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• W2725814939 abstract "Synaptic plasticity (e.g., long-term potentiation [LTP]) is considered the cellular correlate of learning. Recent optogenetic studies on memory engram formation assign a critical role in learning to suprathreshold activation of neurons and their integration into active engrams (“engram cells”). Here we review evidence that ensemble integration may result from LTP but also from cell-autonomous changes in membrane excitability. We propose that synaptic plasticity determines synaptic connectivity maps, whereas intrinsic plasticity—possibly separated in time—amplifies neuronal responsiveness and acutely drives engram integration. Our proposal marks a move away from an exclusively synaptocentric toward a non-exclusive, neurocentric view of learning. Synaptic plasticity (e.g., long-term potentiation [LTP]) is considered the cellular correlate of learning. Recent optogenetic studies on memory engram formation assign a critical role in learning to suprathreshold activation of neurons and their integration into active engrams (“engram cells”). Here we review evidence that ensemble integration may result from LTP but also from cell-autonomous changes in membrane excitability. We propose that synaptic plasticity determines synaptic connectivity maps, whereas intrinsic plasticity—possibly separated in time—amplifies neuronal responsiveness and acutely drives engram integration. Our proposal marks a move away from an exclusively synaptocentric toward a non-exclusive, neurocentric view of learning. Ever since its discovery in the early 1970s, long-term potentiation (LTP) of synaptic transmission (Bliss and Lomo, 1973Bliss T.V. Lomo T. Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path.J. Physiol. 1973; 232: 331-356Crossref PubMed Scopus (4090) Google Scholar) has been seen as a plausible cellular mechanism underlying information storage and learning. LTP indeed meets the basic requirements that a cellular learning correlate needs to fulfill: LTP increases synaptic weights and enhances the probability that an active synaptic input contributes to action potential generation; LTP lasts sufficiently long to lay the foundation for stable memories; LTP can be input-specific and thus allows for selective information storage; and LTP is actively reversed by long-term depression (LTD), enabling bidirectional modification (for reviews on LTP/LTD in different neural circuits, see Pittenger and Kandel, 2003Pittenger C. Kandel E.R. In search of general mechanisms for long-lasting plasticity: Aplysia and the hippocampus.Philos. Trans. R. Soc. Lond. B Biol. Sci. 2003; 358: 757-763Crossref PubMed Scopus (115) Google Scholar [Aplysia]; Malenka and Nicoll, 1993Malenka R.C. Nicoll R.A. NMDA-receptor-dependent synaptic plasticity: multiple forms and mechanisms.Trends Neurosci. 1993; 16: 521-527Abstract Full Text PDF PubMed Scopus (653) Google Scholar [hippocampus]; Singer, 1995Singer W. Development and plasticity of cortical processing architectures.Science. 1995; 270: 758-764Crossref PubMed Google Scholar [neocortex]; Jörntell and Hansel, 2006Jörntell H. Hansel C. Synaptic memories upside down: bidirectional plasticity at cerebellar parallel fiber-Purkinje cell synapses.Neuron. 2006; 52: 227-238Abstract Full Text Full Text PDF PubMed Scopus (213) Google Scholar [cerebellum]). However, a preeminent role of LTP—and, in extension, synaptic plasticity—in learning has been challenged based on the argument that properties of LTP do not match crucial properties of learning. Most importantly, learning can result from single experiences, whereas LTP typically requires repetitive stimulation (for this and other critiques of the synaptic learning theory, see Gallistel and Matzel, 2013Gallistel C.R. Matzel L.D. The neuroscience of learning: beyond the Hebbian synapse.Annu. Rev. Psychol. 2013; 64: 169-200Crossref PubMed Scopus (53) Google Scholar, Gallistel and Balsam, 2014Gallistel C.R. Balsam P.D. Time to rethink the neural mechanisms of learning and memory.Neurobiol. Learn. Mem. 2014; 108: 136-144Crossref PubMed Scopus (29) Google Scholar). New technologies based on the manipulation of neuronal activity using optogenetics now allow us to monitor and manipulate “mnemic traces” (Semon, 1904Semon R. Die Mneme als erhaltendes Prinzip im Wechsel des organischen Geschehens. Wilhelm Engelmann, Leipzig1904Google Scholar), or memory engrams, enabling a critical assessment of established views on the cellular events that underlie memory storage and retrieval (for a review, see Tonegawa et al., 2015Tonegawa S. Pignatelli M. Roy D.S. Ryan T.J. Memory engram storage and retrieval.Curr. Opin. Neurobiol. 