8. Cowen, R.K., Paris, C.B., andSrinivasan, A. (2006). Scaling ofconnectivity in marine populations.Science 311, 522–527.

9. James, M.K., Armsworth, P.R.,Mason, L.B., and Bode, L. (2002). Thestructure of reef fish metapopulations:modeling larval dispersal and retentionpatterns. Proc. R. Soc. Lond. B 269,2079–2086.

10. Bode, M., Bode, L., and Armsworth, P.R.(2006). Larval dispersal reveals sourcesand sinks in the Great Barrier Reef. Mar.Ecol. Prog. Ser. 308, 17–25.

11. Baums, I.B., Miller, M.B., andHellberg, M.E. (2005). Regionally isolatedpopulations of an imperiled Caribbeancoral, Acropora palmata. Mol. Ecol. 14,1377–1390.

12. Volmer, S.V., and Palumbi, S.R. (2006).Restricted gene flow in the Caribbeanstaghorn coral Acropora cervicornis:Implications for the recovery of

endangered reefs. J. Hered.,in press.

13. Taylor, M.S., and Hellberg, M.E. (2003).Genetic evidence for local retention ofpelagic larvae in a Caribbean coral reeffish. Science 299, 107–109.

14. Purcell, J.F.H., Cowen, R.K.,Hughes, C.R., and Williams, D.A. (2006).Weak genetic structure indicates strongdispersal limits: a tale of two coralreef fish. Proc. R. Soc. Lond. B 273,1483–1490.

15. Wolanski, E., and Hamner, W.M. (1988).Topographically controlled fronts in theocean and their biological influence.Science 241, 177–181.

16. Oliver, J.K., King, B.A., Willis, B.L.,Babcock, B.C., and Wolanski, E. (1992).Dispersal of coral larvae from alagoonal reef. 2. Comparisons betweenmodel predictions and observedconcentrations. Cont. Shelf Sci. 12,873–889.

17. Miller, K.J. (2005). In situ fertilizationsuccess in the Scleractinian coralGoniastrea favulus. Coral Reefs 24,313–317.

18. Sale, P.F., Cowen, R.K., Danilowicz, B.S.,Jones, G.P., Kritzer, J.P., Lindeman, K.C.,Planes, S., Polunin, N.V.C., Russ, G.R.,Sadovy, Y.J., et al. (2005). Criticalscience gaps impede use of no-takefishery reserves. Trends Ecol. Evol. 20,74–80.

19. Hoegh-Guldberg, O. (2006). Complexitiesof coral reef recovery. Science 311,42–43.

Biology Department, Woods HoleOceanographic Institution, Woods Hole,Massachusetts 02543, USA.E-mail: sthorrold@whoi.edu

DOI: 10.1016/j.cub.2006.07.034

Current Biology Vol 16 No 16R640

Memory Traces: Snails Reveala Novel Storage Mechanism

A new study of memory traces in an invertebrate challenges conventionin two ways: first, by demonstrating a persistent change in synapticstrength that is maintained remotely, via the passive spread of somaticdepolarization; and second, by localizing a critical memory trace toneurons located outside the behavioral circuit affected by learning.

William Frost

We are to a large extent a productof our memories, so there is muchto gain by deciphering howexperiences are stored in the brain.One approach is to train animalsand then search their nervoussystems for the underlying memorytraces — the persistent nervoussystem alterations encoding thebehavioral change in question [1].A study reported recently inCurrent Biology by Kemenes et al.[2] uses this approach to challengetwo conventional views of memorytraces.

The memory trace in questionencodes appetitive classicalconditioning of feeding in thefreshwater pond snail Lymnaeastagnalis. In a single-trial trainingprotocol, animals received eithera paired or unpaired presentationof an initially neutral amyl acetateflavor, the conditioned stimulus(CS), and feeding-elicitingsucrose, the unconditionedstimulus (US). Those receiving thepaired CS–US presentation latergenerated a feeding responseto the amyl acetate alone,

demonstrating that they hadlearned the association. Thememory for this single-triallearning lasted two weeks aftertraining, an impressiveaccomplishment for a pondsnail. Comparing brains frompaired and unpaired animalsshowed that associative trainingproduced a 10 mV depolarizationin the cerebral giant cell,a bilaterally paired singleserotonergic neuron locatedoutside the feeding network thatmodulates its responsiveness tofood stimuli. This depolarizationdeveloped one day aftertraining and persisted for theduration of the behavioral learning.

