Synaptic Mechanisms for Plasticity in Neocortex

Department of Molecular and Cell Biology, and Helen Wills Neuroscience Institute, University of California, Berkeley, USA.
Annual Review of Neuroscience (Impact Factor: 19.32). 04/2009; 32(1):33-55. DOI: 10.1146/annurev.neuro.051508.135516
Source: PubMed


Sensory experience and learning alter sensory representations in cerebral cortex. The synaptic mechanisms underlying sensory cortical plasticity have long been sought. Recent work indicates that long-term cortical plasticity is a complex, multicomponent process involving multiple synaptic and cellular mechanisms. Sensory use, disuse, and training drive long-term potentiation and depression (LTP and LTD), homeostatic synaptic plasticity and plasticity of intrinsic excitability, and structural changes including formation, removal, and morphological remodeling of cortical synapses and dendritic spines. Both excitatory and inhibitory circuits are strongly regulated by experience. This review summarizes these findings and proposes that these mechanisms map onto specific functional components of plasticity, which occur in common across the primary somatosensory, visual, and auditory cortices.

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    • ", 1975 ; Thompson et al . , 1983 ; Feldman , 2009 ) , but it is at least two orders of magnitude slower than the timescale of associative plasticity , which changes synaptic weights within minutes or even tens of seconds . Runaway dynamics of synaptic weights and activity can be induced by Hebbian - type learning rules within seconds or minutes ( e . "
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    ABSTRACT: Homosynaptic Hebbian-type plasticity provides a cellular mechanism of learning and refinement of connectivity during development in a variety of biological systems. In this review we argue that a complimentary form of plasticity-heterosynaptic plasticity-represents a necessary cellular component for homeostatic regulation of synaptic weights and neuronal activity. The required properties of a homeostatic mechanism which acutely constrains the runaway dynamics imposed by Hebbian associative plasticity have been well-articulated by theoretical and modeling studies. Such mechanism(s) should robustly support the stability of operation of neuronal networks and synaptic competition, include changes at non-active synapses, and operate on a similar time scale to Hebbian-type plasticity. The experimentally observed properties of heterosynaptic plasticity have introduced it as a strong candidate to fulfill this homeostatic role. Subsequent modeling studies which incorporate heterosynaptic plasticity into model neurons with Hebbian synapses (utilizing an STDP learning rule) have confirmed its ability to robustly provide stability and competition. In contrast, properties of homeostatic synaptic scaling, which is triggered by extreme and long lasting (hours and days) changes of neuronal activity, do not fit two crucial requirements for a hypothetical homeostatic mechanism needed to provide stability of operation in the face of on-going synaptic changes driven by Hebbian-type learning rules. Both the trigger and the time scale of homeostatic synaptic scaling are fundamentally different from those of the Hebbian-type plasticity. We conclude that heterosynaptic plasticity, which is triggered by the same episodes of strong postsynaptic activity and operates on the same time scale as Hebbian-type associative plasticity, is ideally suited to serve a homeostatic role during on-going synaptic plasticity.
    Frontiers in Computational Neuroscience 07/2015; 9:89. DOI:10.3389/fncom.2015.00089 · 2.20 Impact Factor
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    • "Thus, the details of short-term synaptic plasticity and dendritic integration are both major factors in determining the net change in synaptic strength in response to complex pre-and postsynaptic spike trains. Both frequency-dependent and spike timing–dependent synaptic modifications are likely due to similar or the same underlying biological processes (Feldman 2009, Sjöström & Nelson 2002). "
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    ABSTRACT: Synapses are highly plastic and are modified by changes in patterns of neural activity or sensory experience. Plasticity of cortical excitatory synapses is thought to be important for learning and memory, leading to alterations in sensory representations and cognitive maps. However, these changes must be coordinated across other synapses within local circuits to preserve neural coding schemes and the organization of excitatory and inhibitory inputs, i.e., excitatory-inhibitory balance. Recent studies indicate that inhibitory synapses are also plastic and are controlled directly by a large number of neuromodulators, particularly during episodes of learning. Many modulators transiently alter excitatory-inhibitory balance by decreasing inhibition, and thus disinhibition has emerged as a major mechanism by which neuromodulation might enable long-term synaptic modifications naturally. This review examines the relationships between neuromodulation and synaptic plasticity, focusing on the induction of long-term changes that collectively enhance cortical excitatory-inhibitory balance for improving perception and behavior. Expected final online publication date for the Annual Review of Neuroscience Volume 38 is July 08, 2015. Please see for revised estimates.
    Annual Review of Neuroscience 04/2015; 38(1). DOI:10.1146/annurev-neuro-071714-034002 · 19.32 Impact Factor
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    • "Training-dependent gains in performance may appear hours after the termination of training, for example 24 h post-training. It has been proposed that these delayed ( " offline " ) gains in performance reflect memory consolidation neural processes within the processing stream that are involved in task performance, i.e., these processes are triggered by the training experience but require time to reach completion (Feldman, 2009; Xu et al., 2009; Caroni et al., 2012). The resulting gains are maintained for weeks (e.g., Korman et al., 2003; Dorfberger et al., 2007; but see Savion-Lemieux and Penhune, 2005). "
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    ABSTRACT: Many new skills are acquired during early childhood. Typical laboratory skill learning tasks are not applicable for developmental studies that involve children younger than 8 years of age. It is not clear whether young children and adults share a basic underlying skill learning mechanism. In the present study, the learning and retention of a simple grapho-motor pattern were studied in three age groups: 5–6, 7–8, and 19–29 years. Each block of the task consists of identical patterns arranged in a spaced writing array. Progression across the block involves on-page movements while producing the pattern, and off-page movements between patterns.The participants practiced the production of the pattern using a digitizing tablet and were tested at 24 h and 2 weeks post-practice. All age groups produced the task blocks more quickly with practice, and the learning rate was inversely related to the initial production time. All groups exhibited additional gains 24 h post-practice that were well-retained 2 weeks later. The accuracy of the participants was maintained throughout the 2-weeks period. These findings suggest that young children and young adults use a similar mechanism when learning the task. Nevertheless, the 6-years-old spent more time off-page during retention testing than when tested at 24 h post-practice, thus supporting the notion that an age advantage may exists in the long-term retention of skills due to planning-dependent aspects.
    Frontiers in Psychology 04/2015; 6. DOI:10.3389/fpsyg.2015.00225 · 2.80 Impact Factor
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