nature neuroscience • volume 1 no 7 • november 1998 539

Cortical neurons are exquisitely sensitiveto, and selective for, particular patterns ofsensory input. Some of this sensitivity aris-es from a remarkable feature of corticalmicrocircuitry—the extensive recurrentexcitatory connections between pyramidalneurons. These connections allow positivefeedback to dramatically amplify afferentsignals, and modeling studies suggest thatthis amplification is important in enhanc-ing cortical selectivity1,2. However, thesestudies also show that recurrent excitatorycircuits are intrinsically unstable. Withouta strong brake on recurrent excitation, theactivity triggered by afferent input can con-tinue to grow unchecked. One importantregulator of recurrent excitation is feedbackinhibition provided by GABAergicinterneurons, which also receive excitationfrom pyramidal neurons. For cortical net-works to function properly, a delicate bal-ance between these two opposing forcesmust be maintained; there must be enoughrecurrent excitation to maintain selectivity,and enough recurrent inhibition to preventrunaway excitation. If this balance betweenexcitation and inhibition tips too fartoward excitation, stability will be lost.Conversely, if the balance tips too fartoward inhibition, the circuit will attenu-ate, rather than amplify, afferent input.

What regulates the balance betweencortical excitation and inhibition? Themultiple mechanisms involved seem to berich enough to continue to occupy corti-cal physiologists for some time, but animportant piece of the puzzle has beenuncovered in an elegant study reported inthis issue of Nature Neuroscience3. Galaret-ta and Hestrin used dual intracellularrecordings from synaptically connectedpyramidal neurons and interneurons in rat

network more stable and less prone to run-away excitation.

Interest in the dynamic properties ofcortical synapses has increased recentlywith the finding that short-term plasticitymay have important computational con-sequences for cortical circuit function4–6.The ability of a presynaptic cell to influ-ence the activity of a postsynaptic celldepends both on the strength of the synap-tic connection (the amplitude of each post-synaptic current or PSC), and on the rateof presynaptic firing (the number of PSCsper second). When excitatory synapses arestimulated more rapidly than a critical fre-

Synaptic depression: a key player inthe cortical balancing actSacha B. Nelson and Gina G. Turrigiano

What regulates the balance between cortical excitation and inhibition? Galaretta and Hestrinshow that prolonged firing induces a much stronger depression at excitatory synapses than atinhibitory ones, making the network more stable and less prone to runaway excitation.

neocortical slices to compare the short-term plasticity of excitatory and inhibito-ry synapses. They find, as has beenreported previously, that both classes ofsynapses decrease in strength with repeat-ed stimulation, a process known as synap-tic depression. The important finding ofthis paper is that, although initial rates ofdepression are similar at both classes ofsynapses, prolonged firing induces a muchstronger depression of excitatory synapsesthan of inhibitory synapses. This impliesthat over time, activity can shift the rela-tive strength of excitatory and inhibitorysynapses to favor inhibition, making the

news and views

Sacha Nelson and Gina Turrigiano are at theDepartment of Biology and Center for ComplexSystems, MS 8, Brandeis University, Waltham,Massachusetts 02454, USAe-mail: nelson@brandeis.edu andturrigiano@brandeis.edu

Fig. 1. Differential synaptic depressiondynamically adjusts the balance between cor-tical excitation and inhibition to promote sta-bility. Cortical activity depends upon therelative strengths of recurrent excitatorysynapses between pyramidal neurons and theexcitatory and inhibitory synapses linkingpyramidal neurons with GABAergic interneu-rons. One class of these interneurons isshown (multipolar neurons). Connectionswith extrinsic afferents are not shown. Lowerpanel is an idealized plot of the relative activa-tion of excitatory and inhibitory synapses.When excitation is strong and inhibition isweak, epileptiform bursting may result; wheninhibition is strong and excitation is weak,activity may be silenced. Varying levels ofafferent drive will lead to different levels ofexcitation and inhibition, tracing out a diago-nal line in the plot whose slope depends onthe relative strength of excitation and inhibi-tion. Central diagonal line indicates perfectlybalanced network. Arrows indicate hypothet-ical and observed effects of differentialdepression on network activity. If the accu-mulation of synaptic depression were greaterat inhibitory synapses, the balance would shiftto favor excitation (clockwise rotation) andthe network would easily become unstable.This was not observed. Instead synapticdepression was found to be greater at excita-tory synapses, leading to relatively greaterinhibition (counter-clockwise rotation) andincreased stability.

Pyramidal(excitatory)

Multipolar(inhibitory)

NoActivity

Epileptiformactivity

Excitation

Inh

ibit

ion

Bob Crim

i

1998 Nature America Inc. • http://neurosci.nature.com19

98 N

atur

e A

mer

ica

Inc.

