Long-Term Plasticity of Intrinsic Excitability: Learning Rules and Mechanisms

Abstract

Spatio-temporal configurations of distributed activity in the brain is thought to contribute to the coding of neuronal information and synaptic contacts between nerve cells could play a central role in the formation of privileged pathways of activity. Synaptic plasticity is not the exclusive mode of regulation of information processing in the brain, and persistent regulations of ionic conductances in some specialized neuronal areas such as the dendrites, the cell body, and the axon could also modulate, in the long-term, the propagation of neuronal information. Persistent changes in intrinsic excitability have been reported in several brain areas in which activity is elevated during a classical conditioning. The role of synaptic activity seems to be a determinant in the induction, but the learning rules and the underlying mechanisms remain to be defined. We discuss here the role of synaptic activity in the induction of intrinsic plasticity in cortical, hippocampal, and cerebellar neurons. Activation of glutamate receptors initiates a long-term modification in neuronal excitability that may represent a parallel, synergistic substrate for learning and memory. Similar to synaptic plasticity, long-lasting intrinsic plasticity appears to be bidirectional and to express a certain level of input or cell specificity. These nonsynaptic forms of plasticity affect the signal propagation in the axon, the dendrites, and the soma. They not only share common learning rules and induction pathways with the better-known synaptic plasticity such as NMDA receptor dependent LTP and LTD, but also contribute in synergy with these synaptic changes to the formation of a coherent engram. What Are the Cellular Learning Rules?The most remarkable feature of the brain is its capacity to collect new information from the environment and to store it in order to produce changes in the behavior. Over the last decades, the aim of most neuroscientists in the field of brain plasticity has been to establish learning rules that could account for this storage at the cellular level. The idea that memory storage in the brain results from activity-dependent changes in synaptic strength was developed by Hebb (1949), who proposed that excitatory synapses linking two cells could be strengthened if both cells were active simultaneously. This learning rule has been verified and extended over the last two decades (for review, see Sourdet and Debanne 1999;Abbott and Nelson 2000;Bi and Poo 2001;Sjöström and Nelson 2002). One of the goals of this review is to discuss whether the learning rules and inductions mechanisms defined for synaptic plasticity also apply to other forms of plasticity that affect ion channels in nonsynaptic structures of the neuron. Synaptic and Nonsynaptic PlasticityThe synapse is the anatomical and functional interface between individual nerve cells, and thus occupies a strategic position. It is generally considered as a privileged element involved in short-or long-term modifications of the transmission of neuronal message in the brain. The ...

Effects of Hebbian learning on the dynamics and structure of random networks with inhibitory and excitatory neurons

“…One interesting development would thus consist in trying to find learning rules or settings that would guaranty that the system remains close to the edge of chaos, even at long learning times. As an attractive possibility, the plasticity of intrinsic properties [12] could allow the network to stabilize its activity in this region. is an average over 20 realizations (standard deviations are omitted for clarity).…”

Histone H1 Poly[ADP]-Ribosylation Regulates the Chromatin Alterations Required for Learning Consolidation

“…Because long-term changes in synaptic efficacy in the hippocampus seems to be necessary for learning and memory (Daoudal and Debanne, 2003;Gruart et al, 2006;Clarke et al, 2010), we examined the role of PARP-1 in the long-lasting changes of synaptic transmission efficacy induced by highfrequency stimulation (HFS) at the CA3-CA1 synapses. Tiq-A administration before six HFS protocols (HFS, consisting of five trains at 200 Hz, lasting 100 ms, and presented at a rate of 1/s) provoked a deficit in long-LTP when compared with vehicleinjected mice tested 1 or 2 h after application of HFS protocol as suggested by the time ϫ treatment interaction (F (50,9) ϭ 6.19, p Ͻ 0.001; the fEPSP slope 1 h after HFS was 165.95 Ϯ 8.95 and 117.57 Ϯ 10.09 for vehicle-and Tiq-A-injected mice, respectively, and 2 h after HFS was 182.22 Ϯ 4.21 and 110.54 Ϯ 5.21 for vehicle-and Tiq-A-injected mice, respectively) ( Fig.…”

Delay learning and polychronization for reservoir computing

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