Spike Bursts Research Articles

High-frequency burst spiking in layer 5 thick-tufted pyramids of rat primary somatosensory cortex encodes exploratory touch

Diversity of cell-types that collectively shape the cortical microcircuit ensures the necessary computational richness to orchestrate a wide variety of behaviors. The information content embedded in spiking activity of identified cell-types remain unclear to a large extent. Here, we recorded spike responses upon whisker touch of anatomically identified excitatory cell-types in primary somatosensory cortex in naive, untrained rats. We find major differences across layers and cell-types. The temporal structure of spontaneous spiking contains high-frequency bursts (≥100 Hz) in all morphological cell-types but a significant increase upon whisker touch is restricted to layer L5 thick-tufted pyramids (L5tts) and thus provides a distinct neurophysiological signature. We find that whisker touch can also be decoded from L5tt bursting, but not from other cell-types. We observed high-frequency bursts in L5tts projecting to different subcortical regions, including thalamus, midbrain and brainstem. We conclude that bursts in L5tts allow accurate coding and decoding of exploratory whisker touch.

Simulation of spiking activities neuron models using the Euler method

Simulation of neuron spiking activity models has been carried out using the Euler method. This study aims to simulate spiking activity in a neuron model. The neuron model used is the Hodgkin-Huxley neuron model, Integrate and Fire neuron model, Wilson neuron model, and Izhikevich neuron model. The research was conducted by implementing the mathematical equations of each neuron model used and then recording the membrane potential changes from time to time using the Euler method in MATLAB. The different forms of spiking activity were done by varying the variable’s value in each mathematical equation of a neuron model that describes the processing of action potentials (spikes) influenced by ion channel activity. The results showed that the Integrate and Fire neuron models produce regular spiking (RS), Hodgkin-Huxley neuron models have regular spiking (RS) forms, Wilson neuron models produce regular spiking (RS), fast-spiking (FS), and intrinsic bursting (IB), Izhikevich neuron model produces regular spiking (RS), fast-spiking (FS), intrinsic bursting (IB), chattering neurons (CH), and low threshold spiking (LTS). The complexity of the variables used and the spiking activity generated by each neuron model can provide an overview of computational efficiency and proximity to actual biological neurons.

Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits.

Synaptic plasticity is believed to be a key physiological mechanism for learning. It is well established that it depends on pre- and postsynaptic activity. However, models that rely solely on pre- and postsynaptic activity for synaptic changes have, so far, not been able to account for learning complex tasks that demand credit assignment in hierarchical networks. Here we show that if synaptic plasticity is regulated by high-frequency bursts of spikes, then pyramidal neurons higher in a hierarchical circuit can coordinate the plasticity of lower-level connections. Using simulations and mathematical analyses, we demonstrate that, when paired with short-term synaptic dynamics, regenerative activity in the apical dendrites and synaptic plasticity in feedback pathways, a burst-dependent learning rule can solve challenging tasks that require deep network architectures. Our results demonstrate that well-known properties of dendrites, synapses and synaptic plasticity are sufficient to enable sophisticated learning in hierarchical circuits.

Efficient learning with augmented spikes: A case study with image classification

Efficient learning of spikes plays a valuable role in training spiking neural networks (SNNs) to have desired responses to input stimuli. However, current learning rules are limited to a binary form of spikes. The seemingly ubiquitous phenomenon of burst in nervous systems suggests a new way to carry more information with spike bursts in addition to times. Based on this, we introduce an advanced form, the augmented spikes, where spike coefficients are used to carry additional information. How could neurons learn and benefit from augmented spikes remains unclear. In this paper, we propose two new efficient learning rules to process spatiotemporal patterns composed of augmented spikes. Moreover, we examine the learning abilities of our methods with a synthetic recognition task of augmented spike patterns and two practical ones for image classification. Experimental results demonstrate that our rules are capable of extracting information carried by both the timing and coefficient of spikes. Our proposed approaches achieve remarkable performance and good robustness under various noise conditions, as compared to benchmarks. The improved performance indicates the merits of augmented spikes and our learning rules, which could be beneficial and generalized to a broad range of spike-based platforms.

Benign EEG variants in the sleep–wake cycle: A prospective observational study using the 10–20 system and additional electrodes