•ht

tp://

neur

osci

.nat

ure.

com

540 nature neuroscience • volume 1 no 7 • november 1998

news and views

quency of 10 to 20 Hz, PSC amplitudesdepress to a level that is inversely propor-tional to the rate of stimulation. Thisresults in saturation of the total synapticdrive (‘synaptic impact’), defined as theproduct of the presynaptic firing rate andthe PSC amplitude. Doubling the presy-naptic firing rate causes the average ampli-tude of each PSC to be halved, and hencetheir product remains constant. Synapticdepression therefore acts as a form ofsynapse-specific gain control, which makesthe total impact of each synapse relativelyindependent of the steady-state firing rateof the presynaptic cell.

The advantage of this dynamic adjust-ment of synaptic strengths becomes clearwhen one considers the effects of transientchanges in presynaptic firing rates. Synap-tic depression enables the postsynaptic cellto respond transiently to relative, ratherthan absolute, changes in presynaptic fir-ing rate. For example, the postsynaptic cellwill respond equally to an increment from10 Hz to 20 Hz and from 100 to 200 Hz,even though the absolute changes in rateare very different. In contrast, the sameabsolute change in rate, for example theincrement from 100 Hz to 110 Hz, willproduce a smaller response than the incre-ment from 10 Hz to 20 Hz. This is usefulbecause a doubling of firing rate of thepresynaptic cell (from 10 to 20 Hz) is muchmore likely to signal a significant changein the outside world than a 10% increase(from 100 to 110 Hz), even though theabsolute magnitude of both changes isidentical. Without rapid synaptic depres-sion, the postsynaptic cell’s activity wouldbe dominated by rapidly firing inputs andwould be relatively insensitive to fluctua-tions in the activity of more slowly firinginputs.

In addition to this rapid form ofdepression, cortical synapses show a slow-er form of depression when stimulated forlonger periods of time. Varela and col-leagues7 analyzed responses to complexstimulus trains and found evidence for aweak but persistent form of synapticdepression recovering with a time constantof 5–20 seconds. Because the depression isslow and weak (that is, a small reductionper presynaptic spike), although synapsesmay reach steady state with respect to themore rapid form of depression after onlya few presynaptic action potentials, they donot reach true steady state for much longer.This has now been beautifully demon-strated by Galaretta and Hestrin, who showthat when the presynaptic firing rate israised from 0.25 Hz to 20 Hz, there is notonly a rapid form of depression as

This may allow the cortex to function at amuch higher initial gain (that is, muchgreater level of recurrent excitation) thanwould otherwise be stable. High gain maybe especially useful when activity levels arelow, as a means to amplify small afferentsignals.

This shift in the balance of excitationand inhibition could also account for someof the changes observed during prolongedsensory stimulation. Prolonged visualstimulation in vivo causes a reduction incortical responsiveness termed contrastadaptation. Carandini and Ferster9 haveshown that this adaptation is accompaniedby a membrane hyperpolarization of visu-al cortical neurons. One interpretation ofthis finding3,9,10 is that the hyperpolariza-tion reflects a shift in the balance betweenexcitation and inhibition caused by differ-ential depression at the two classes ofsynapses.

Although it is very attractive, the ideathat differential synaptic depression stabi-lizes cortical networks is based on a num-ber of assumptions that are as yet untested.First, depression in adult cortex in vivomay differ from that in the slices fromdeveloping cortex that Galaretta and Hes-trin studied. Data from several laborato-ries suggest that depression may bedevelopmentally regulated7,11 (see alsoReyes, A. D. & Sakmann, B. Soc. Neurosci.Abst. 24, 318, 1998) and may differ in vivoand in vitro (Sanchez-Vives, M. V.,McCormick, D. A. & Nowak, L. G. Soc.Neurosci. Abst. 24, 896, 1998). The role ofsynaptic depression in adult cortex has yetto be determined. Second, interneuronstend to have higher firing rates than pyra-midal neurons, which may equalize theamount of depression at the two classes ofsynapse. Third, the balance between exci-tation and inhibition depends not only onthe properties of excitatory and inhibito-ry inputs to pyramidal neurons, but on theproperties of the excitatory connectionbetween pyramidal and interneurons.Galaretta and Hestrin show that excitatorysynapses onto interneurons show slowdepression that is comparable to the slowdepression at pyramidal-to-pyramidalneuron synapses. This slow depression ofthe excitatory drive to interneurons wouldtend to reduce recurrent inhibition at highfrequencies, and this effect could preventa net shift from excitation to inhibition.

