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 PLOS Computational Biology , 2015, DOI: 10.1371/journal.pcbi.1004632 Abstract: Glutamatergic synapse size remodeling is governed not only by specific activity forms but also by apparently stochastic processes with well-defined statistics. These spontaneous remodeling processes can give rise to skewed and stable synaptic size distributions, underlie scaling of these distributions and drive changes in glutamatergic synapse size “configurations”. Where inhibitory synapses are concerned, however, little is known on spontaneous remodeling dynamics, their statistics, their activity dependence or their long-term consequences. Here we followed individual inhibitory synapses for days, and analyzed their size remodeling dynamics within the statistical framework previously developed for glutamatergic synapses. Similar to glutamatergic synapses, size distributions of inhibitory synapses were skewed and stable; at the same time, however, sizes of individual synapses changed considerably, leading to gradual changes in synaptic size configurations. The suppression of network activity only transiently affected spontaneous remodeling dynamics, did not affect synaptic size configuration change rates and was not followed by the scaling of inhibitory synapse size distributions. Comparisons with glutamatergic synapses within the same dendrites revealed a degree of coupling between nearby inhibitory and excitatory synapse remodeling, but also revealed that inhibitory synapse size configurations changed at considerably slower rates than those of their glutamatergic neighbors. These findings point to quantitative differences in spontaneous remodeling dynamics of inhibitory and excitatory synapses but also reveal deep qualitative similarities in the processes that control their sizes and govern their remodeling dynamics.
 PLOS Biology , 2012, DOI: 10.1371/journal.pbio.0040207 Abstract: Short-term synaptic plasticity (STP) is an important mechanism for modifying neural circuits during computation. Although STP is much studied, its role in the processing of complex natural spike patterns is unknown. Here we analyze the responses of excitatory and inhibitory hippocampal synapses to natural spike trains at near-physiological temperatures. Our results show that excitatory and inhibitory synapses express complementary sets of STP components that selectively change synaptic strength during epochs of high-frequency discharge associated with hippocampal place fields. In both types of synapses, synaptic strength rapidly alternates between a near-constant level during low activity and another near-constant, but elevated (for excitatory synapses) or reduced (for inhibitory synapses) level during high-frequency epochs. These history-dependent changes in synaptic strength are largely independent of the particular temporal pattern within the discharges, and occur concomitantly in the two types of synapses. When excitatory and feed-forward inhibitory synapses are co-activated within the hippocampal feed-forward circuit unit, the net effect of their complementary STP is an additional increase in the gain of excitatory synapses during high-frequency discharges via selective disinhibition. Thus, excitatory and feed-forward inhibitory hippocampal synapses in vitro act synergistically as an adaptive filter that operates in a switch-like manner and is selective for high-frequency epochs.
 PLOS Biology , 2006, DOI: 10.1371/journal.pbio.0040207 Abstract: Short-term synaptic plasticity (STP) is an important mechanism for modifying neural circuits during computation. Although STP is much studied, its role in the processing of complex natural spike patterns is unknown. Here we analyze the responses of excitatory and inhibitory hippocampal synapses to natural spike trains at near-physiological temperatures. Our results show that excitatory and inhibitory synapses express complementary sets of STP components that selectively change synaptic strength during epochs of high-frequency discharge associated with hippocampal place fields. In both types of synapses, synaptic strength rapidly alternates between a near-constant level during low activity and another near-constant, but elevated (for excitatory synapses) or reduced (for inhibitory synapses) level during high-frequency epochs. These history-dependent changes in synaptic strength are largely independent of the particular temporal pattern within the discharges, and occur concomitantly in the two types of synapses. When excitatory and feed-forward inhibitory synapses are co-activated within the hippocampal feed-forward circuit unit, the net effect of their complementary STP is an additional increase in the gain of excitatory synapses during high-frequency discharges via selective disinhibition. Thus, excitatory and feed-forward inhibitory hippocampal synapses in vitro act synergistically as an adaptive filter that operates in a switch-like manner and is selective for high-frequency epochs.
