Abstract

Long-term potentiation (LTP) of synaptic transmission is traditionally elicited by massively synchronous, high-frequency inputs, which rarely occur naturally. Recent in vitro experiments have revealed that both LTP and long-term depression (LTD) can arise by appropriately pairing weak synaptic inputs with action potentials in the postsynaptic cell. This discovery has generated new insights into the conditions under which synaptic modification may occur in pyramidal neurons in vivo. First, it has been shown that the temporal order of the synaptic input and the postsynaptic spike within a narrow temporal window determines whether LTP or LTD is elicited, according to a temporally asymmetric Hebbian learning rule. Second, backpropagating action potentials are able to serve as a global signal for synaptic plasticity in a neuron compared with local associative interactions between synaptic inputs on dendrites. Third, a specific temporal pattern of activity -postsynaptic bursting -accompanies synaptic potentiation in adults. Introduction Acts of recollection, as they occur in experience, are due to the fact that one movement has by nature another that succeeds it in regular order. If this order be necessary, whenever a subject experiences the former of two movements thus connected, it will (invariably) experience the latter. Aristotle, Fourth century B.C. De memoria et reminiscentia [Title translation: On memory and reminiscences] This citation from Aristotle highlights two properties of long-term memories for facts and events: their associative nature and their temporal order. These properties were incorporated into an influential proposal for synaptic plasticity made by Donald Hebb in 1949. He suggested that reverberatory activity in transient assemblies of neurons carries a memory trace that becomes permanently laid down as changes in synaptic weights when a presynaptic neuron repeatedly or persistently takes part in firing the postsynaptic cell [1]. Major research efforts that are underway to explain long-term memory have uncovered mechanisms that are consistent with both the associative nature and the temporal order emphasized in Hebb's proposal. The first biological mechanism discovered that could potentially support Hebb's learning rule was long-term potentiation (LTP) of synaptic transmission, as described by Bliss and Lømo [2,3]. The original protocol for inducing LTP was high-frequency stimulation of presynaptic neurons. However, the highly synchronous population activity required to induce this type of LTP has never been observed during learning in vivo. An important question is whether synaptic potentiation could be induced by more natural activity patterns based on the relative timing of presynaptic and postsynaptic activity as originally suggested by Hebb. In 1994, Stuart and Sakmann [4] reported that action potentials can backpropagate in the dendrites of cortical pyramidal neurons. More recently, it has been shown that backpropagating spikes could directly serve as an associative signal for LTP induction under some experimental conditions [5,6]. These papers have raised interest in the induction criteria for LTP, using behaviorally relevant stimuli. This paper briefly reviews the type of neuronal activity that can be recorded during learning episodes in vivo, and, with this background, discusses three fundamental questions about synaptic learning rules based on recent experimental evidence obtained in vitro: 1. Are synaptic learning rules temporal coincidence rules, or is the temporal order of presynaptic and postsynaptic activity important? 2. Is the postsynaptic induction of long-term plasticity controlled by an associative signal localized in dendritic segments, or is there a signal that is global to the neuron? 3. Is all successful information transfer through a neuron associated with updating of synaptic weights, or is there a specific type of activity that occurs during synaptic modification? In this review, we focus on the postsynaptic neuron in inducing and regulating synaptic plasticity and emphasize the predictive, in addition to the associative, nature of Hebbian learning. Natural patterns of activity and long-term synaptic plasticity Ole Paulsen* and Terrence J Sejnowski † Natural patterns of activity and long-term synaptic plasticity Paulsen and Sejnowski 173 Neuronal activity during behavioral learning The conditions for synaptic plasticity in the behaving animal must be sought among the activity patterns that occur during learning. The hippocampus is a structure of critical importance in memory for facts and events [7]. These observations raise the possibility that burst firing and phase-related firing patterns could support the induction of synaptic potentiation. Recent in vitro experiments have addressed this issue. Temporal constraint on pre-and postsynaptic activity: an asymmetric Hebbian learning rule The Hebbian learning rule has often been interpreted to mean that synaptic potentiation should occur as a consequence of coincident activity in presynaptic and postsynaptic neurons. However, Hebb's original suggestion incorporated a temporal constraint, namely that presynaptic activity must precede the activity in the postsynaptic element for potentiation to occur [1]. In computer simulations of recurrent hippocampal networks, temporally asymmetric Hebbian synaptic plasticity supports sequence learning The motion of visual stimuli provides the visual cortex with a sequence of highly correlated inputs. The development of direction selectivity in developing visual cortical neurons can be modeled with an asymmetric Hebbian rule implemented in a recurrent network [34 •• ]. Backpropagating action