2015; 35: 101-109Crossref PubMed Scopus (51) Google Scholar, Holtmaat and Caroni, 2016Holtmaat A. Caroni P. Functional and structural underpinnings of neuronal assembly formation in learning.Nat. Neurosci. 2016; 19: 1553-1562Crossref PubMed Scopus (21) Google Scholar). Using these techniques, Nabavi et al., 2014Nabavi S. Fox R. Proulx C.D. Lin J.Y. Tsien R.Y. Malinow R. Engineering a memory with LTD and LTP.Nature. 2014; 511: 348-352Crossref PubMed Scopus (266) Google Scholar were able to show that optogenetic stimulation of auditory inputs to the amygdala, timed to mimic LTD and LTP protocols, successfully inactivates and reactivates fear memories, respectively. This finding is in line with the long-standing notion that synaptic plasticity is a cellular correlate of learning (e.g., blockade of N-methyl-D-aspartate [NMDA] receptor signaling or Ca2+/calmodulin-dependent protein kinase II [CaMKII] activation prevents LTP and impairs fear conditioning; Kim et al., 1991Kim J.J. DeCola J.P. Landeira-Fernandez J. Fanselow M.S. N-methyl-D-aspartate receptor antagonist APV blocks acquisition but not expression of fear conditioning.Behav. Neurosci. 1991; 105: 126-133Crossref PubMed Scopus (237) Google Scholar, Miller et al., 2002Miller S. Yasuda M. Coats J.K. Jones Y. Martone M.E. Mayford M. Disruption of dendritic translation of CaMKIIalpha impairs stabilization of synaptic plasticity and memory consolidation.Neuron. 2002; 36: 507-519Abstract Full Text Full Text PDF PubMed Scopus (325) Google Scholar; but see also Gu et al., 2002Gu Y. McIlwain K.L. Weeber E.J. Yamagata T. Xu B. Antalffy B.A. Reyes C. Yuva-Paylor L. Armstrong D. Zoghbi H. et al.Impaired conditioned fear and enhanced long-term potentiation in Fmr2 knock-out mice.J. Neurosci. 2002; 22: 2753-2763Crossref PubMed Google Scholar, for a dissociation between effects on LTP and fear conditioning in a fragile X syndrome mouse model). The study does not, however, provide a critical test for a general, pan-essential involvement of synaptic plasticity in memory formation. Optogenetics has also been used to study memory storage and retrieval by engram cells. An important first step has been the development of transgenic mice, in which activation of the c-fos promoter is coupled to the expression of the tetracycline transactivator (tTA; Reijmers et al., 2007Reijmers L.G. Perkins B.L. Matsuo N. Mayford M. Localization of a stable neural correlate of associative memory.Science. 2007; 317: 1230-1233Crossref PubMed Scopus (297) Google Scholar). Using this technique, it is possible to label neurons that have been activated (c-fos promoter) during a specific conditioning period (conditioning in the absence of doxycycline; Reijmers et al., 2007Reijmers L.G. Perkins B.L. Matsuo N. Mayford M. Localization of a stable neural correlate of associative memory.Science. 2007; 317: 1230-1233Crossref PubMed Scopus (297) Google Scholar). When coupled to the expression of channelrhodopsin 2 and the fluorescent marker enhanced yellow fluorescent protein (EYFP) (ChR2-EYFP), an elegant system becomes available that allows for the fluorescence labeling and light-triggered re-activation of neurons that participate in a memory engram (Figure 1A). This technique has been used to optogenetically retrieve fear memories in the hippocampus. The experiments were designed to obtain an expression of ChR2-EYFP only in those neurons of the dentate gyrus that were active during the conditioning phase and in which the c-fos promoter was activated. Subsequent light stimulation resulted in increased freezing, suggesting a successful, optogenetic retrieval of the fear memory engram (Liu et al., 2012Liu X. Ramirez S. Pang P.T. Puryear C.B. Govindarajan A. Deisseroth K. Tonegawa S. Optogenetic stimulation of a hippocampal engram activates fear memory recall.Nature. 