 PLOS ONE , 2013, DOI: 10.1371/journal.pone.0054301 Abstract: Associative fear learning, resulting from whisker stimulation paired with application of a mild electric shock to the tail in a classical conditioning paradigm, changes the motor behavior of mice and modifies the cortical functional representation of sensory receptors involved in the conditioning. It also induces the formation of new inhibitory synapses on double-synapse spines of the cognate barrel hollows. We studied density and distribution of polyribosomes, the putative structural markers of enhanced synaptic activation, following conditioning. By analyzing serial sections of the barrel cortex by electron microscopy and stereology, we found that the density of polyribosomes was significantly increased in dendrites of the barrel activated during conditioning. The results revealed fear learning-induced increase in the density of polyribosomes associated with both excitatory and inhibitory synapses located on dendritic spines (in both single- and double-synapse spines) and only with the inhibitory synapses located on dendritic shafts. This effect was accompanied by a significant increase in the postsynaptic density area of the excitatory synapses on single-synapse spines and of the inhibitory synapses on double-synapse spines containing polyribosomes. The present results show that associative fear learning not only induces inhibitory synaptogenesis, as demonstrated in the previous studies, but also stimulates local protein synthesis and produces modifications of the synapses that indicate their potentiation.
 PLOS ONE , 2014, DOI: 10.1371/journal.pone.0101109 Abstract: Spike-Timing Dependent Plasticity (STDP) is characterized by a wide range of temporal kernels. However, much of the theoretical work has focused on a specific kernel – the “temporally asymmetric Hebbian” learning rules. Previous studies linked excitatory STDP to positive feedback that can account for the emergence of response selectivity. Inhibitory plasticity was associated with negative feedback that can balance the excitatory and inhibitory inputs. Here we study the possible computational role of the temporal structure of the STDP. We represent the STDP as a superposition of two processes: potentiation and depression. This allows us to model a wide range of experimentally observed STDP kernels, from Hebbian to anti-Hebbian, by varying a single parameter. We investigate STDP dynamics of a single excitatory or inhibitory synapse in purely feed-forward architecture. We derive a mean-field-Fokker-Planck dynamics for the synaptic weight and analyze the effect of STDP structure on the fixed points of the mean field dynamics. We find a phase transition along the Hebbian to anti-Hebbian parameter from a phase that is characterized by a unimodal distribution of the synaptic weight, in which the STDP dynamics is governed by negative feedback, to a phase with positive feedback characterized by a bimodal distribution. The critical point of this transition depends on general properties of the STDP dynamics and not on the fine details. Namely, the dynamics is affected by the pre-post correlations only via a single number that quantifies its overlap with the STDP kernel. We find that by manipulating the STDP temporal kernel, negative feedback can be induced in excitatory synapses and positive feedback in inhibitory. Moreover, there is an exact symmetry between inhibitory and excitatory plasticity, i.e., for every STDP rule of inhibitory synapse there exists an STDP rule for excitatory synapse, such that their dynamics is identical.
 Neural Development , 2011, DOI: 10.1186/1749-8104-6-31 Abstract: We demonstrate that YFP-NL2 is present at inhibitory synapses in the inner plexiform layer by its co-localization with gephyrin, the γ2 subunit of the GABAA receptor and glycine receptors. YFP-NL2 puncta were apposed to the vesicular inhibitory transmitter transporter VGAT but not to CtBP2, a marker of presynaptic ribbons found at bipolar cell terminals. Similar patterns of co-localization with synaptic markers were observed for endogenous NL2. We also verified that expression of YFP-NL2 in the transgenic line did not significantly alter spontaneous inhibitory synaptic transmission onto RGCs. Using these mice, we found that, on average, the density of inhibitory synapses on individual arbors increased gradually until eye opening (postnatal day 15). A small centro-peripheral gradient in density found in mature arbors was apparent at the earliest age we examined (postnatal day 8). Unexpectedly, the adult ratio of inhibitory/excitatory postsynaptic sites was rapidly attained, shortly after glutamatergic synaptogenesis commenced (postnatal day 7).Our observations suggest that bipolar and amacrine cell synaptogenesis onto RGCs appear coordinated to rapidly attain a balanced ratio of excitatory and inhibitory synapse densities prior to the onset of visual experience.The normal functioning of the nervous system requires balanced excitatory and inhibitory neurotransmission. If excitation or inhibition is perturbed, neurons undergo alterations in their intrinsic excitability and synaptic transmission in order to restore a balance, and prevent their circuits from undergoing epileptiform activity [1,2]. While such homeostatic plasticity in mature neuronal networks is well studied [3], much less is known concerning how balanced excitation and inhibition is normally achieved during development. In many parts of the central nervous system (CNS), interneurons containing the classical inhibitory transmitters γ-aminobutyric acid (GABA) or glycine form functional synaptic connections
 Hideo Hasegawa Quantitative Biology , 1999, Abstract: Numerical calculations have been made on the spike-train response of a pair of Hodgkin-Huxley (HH) neurons coupled by synapses and axons with time delay. The recurrent excitatory-excitatory, inhibitory-inhibitory, excitatory-inhibitory, and inhibitory-excitatory couplings are adopted. The coupled, excitable HH neurons are assumed to receive the two kinds of spike-train inputs: the transient input consisting of M impulses for the finite duration (M: integer) and the sequential input with the constant interspike interval (ISI). The HH neurons in all the kinds of couplings are found to play a role of memory storage with on-off switching. When the coupling strength and the time delay are changed, the distribution of the output ISI $T_{\rm o}$ shows bifurcation (multifurcation), metastability and chaotic behavior. The calculation of the time correlation shows that the synchronization between the two HH neurons is well preserved even when the distribution of their $T_{\rm o}$ is chaotic. The correlation dimension of the cycles of $T_{\rm o}$ is shown to depend not only on the model parameters but also on the type of input ISIs.
