Physiological roles of endocytosis and presynaptic scaffold in vesicle replenishment at fast and slow central synapses.

After exocytosis, release sites are cleared of vesicular residues to replenish with transmitter-filled vesicles. Endocytic and scaffold proteins are thought to underlie this site-clearance mechanism. However, the physiological significance of this mechanism at diverse mammalian central synapses remains unknown. Here, we tested this in a physiologically optimized condition using action potential evoked EPSCs at fast calyx synapse and relatively slow hippocampal CA1 synapse, in post-hearing mice brain slices at 37°C and in 1.3 mM [Ca2+]. Pharmacological block of endocytosis enhanced synaptic depression at the calyx synapse, whereas it attenuated synaptic facilitation at the hippocampal synapse. Block of scaffold protein activity likewise enhanced synaptic depression at the calyx but had no effect at the hippocampal synapse. At the fast calyx synapse, block of endocytosis or scaffold protein activity significantly enhanced synaptic depression as early as 10 ms after the stimulation onset. Unlike previous reports, neither endocytic blockers nor scaffold protein inhibitors prolonged the recovery from short-term depression. We conclude that the release-site clearance by endocytosis can be a universal phenomenon supporting vesicle replenishment at both fast and slow synapses, whereas the presynaptic scaffold mechanism likely plays a specialized role in vesicle replenishment predominantly at fast synapses.

Representing stimulus motion with waves in adaptive neural fields.

Traveling waves of neural activity emerge in cortical networks both spontaneously and in response to stimuli. The spatiotemporal structure of waves can indicate the information they encode and the physiological processes that sustain them. Here, we investigate the stimulus-response relationships of traveling waves emerging in adaptive neural fields as a model of visual motion processing. Neural field equations model the activity of cortical tissue as a continuum excitable medium, and adaptive processes provide negative feedback, generating localized activity patterns. Synaptic connectivity in our model is described by an integral kernel that weakens dynamically due to activity-dependent synaptic depression, leading to marginally stable traveling fronts (with attenuated backs) or pulses of a fixed speed. Our analysis quantifies how weak stimuli shift the relative position of these waves over time, characterized by a wave response function we obtain perturbatively. Persistent and continuously visible stimuli model moving visual objects. Intermittent flashes that hop across visual space can produce the experience of smooth apparent visual motion. Entrainment of waves to both kinds of moving stimuli are well characterized by our theory and numerical simulations, providing a mechanistic description of the perception of visual motion.

A coupled neural field model for the standard consolidation theory.

The standard consolidation theory states that short-term memories located in the hippocampus enable the consolidation of long-term memories in the neocortex. In other words, the neocortex slowly learns long-term memories with a transient support of the hippocampus that quickly learns unstable memories. However, it is not clear yet what could be the neurobiological mechanisms underlying these differences in learning rates and memory time-scales. Here, we propose a novel modeling approach of the standard consolidation theory, that focuses on its potential neurobiological mechanisms. In addition to synaptic plasticity and spike frequency adaptation, our model incorporates adult neurogenesis in the dentate gyrus as well as the difference in size between the neocortex and the hippocampus, that we associate with distance-dependent synaptic plasticity. We also take into account the interconnected spatial structure of the involved brain areas, by incorporating the above neurobiological mechanisms in a coupled neural field framework, where each area is represented by a separate neural field with intra- and inter-area connections. To our knowledge, this is the first attempt to apply neural fields to this process. Using numerical simulations and mathematical analysis, we explore the short-term and long-term dynamics of the model upon alternance of phases of hippocampal replay and retrieval cue of an external input. This external input is encodable as a memory pattern in the form of a multiple bump attractor pattern in the individual neural fields. In the model, hippocampal memory patterns become encoded first, before neocortical ones, because of the smaller distances between the bumps of the hippocampal memory patterns. As a result, retrieval of the input pattern in the neocortex at short time-scales necessitates the additional input delivered by the memory pattern of the hippocampus. Neocortical memory patterns progressively consolidate at longer times, up to a point where their retrieval does not need the support of the hippocampus anymore. At longer times, perturbation of the hippocampal neural fields by neurogenesis erases the hippocampus pattern, leading to a final state where the memory pattern is exclusively evoked in the neocortex. Therefore, the dynamics of our model successfully reproduces the main features of the standard consolidation theory. This suggests that neurogenesis in the hippocampus and distance-dependent synaptic plasticity coupled to synaptic depression and spike frequency adaptation, are indeed critical neurobiological processes in memory consolidation.

