During high-frequency network activities, fast-spiking, parvalbumin-expressing basket cells (PV
-BCs) generate barrages of fast synaptic inhibition to control the probability and precise timing of ...action potential (AP) initiation in principal neurons. Here we describe a subcellular specialization that contributes to the high speed of synaptic inhibition mediated by PV
-BCs. Mapping of hyperpolarization-activated cyclic nucleotide-gated (HCN) channel distribution in rat hippocampal PV
-BCs with subcellular patch-clamp methods revealed that functional HCN channels are exclusively expressed in axons and completely absent from somata and dendrites. HCN channels not only enhance AP initiation during sustained high-frequency firing but also speed up the propagation of AP trains in PV
-BC axons by dynamically opposing the hyperpolarization produced by Na
-K
ATPases. Since axonal AP signaling determines the timing of synaptic communication, the axon-specific expression of HCN channels represents a specialization for PV
-BCs to operate at high speed.
Fast-spiking, parvalbumin-expressing GABAergic interneurons (PV+-BCs) express a complex machinery of rapid signaling mechanisms, including specialized voltage-gated ion channels to generate brief ...action potentials (APs). However, short APs are associated with overlapping Na+ and K+ fluxes and are therefore energetically expensive. How the potentially vicious combination of high AP frequency and inefficient spike generation can be reconciled with limited energy supply is presently unclear. To address this question, we performed direct recordings from the PV+-BC axon, the subcellular structure where active conductances for AP initiation and propagation are located. Surprisingly, the energy required for the AP was, on average, only ∼1.6 times the theoretical minimum. High energy efficiency emerged from the combination of fast inactivation of Na+ channels and delayed activation of Kv3-type K+ channels, which minimized ion flux overlap during APs. Thus, the complementary tuning of axonal Na+ and K+ channel gating optimizes both fast signaling properties and metabolic efficiency.
•Brief AP duration and high AP frequency in PV+-BCs may imply high metabolic cost•Energy for AP generation in PV+-BC axons is only 1.6 times the theoretical minimum•Fast Nav inactivation and delayed Kv3 activation maximize AP energy efficiency•Tuning of Nav–Kv3 gating optimizes fast signaling and energetics in interneurons
Hu et al. demonstrate that action potentials in parvalbumin-expressing GABAergic interneuron axons are energetically efficient, which is highly unexpected given their brief duration. High energy efficiency emerges from the combination of fast inactivation of voltage-gated Na+ channels and delayed activation of Kv3 channels in the axon.
GABAergic inhibition is an important regulator of excitability in neuronal networks. In addition, inhibitory synaptic signals contribute crucially to the organization of spatiotemporal patterns of ...network activity, especially during coherent oscillations. In order to maintain stable network states, the release of GABA by interneurons must be plastic in timing and amount. This homeostatic regulation is achieved by several pre- and postsynaptic mechanisms and is triggered by various activity-dependent local signals such as excitatory input or ambient levels of neurotransmitters. Here, we review findings on the availability of GABA for release at presynaptic terminals of interneurons. Presynaptic GABA content seems to be an important determinant of inhibitory efficacy and can be differentially regulated by changing synthesis, transport, and degradation of GABA or related molecules. We will discuss the functional impact of such regulations on neuronal network patterns and, finally, point towards pharmacological approaches targeting these processes.