Predicting the ultimate effects of differ-ential synaptic depression at differentsynapses will require a deep understandingof cortical circuit dynamics. Multiple mech-anisms operating over different time scalesmust be at work to keep cortical activity

described previously, but also a slowercomponent that reaches steady state onlyafter several hundred action potentials.Remarkably, during these long trains theEPSC amplitude depresses almost to zero(although there is partial recovery afteronly a brief interval). In contrast to therapid depression studied previously, theslower form of depression changes theimpact of the synapse in a frequency-dependent manner. This occurs because,at least for excitatory synapses, the slowdepression causes the PSC amplitude todecrease to a level that is less than theinverse of the presynaptic firing rate.

A key finding of the present study isthat inhibitory synapses show much weak-er slow depression than excitatory synaps-es. Over the frequency range (5–20 Hz)where the impact of the excitatory synaps-es is declining, the impact of the inhibitorysynapses grows. The impact of inhibitorypostsynaptic currents (IPSCs) growsbecause there is little change in IPSCamplitude with frequency over this range,and therefore the product of IPSC ampli-tude and frequency increases. What thismeans is that the relative strength of exci-tatory and inhibitory synapses is not fixed,but varies dynamically as a function of thefrequency and duration of presynapticactivity.

The mechanism of the slow depressionis not yet clear, but Galaretta and Hestrinspeculate that it reflects depletion of a read-ily releasable pool of synaptic vesicles. Thekinetics of the slow depression is similar tothe kinetics of vesicle recycling in severalpreparations8. Consistent with the idea thatdepression results from reduced presynap-tic release, Galaretta and Hestrin show thatthe slow depression increases the rate ofsynaptic failures (action potentials that donot result in release events). By recordingfrom synaptically connected pairs of neu-rons, they were able to verify that these fail-ures did not simply result from a failure toevoke a presynaptic action potential.

What is the function of this slow formof depression at excitatory synapses?Galaretta and Hestrin suggest that it is animportant mechanism for maintaining sta-bility in cortical circuits. Model circuits thatcontain recurrent excitation and recurrentinhibition amplify afferent signals with again that depends on the balance betweenexcitation and inhibition. The presentresults suggest that the gain of the circuitmay be dynamic. At low levels of activity,recurrent excitation leads to high gain, butas activity grows, differential depressionturns down the gain by reducing excitationto a greater degree than inhibition (Fig. 1).

1998 Nature America Inc. • http://neurosci.nature.com19

98 N

atur

e A

mer

ica

Inc.

•ht

tp://

neur

osci

.nat

ure.

com

news and views

nature neuroscience • volume 1 no 7 • november 1998 541

within the appropriate operating range. Forexample, at shorter time scales, excitatoryinputs to some classes of interneurons showfacilitation (a transient increase in synapticstrength lasting a small fraction of a sec-ond)12–14. This would tend to promote sta-bility by boosting recurrent inhibition. Inaddition, differential depression of excita-tory and inhibitory inputs can occur evenwith very brief trains in layer 2/3 in visualcortex (Song, S., Varela, J., Abbott, L., Tur-rigiano, G. & Nelson, S. Soc. Neurosci. Abst.23, 2362, 1997). At longer time scales, activ-ity can regulate the balance between exci-tation and inhibition by selectively adjustingthe quantal amplitude of different classesof excitatory synapses15. Presumably, thisrich cast of mechanisms, of which we havementioned only a few, are required to max-imize the flexibility with which cortical

synaptic strengths can be finely tuned tocompensate for changes in activity occur-ring over time scales that range from mil-liseconds to days. Although it is not yet clearhow these diverse mechanisms interact, thedifferential synaptic depression at excitato-ry and inhibitory synapses uncovered byGalaretta and Hestrin is likely to make animportant contribution to the maintenanceof cortical stability.

1. Sompolinsky, H. & Shapley, R. Curr. Op.Neurobiol. 7, 514–522 (1997).

2. Douglas, R. J., Koch, C., Mahowald, M.,Martin, K. A. C. & Suarez H. H. Science 269,981–985 (1995).

3. Galaretta, M. & Hestrin, S. Nature Neurosci. 1,587–594 (1998).

4. Thomson, A. M. & Deuchars, J. TrendsNeurosci. 17, 119–126 (1994).

5. Abbott L. F., Sen, K., Varela, J. A. & Nelson, S. B.

Fast synaptic neurotransmission in thenervous system depends on the close spa-tial apposition and high local concentra-tion of pre- and postsynaptic signalingmolecules at individual synapses. Varioussubsynaptic proteins are known to be cru-cial for the postsynaptic localizationand/or anchoring of excitatory neuro-transmitter receptors. At the neuromus-cular junction, the tight packing ofnicotinic acetylcholine receptors requiresthe peripheral membrane protein Rapsyn,whereas excitatory glutamate receptors arethought to localize at dendritic postsy-naptic sites via interactions with a familyof proteins containing multiple copies ofthe PDZ protein–protein interactionmotif. Similarly, GABAA receptors, whichmediate postsynaptic inhibition at about