While memories have long beenknown to be encoded by stablealterations in synaptic strength[3–5], there is a growing realizationthat changes in neuronalexcitability are also important[6–8]. Persistent depolarization,such as that exhibited by thecerebral giant cell neurons, wouldconventionally be expected to beassociated with alterations inspontaneous firing rate, firingthreshold or firing responses to

synaptic inputs. However,Kemenes et al. [2] observed noneof these effects on cerebral giantcell firing. The two neurons merelysat, quietly depolarized, outsidethe feeding network, givinglittle evidence that they mightbe playing a key role in storingthe memory for this learningparadigm. Many of us would havemoved on at this point, to searchwithin the feeding circuit proper fora more promising memory trace.

Fortunately, Kemenes et al. [2]pressed on to evaluate the possibleimpact of this persistent shift incerebral giant cell resting potential.By injecting constant intracellularcurrent into cerebral giant cells innaı̈ve preparations, the authorsdepolarized the cells by the sameamount as occurred duringlearning. At the same time, theyalso used controlled, brief currentpulses to force the spontaneousfiring rate of the cerebral giant cellsto remain unchanged. Surprisingly,with no change in cerebral giant cellspontaneous rate orfiring responseto CS administration, these naı̈vepreparations nonethelessappeared as though they had beentrained, generating feeding motorprograms when amyl acetate waspresented to the animal’s lips!Further experiments suggestedthat this occurred via an increasedCS recruitment of cerebral-buccalinterneurons that drive the feedingcentral pattern generator.

How could a simpledepolarization in the cerebral giantcell neurons, occurring with no

Geographic Parthenogenesis:Recurrent Patterns Down Under

A recent study reports striking similarities in the origin and spread ofparthenogenesis in two distantly related animals of the Australian aridzone, suggesting that the loss of sex was driven by a very generalselective force.

Christoph Vorburger

Geographic parthenogenesis,a term coined by Vandel [1], refersto the common finding thatparthenogens — organisms

reproducing without sex — havedifferent geographicaldistributions than their closestsexual relatives. Such differenceshave long attracted the interest ofevolutionary biologists. The hope

DispatchR641

change in their firing properties,nonetheless enhance theresponsiveness of the feedingcircuit to a specific chemical lipstimulus? Invertebrateneurobiologists have known forsome 30 years that steady-stateshifts in the soma resting potentialof presynaptic neurons can act tomodulate their spike-mediatedtransmitter release [9–12],apparently via passive(electrotonic) spread of thepotential change to the synapticterminals, where it affects restingcalcium levels. Kemenes et al. [2]used an impressive range ofapproaches to confirm thismechanism in the cerebral giantcells, including simultaneouselectrode impalements of somaand axon, voltage- andcalcium-sensitive dye recording,and reconstituting cerebral giantcell synaptic connections in cellculture. They conclude that,even though the cerebral giantcells do not fire more to the CSafter paired training, theirdepolarization-enhancedsynapses nonetheless enhancethe ability of CS-activated afferentneurons to excite the cerebral-buccal interneurons, increasingfeeding responsiveness to theCS. An intriguing aspect of thisextrinsic storage scheme is thatit allows the feeding network, inprinciple, to remain in a naı̈vestate throughout the durationof the learning, allowing theanimal’s frequent spontaneousbouts of feeding to occurunaltered.

The report by Kemenes et al. [2]has relevance well beyondinvertebrate neurobiology.Although the ability of somamembrane potential to modulatespike-mediated transmitterrelease has long been knownfrom invertebrate studies, thismechanism of synaptic plasticityhas just recently been describedin three different regions of thevertebrate brain [13–16]. One suchlocus is the hippocampus, a majorsite of learning-related synapticplasticity, so it is presumablyjust a matter of time before thisnovel memory mechanism,demonstrated so convincinglyhere in Lymnaea, is evaluatedin the vertebrate brain.