Hypothalamic neurons are main regulators of energy homeostasis. Neuronal function essentially depends on plasma membrane-located gangliosides. The present work demonstrates that hypothalamic ...integration of metabolic signals requires neuronal expression of glucosylceramide synthase (GCS; UDP-glucose:ceramide glucosyltransferase). As a major mechanism of central nervous system (CNS) metabolic control, we demonstrate that GCS-derived gangliosides interacting with leptin receptors (ObR) in the neuronal membrane modulate leptin-stimulated formation of signaling metabolites in hypothalamic neurons. Furthermore, ganglioside-depleted hypothalamic neurons fail to adapt their activity (c-Fos) in response to alterations in peripheral energy signals. Consequently, mice with inducible forebrain neuron-specific deletion of the UDP-glucose:ceramide glucosyltransferase gene (Ugcg) display obesity, hypothermia, and lower sympathetic activity. Recombinant adeno-associated virus (rAAV)-mediated Ugcg delivery to the arcuate nucleus (Arc) significantly ameliorated obesity, specifying gangliosides as seminal components for hypothalamic regulation of body energy homeostasis.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The key role of APP in the pathogenesis of Alzheimer disease is well established. However, postnatal lethality of double knockout mice has so far precluded the analysis of the physiological functions ...of APP and the APLPs in the brain. Previously, APP family proteins have been implicated in synaptic adhesion, and analysis of the neuromuscular junction of constitutive APP/APLP2 mutant mice showed deficits in synaptic morphology and neuromuscular transmission. Here, we generated animals with a conditional APP/APLP2 double knockout (cDKO) in excitatory forebrain neurons using NexCre mice. Electrophysiological recordings of adult NexCre cDKOs indicated a strong synaptic phenotype with pronounced deficits in the induction and maintenance of hippocampal LTP and impairments in paired pulse facilitation, indicating a possible presynaptic deficit. These deficits were also reflected in impairments in nesting behavior and hippocampus-dependent learning and memory tasks, including deficits in Morris water maze and radial maze performance. Moreover, while no gross alterations of brain morphology were detectable in NexCre cDKO mice, quantitative analysis of adult hippocampal CA1 neurons revealed prominent reductions in total neurite length, dendritic branching, reduced spine density and reduced spine head volume. Strikingly, the impairment of LTP could be selectively rescued by acute application of exogenous recombinant APPsα, but not APPsβ, indicating a crucial role for APPsα to support synaptic plasticity of mature hippocampal synapses on a rapid time scale. Collectively, our analysis reveals an essential role of APP family proteins in excitatory principal neurons for mediating normal dendritic architecture, spine density and morphology, synaptic plasticity and cognition.
Key points
Ectopic action potentials (EAPs) arise at distal locations in axonal fibres and are often associated with neuronal pathologies such as epilepsy or nerve injury, but they also occur during ...physiological network conditions. This study investigates whether initiation of such EAPs is modulated by subthreshold synaptic activity.
Somatic subthreshold potentials invade the axonal compartment to considerable distances (>350 μm), whereas spread of axonal subthreshold potentials to the soma is inefficient.
Ectopic spike generation is entrained by conventional synaptic signalling mechanisms. Excitatory synaptic potentials promote EAPs, whereas inhibitory synaptic potentials block EAPs.
The modulation of ectopic excitability depends on propagation of somatic voltage deflections to the axonal EAP initiation site.
Synaptic modulation of EAP initiation challenges the view of the distal axon being independent of synaptic activity and may contribute to mechanisms underlying fast network oscillations and pathological network activity.
While most action potentials are generated at the axon initial segment, they can also be triggered at more distal sites along the axon. Such ectopic action potentials (EAPs) occur during several neuronal pathologies such as epilepsy, nerve injuries and inflammation but have also been observed during physiological network activity. EAPs propagate antidromically towards the somato‐dendritic compartment where they modulate synaptic plasticity. Here we investigate the converse signal direction: do somato‐dendritic synaptic potentials affect the generation of ectopic spikes? We measured anti‐ and orthodromic spikes in the soma and axon of mouse hippocampal CA1 pyramidal cells. We found that synaptic potentials propagate reliably through the axon, causing significant voltage transients at distances >350 μm. At these sites, excitatory input efficiently facilitated EAP initiation in distal axons and, conversely, inhibitory input suppressed EAP initiation. Our data reveal a new mechanism by which ectopically generated spikes can be entrained by conventional synaptic signalling during normal and pathological network activity.
Key points
Ectopic action potentials (EAPs) arise at distal locations in axonal fibres and are often associated with neuronal pathologies such as epilepsy or nerve injury, but they also occur during physiological network conditions. This study investigates whether initiation of such EAPs is modulated by subthreshold synaptic activity.