Interactions between specialized gain control mechanisms in olfactory processing.

Gain control is a process that adjusts a system's sensitivity when input levels change. Neural systems contain multiple mechanisms of gain control, but we do not understand why so many mechanisms are needed or how they interact. Here, we investigate these questions in the Drosophila antennal lobe, where we identify several types of inhibitory interneurons with specialized gain control functions. We find that some interneurons are nonspiking, with compartmentalized calcium signals, and they specialize in intra-glomerular gain control. Conversely, we find that other interneurons are recruited by strong and widespread network input; they specialize in global presynaptic gain control. Using computational modeling and optogenetic perturbations, we show how these mechanisms can work together to improve stimulus discrimination while also minimizing temporal distortions in network activity. Our results demonstrate how the robustness of neural network function can be increased by interactions among diverse and specialized mechanisms of gain control.

Multivesicular release favors short term synaptic depression in hippocampal autapses.

Presynaptic terminals of the central nervous system can support univesicular and multivesicular synchronous release of neurotransmitters, however, the functional implications of the prevalence of one mechanism over the other are yet unresolved. Here, we took advantage of the expression of SF-iGluSnFR.S72A in the astrocytic feeder layer of autaptic hippocampal neuronal cultures to associate the liberation of glutamate to excitatory postsynaptic currents. The presence of the glutamate sensor in glial cells avoided any interference with the function of endogenous postsynaptic receptors. It was possible to optically detect changes in neurotransmitter release probability, which was heterogeneous among synaptic boutons studied. For each neuron investigated, the liberation of neurotransmitters occurred through a predominant mechanism. The prevalence of multivesicular over univesicular release increased synaptic strength and enhanced short-term synaptic depression. These results show that the preference of hippocampal boutons to synchronously release one or more vesicles determines the strength and low pass filtering properties of the synapses established.

Representing stimulus motion with waves in adaptive neural fields.

Traveling waves of neural activity emerge in cortical networks both spontaneously and in response to stimuli. The spatiotemporal structure of waves can indicate the information they encode and the physiological processes that sustain them. Here, we investigate the stimulus-response relationships of traveling waves emerging in adaptive neural fields as a model of visual motion processing. Neural field equations model the activity of cortical tissue as a continuum excitable medium, and adaptive processes provide negative feedback, generating localized activity patterns. Synaptic connectivity in our model is described by an integral kernel that weakens dynamically due to activity-dependent synaptic depression, leading to marginally stable traveling fronts (with attenuated backs) or pulses of a fixed speed. Our analysis quantifies how weak stimuli shift the relative position of these waves over time, characterized by a wave response function we obtain perturbatively. Persistent and continuously visible stimuli model moving visual objects. Intermittent flashes that hop across visual space can produce the experience of smooth apparent visual motion. Entrainment of waves to both kinds of moving stimuli are well characterized by our theory and numerical simulations, providing a mechanistic description of the perception of visual motion.

A theoretical model reveals specialized synaptic depressions and temporal frequency tuning in retinal parallel channels.

In the Outer Plexiform Layer of a retina, a cone pedicle provides synaptic inputs for multiple cone bipolar cell (CBC) subtypes so that each subtype formats a parallelized processing channel to filter visual features from the environment. Due to the diversity of short-term depressions among cone-CBC contacts, these channels have different temporal frequency tunings. Here, we propose a theoretical model based on the hierarchy Linear-Nonlinear-Synapse framework to link the synaptic depression and the neural activities of the cone-CBC circuit. The model successfully captures various frequency tunings of subtype-specialized channels and infers synaptic depression recovery time constants inside circuits. Furthermore, the model can predict frequency-tuning behaviors based on synaptic activities. With the prediction of region-specialized UV cone parallel channels, we suggest the acute zone in the zebrafish retina supports detecting light-off events at high temporal frequencies.

