurrents in a more controlled and quantitative manner, weused the hybrid clamp method (Lancaster and Adams,1986; Wolfart et al., 2001). The neuron is first depolarizedfrom �80 to �60 mV for 100 ms in current clamp to inducenclamped spikes, and then switched back to �80 mV inoltage clamp (Fig. 5C). Since Finit was mainly responsible
for SFA, the duration of the depolarization was restricted to100 ms, corresponding to the beginning of a spike train.We observed a significant negative correlation of the AHPcurrent amplitude with the SFA ratio (Spearman’sr��0.65, P�0.016, n�12), suggesting that a difference inexpression or recruitment of SK channels participates inthe SFA phenotype.
Correlation between spontaneous and evokedactivity patterns
We investigated whether the variable SFA pattern ob-served in dopaminergic neuron evoked activity was asso-ciated with differences in the pattern of their tonic activity.Tonic activity, characterized by low frequency non-burstyfiring, is displayed spontaneously in slices in a very regu-lar, pacemaker-like pattern. Correlation analysis of spon-taneous activity characteristics vs. SFA ratio performed in26 neurons (Fig. 6) showed that the mean and the stan-dard deviation of the spontaneous firing frequency werenot affected by the SFA. However, the coefficient of vari-ation of spontaneous interspike intervals significantly in-creased with the SFA ratio measured on evoked activity(Spearman’s r�0.6656, P�0.001), indicating that the reg-ularity of evoked and spontaneous spiking patterns arecorrelated.
DISCUSSION
In this study, we show that SNc dopaminergic neuronsrecorded in juvenile rat brain slices display heterogeneousspiking patterns, from regular to adapting. SFA is due to ahigher initial instantaneous frequency, associated with asmaller and slower AHP in the first spikes of the train.Consistently, blockade of the AHP current SK by apamineincreases SFA. Finally, we observed a correlation betweenthe regularity of evoked and spontaneous activity patterns.
The decreased initial AHP current associated with SFAis not likely to arise only from differences in calcium cur-rents or buffering dynamics, since it is also observablewhen tested using the hybrid clamp protocol. Alternatehypothesis include differences in expression of SK3 chan-nels, and in the modulation of their gating. The evolution ofSFA magnitude along development suggests that the dif-ferent patterns observed here reflect less the existence ofdistinct dopaminergic neuron sub-populations than dopa-minergic neurons at different stages of their maturationprocess. Therefore expression and/or gating of the SKcurrent could be progressively established during the firsttwo post-natal weeks, participating in the maturation ofdopaminergic neuron firing activity observed in vitro(Mereu et al., 1997) and in vivo (Tepper et al., 1990). The
ontinuous distribution of SFA ratios also points more to-
sdl
M. Vandecasteele et al. / Neuroscience 192 (2011) 1–106
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Fig. 4. Components of the AP involved in spike frequency adaptation. (A) The adaptation ratio linearly and significantly increases with the initialinstantaneous frequency of discharge (left), but is weakly correlated with the final instantaneous frequency of discharge (right) (n�133 neurons). (B)Comparison of the first (continuous line) and last (dashed line) APs in a train of spikes, in a regular spiking (SFA ratio�1.0, black traces) and a highlyadapting (SFA ratio�2.9, red traces) neuron. (B1) Superimposition of the first and the last interspike interval of the train reveals that their waveformsare similar in the regular spiking neuron (upper panel), contrarily to the highly adapting neuron where the last interspike interval shows a much longerAHP than the first (lower panel). (B2) Superimposition of the first spike of the train from a regular and an adapting neuron shows different waveforms,with a longer AHP in the regular neuron (upper panel), while the superimposition of the last interspike interval of the train of each type of neuron revealssimilar waveforms (lower panel). (C) Quantitative comparisons of the spike components in the first and last interspike intervals in (black triangles: SFAratio �1.02, n�15, and open squares: SFA ratio �2.5, n�15) neurons. (�) indicates a significant difference (P�0.01) between the first and the lastpike in higher SFA neurons (neurons with lower SFA ratio did not display any significant difference in the parameters studied). # indicates a significant
ifference (P�0.01) between neurons with higher SFA ratio and those with lower SFA ratio. For interpretation of the references to color in this figureegend, the reader is referred to the Web version of this article.
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M. Vandecasteele et al. / Neuroscience 192 (2011) 1–10 7
wards a progressive maturation in adaptation phenotypethan an abrupt switch, and the age groups defined in thisstudy are intended for analytical purposes more thanstrongly defined windows of maturation. However, consid-ering the apoptotic events occurring in SNc between P10
and P15 (Burke, 2003), we cannot exclude that the neuronsthat express stronger SK currents at the beginning of thetrain (and are therefore more regular spiking) are specifi-cally selected to survive in this process.