Somatic subthreshold potentials invade the axonal compartment to considerable distances (>350 μm), whereas spread of axonal subthreshold potentials to the soma is inefficient.
Ectopic spike generation is entrained by conventional synaptic signalling mechanisms. Excitatory synaptic potentials promote EAPs, whereas inhibitory synaptic potentials block EAPs.
The modulation of ectopic excitability depends on propagation of somatic voltage deflections to the axonal EAP initiation site.
Synaptic modulation of EAP initiation challenges the view of the distal axon being independent of synaptic activity and may contribute to mechanisms underlying fast network oscillations and pathological network activity.
Many image segmentation algorithms first generate an affinity graph and then partition it. We present a machine learning approach to computing an affinity graph using a convolutional network (CN) ...trained using ground truth provided by human experts. The CN affinity graph can be paired with any standard partitioning algorithm and improves segmentation accuracy significantly compared to standard hand-designed affinity functions.
We apply our algorithm to the challenging 3D segmentation problem of reconstructing neuronal processes from volumetric electron microscopy (EM) and show that we are able to learn a good affinity graph directly from the raw EM images. Further, we show that our affinity graph improves the segmentation accuracy of both simple and sophisticated graph partitioning algorithms.
In contrast to previous work, we do not rely on prior knowledge in the form of hand-designed image features or image preprocessing. Thus, we expect our algorithm to generalize effectively to arbitrary image types.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
In the present work, neural networks are applied to formulate parametrized hyperelastic constitutive models. The models fulfill all common mechanical conditions of hyperelasticity by ...construction. In particular, partially input convex neural network (pICNN) architectures are applied based on feed-forward neural networks. Receiving two different sets of input arguments, pICNNs are convex in one of them, while for the other, they represent arbitrary relationships which are not necessarily convex. In this way, the model can fulfill convexity conditions stemming from mechanical considerations without being too restrictive on the functional relationship in additional parameters, which may not necessarily be convex. Two different models are introduced, where one can represent arbitrary functional relationships in the additional parameters, while the other is monotonic in the additional parameters. As a first proof of concept, the model is calibrated to data generated with two differently parametrized analytical potentials, whereby three different pICNN architectures are investigated. In all cases, the proposed model shows excellent performance.
Cognitive and behavioral functions depend on the activation of stable neuronal assemblies, i.e. distributed groups of co-active neurons within neuronal networks. It is therefore crucial to monitor ...distributed patterns of activity in real time with single-neuron resolution. Microelectrode recordings allow detection of coincidence between discharges of identified units at high temporal resolution, but are not able to reveal the full spatial pattern of activity in multi-cellular assemblies. Therefore, observation of such distributed sets of neurons is a stronghold of optical techniques, but the required resolution, sensitivity, and speed are still challenging current technology. Here, we report a new approach for monitoring neuronal assemblies, using memory-related network oscillations in rodent hippocampal circuits as a model. The cytosolic calcium-sensitive fluorescent protein GCaMP3.NES was expressed using recombinant adeno-associated viral (rAAV)-mediated gene transfer in CA3 pyramidal neurons of cultured mouse hippocampal slices. After 14–21days in culture, field potential recordings revealed spontaneous occurrence of sharp wave-ripple network events during which a fraction of local neurons is coherently activated. Using a custom-built epi-fluorescence microscope we could monitor a field of view of 410μm×410μm with single-neuron optical resolution (20× objective, 0.4 NA). We developed a highly sensitive and specific wavelet-based method of cell identification allowing simultaneous observation of more than 150 neurons at frame rates of up to 60Hz. Our recording configuration and image analysis provide a tool to investigate cognition-related activity patterns in the hippocampus and other circuits.
► We observe spontaneous calcium transients in cultured hippocampal slices. ► Protein-based calcium dyes are expressed by viral gene transfer. ► Signal-to-noise ratio is optimized by wavelet-based filtering. ► Single cells can be distinguished by a rigid classifying algorithm. ► Our method allows analysis of co-active assemblies of multiple neurons.
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