Persistent synaptic inhibition of the subthalamic nucleus by high frequency stimulation.

BACKGROUND: Deep brain stimulation (DBS) provides symptomatic relief in a growing number of neurological indications, but local synaptic dynamics in response to electrical stimulation that may relate to its mechanism of action have not been fully characterized. OBJECTIVE: The objectives of this study were to (1) study local synaptic dynamics during high frequency extracellular stimulation of the subthalamic nucleus (STN), and (2) compare STN synaptic dynamics with those of the neighboring substantia nigra pars reticulata (SNr). METHODS: Two microelectrodes were advanced into the STN and SNr of patients undergoing DBS surgery for Parkinson's disease (PD). Neuronal firing and evoked field potentials (fEPs) were recorded with one microelectrode during stimulation from an adjacent microelectrode. RESULTS: Inhibitory fEPs could be discerned within the STN and their amplitudes predicted bidirectional effects on neuronal firing (p = .013). There were no differences between STN and SNr inhibitory fEP dynamics at low stimulation frequencies (p > .999). However, inhibitory neuronal responses were sustained over time in STN during high frequency stimulation but not in SNr (p < .001) where depression of inhibitory input was coupled with a return of neuronal firing (p = .003). INTERPRETATION: Persistent inhibitory input to the STN suggests a local synaptic mechanism for the suppression of subthalamic firing during high frequency stimulation. Moreover, differences in the resiliency versus vulnerability of inhibitory inputs to the STN and SNr suggest a projection source- and frequency-specificity for this mechanism. The feasibility of targeting electrophysiologically-identified neural structures may provide insight into how DBS achieves frequency-specific modulation of neuronal projections.

Temporal filters in response to presynaptic spike trains: interplay of cellular, synaptic and short-term plasticity time scales.

Temporal filters, the ability of postsynaptic neurons to preferentially select certain presynaptic input patterns over others, have been shown to be associated with the notion of information filtering and coding of sensory inputs. Short-term plasticity (depression and facilitation; STP) has been proposed to be an important player in the generation of temporal filters. We carry out a systematic modeling, analysis and computational study to understand how characteristic postsynaptic (low-, high- and band-pass) temporal filters are generated in response to periodic presynaptic spike trains in the presence STP. We investigate how the dynamic properties of these filters depend on the interplay of a hierarchy of processes, including the arrival of the presynaptic spikes, the activation of STP, its effect on the excitatory synaptic connection efficacy, and the response of the postsynaptic cell. These mechanisms involve the interplay of a collection of time scales that operate at the single-event level (roughly, during each presynaptic interspike-interval) and control the long-term development of the temporal filters over multiple presynaptic events. These time scales are generated at the levels of the presynaptic cell (captured by the presynaptic interspike-intervals), short-term depression and facilitation, synaptic dynamics and the post-synaptic cellular currents. We develop mathematical tools to link the single-event time scales with the time scales governing the long-term dynamics of the resulting temporal filters for a relatively simple model where depression and facilitation interact at the level of the synaptic efficacy change. We extend our results and tools to account for more complex models. These include multiple STP time scales and non-periodic presynaptic inputs. The results and ideas we develop have implications for the understanding of the generation of temporal filters in complex networks for which the simple feedforward network we investigate here is a building block.

Frequency-dependent depression of the NTS synapse affects the temporal response of the antihypertensive effect of auricular vagus nerve stimulation (aVNS).