ObjectivesTo study the prevalence of benign EEG variants (BEVs) in the sleep–wake cycle among 1163 consecutive patients. MethodsProspective, observational EEG study using the 10–20 system with systematically two additional anterior-temporal electrodes. Depending on clinical indications, other electrodes were added. REM sleep identification was based on its characteristic EEG grapho-elements and rapid eye movements, clearly detectable with the additional anterior-temporal and fronto-polar electrodes due to eye proximity. The video-EEG monitoring duration was between 24hours and eight days. ResultsWe identified 710 patients (61%) with BEVs. Positive occipital sharp transients of sleep (POSTs) were observed in 36.4% of participants, mu rhythm in 22.4%, lambda waves in 16.7%, wicket spikes (WS) in 15%, 14- and 6-Hz positive bursts in 8.3%, benign sporadic sleep spikes (BSSS) in 3.3%, rhythmic mid-temporal theta burst of drowsiness (RMTD) in 2.15%, midline theta rhythm in 2.1% and six-Hz spike and wave (SW) bursts in 0.1%. WS and RMTD were present during wakefulness, NREM (14.1%, 1.3%, respectively) and REM sleep (3.3%, 1.1%, respectively). Mu rhythm was also observed during NREM (1.5%) and REM sleep (7.7%). Fourteen- and 6-Hz positive bursts were present during NREM (4.5%) and REM sleep (6.5%). BSSS and six-Hz SW bursts were only observed during NREM sleep. ConclusionsThe prevalence of BEVs is much higher than current estimates. POSTs and WS can no longer be considered as unusual patterns but physiological patterns of NREM sleep. RMTD and mu rhythm may be observed during NREM and REM sleep.

Radio Spectral Imaging of an M8.4 Eruptive Solar Flare: Possible Evidence of a Termination Shock

Abstract Solar flare termination shocks have been suggested as one of the viable mechanisms for accelerating electrons and ions to high energies. Observational evidence of such shocks, however, remains rare. Using radio dynamic spectroscopic imaging of a long-duration C1.9 flare obtained by the Karl G. Jansky Very Large Array (VLA), Chen et al. suggested that a type of coherent radio bursts, referred to as “stochastic spike bursts,” were radio signatures of nonthermal electrons interacting with myriad density fluctuations at the front of a flare termination shock. Here we report another stochastic spike burst event recorded during the extended energy release phase of a long-duration M8.4-class eruptive flare on 2012 March 10. VLA radio spectroscopic imaging of the spikes in 1.0–1.6 GHz shows that, similar to the case of Chen et al., the burst centroids form an extended, ∼10″-long structure in the corona. By combining extreme-ultraviolet imaging observations of the flare from two vantage points with hard X-ray and ultraviolet observations of the flare ribbon brightenings, we reconstruct the flare arcade in three dimensions. The results show that the spike source is located at ∼60 Mm above the flare arcade, where a diffuse supra-arcade fan and multitudes of plasma downflows are present. Although the flare arcade and ribbons seen during the impulsive phase do not allow us to clearly understand how the observed spike source location is connected to the flare geometry, the cooling flare arcade observed 2 hr later suggests that the spikes are located in the above-the-loop-top region, where a termination shock presumably forms.

Noninvasive neuromagnetic single-trial analysis of human neocortical population spikes

Neuronal spiking is commonly recorded by invasive sharp microelectrodes, whereas standard noninvasive macroapproaches (e.g., electroencephalography [EEG] and magnetoencephalography [MEG]) predominantly represent mass postsynaptic potentials. A notable exception are low-amplitude high-frequency (∼600 Hz) somatosensory EEG/MEG responses that can represent population spikes when averaged over hundreds of trials to raise the signal-to-noise ratio. Here, a recent leap in MEG technology-featuring a factor 10 reduction in white noise level compared with standard systems-is leveraged to establish an effective single-trial portrayal of evoked cortical population spike bursts in healthy human subjects. This time-resolved approach proved instrumental in revealing a significant trial-to-trial variability of burst amplitudes as well as time-correlated (∼10 s) fluctuations of burst response latencies. Thus, ultralow-noise MEG enables noninvasive single-trial analyses of human cortical population spikes concurrent with low-frequency mass postsynaptic activity and thereby could comprehensively characterize cortical processing, potentially also in diseases not amenable to invasive microelectrode recordings.

Electro-clinical features in epileptic children with chromosome 15q duplication syndrome

ObjectiveWe aimed to describe epilepsy and EEG patterns related to vigilance states and age, in chromosome15-long-arm-duplication-syndrome (dup15q) children with epilepsy, in both duplication types: interstitial (intdup15) and isodicentric (idic15). MethodsClinical data and 70 EEGs of 12 patients (5 intdup15, 7 idic15), followed from 4.5 m.o to 17y4m (median follow-up 8y3m), were retrospectively reviewed. EEGs were analyzed visually and using power spectrum analysis. ResultsSeventy video-EEGs were analyzed (1–16 per patient, median 6), follow-up lasting up to 8y10m (median 4y2m): 25 EEGs in intdup15 (8 m.o to 12y.o, median 4y6m) and 45 EEGs in idic15 (7 m.o to 12 y.o, median 15 m). Epilepsy: 6 West syndrome (WS) (2intdup15, 4idic15); 4 Lennox-Gastaut syndromes (LGS) (1 intdup15, 3 idic15), 2 evolving from WS; focal epilepsy (3 intdup15). In idic15, WS displayed additional myoclonic seizures (3), atypical (4) or no hypsarrhythmia (2) and posterior predominant spike and polyspike bursts (4). Beta-band rapid-rhythms (RR): present in 11 patients, power decreased during non-REM-sleep, localization shifted from diffuse to anterior, peak frequency increased with age. ConclusionWS with peculiar electro-clinical features and LGS, along with beta-band RR decreasing in non-REM-sleep and shifting from diffuse to anterior localization with age are recognizable features pointing towards dup15q diagnosis in children with autism spectrum disorder and developmental delay. SignificanceThis study describes electroclinical features in both interstitial and isodicentric duplications of chromosome 15q, in epileptic children, including some recent extensions regarding sleep features; and illustrates how the temporo-spatial organization of beta oscillations can be of significant help in directing towards dup15q diagnosis hypothesis.