2012; 484: 381-385Crossref PubMed Scopus (5) Google Scholar; for a review, see Tonegawa et al., 2015Tonegawa S. Pignatelli M. Roy D.S. Ryan T.J. Memory engram storage and retrieval.Curr. Opin. Neurobiol. 2015; 35: 101-109Crossref PubMed Scopus (51) Google Scholar). Photo-activation has subsequently been used to create artificial neuronal ensembles in the visual cortex that can be reactivated upon stimulation of individual neurons participating in the ensemble (Carrillo-Reid et al., 2016Carrillo-Reid L. Yang W. Bando Y. Peterka D.S. Yuste R. Imprinting and recalling cortical ensembles.Science. 2016; 353: 691-694Crossref PubMed Scopus (148) Google Scholar). The photo-activation of channelrhodopsin opens nonspecific cation conductances that depolarize the labeled neurons and initiates spike firing (Figure 1B). In these studies, light-triggered memory recall rests on the channelrhodopsin-mediated depolarization that brings the cell closer to the spike threshold. Remarkably, in the presence of the protein synthesis inhibitor anisomycin, which blocks the late phase of LTP, photo-activation caused freezing at a rate that was indistinguishable from controls (Ryan et al., 2015Ryan T.J. Roy D.S. Pignatelli M. Arons A. Tonegawa S. Memory. Engram cells retain memory under retrograde amnesia.Science. 2015; 348: 1007-1013Crossref PubMed Scopus (110) Google Scholar). Context-dependent freezing also took place, although at a significantly reduced rate. Of note, anisomycin treatment prevented the strengthening of synaptic weights and the increase in spine density that is observed under control conditions but unveiled an increase in intrinsic excitability (slope of the spike frequency versus injected current curve; f-i curve) (Ryan et al., 2015Ryan T.J. Roy D.S. Pignatelli M. Arons A. Tonegawa S. Memory. Engram cells retain memory under retrograde amnesia.Science. 2015; 348: 1007-1013Crossref PubMed Scopus (110) Google Scholar). These studies allow several conclusions of interest. First, the observation that photo-activation alone—in control or anisomycin-treated mice—triggers freezing shows that the ultimately decisive factor in memory recall is the suprathreshold re-activation of participating engram cells. From the perspective of synaptic learning theories, the interpretation of this finding is that, under physiological conditions, enhanced synaptic weights increase the probability for spike firing in the engram cell and that photo-stimulation simply bypasses the need for a sufficiently strong synaptic drive (Nabavi et al., 2014Nabavi S. Fox R. Proulx C.D. Lin J.Y. Tsien R.Y. Malinow R. Engineering a memory with LTD and LTP.Nature. 2014; 511: 348-352Crossref PubMed Scopus (266) Google Scholar, Poo et al., 2016Poo M.M. Pignatelli M. Ryan T.J. Tonegawa S. Bonhoeffer T. Martin K.C. Rudenko A. Tsai L.H. Tsien R.W. Fishell G. et al.What is memory? The present state of the engram.BMC Biol. 2016; 14: 40Crossref PubMed Scopus (43) Google Scholar). However, freezing also occurs in anisomycin-treated mice when they are placed in the context in which they were conditioned—in the absence of photo-activation and in the absence of synapse or spine plasticity but with a significant, >30% increase in excitability present (Ryan et al., 2015Ryan T.J. Roy D.S. Pignatelli M. Arons A. Tonegawa S. Memory. Engram cells retain memory under retrograde amnesia.Science. 2015; 348: 1007-1013Crossref PubMed Scopus (110) Google Scholar). Together, these findings raise the possibility that non-synaptic, cell-autonomous modulation of neuronal excitability is sufficient for engram integration under some conditions (Figure 1C) and that, therefore, synaptic plasticity is not essential for the integration process (note that the terms “non-synaptic” and “intrinsic” refer to the expression phase of this form of plasticity; synaptic activation is needed for its induction). An intrinsic plasticity-dependent engram model is reminiscent of a class of so-called “constructive” machine learning algorithms in which the ability to move artificial neurons in and out of ensembles is used for optimization of multiple-layer networks (e.g., Mezard and Nadal, 1989Mezard M. Nadal J.P. Learning in feedforward layered networks: the tiling algorithm.J. Phys. Math. Gen. 1989; 22: 2191-2203Crossref Scopus (228) Google Scholar, Marblestone et al., 2016Marblestone A.H. Wayne G. Kording K.P. Toward an integration of deep learning and neuroscience.Front. Comput. Neurosci. 