Objective. Auricular vagus nerve stimulation (aVNS) has recently emerged as a promising neuromodulation modality for blood pressure (BP) reduction due to its ease of use although its efficacy is still limited compared to direct baroreflex stimulation. Previous studies have also indicated that synaptic depression of nucleus tractus solitarius (NTS) in the baroreflex pathway depends on stimulus frequency. However, the nature of this frequency dependence phenomenon on antihypertensive effect has been unknown for aVNS. We aimed to investigate the antihypertensive effect of aVNS considering frequency-dependent depression characteristic in the NTS synapse. We explored NTS activation and BP reduction induced by aVNS and by direct secondary neuron stimulation (DS).Approach. Both protocols were performed with recording of NTS activation and BP response with stimulation for each frequency parameter (2, 4, 20, 50, and 80 Hz).Main results. The BP recovery time constant was significantly dependent on the frequency of DS and aVNS (DS-2 Hz: 8.17 ± 4.98; 4 Hz: 9.73 ± 6.3; 20 Hz: 6.61 ± 3.28; 50 Hz: 4.93 ± 1.65; 80 Hz: 4.00 ± 1.43,p< 0.001, Kruskal-Wallis (KW) H-test/aVNS-2 Hz: 4.02 ± 2.55; 4 Hz: 8.13 ± 4.05; 20 Hz: 6.40 ± 3.16; 50 Hz: 5.18 ± 2.37; 80 Hz: 3.13 ± 1.29,p< 0.05, KW H-test) despite no significant BP reduction at 2 Hz compared to sham groups (p> 0.05, Mann-Whitney U-test).Significance. Our observations suggest that the antihypertensive effect of aVNS is influenced by the characteristics of frequency-dependent synaptic depression in the NTS neuron in terms of the BP recovery time. These findings suggest that the antihypertensive effect of aVNS can be improved with further understanding of the neurological properties of the baroreflex associated with aVNS, which is critical to push this new modality for clinical interpretation.

Auditory cortex modelled as a dynamical network of oscillators: understanding event-related fields and their adaptation.

Adaptation, the reduction of neuronal responses by repetitive stimulation, is a ubiquitous feature of auditory cortex (AC). It is not clear what causes adaptation, but short-term synaptic depression (STSD) is a potential candidate for the underlying mechanism. In such a case, adaptation can be directly linked with the way AC produces context-sensitive responses such as mismatch negativity and stimulus-specific adaptation observed on the single-unit level. We examined this hypothesis via a computational model based on AC anatomy, which includes serially connected core, belt, and parabelt areas. The model replicates the event-related field (ERF) of the magnetoencephalogram as well as ERF adaptation. The model dynamics are described by excitatory and inhibitory state variables of cell populations, with the excitatory connections modulated by STSD. We analysed the system dynamics by linearising the firing rates and solving the STSD equation using time-scale separation. This allows for characterisation of AC dynamics as a superposition of damped harmonic oscillators, so-called normal modes. We show that repetition suppression of the N1m is due to a mixture of causes, with stimulus repetition modifying both the amplitudes and the frequencies of the normal modes. In this view, adaptation results from a complete reorganisation of AC dynamics rather than a reduction of activity in discrete sources. Further, both the network structure and the balance between excitation and inhibition contribute significantly to the rate with which AC recovers from adaptation. This lifetime of adaptation is longer in the belt and parabelt than in the core area, despite the time constants of STSD being spatially homogeneous. Finally, we critically evaluate the use of a single exponential function to describe recovery from adaptation.

Activity-Dependent Modulation of Tonic GABA Currents by Endocannabinoids in Hirudo verbana.

Endocannabinoids are lipid neuromodulators that are synthesized on demand and primarily signal in a retrograde manner to elicit depression of excitatory and inhibitory synapses. Despite the considerable interest in their potential analgesic effects, there is evidence that endocannabinoids can have both pro-nociceptive and anti-nociceptive effects. The mechanisms contributing to the opposing effects of endocannabinoids in nociception need to be better understood before cannabinoid-based therapies can be effectively utilized to treat pain. Using the medicinal leech, Hirudo verbana, this work investigates whether endocannabinoids modulate tonic inhibition onto non-nociceptive afferents. In voltage clamp recordings, we analyzed changes in the tonic inhibition in pressure-sensitive (P) cells following pre-treatment with endocannabinoids, 2-arachidonoylglycerol (2-AG) or anandamide (AEA). We also tested whether high frequency stimulation (HFS) of nociceptive (N) cells could also modulate tonic inhibition. Both endocannabinoid application and N cell HFS depressed tonic inhibition in the P cell. Depression of tonic inhibition by N cell HFS was blocked by SB 366791 (a TRPV1 inhibitor). SB 366791 also prevented 2-AG-and AEA-induced depression of tonic inhibition. HFS-induced depression was not blocked by tetrahydrolipstatin (THL), which prevents 2-AG synthesis, nor AM 251 (a CB1 receptor inverse agonist). These results illustrate a novel activity-dependent modulation of tonic GABA currents that is mediated by endocannabinoid signaling and is likely to play an important role in sensitization of non-nociceptive afferent pathways.

