Frontiers in Neural Circuits

Publisher: Frontiers

Current impact factor: 3.60

Impact Factor Rankings

2016 Impact Factor Available summer 2017
2014 / 2015 Impact Factor 3.568
2013 Impact Factor 2.95
2012 Impact Factor 3.333
2011 Impact Factor 5.098

Impact factor over time

Impact factor
Year

Additional details

5-year impact 3.68
Cited half-life 2.00
Immediacy index 0.39
Eigenfactor 0.01
Article influence 1.54
Other titles Frontiers in neural circuits (online)
ISSN 1662-5110
OCLC 250619181
Material type Document, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Frontiers

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • On open access repositories
    • Authors retain copyright
    • Creative Commons Attribution License
    • Published source must be acknowledged
    • Publisher's version/PDF may be used
    • Set statement to accompany [This Document is Protected by copyright and was first published by Frontiers. All rights reserved. it is reproduced with permission.]
    • Articles are placed in PubMed Central immediately on behalf of authors.
    • All titles are open access journals
    • Publisher last contacted on 16/07/2015
  • Classification
    green

Publications in this journal

  • Tamás D. Fehérvári · Tetsuya Yagi

    No preview · Article · Feb 2016 · Frontiers in Neural Circuits
  • [Show abstract] [Hide abstract]
    ABSTRACT: The output of a neuronal network depends on the organization and functional properties of its component cells and synapses. While the characterization of synaptic properties has lagged cellular analyses, a potentially important aspect in rhythmically active networks is how network synapses affect, and are in turn affected by, network activity. This could lead to a potential circular interaction where short-term activity-dependent synaptic plasticity is both influenced by and influences the network output. The analysis of synaptic plasticity in the lamprey locomotor network was extended here to characterize the short-term plasticity of connections between network interneurons and to try and address its potential network role. Paired recordings from identified interneurons in quiescent networks showed synapse-specific synaptic properties and plasticity that supported the presence of two hemisegmental groups that could influence bursting: depression in an excitatory interneuron group, and facilitation in an inhibitory feedback circuit. The influence of activity-dependent synaptic plasticity on network activity was investigated experimentally by changing Ringer Ca2+ levels, and in a simple computer model. A potential caveat of the experimental analyses was that changes in Ringer Ca2+ (and compensatory adjustments in Mg2+ in some cases) could alter several other cellular and synaptic properties. Several of these properties were tested, and while there was some variability, these were not usually significantly affected by the Ringer changes. The experimental analyses suggested that depression of excitatory inputs had the strongest influence on the patterning of network activity. The simulation supported a role for this effect, and also suggested that the inhibitory facilitating group could modulate the influence of the excitatory synaptic depression. Short-term activity-dependent synaptic plasticity has not generally been considered in spinal cord models. These results provide further evidence for short-term plasticity between locomotor network interneurons. As this plasticity could influence the patterning of the network output it should be considered as a potential functional component of spinal cord networks.
    No preview · Article · Feb 2016 · Frontiers in Neural Circuits
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: How complex natural sounds are represented by the main converging center of the auditory midbrain, the central inferior colliculus, is an open question. We applied neural discrimination to determine the variation of detailed encoding of individual vocalizations across the best frequency gradient of the central inferior colliculus. The analysis was based on collective responses from several neurons. These multi-unit spike trains were recorded from guinea pigs exposed to a spectrotemporally rich set of eleven species-specific vocalizations. Spike trains of disparate units from the same recording were combined in order to investigate whether groups of multi-unit clusters represent the whole set of vocalizations more reliably than only one unit, and whether temporal response correlations between them facilitate an unambiguous neural representation of the vocalizations. We found a spatial distribution of the capability to accurately encode groups of vocalizations across the best frequency gradient. Different vocalizations are optimally discriminated at different locations of the best frequency gradient. Furthermore, groups of a few multi-unit clusters yield improved discrimination over only one multi-unit cluster between all tested vocalizations. However, temporal response correlations between units do not yield better discrimination. Our study is based on a large set of units of simultaneously recorded responses from several guinea pigs and electrode insertion positions. Our findings suggest abroadly distributed code for behaviorally relevant vocalizations in the mammalian inferior colliculus.Responses from a few non-interacting units are sufficient to faithfully represent the whole set of studied vocalizations with diverse spectrotemporal properties.
    Preview · Article · Feb 2016 · Frontiers in Neural Circuits
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Classical Hebbian learning puts the emphasis on joint pre- and postsynaptic activity, but neglects the potential role of neuromodulators. Since neuromodulators convey information about novelty or reward, the influence of neuromodulatorson synaptic plasticity is useful not just for action learning in classical conditioning, but also to decide 'when' to create new memories in response to a flow of sensory stimuli. In this review, we focus on timing requirements for pre- and postsynaptic activity in conjunction with one or several phasic neuromodulatory signals. While the emphasis of the text is on conceptual models and mathematical theories, we also discuss some experimental evidence for neuromodulation of Spike-Timing-Dependent Plasticity. We highlight the importance of synaptic mechanisms in bridging the temporal gap between sensory stimulation and neuromodulatory signals, and develop a framework for a class of neo-Hebbian three-factor learning rules that depend on presynaptic activity, postsynaptic variables as well as the influence of neuromodulators.
    Preview · Article · Jan 2016 · Frontiers in Neural Circuits