2016; 10: 94Crossref PubMed Scopus (43) Google Scholar). Intrinsic plasticity functionally resembles such a mechanism because it modulates the activity level and output efficacy of the entire neuron rather than selected subsets of its inputs. But is there indeed a physiological equivalent to such operating algorithms used in machine learning? Although intrinsic plasticity has been observed in electrophysiological recordings and has been characterized in some molecular and cellular detail, a conceptual framework for its role in learning and memory is still missing. Here we will summarize what is known about intrinsic plasticity, present first steps toward an “intrinsic theory” of learning, and discuss which experiments are needed to test whether intrinsic plasticity can indeed assume key functions in learning and memory. We suggest that purely synaptic learning theories are no longer enough to reconcile models of information storage in neural networks with the emerging role of entire neurons (“engram cells”) in memory engram physiology. We propose an extended learning hypothesis in which we assign a more broadly defined role in establishing connectivity maps to synapses and add plasticity of intrinsic excitability as a mechanism for engram integration:(1)The decisive factor in memory engram formation and recall is the activation/integration of participating neurons (engram cells). Two plasticity processes are critically involved: synaptic and intrinsic plasticity.(2)Intrinsic plasticity sets an amplification factor that enhances or lowers synaptic penetrance and defines the neuron’s presence within a memory engram. Here we introduce the term synaptic penetrance in analogy to genetic penetrance to describe that synaptic weight changes (as in LTP) do not always result in enhanced spike firing but that other factors, such as intrinsic amplification, provide important co-determinants. Intrinsic plasticity alone can, under some conditions, mediate engram cell integration based on pre-existing but unaltered synaptic connectivity.(3)Synapses play three fundamental roles in learning: they convey the specific information contents and input patterns that are to be memorized; synaptic plasticity shapes connectivity maps by establishing connection patterns and by assigning synaptic weights; and synaptic activity triggers intrinsic plasticity (induction phase) and drives the (re)activation of memory engrams, albeit without the need for accompanying changes in synaptic weight.(4)From the above, it follows that learned information is represented in two different ways in memory engrams: first by the synaptic inputs that convey information to a neuron and collectively determine the coding identity of this neuron, and second by the neuron itself, whose response threshold and activation characteristics determine its effect on target circuits and the representation weight of the information it encodes. In a recent review, we compared molecular signaling cascades involved in LTD and developmental synaptic pruning at synapses in the visual cortex, the cerebellum, and at the neuromuscular junction and found that, at each type of synapse, the signaling pathways used for developmental and adult plasticity almost completely overlap (Piochon et al., 2016aPiochon C. Kano M. Hansel C. LTD-like molecular pathways in developmental synaptic pruning.Nat. Neurosci. 2016; 19: 1299-1310Crossref PubMed Scopus (36) Google Scholar). This observation suggests that forms of synaptic plasticity found in the adult brain (LTD and LTP) may serve similar functions as their equivalents in the developing brain; namely, the weakening/elimination of weak synapses and the strengthening/stabilization of efficient ones. A more general prediction from these findings is that the optimization of neural circuits and synaptic input maps continues into adulthood and that synaptic plasticity is the cellular tool used to fine-tune these connectivity maps in an experience-dependent way. This prediction is the basis for a core claim of our hypothesis: synaptic plasticity primarily forms and adjusts connectivity maps and only under specific conditions contributes to acute learning effects. What then is the evidence that intrinsic plasticity provides a crucial cellular learning correlate? Most importantly, intrinsic plasticity has been observed in vivo (Table 1), and available evidence demonstrates a role in some forms of learning. Using intracellular recordings from layer 5 pyramidal neurons in the motor cortex of anesthetized rats, Paz et al., 2009Paz J.T. Mahon S. Tiret P. Genet S. Delord B. Charpier S. Multiple forms of activity-dependent intrinsic plasticity in layer V cortical neurones in vivo.J. Physiol. 