A Scalar Poincaré Map for Anti-phase Bursting in Coupled Inhibitory Neurons With Synaptic Depression.

Short-term synaptic plasticity is found in many areas of the central nervous system. In the inhibitory half-center central pattern generators involved in locomotion, synaptic depression is believed to act as a burst termination mechanism, allowing networks to generate anti-phase bursting patterns of varying periods. To better understand burst generation in these central pattern generators, we study a minimal network of two neurons coupled through depressing synapses. Depending on the strength of the synaptic conductance between the two neurons, this network can produce symmetric n : n anti-phase bursts, where neurons fire n spikes in alternation, with the period of such solutions increasing with the strength of the synaptic conductance. Relying on the timescale disparity in the model, we reduce the eight-dimensional network equations to a fully-explicit scalar Poincaré burst map. This map tracks the state of synaptic depression from one burst to the next and captures the complex bursting dynamics of the network. Fixed points of this map are associated with stable burst solutions of the full network model, and are created through fold bifurcations of maps. We derive conditions that predict the bifurcations between n : n and (n + 1) : (n + 1) solutions, producing a full bifurcation diagram of the burst cycle period. Predictions of the Poincaré map fit excellently with numerical simulations of the full network model and allow the study of parameter sensitivity for rhythm generation.

Quantal analysis estimates docking site occupancy determining short-term depression at hippocampal glutamatergic synapses.

Before fusion, synaptic vesicles (SVs) pause at discrete release/docking sites. During repetitive stimulation, the probability of site occupancy changes following SV fusion and replenishment. The occupancy probability is considered to be one of the crucial determinants of synaptic strength, but it is difficult to estimate separately because it usually blends with other synaptic parameters. Thus, the contribution of site occupancy to synaptic function, particularly to synaptic depression, remains elusive. Here, we directly estimated the occupancy probability at the hippocampal mossy fibre-CA3 interneuron synapse showing synaptic depression, using statistics of counts of vesicular events detected by deconvolution. We found that this synapse had a particularly high occupancy (∼0.85) with a high release probability of a docked SV (∼0.8) under 3 mm external calcium conditions. Analyses of quantal amplitudes and SV counts indicated that quantal size reduction decreased the amplitudes of all responses in a train to a similar degree, whereas release/docking site number was unchanged during trains, suggesting that quantal size and release/docking site number had little influence on the extent of synaptic depression. Model simulations revealed that the initial occupancy with high release probability and slow replenishment determined the time course of synaptic depression. Consistently, decreasing external calcium concentration reduced both the occupancy and release probability, and the reductions in turn produced less depression. Based on these results, we suggest that the occupancy probability is a crucial determinant of short-term synaptic depression at glutamatergic synapses in the hippocampus. KEY POINTS: The occupancy probability of a release/docking site by a synaptic vesicle at presynaptic terminals is considered to be one of the crucial determinants of synaptic strength, but it is difficult to estimate separately from other synaptic parameters. Here, we directly estimate the occupancy probability at the hippocampal mossy fibre-interneuron synapse using statistics of vesicular events detected by deconvolution. We show that the synapses have particularly high occupancy (0.85) with high release probability (0.8) under high external calcium concentration ([Ca2+ ]o ) conditions, and that both parameter values change with [Ca2+ ]o , shaping synaptic depression. Analyses of the quantal amplitudes and synaptic vesicle counts suggest that quantal sizes and release/docking site number have little influence on the extent of synaptic depression. The results suggest that the occupancy probability is a crucial determinant of short-term synaptic depression at glutamatergic synapses in the hippocampus.