Two lessons emerge from thisimportant study. First, we mustnow face the fact that neuronscan store memory somewhatcryptically, by a simple change inresting membrane potential, withno effect on their firing threshold,tonic firing, or firing responses toinputs. Second, critical memorytraces may lurk, again somewhathidden, outside of the circuitsmediating the altered behaviors.The good news for memoryresearchers is that we are nowaware of additional guises thatmemory traces can take. But thiscomes with the realization thatwhen searching for the essentialplasticity underlying learning wemust now look more widely — bothwithin [1] and outside thecircuits that mediate the modifiedbehavior — as well as for anever-broadening array of cellularmechanisms of plasticity.

References1. Thompson, R.F. (2005). In search of

memory traces. Annu. Rev. Psychol. 56,1–23.

2. Kemenes, I., Straub, V.A., Nikitin, E.S.,Staras, K., O’Shea, M., Kemenes, G., andBenjamin, P.R. (2006). Role of delayednon-synaptic neuronal plasticity inlong-term associative memory. Curr. Biol.16, 1269–1279.

3. Bliss, T.V.P., and Collingridge, G.L. (1993).A synaptic model of memory: Long-termpotentiation in the hippocampus. Nature361, 31–39.

4. Martin, S.J., Grimwood, P.D., andMorris, R.G. (2000). Synaptic plasticityand memory: an evaluation of thehypothesis. Annu. Rev. Neurosci. 23,649–711.

5. Kandel, E.R. (2001). The molecular biologyof memory storage: a dialogue betweengenes and synapses. Science 294,1030–1038.

6. Hansel, C., Linden, D.J., and D’Angelo, E.(2001). Beyond parallel fiber LTD: the

diversity of synaptic and non-synapticplasticity in the cerebellum. Nat. Neurosci.4, 467–475.

7. Daoudal, G., and Debanne, D. (2003).Long-term plasticity of intrinsicexcitability: learning rules andmechanisms. Learn. Mem. 10,456–465.

8. Zhang, W., and Linden, D.J. (2003). Theother side of the engram: experience-driven changes in neuronal intrinsicexcitability. Nat. Rev. Neurosci. 4,885–900.

9. Nicholls, J., and Wallace, B.G. (1978).Modulation of transmission at aninhibitory synapse in the central nervoussystem of the leech. J. Physiol. 281,157–170.

10. Shapiro, E., Castellucci, V.F., andKandel, E.R. (1980). Presynapticmembrane potential affects transmitterrelease in an identified neuron inAplysia by modulating the Ca2+ andK+ currents. Proc. Natl. Acad. Sci. USA77, 629–633.

11. Hume, R.I., and Getting, P.A. (1982).Motor organization of Tritonia swimming.II. Synaptic drive to flexion neurons frompremotor interneurons. J. Neurophysiol.47, 75–90.

12. Frost, W.N., Tian, L.-M., Hoppe, T.A.,Mongeluzi, D.L., and Wang, J. (2003). Acellular mechanism for prepulse inhibition.Neuron 40, 991–1001.

13. Awatramani, G.B., Price, G.D., andTrussell, L.O. (2005). Modulation oftransmitter release by presynaptic restingpotential and background calcium levels.Neuron 48, 109–121.

14. Shu, Y., Hasenstaub, A., Duque, A., Yu, Y.,and McCormick, D.A. (2006). Modulationof intracortical synaptic potentials bypresynaptic somatic membrane potential.Nature 441, 761–765.

15. Alle, H., and Geiger, J.R. (2006).Combined analog and action potentialcoding in hippocampal mossy fibers.Science 311, 1290–1293.

16. Marder, E. (2006). Neurobiology:extending influence. Nature 441, 702–703.

Department of Cell Biology andAnatomy, The Chicago Medical School,Rosalind Franklin University of Medicineand Science, 3333 Green Bay Road,North Chicago, Illinois 60064, USA.E-mail: William.Frost@rosalindfranklin.edu

DOI: 10.1016/j.cub.2006.07.028