2009; 587: 3189-3205Crossref PubMed Scopus (22) Google Scholar found that repeated injection of suprathreshold, depolarizing current pulses led to a long-term change in the intrinsic excitability of these neurons. Excitability was determined by injecting current pulses during the test periods before and after tetanization and by measuring the slope of the f-i curve as well as the spike threshold and was altered in 21 of 33 recordings. Intrinsic potentiation occurred about twice as often as depression (Paz et al., 2009Paz J.T. Mahon S. Tiret P. Genet S. Delord B. Charpier S. Multiple forms of activity-dependent intrinsic plasticity in layer V cortical neurones in vivo.J. Physiol. 2009; 587: 3189-3205Crossref PubMed Scopus (22) Google Scholar). Similarly, repeated current injection caused intrinsic potentiation (18 of 30) or depression (12 of 30) in layer 5 pyramidal neurons of the barrel cortex of anesthetized rats (Mahon and Charpier, 2012Mahon S. Charpier S. Bidirectional plasticity of intrinsic excitability controls sensory inputs efficiency in layer 5 barrel cortex neurons in vivo.J. Neurosci. 2012; 32: 11377-11389Crossref PubMed Scopus (21) Google Scholar; for example traces from layer 2/3 barrel cortex neurons, see Figure 2). Importantly, intrinsic plasticity is not an artifact of anesthesia; increases in spontaneous spike firing were observed subsequent to parallel fiber (PF) burst stimulation in Purkinje cells of non-anesthetized, decerebrated rats (Belmeguenai et al., 2010Belmeguenai A. Hosy E. Bengtsson F. Pedroarena C.M. Piochon C. Teuling E. He Q. Ohtsuki G. De Jeu M.T. Elgersma Y. et al.Intrinsic plasticity complements long-term potentiation in parallel fiber input gain control in cerebellar Purkinje cells.J. Neurosci. 2010; 30: 13630-13643Crossref PubMed Scopus (57) Google Scholar). These studies show that intrinsic plasticity is an activity-dependent phenomenon that can be observed in vivo in cell types as diverse as pyramidal cells and Purkinje cells. They also show that intrinsic plasticity differs from homeostatic plasticity (for a review, see Turrigiano, 2011Turrigiano G. Too many cooks? Intrinsic and synaptic homeostatic mechanisms in cortical circuit refinement.Annu. Rev. Neurosci. 2011; 34: 89-103Crossref PubMed Scopus (302) Google Scholar) because, in the majority of recordings, neuronal activation causes a further increase in spike firing.Table 1Intrinsic Plasticity Studied Using In Vivo Electrical or Behavioral ConditioningCircuitNeuronMethodConditioningExcitabilityMechanismReferenceMotor cortex (cat)neuronsintracellular recording (awake)eyeblink↑NDAou et al., 1992Aou S. Woody C.D. Birt D. Increases in excitability of neurons of the motor cortex of cats after rapid acquisition of eye blink conditioning.J. Neurosci. 1992; 12: 560-569Crossref PubMed Google ScholarMotor cortex (rat)LV pyramidal cellsintracellular recording (anesthetized)intracellular conditioning↑ ↓NDPaz et al., 2009Paz J.T. Mahon S. Tiret P. Genet S. Delord B. Charpier S. Multiple forms of activity-dependent intrinsic plasticity in layer V cortical neurones in vivo.J. Physiol. 2009; 587: 3189-3205Crossref PubMed Scopus (22) Google ScholarSomatosensory cortex (rat)LV pyramidal cellsintracellular recording (anesthetized)intracellular conditioning↑ ↓SK-type K current? (Sourdet et al., 2003Sourdet V. Russier M. Daoudal G. Ankri N. Debanne D. Long-term enhancement of neuronal excitability and temporal fidelity mediated by metabotropic glutamate receptor subtype 5.J. Neurosci. 2003; 23: 10238-10248Crossref PubMed Google Scholar)Mahon and Charpier, 2012Mahon S. Charpier S. Bidirectional plasticity of intrinsic excitability controls sensory inputs efficiency in layer 5 barrel cortex neurons in vivo.J. Neurosci. 