TRPM7 is critical for short-term synaptic depression by regulating synaptic vesicle endocytosis.

Transient receptor potential melastatin 7 (TRPM7) contributes to a variety of physiological and pathological processes in many tissues and cells. With a widespread distribution in the nervous system, TRPM7 is involved in animal behaviors and neuronal death induced by ischemia. However, the physiological role of TRPM7 in central nervous system (CNS) neuron remains unclear. Here, we identify endocytic defects in neuroendocrine cells and neurons from TRPM7 knockout (KO) mice, indicating a role of TRPM7 in synaptic vesicle endocytosis. Our experiments further pinpoint the importance of TRPM7 as an ion channel in synaptic vesicle endocytosis. Ca2+ imaging detects a defect in presynaptic Ca2+ dynamics in TRPM7 KO neuron, suggesting an importance of Ca2+ influx via TRPM7 in synaptic vesicle endocytosis. Moreover, the short-term depression is enhanced in both excitatory and inhibitory synaptic transmissions from TRPM7 KO mice. Taken together, our data suggests that Ca2+ influx via TRPM7 may be critical for short-term plasticity of synaptic strength by regulating synaptic vesicle endocytosis in neurons.

Naturalistic Spike Trains Drive State-Dependent Homeostatic Plasticity in Superficial Layers of Visual Cortex.

The history of neural activity determines the synaptic plasticity mechanisms employed in the brain. Previous studies report a rapid reduction in the strength of excitatory synapses onto layer 2/3 (L2/3) pyramidal neurons of the primary visual cortex (V1) following two days of dark exposure and subsequent re-exposure to light. The abrupt increase in visually driven activity is predicted to drive homeostatic plasticity, however, the parameters of neural activity that trigger these changes are unknown. To determine this, we first recorded spike trains in vivo from V1 layer 4 (L4) of dark exposed (DE) mice of both sexes that were re-exposed to light through homogeneous or patterned visual stimulation. We found that delivering the spike patterns recorded in vivo to L4 of V1 slices was sufficient to reduce the amplitude of miniature excitatory postsynaptic currents (mEPSCs) of V1 L2/3 neurons in DE mice, but not in slices obtained from normal reared (NR) controls. Unexpectedly, the same stimulation pattern produced an up-regulation of mEPSC amplitudes in V1 L2/3 neurons from mice that received 2 h of light re-exposure (LE). A Poisson spike train exhibiting the same average frequency as the patterns recorded in vivo was equally effective at depressing mEPSC amplitudes in L2/3 neurons in V1 slices prepared from DE mice. Collectively, our results suggest that the history of visual experience modifies the responses of V1 neurons to stimulation and that rapid homeostatic depression of excitatory synapses can be driven by non-patterned input activity.

NMDA Receptor-Dependent Synaptic Depression in Potentiated Synapses of the Anterior Cingulate Cortex of adult Mice.

Long-term potentiation (LTP) is an important molecular mechanism for chronic pain in the anterior cingulate cortex (ACC), a key cortical region for pain perception and emotional regulation. Inhibiting ACC LTP via various manipulations or pharmacological treatments blocks chronic pain. Long-term depression (LTD) is another form of synaptic plasticity in the ACC, which is also proved to be involved in the mechanisms of chronic pain. However, less is known about the interactive relationship between LTP and LTD in the ACC. Whether the synaptic depression could be induced after synaptic LTP in the ACC is not clear. In the present study, we used multi-channel field potential recording systems to study synaptic depression after LTP in the ACC of adult mice. We found that low frequency stimulus (LFS: 1 Hz, 15 min) inhibited theta burst stimulation (TBS)-induced LTP at 30 min after the induction of LTP. However, LFS failed to induce depression at 90 min after the induction of LTP. Furthermore, NMDA receptor antagonist AP-5 blocked the induction of synaptic depression after potentiation. The GluN2B-selective antagonist Ro25-6981 also inhibited the phenomenon in the ACC, while the GluN2A-selective antagonist NVP-AAM077 and the GluN2C/D-selective antagonist PPDA and UBP145 had no any significant effect. These results suggest that synaptic LTP can be depressed by LTD in a time dependent manner, and GluN2B-containing NMDA receptors play important roles in this form of synaptic depression.