potentials as a global neuronal associative signal The induction of LTP at some excitatory synapses on pyramidal neurons depends on the activation of NMDA receptors [3]. NMDA receptors are thought to serve as molecular coincidence detectors, requiring the presynaptic release of glutamate immediately followed by postsynaptic depolarization. Where does the postsynaptic depolarization originate? The traditional view is that a 'strong' synaptic input can depolarize the local dendritic branch sufficiently to enable the activation of NMDA receptors at 'weak' inputs on neighboring synapses [3]. However, backpropagating action potentials could also provide the postsynaptic associative signal [35 • ]. A backpropagating action potential would serve as a global dendritic associative signal, reaching a large fraction -and potentially all -of the synapses on a single neuron. The extent of the influence of the backpropagating action potential could be subject to control by ion channels and synaptic inhibition. The physiological control of dendritic backpropagation of action potentials has recently been reviewed elsewhere [36 • ]. A specific postsynaptic activity signaling synaptic potentiation would be interesting for at least two reasons. First, it re-emphasizes the critical role of activity in the postsynaptic neuron for synaptic plasticity to occur. Second, it suggests that at least three logic levels of signaling exist in memory encoding: silence, single spikes transferring information, and bursts signifying changes in synaptic weights. Whereas in developing neurons single spikes provide the adequate signal for laying down the architecture of a network, in the adult a reinforcement signal -bursting triggered by a specific afferent input -might be required for synaptic plasticity to occur. speculate that the burst firing that is so prevalent during sleep might have a function related to the maintenance of synaptic weights in recently altered synapses ('consolidation') and for the structural reorganization of the neuropil, perhaps involving new spines and dendritic branches, which may require gene regulation Computational consequences The demonstration that patterns of activity that occur in vivo during learning can elicit long-term changes of synaptic strengths in vitro makes it more likely that we are getting closer to understanding the mechanisms underlying learning and memory. If so, then some of the conditions accompanying these changes may be important clues to the cellular substrates of the behavioral changes that accompany learning. In particular, the time scale and the temporal asymmetry in the learning rule have important implications for the organization of cortical circuits. The importance of temporal order on a millisecond time scale for eliciting LTP and LTD suggests that precise cellular and molecular mechanisms may regulate spike timing in cortical circuits The timing of a spike in the postsynaptic neuron divides the excitatory input activities that occur during the +/-20 ms temporal window into two groups: those synapses that contributed to depolarization preceding the spike, and those that cannot have contributed because they were activated after the spike. This causal structure is directly translated into synaptic plasticity by the temporally asymmetric learning rule, which potentiates those synapses that are active immediately preceding the postsynaptic spike and depresses those synapses that are active directly after the spike [5]. This takes into account the temporal order of continuous events in the world, as noted by Aristotle. The temporally asymmetric Hebbian learning rule implements the temporal difference (TD) learning algorithm in reinforcement learning Temporal order is also important for classical conditioning, though the time window is a few seconds -two orders of magnitude longer than that found in the cortex and hippocampus. Thus, TD learning can be used by the cortex to memorize long sequences of input states, which might be useful for storing a musical composition, in addition to the much slower learning of strategies for survival in an uncertain environment Perhaps the most exciting theoretical implication of the temporally asymmetric Hebbian learning rule is its ability to create and stabilize activity patterns in neural assemblies. First, the combination of LTP and LTD achieves a balance which overcomes the problem of synaptic saturation found to occur with learning rules that can only increase the strengths of synapses Conclusions All of the results reported here were from studies on pyramidal neurons. We do not have comparable knowledge of interneurons, which are highly diverse and may have a variety of different roles in regulating synaptic plasticity. Without an account of mechanisms for plasticity in interneurons it will not be possible to understand how a network of neurons learns new patterns of activity. Another important area that this review has not focused on is presynaptic mechanisms that might also be involved in the maintenance of synaptic plasticity. The discovery of backpropagating action potentials has refocused attention on the role of the postsynaptic neuron in synaptic plasticity. Evidence is mounting that the relative timing of presynaptic activity and backpropagating action potentials in the postsynaptic cell can induce longterm synaptic changes in hippocampal pyramidal neurons by activity patterns known to occur during learning in vivo. The shift of emphasis to the temporal domain has opened up an exciting new chapter in the theoretical analysis of synaptic plasticity and neural networks, in which the predictive rather than the associative nature of Hebbian learning is being explored