2012; 32: 11377-11389Crossref PubMed Scopus (21) Google ScholarCA1 hippocampus (rabbit)pyramidal cellsintracellular recording in slice (in vivo conditioning)eyeblink↑SK- or BK-type K current? (McKay et al., 2012McKay B.M. Oh M.M. Galvez R. Burgdorf J. Kroes R.A. Weiss C. Adelman J.P. Moskal J.R. Disterhoft J.F. Increasing SK2 channel activity impairs associative learning.J. Neurophysiol. 2012; 108: 863-870Crossref PubMed Scopus (20) Google Scholar, Matthews and Disterhoft, 2009Matthews E.A. Disterhoft J.F. Blocking the BK channel impedes acquisition of trace eyeblink conditioning.Learn. Mem. 2009; 16: 106-109Crossref PubMed Scopus (26) Google Scholar)Disterhoft et al., 1986Disterhoft J.F. Coulter D.A. Alkon D.L. Conditioning-specific membrane changes of rabbit hippocampal neurons measured in vitro.Proc. Natl. Acad. Sci. USA. 1986; 83: 2733-2737Crossref PubMed Google ScholarCA1 hippocampus (rat)pyramidal cellswhole-cell recordings in slice (in vivo conditioning)fear conditioning↑ ↓NDMcKay et al., 2009McKay B.M. Matthews E.A. Oliveira F.A. Disterhoft J.F. Intrinsic neuronal excitability is reversibly altered by a single experience in fear conditioning.J. Neurophysiol. 2009; 102: 2763-2770Crossref PubMed Scopus (39) Google ScholarLateral amygdala (mouse)principal neuronswhole-cell recordingsoverexpression CREB or dnKCNQ2↑CREB fear memory allocation during subsequent trainingYiu et al., 2014Yiu A.P. Mercaldo V. Yan C. Richards B. Rashid A.J. Hsiang H.L. Pressey J. Mahadevan V. Tran M.M. Kushner S.A. et al.Neurons are recruited to a memory trace based on relative neuronal excitability immediately before training.Neuron. 2014; 83: 722-735Abstract Full Text Full Text PDF PubMed Scopus (108) Google ScholarCerebellum (rabbit)Purkinje cellsintracellular recording in slice (in vivo conditioning)eyeblink↑A-type K currentSchreurs et al., 1998Schreurs B.G. Gusev P.A. Tomsic D. Alkon D.L. Shi T. Intracellular correlates of acquisition and long-term memory of classical conditioning in Purkinje cell dendrites in slices of rabbit cerebellar lobule HVI.J. Neurosci. 1998; 18: 5498-5507Crossref PubMed Google ScholarCerebellum (rat)Purkinje cellssingle-unit extracellular (awake, decerebrated)synaptic activation↑SK-type K currentBelmeguenai et al., 2010Belmeguenai A. Hosy E. Bengtsson F. Pedroarena C.M. Piochon C. Teuling E. He Q. Ohtsuki G. De Jeu M.T. Elgersma Y. et al.Intrinsic plasticity complements long-term potentiation in parallel fiber input gain control in cerebellar Purkinje cells.J. Neurosci. 2010; 30: 13630-13643Crossref PubMed Scopus (57) Google ScholarThe table summarizes reports of intrinsic plasticity observed during in vivo recordings or in recordings from slices that were prepared subsequent to in vivo conditioning. Note that this is an incomprehensive selection that is focused on mammalian studies. ND, not determined; CREB, cAMP response element-binding protein. The question marks in the Mechanism column indicate that the cellular mechanisms listed here are suggested by separate studies other than the main reference. Open table in a new tab The table summarizes reports of intrinsic plasticity observed during in vivo recordings or in recordings from slices that were prepared subsequent to in vivo conditioning. Note that this is an incomprehensive selection that is focused on mammalian studies. ND, not determined; CREB, cAMP response element-binding protein. The question marks in the Mechanism column indicate that the cellular mechanisms listed here are suggested by separate studies other than the main reference. Plasticity of the intrinsic membrane excitability of neurons has been discussed for many years as a mechanism that might play a role in learning, possibly complementing forms of synaptic plasticity (for a review, see Marder et al., 1996Marder E. Abbott L.F. Turrigiano G.G. Liu Z. Golowasch J. Memory from the dynamics of intrinsic membrane currents.Proc. Natl. Acad. Sci. USA. 1996; 93: 13481-13486Crossref PubMed Scopus (178) Google Scholar, Hansel et al., 2001Hansel C. Linden D.J. D’Angelo E. Beyond parallel fiber LTD: the diversity of synaptic and non-synaptic plasticity in the cerebellum.Nat. Neurosci. 2001; 4: 467-475Crossref PubMed Scopus (487) Google Scholar, Daoudal and Debanne, 2003Daoudal G. Debanne D. Long-term plasticity of intrinsic excitability: learning rules and mechanisms.Learn. Mem. 2003; 10: 456-465Crossref PubMed Scopus (300) Google Scholar, Zhang and Linden, 2003Zhang W. Linden D.J. The other side of the engram: experience-driven changes in neuronal intrinsic excitability.Nat. Rev. Neurosci. 