A theoretical framework for the site-specific and frequency-dependent neuronal effects of deep brain stimulation.

BACKGROUND: Deep brain stimulation is an established therapy for several neurological disorders; however, its effects on neuronal activity vary across brain regions and depend on stimulation settings. Understanding these variable responses can aid in the development of physiologically-informed stimulation paradigms in existing or prospective indications. OBJECTIVE: Provide experimental and computational insights into the brain-region-specific and frequency-dependent effects of extracellular stimulation on neuronal activity. METHODS: In patients with movement disorders, single-neuron recordings were acquired from the subthalamic nucleus, substantia nigra pars reticulata, ventral intermediate nucleus, or reticular thalamus during microstimulation across various frequencies (1-100 Hz) to assess single-pulse and frequency-response functions. Moreover, a biophysically-realistic computational framework was developed which generated postsynaptic responses under the assumption that electrical stimuli simultaneously activated all convergent presynaptic inputs to stimulation target neurons. The framework took into consideration the relative distributions of excitatory/inhibitory afferent inputs to model site-specific responses, which were in turn embedded within a model of short-term synaptic plasticity to account for stimulation frequency-dependence. RESULTS: We demonstrated microstimulation-evoked excitatory neuronal responses in thalamic structures (which have predominantly excitatory inputs) and inhibitory responses in basal ganglia structures (predominantly inhibitory inputs); however, higher stimulation frequencies led to a loss of site-specificity and convergence towards neuronal suppression. The model confirmed that site-specific responses could be simulated by accounting for local neuroanatomical/microcircuit properties, while suppression of neuronal activity during high-frequency stimulation was mediated by short-term synaptic depression. CONCLUSIONS: Brain-region-specific and frequency-dependant neuronal responses could be simulated by considering neuroanatomical (local microcircuitry) and neurophysiological (short-term plasticity) properties.

Short-Term Synaptic Plasticity Makes Neurons Sensitive to the Distribution of Presynaptic Population Firing Rates.

The ability to discriminate spikes that encode a particular stimulus from spikes produced by background activity is essential for reliable information processing in the brain. We describe how synaptic short-term plasticity (STP) modulates the output of presynaptic populations as a function of the distribution of the spiking activity and find a strong relationship between STP features and sparseness of the population code, which could solve this problem. Furthermore, we show that feedforward excitation followed by inhibition (FF-EI), combined with target-dependent STP, promote substantial increase in the signal gain even for considerable deviations from the optimal conditions, granting robustness to this mechanism. A simulated neuron driven by a spiking FF-EI network is reliably modulated as predicted by a rate analysis and inherits the ability to differentiate sparse signals from dense background activity changes of the same magnitude, even at very low signal-to-noise conditions. We propose that the STP-based distribution discrimination is likely a latent function in several regions such as the cerebellum and the hippocampus.

Presynaptic Kv3 channels are required for fast and slow endocytosis of synaptic vesicles.

Since their discovery decades ago, the primary physiological and pathological effects of potassium channels have been attributed to their ion conductance, which sets membrane potential and repolarizes action potentials. For example, Kv3 family channels regulate neurotransmitter release by repolarizing action potentials. Here we report a surprising but crucial function independent of potassium conductance: by organizing the F-actin cytoskeleton in mouse nerve terminals, the Kv3.3 protein facilitates slow endocytosis, rapid endocytosis, vesicle mobilization to the readily releasable pool, and recovery of synaptic depression during repetitive firing. A channel mutation that causes spinocerebellar ataxia inhibits endocytosis, vesicle mobilization, and synaptic transmission during repetitive firing by disrupting the ability of the channel to nucleate F-actin. These results unmask novel functions of potassium channels in endocytosis and vesicle mobilization crucial for sustaining synaptic transmission during repetitive firing. Potassium channel mutations that impair these "non-conducting" functions may thus contribute to generation of diverse neurological disorders.