30% of all synapses in the central nervoussystem, are largely concentrated at post-synaptic membrane specializations. Theirgating is potentiated by benzodiazepines,an effect that is lost in mice deficient inthe abundantly expressed GABAA recep-tor subunit γ2 (ref. 1).

In this issue of Nature Neuroscience(pages 563–571), Essrich and colleaguesshow that cortical and hippocampal neu-rons from these γ2-subunit-deficient micefail to accumulate GABAA receptors atdeveloping synaptic sites. Moreover, theauthors find that this clustering processrequires gephyrin2, a tubulin-binding pro-tein that is essential for the synaptic tar-geting of another class of inhibitoryreceptors, the glycine receptors3. Thesedata extend previous morphological stud-ies suggesting a receptor-clustering func-tion for gephyrin at both glycinergic andGABAergic synapses4,5 and provide exper-imental evidence that specific receptor-subunit-mediated protein–proteininteractions may underlie the synaptic

accumulation of GABAA receptors duringbrain development.

The results of Essrich and colleaguesare convincing and elegant. Staining ofbrain sections from surviving γ2 knock-out mice with specific antibodies revealeda significant reduction in synaptic GABAAreceptor staining. Furthermore, in pri-mary neuronal cultures prepared from theknockout mice, the formation ofGABAergic synapses as monitored byantibody staining was significantlyimpaired. Notably, the density of punc-tate GABAA receptor subunit stainingapposed to presynaptic markers, like theGABA synthesizing enzyme GAD or thesynaptic vesicle protein synaptophysin,was only 20% of that found in neuronsfrom wild-type or heterozygous animals,although total levels of GABAA receptorsubunit mRNA and protein were not sig-nificantly altered. Correspondingly, thefrequency of spontaneous miniature post-synaptic GABA currents (mPSCs) wasreduced by about 80%. This is consistentwith a loss of most GABAergic inputs; theremaining current may be carried byreceptors that do not contain the γ2 sub-unit. Previous studies have shown that theγ2 subunit is not essential for the forma-tion of functional GABAA receptors.Whether the reduction in mPSC frequen-cy merely reflects a lack of synaptic recep-tors or also relates to changes inelementary conductance or plasma mem-brane incorporation rates cannot bedetermined from the present data.

Immunocytochemical data on thesynaptic accumulation of gephyrin sup-port the notion that the reduction in

Gephyrin, a major player inGABAergic postsynapticmembrane assembly?Heinrich Betz

A new study shows that the glycine receptor clustering proteingephyrin is involved in postsynaptic localization of GABAAreceptors, which also requires the receptor’s γ2 subunit.

Heinrich Betz is at the Max-Plank-Institute forBrain Research, Deparment of Neurochemistry,Deutschordenstrasse 46, 60528 Frankfurt,Germanyemail: neurochemie@mpih-frankfurt.mpg.de

Science 275, 220–222 (1997).

6. Tsodyks, M. V. & Markram, H. Proc. Natl.Acad. Sci. USA 94, 719–723 (1997).

7. Varela, J. A. et al. J. Neurosci. 17, 7926–7940(1997).

8. Betz, W. J. & Wu, L. G. Curr. Biol. 5, 1098–1101(1995).

9. Carandini, M. & Ferster, D. Science 276,949–952 (1997).

10. Chance, F., Nelson, S. B. & Abbott, L. F. J.Neurosci. 18, 4785–4799 (1998).

11. O’Donovan, M. & Rinzel, J. Trends Neurosci.20, 431–433 (1997).

12. Thomson, A. M. J. Physiol. (Lond.) 502,131–147 (1997).

13. Markram, H., Tsodyks, M. V. & Wang, Y. Proc.Natl. Acad. Sci. USA 95, 5323–5328 (1998).

14. Reyes, A. et al. Nature Neurosci. 1, 279–285(1998).

15. Rutherford, L. C., Nelson, S. B. & Turrigiano,G. G. Neuron 21, 521–530 (1998).

1998 Nature America Inc. • http://neurosci.nature.com19

98 N

atur

e A

mer

ica

Inc.

•ht

tp://

neur

osci

.nat

ure.

com