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: During even the most quiescent behavioral periods, the cortex and thalamus express rich spontaneous activity in the form of slow (<1 Hz), synchronous network state transitions. Throughout this so-called slow oscillation, cortical and thalamic neurons fluctuate between periods of intense synaptic activity (Up states) and almost complete silence (Down states). The two decades since the original characterization of the slow oscillation in the cortex and thalamus have seen considerable advances in deciphering the cellular and network mechanisms associated with this pervasive phenomenon. There are, nevertheless, many questions regarding the slow oscillation that await more thorough illumination, particularly the mechanisms by which Up states initiate and terminate, the functional role of the rhythmic activity cycles in unconscious or minimally conscious states, and the precise relation between Up states and the activated states associated with waking behavior. Given the substantial advances in multineuronal recording and imaging methods in both in vivo and in vitro preparations, the time is ripe to take stock of our current understanding of the slow oscillation and pave the way for future investigations of its mechanisms and functions. My aim in this Review is to provide a comprehensive account of the mechanisms and functions of the slow oscillation, and to suggest avenues for further exploration.
    Preview · Article · Jan 2016 · Frontiers in Neural Circuits
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In the mammalian central nervous system, most sensory information passes through primary sensory thalamic nuclei, however the consequence of this remains unclear. Various propositions exist, likening the thalamus to a gate, or a high pass filter. Here, using a simple leaky integrate and fire model based on physiological parameters, we show that the thalamus behaves akin to a low pass filter. Specifically, as individual cells in the thalamus rely on consistent drive to spike, stimuli that is rapidly and continuously changing over time such that it activates sensory cells with different receptive fields are unable to drive thalamic spiking. This means that thalamic encoding is robust to sensory noise, however it induces a lag in sensory representation. Thus, the thalamus stabilizes encoding of sensory information, at the cost of response rate.
    Preview · Article · Jan 2016 · Frontiers in Neural Circuits
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Recent evidence suggests that parallel synapses from the same axonal branch onto the same dendritic branch have almost identical strength. It has been proposed that this alignment is only possible through learning rules that integrate activity over long time spans. However, learning mechanisms such as spike-timing-dependent plasticity (STDP) are commonly assumed to be temporally local. Here, we propose that the combination of temporally local STDP and a multiplicative synaptic normalization mechanism is sufficient to explain the alignment of parallel synapses. To address this issue, we introduce three increasingly complex models: First, we model the idealized interaction of STDP and synaptic normalization in a single neuron as a simple stochastic process and derive analytically that the alignment effect can be described by a so-called Kesten process. From this we can derive that synaptic efficacy alignment requires potentiation-dominated learning regimes. We verify these conditions in a single-neuron model with independent spiking activities but more realistic synapses. As expected, we only observe synaptic efficacy alignment for long-term potentiation-biased STDP. Finally, we explore how well the findings transfer to recurrent neural networks where the learning mechanisms interact with the correlated activity of the network. We find that due to the self-reinforcing correlations in recurrent circuits under STDP, alignment occurs for both long-term potentiation- and depression-biased STDP, because the learning will be potentiation dominated in both cases due to the potentiating events induced by correlated activity. This is in line with recent results demonstrating a dominance of potentiation over depression during waking and normalization during sleep. This leads us to predict that individual spine pairs will be more similar after sleep compared to after sleep deprivation. In conclusion, we show that synaptic normalization in conjunction with coordinated potentiation—in this case, from STDP in the presence of correlated pre- and post-synaptic activity—naturally leads to an alignment of parallel synapses.
    Preview · Article · Jan 2016 · Frontiers in Neural Circuits
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: A reason why the thalamus is more than a passive gateway for sensory signals is that two-third of the synapses of thalamocortical neurons are directly or indirectly related to the activity of corticothalamic axons. While the responses of thalamocortical neurons evoked by sensory stimuli are well characterized, with ON- and OFF-center receptive field structures, the prevalence of synaptic noise resulting from neocortical feedback in intracellularly recorded thalamocortical neurons in vivo has attracted little attention. However, in vitro and modeling experiments point to its critical role for the integration of sensory signals. Here we combine our recent findings in a unified framework suggesting the hypothesis that corticothalamic synaptic activity is adapted to modulate the transfer efficiency of thalamocortical neurons during selective attention at three different levels: First, on ionic channels by interacting with intrinsic membrane properties, second at the neuron level by impacting on the input-output gain, and third even more effectively at the cell assembly level by boosting the information transfer of sensory features encoded in thalamic subnetworks. This top-down population control is achieved by tuning the correlations in subthreshold membrane potential fluctuations and is adapted to modulate the transfer of sensory features encoded by assemblies of thalamocortical relay neurons. We thus propose that cortically-controlled (de-)correlation of subthreshold noise is an efficient and swift dynamic mechanism for selective attention in the thalamus.
    Preview · Article · Dec 2015 · Frontiers in Neural Circuits
  • [Show abstract] [Hide abstract]
    ABSTRACT: It has long been known that the vast majority of all information en route to the cerebral cortex must first pass through the thalamus. The long held view that the thalamus serves as a simple hi fidelity relay station for sensory information to the cortex, however, has over recent years been dispelled. Indeed, multiple projections from the vestibular nuclei to thalamic nuclei (including the ventrobasal nuclei, and the geniculate bodies)regions typically associated with other modalities-have been described. Further, some thalamic neurons have been shown to respond to stimuli presented from across sensory modalities. For example, neurons in the rat anterodorsal and laterodorsal nuclei of the thalamus respond to visual, vestibular, proprioceptive and somatosensory stimuli and integrate this information to compute heading within the environment. Together, these findings imply that the thalamus serves crucial integrative functions, at least in regard to vestibular processing, beyond that imparted by a "simple" relay. In this mini review we outline the vestibular inputs to the thalamus and provide some clinical context for vestibular interactions in the thalamus. We then focus on how vestibular inputs interact with other sensory systems and discuss the multisensory integration properties of the thalamus.
    No preview · Article · Dec 2015 · Frontiers in Neural Circuits