2003; 4: 885-900Crossref PubMed Scopus (482) Google Scholar, Frick and Johnston, 2005Frick A. Johnston D. Plasticity of dendritic excitability.J. Neurobiol. 2005; 64: 100-115Crossref PubMed Scopus (92) Google Scholar, Mozzachiodi and Byrne, 2010Mozzachiodi R. Byrne J.H. More than synaptic plasticity: role of nonsynaptic plasticity in learning and memory.Trends Neurosci. 2010; 33: 17-26Abstract Full Text Full Text PDF PubMed Scopus (121) Google Scholar). Intrinsic plasticity has been described in a variety of preparations but has been most often examined in recordings from brain slices. The phenomenon itself is less strictly defined than synaptic plasticity and has been probed using various measures, such as spontaneous and evoked spike rates, the spike threshold, and the afterhyperpolarization (AHP) amplitude. Similar to synaptic plasticity, intrinsic excitability changes may result from brain-derived neurotrophic factor (BDNF) signaling (Desai et al., 1999Desai N.S. Rutherford L.C. Turrigiano G.G. BDNF regulates the intrinsic excitability of cortical neurons.Learn. Mem. 1999; 6: 284-291Crossref PubMed Google Scholar, Graves et al., 2016Graves A.R. Moore S.J. Spruston N. Tryba A.K. Kaczorowski C.C. Brain-derived neurotrophic factor differentially modulates excitability of two classes of hippocampal output neurons.J. Neurophysiol. 2016; 116: 466-471Crossref PubMed Scopus (8) Google Scholar). In contrast to synaptic plasticity, intrinsic plasticity is not mediated by changes in neurotransmitter receptors but results from modifications of voltage- or calcium-dependent ion channels such as potassium (K) channels or mixed Na/K channels. For example, forms of intrinsic plasticity have been described that are mediated by changes in A-type K channels (Schreurs et al., 1998Schreurs B.G. Gusev P.A. Tomsic D. Alkon D.L. Shi T. Intracellular correlates of acquisition and long-term memory of classical conditioning in Purkinje cell dendrites in slices of rabbit cerebellar lobule HVI.J. Neurosci. 1998; 18: 5498-5507Crossref PubMed Google Scholar, Frick et al., 2004Frick A. Magee J. Johnston D. LTP is accompanied by an enhanced local excitability of pyramidal neuron dendrites.Nat. Neurosci. 2004; 7: 126-135Crossref PubMed Scopus (292) Google Scholar), large-conductance, calcium-dependent K (BK) channels (Nelson et al., 2005Nelson A.B. Gittis A.H. du Lac S. Decreases in CaMKII activity trigger persistent potentiation of intrinsic excitability in spontaneously firing vestibular nucleus neurons.Neuron. 2005; 46: 623-631Abstract Full Text Full Text PDF PubMed Scopus (79) Google Scholar), small-conductance, calcium-dependent K (SK) channels (Sourdet et al., 2003Sourdet V. Russier M. Daoudal G. Ankri N. Debanne D. Long-term enhancement of neuronal excitability and temporal fidelity mediated by metabotropic glutamate receptor subtype 5.J. Neurosci. 2003; 23: 10238-10248Crossref PubMed Google Scholar, Lin et al., 2008Lin M.T. Luján R. Watanabe M. Adelman J.P. Maylie J. SK2 channel plasticity contributes to LTP at Schaffer collateral-CA1 synapses.Nat. Neurosci. 2008; 11: 170-177Crossref PubMed Scopus (127) Google Scholar, Belmeguenai et al., 2010Belmeguenai A. Hosy E. Bengtsson F. Pedroarena C.M. Piochon C. Teuling E. He Q. Ohtsuki G. De Jeu M.T. Elgersma Y. et al.Intrinsic plasticity complements long-term potentiation in parallel fiber input gain control in cerebellar Purkinje cells.J. Neurosci. 2010; 30: 13630-13643Crossref PubMed Scopus (57) Google Scholar), as well as hyperpolarization-activated and cyclic nucleotide-gated (HCN) channels (Nolan et al., 2003Nolan M.F. Malleret G. Lee K.H. Gibbs E. Dudman J.T. Santoro B. Yin D. Thompson R.F. Siegelbaum S.A. Kandel E.R. Morozov A. The hyperpolarization-activated HCN1 channel is important for motor" @default.
• W2725814939 created "2017-07-14" @default.
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• W2725814939 date "2017-07-01" @default.
• W2725814939 modified "2023-10-14" @default.
• W2725814939 title "Toward a Neurocentric View of Learning" @default.
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