 Frontiers in Neuroanatomy , 2014, DOI: 10.3389/fnana.2014.00108 Abstract: In the inferior colliculus (IC) cells integrate inhibitory input from the brainstem and excitatory input from both the brainstem and auditory cortex. In order to understand how these inputs are integrated by IC cells identification of their synaptic arrangements is required. We used electron microscopy to characterize GABAergic synapses in the dorsal cortex, central nucleus, and lateral cortex of the IC (ICd, ICc, and IClc) of guinea pigs. Throughout the IC, GABAergic synapses are characterized by pleomorphic vesicles and symmetric junctions. Comparisons of GABAergic synapses with excitatory synapses revealed differences (in some IC subdivisions) between the distributions of these synapse types onto IC cells. For excitatory cells in the IClc and ICd GABAergic synapses are biased toward the somas and large dendrites, whereas the excitatory boutons are biased toward spines and small dendrites. This arrangement could allow for strong inhibitory gating of excitatory inputs. Such differences in synaptic distributions were not observed in the ICc, where the two classes of bouton have similar distributions along the dendrites of excitatory cells. Interactions between excitatory and GABAergic inputs on the dendrites of excitatory ICc cells may be more restricted (i.e., reflecting local dendritic processing) than in the other IC subdivisions. Comparisons across IC subdivisions revealed evidence for two classes of GABAergic boutons, a small GABAergic (SG) class that is present throughout the IC and a large GABAergic (LG) class that is almost completely restricted to the ICc. In the ICc, LG, and SG boutons differ in their targets. SG boutons contact excitatory dendritic shafts most often, but also contact excitatory spines and somas (excitatory and GABAergic). LG synapses make comparatively fewer contacts on excitatory shafts, and make comparatively more contacts on excitatory spines and on somas (excitatory and GABAergic). LG boutons likely have a lemniscal origin.
 PLOS ONE , 2012, DOI: 10.1371/journal.pone.0039572 Abstract: Classical electron microscopic studies of the mammalian brain revealed two major classes of synapses, distinguished by the presence of a large postsynaptic density (PSD) exclusively at type 1, excitatory synapses. Biochemical studies of the PSD have established the paradigm of the synapse as a complex signal-processing machine that controls synaptic plasticity. We report here the results of a proteomic analysis of type 2, inhibitory synaptic complexes isolated by affinity purification from the cerebral cortex. We show that these synaptic complexes contain a variety of neurotransmitter receptors, neural cell-scaffolding and adhesion molecules, but that they are entirely lacking in cell signaling proteins. This fundamental distinction between the functions of type 1 and type 2 synapses in the nervous system has far reaching implications for models of synaptic plasticity, rapid adaptations in neural circuits, and homeostatic mechanisms controlling the balance of excitation and inhibition in the mature brain.
 Frontiers in Cellular Neuroscience , 2014, DOI: 10.3389/fncel.2014.00093 Abstract: Learning is believed to depend on lasting changes in synaptic efficacy such as long-term potentiation and long-term depression. As a result, a profusion of studies has tried to elucidate the mechanisms underlying these forms of plasticity. Traditionally, experience-dependent changes at excitatory synapses were assumed to underlie learning and memory formation. However, with the relatively more recent investigation of inhibitory transmission, it had become evident that inhibitory synapses are not only plastic, but also provide an additional way to modulate excitatory transmission and the induction of plasticity at excitatory synapses. Thanks to recent technological advances, progress has been made in understanding synaptic transmission and plasticity from particular interneuron subtypes. In this review article, we will describe various forms of synaptic plasticity that have been ascribed to two fairly well characterized populations of interneurons in the hippocampus, those expressing cholecystokinin (CCK) and parvalbumin (PV). We will discuss the resulting changes in the strength and plasticity of excitatory transmission that occur in the local circuit as a result of the modulation of inhibitory transmission. We will focus on the hippocampus because this region has a relatively well-understood circuitry, numerous forms of activity-dependent plasticity and a multitude of identified interneuron subclasses.
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