Modulation of the SK-mediated AHP tunes the excit-ability and modifies the firing of DA neurons in vitro and inivo (Ji et al., 2009; Herrik et al., 2010). The SK current isnvolved in the control of dopaminergic neuron firing modetonic vs. phasic) (Wolfart and Roeper, 2002; Komendan-ov et al., 2004; Waroux et al., 2005). Blockade of SKurrent by apamine, combined with an activation of NMDAeceptors, is indeed a typical method to induce phasicctivity in dopaminergic neurons in vitro (Seutin et al.,993). Moreover, gating of SK channels can be physiolog-
cally modulated by neurotransmitters (Allen et al., 2007;aingret et al., 2008). Therefore, excitatory and inhibitory
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Fig. 5. SK-mediated current is involved in spike frequency adaptationin control conditions or during bath application of apamine (100 nM) isignificantly (* P�0.05, Wilcoxon test) under apamine treatment (n�ondition is indicated by the black dash. (C) Hybrid clamp recordings odapting (red trace) neuron. Middle: the same neurons were subjecteV for 100 ms in current clamp to induce unclamped spikes, then heldight: the amplitude of the AHP current was significantly correlated withnd suggests that it is the SK themselves that act differently rather tha
n this figure legend, the reader is referred to the Web version of this
nputs could influence the firing pattern of dopaminergic n
eurons both directly (Overton and Clark, 1997) and indi-ectly through SK channels, highlighting the likely interplayf afferents and intrinsic properties. Lastly, the correlationetween SFA and variability in spontaneous firing fre-uency is in accordance with previous studies highlightinghe key role of SK currents in maintaining the regularity ofopaminergic neuron tonic activity (Shepard and Bunney,988; Seutin et al., 1993; Ping and Shepard, 1996; Wolfartt al., 2001; Waroux et al., 2005; Cui et al., 2004). Forxample, a higher percentage of SNc dopaminergic neu-ons display a regular spiking activity compared to ventralegmental area dopaminergic neurons, which is quantita-ively correlated with their higher expression of the SK3hannel (Wolfart et al., 2001). Such roles in the shaping ofring activity confer to SK current a critical position inopaminergic neuron physiology.
Interestingly, SFA has been dually linked to long-termlasticity. Indeed, neurons displaying SFA are expected toxhibit more optimal spike-timing dependent plasticity, aorrelated-based Hebbian learning rule, by enhancing the
nitial evoked response (more spikes in the postsynaptic
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r = -0.6492p= 0.0163
in of spikes evoked by a stimulation (�40 pA above spike threshold),e neuron. Holding potential: �60 mV. (B) Adaptation ratio increasess represent individual neurons. The mean adaptation ratio for eachrrents. Left: evoked spiking patterns of a regular (black trace) and an
brid clamp protocol: initially held at �80 mV, and depolarized to �6080 mV in voltage clamp to measure the amplitude of the AHP current.ratio. This confirms that the AHP is involved in the SFA phenomenon,
ium influx activating them. For interpretation of the references to color
min nM)
AP threshold
20
p
. (A) Tran the sam7). Circlef AHP cu
d to a hyback to �the SFA
euron) when compared to regular neurons (Hennequin et
siC2s ly associai er is refe
M. Vandecasteele et al. / Neuroscience 192 (2011) 1–108
al., 2010). Reciprocally, long-term plasticity conditioninghas been shown to modulate the amplitude of the AHP andconsequently the SFA (Sun, 2009; Cohen-Matsliah et al.,2010). The higher magnitude of SFA in younger animalscould therefore underlie, or result from an early postnatalperiod of heightened plasticity in dopaminergic neurons.
SFA has been proposed to be involved in forwardmasking: when several inputs hit sequentially in time thereceiving neuron displaying an SFA, the first input triggersa full neuronal response inhibiting subsequent ones(Wang, 1998; Liu and Wang, 2001). In addition, somestudies suggest that SFA could stabilize synchronization ofneuronal assemblies (Crook et al., 1998; Van Vreeswijkand Hansel, 2001) and that depending on the SFA value,a preferred neuronal oscillatory frequency can be pre-dicted (Fuhrmann et al., 2002). This latter role could beparticularly relevant in dopaminergic neurons since thesecells display oscillatory firing both at the single spike andburst level (Grace and Bunney, 1984b; Zhang et al., 2008).
Genetic studies have indeed suggested that CAG tri-nucleotide-enriched forms of the KCNN3 gene (coding theSK3 channels) could be a factor promoting schizophrenia(Gargus et al., 1998; Vincent et al., 2000). Long glutaminestretches would stabilize the SK3 channel, therefore en-
SFA ratio
Inte
rsp
ike
inte
rval
mea
n (s
)
Inte
rsp
ike
inte
rval
stan
dar
d d
evia
tio
n (s
)
A
C
15 mV
500 ms
-60 mV
-60 mV
-40 mV
-40 mV
20 mV
500 ms
0.8
0.6
0.4
0.2
043210
0.2
0.15
0.1
0.05
00
r = -0.12p > 0.1
Fig. 6. Spike frequency adaptation is associated with a decreased rpontaneous (right) activity in a regular spiking (black traces) and an antervals are distributed on a wider range in an adapting neuron (red borrelations between adaptation ratio and spontaneous interspike inte6 dopaminergic neurons: SFA intensity significantly increases withpontaneous interspike intervals. This indicates that SFA is specificalnterpretation of the references to color in this figure legend, the read
hancing the net weight of SK conductance in dopaminergic
neurons (Gargus et al., 1998). Such increase of SK con-ductance would lead to a pathological regularization ofventral tegmental area dopaminergic neuron firing activity(Gargus et al., 1998; Wolfart et al., 2001). Consideringtheir putative involvement in schizophrenia, as well as inother central nervous system disorders (Blank et al.,2004), SK channels have now become a therapeutic targetof growing interest.
Acknowledgments—We thank Anne-Marie Godeheu for technicalassistance for histology, and Marie Grimoin for assistance withlow EGTA experiments. This work was supported by Fondation deFrance grant 20020111943, ANR Mecarec, INSERM and theCollege de France.
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