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Hindawi Publishing CorporationNeural PlasticityVolume 2011, Article ID 494675, 2 pagesdoi:10.1155/2011/494675

Editorial

Circuit Mechanisms of Memory Formation

Bjorn M. Kampa,1 Anja Gundlfinger,1 Johannes J. Letzkus,2 and Christian Leibold3

1 Department of Neurophysiology, Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland2 Friedrich Miescher Institute for Biomedical Research, Maulbeerstraße 66, 4058 Basel, Switzerland3 Department of Biology II, University of Munich, 82152 Planegg-Martinsried, Germany

Correspondence should be addressed to Bjorn M. Kampa, [email protected]

Received 25 October 2011; Accepted 25 October 2011

Copyright © 2011 Bjorn M. Kampa et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.

1. Introduction

Memory formation is one of the most fascinating andcomplex brain functions. A large body of research over thelast decades has drastically increased our understanding ofthe molecular and cellular processes underlying learning,most notably through a detailed investigation of synapticplasticity. This reductionist approach, typically involvingin vitro experiments, has been tremendously successful inproviding a mechanistic framework for learning at thelevel of single neurons. However, real-life memories areformed through dynamic interactions of many neuronsembedded in large networks. Investigating the mechanismsand consequences of learning at the level of neuronal circuitsis technically much more demanding, and we are onlybeginning to understand this important topic. This specialissue presents recent progress in illuminating the mostexciting issues in the field of circuit mechanisms of memoryformation. The contributing articles cover essential conceptsand hypotheses underlying memory formation ranging fromsynaptic mechanisms of plasticity in neuronal microcircuitsto circuit reorganizations in response to physiological andpathological influences.

2. Plasticity of Inhibitory Circuits

Neuronal circuits are assembled by intricately interconnectedexcitatory and inhibitory units. The balance of excitation andinhibition is absolutely critical to circuit function. The lion’sshare of research into plasticity has focused on excitatorysynapses. However, GABAergic inhibition in the cortex playsa major role in development and ocular dominance plasticityas reviewed by Heimel et al. Sensory deprivation of the

visual input through one eye leads to the dominance ofthe contralateral eye’s inputs. This also changes the ocularpreference of cortical neurons during the sensitive period.One of the central mechanisms responsible for opening thesensitive period is the maturation of inhibitory innervation,which may also involve plasticity of inhibitory inputs.The many forms and functions of long-term plasticity atGABAergic synapses are reviewed by A. Maffei. New exper-imental work has demonstrated that inhibitory synapses alsoundergo plastic changes and follow their own learning rules.Understanding these rules is crucial to fully comprehend thecircuit mechanisms of memory formation.

3. Neuromodulation of Learning and Memory

The effect of long-range neuromodulatory inputs on localcircuit computations is at present a very dynamic field ofinvestigation, in particular since neuromodulation is wellknown to be critical for many forms of learning. The cho-linergic system is implicated in gating cortical plasticityduring associative learning and sensory map plasticity. M.B. Verhoog and H. D. Mansvelder review how cholinergicmodulation acting via presynaptic ionotropic receptors maycreate brief time windows for synaptic modulation duringspike-timing-dependent plasticity. C. Kohler et al. addressthe modulation of hippocampal and neocortical memorysystems by the relatively little known neuromodulator hista-mine. They provide an overview of the anatomy of histamin-ergic systems, histamine metabolism, receptors, and turnoverand introduce the involvement of histamine in synapticplasticity. Finally, K. Okada et al. discuss how a prominentneuromodulatory signal during learning, the dopaminergic

2 Neural Plasticity

prediction error signal, is computed with a special emphasison the involvement of other neuromodulatory systems.

4. Motor Learning

Circuit plasticity in sensorimotor areas has become a majorinterest since the recent introduction of brain-machine inter-faces. Focusing on motor learning in the rat, J. Francis andW. Song discuss plasticity mechanisms on the behavioral,neurophysiological, and synaptic levels. In addition, theauthors present data on the inhibition of protein kinaseMζ , which is necessary for the maintenance of long-termpotentiation. Relating molecular plasticity with behavioralchanges, these results shed new light on circuit mechanismsof motor learning. These cortical circuits are organized byspecific connections between their neuronal members. Whilemany motifs of synaptic connectivity have been elucidatedin vitro, we still know very little about the organization ofnetwork activity in the intact brain during behavior. D. F.Putrino et al. address this issue in cats, which were trainedto perform skilled movement task. They describe dynamicspiking associations between single neurons in primarymotor cortex, which were highly sensitive to spontaneouserrors in task performance. J. A. Hosp and A. R. Luft finallyreview different physiological and pathological scenariosinducing neuroplasticity and circuit reorganization in themotor cortex. They differentiate between learning of novelmovement sequences in healthy individuals, spontaneouscortical reorganization after ischemic injury, and relearningof skilled movement sequences under neurorehabilitativetraining in the injured brain. Although their main focus lieson studies in rodents and nonhuman primates, the authorsalso provide a useful outlook on the implications of thefindings for clinical practice.

5. Circuit Mechanisms inHippocampus and Amygdala

The hippocampal-entorhinal circuitry provides the mostcrucial anatomical and functional substrate for both memoryformation and spatial navigation. An appealing networkmodel for the consolidation of newly formed memoryinvolves repetition of previously experienced spiking activityin the hippocampus during sleep. L. Buhry et al. con-tribute a comprehensive review over a large collection ofpapers on such hippocampal “replay” phenomena, which arecorrelated to neural sequences recorded during precedingexploration phases. They specifically focus on the relationof these activity sequences to memory consolidation duringsleep. The point is made that all the different flavors ofthose sequence-like activities no longer allow to see thosesequences as a mere memory replay phenomenon. Theauthors therefore propose the broader conceptual frameworkof offline sequential activity and discuss its possible relationto cognitive functions. In similar lines, J. H. L. P. Sadowskiet al. review in vivo studies of hippocampal sharp waveripple complexes and their relation to sequence replayphenomena. In contrast to the review by L. Buhry et al.,they mostly focus on the cellular and circuit mechanism that

could underlie this phenomenon. A particular emphasis islaid on how activity patterns can be transmitted betweenthe different hippocampal and extrahippocampal regionsduring sharp wave oscillations and how synaptic plasticitymay benefit from this dynamical state. K. J. Jeffery thenintroduces the reader to the general concepts and useof discrete and continuous attractor networks involvedin spatial navigation. She reviews the evidence for theexistence of such attractor networks and finally presents ahypothesis—on modeling and experimental work—on howpartial remapping and attractor dynamics can coexist in thehippocampal-entorhinal network. Similar attractor modelscan explain the outcomes of a “teleportation experiment”described by F. Stella and A. Treves. In such an experiment, arat was rapidly “teleported” from one familiar environmentto another by changing the luminance conditions. Theresulting hippocampal activity pattern alternated betweenthe two representations for a short while, mostly withoutshowing intermediate patterns, which indicates attractor-type dynamics. While the hippocampal formation andconnected entorhinal cortex are the most studied systems forclassical declarative memory formation, other types of learn-ing are linked to deep-brain structures. Fear conditioning, forinstance, is a powerful paradigm to investigate the neuronalmechanisms underlying associative learning. The amygdalais a critical brain area for this type of learning, and recentevidence indicates that it functions as a hub which integratesand orchestrates activity in a distributed network of brainareas during aversive learning. In this issue, H. Toyoda etal. review the involvement of the anterior cingulated cortex(ACC) in fear learning and compare the mechanisms ofsynaptic plasticity induction in ACC to those found in theamygdala.

In conclusion, this special issue summarizes a broadrange of topics in the field of circuit plasticity and offers newinsights and perspectives on linking molecular mechanismswith behavioral outcome of learning and memory. Thepresented work covers experimental data and also theoreticalmodels that together can explain some of the intriguingphenomena of computation and memory formation in thebrain.

Bjorn M. KampaAnja Gundlfinger

Johannes J. LetzkusChristian Leibold

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