Tonic firing mode of midbrain dopamine neurons continuously tracks reward values changing moment-by-moment.

Animal behavior is regulated based on the values of future rewards. The phasic activity of midbrain dopamine neurons signals these values. Because reward values often change over time, even on a subsecond-by-subsecond basis, appropriate behavioral regulation requires continuous value monitoring. However, the phasic dopamine activity, which is sporadic and has a short duration, likely fails continuous monitoring. Here, we demonstrate a tonic firing mode of dopamine neurons that effectively tracks changing reward values. We recorded dopamine neuron activity in monkeys during a Pavlovian procedure in which the value of a cued reward gradually increased or decreased. Dopamine neurons tonically increased and decreased their activity as the reward value changed. This tonic activity was evoked more strongly by non-burst spikes than burst spikes producing a conventional phasic activity. Our findings suggest that dopamine neurons change their firing mode to effectively signal reward values in a given situation.

Different effects of monophasic pulses and biphasic pulses applied by a bipolar stimulation electrode in the rat hippocampal CA1 region

BackgroundElectrical pulse stimulations have been applied in brain for treating certain diseases such as movement disorders. High-frequency stimulations (HFS) of biphasic pulses have been used in clinic stimulations, such as deep brain stimulation (DBS), to minimize the risk of tissue damages caused by the electrical stimulations. However, HFS sequences of monophasic pulses have often been used in animal experiments for studying neuronal responses to the stimulations. It is not clear yet what the differences of the neuronal responses to the HFS of monophasic pulses from the HFS of biphasic pulses are.MethodsTo investigate the neuronal responses to the two types of pulses, orthodromic-HFS (O-HFS) and antidromic-HFS (A-HFS) of biphasic and monophasic pulses (1-min) were delivered by bipolar electrodes, respectively, to the Schaffer collaterals (i.e., afferent fibers) and the alveus fibers (i.e., efferent fibers) of the rat hippocampal CA1 region in vivo. Evoked population spikes of CA1 pyramidal neurons to the HFSs were recorded in the CA1 region. In addition, single pulses of antidromic- and orthodromic-test stimuli were applied before and after HFSs to evaluate the baseline and the recovery of neuronal activity, respectively.ResultsSpreading depression (SD) appeared during sequences of 200-Hz monophasic O-HFS with a high incidence (4/5), but did not appear during corresponding 200-Hz biphasic O-HFS (0/6). A preceding burst of population spikes appeared before the SD waveforms. Then, the SD propagated slowly, silenced neuronal firing temporarily and resulted in partial recovery of orthodromically evoked population spikes (OPS) after the end of O-HFS. No SD events appeared during the O-HFS with a lower frequency of 100 Hz of monophasic or biphasic pulses (0/5 and 0/6, respectively), neither during the A-HFS of 200-Hz pulses (0/9). The antidromically evoked population spikes (APS) after 200-Hz biphasic A-HFS recovered to baseline level within ~ 2 min. However, the APS only recovered partially after the 200-Hz A-HFS of monophasic pulses.ConclusionsThe O-HFS with a higher frequency of monophasic pulses can induce the abnormal neuron activity of SD and the A-HFS of monophasic pulses can cause a persisting attenuation of neuronal excitability, indicating neuronal damages caused by monophasic stimulations in brain tissues. The results provide guidance for proper stimulation protocols in clinic and animal experiments.

Neural Coding in Spiking Neural Networks: A Comparative Study for Robust Neuromorphic Systems.

Various hypotheses of information representation in brain, referred to as neural codes, have been proposed to explain the information transmission between neurons. Neural coding plays an essential role in enabling the brain-inspired spiking neural networks (SNNs) to perform different tasks. To search for the best coding scheme, we performed an extensive comparative study on the impact and performance of four important neural coding schemes, namely, rate coding, time-to-first spike (TTFS) coding, phase coding, and burst coding. The comparative study was carried out using a biological 2-layer SNN trained with an unsupervised spike-timing-dependent plasticity (STDP) algorithm. Various aspects of network performance were considered, including classification accuracy, processing latency, synaptic operations (SOPs), hardware implementation, network compression efficacy, input and synaptic noise resilience, and synaptic fault tolerance. The classification tasks on Modified National Institute of Standards and Technology (MNIST) and Fashion-MNIST datasets were applied in our study. For hardware implementation, area and power consumption were estimated for these coding schemes, and the network compression efficacy was analyzed using pruning and quantization techniques. Different types of input noise and noise variations in the datasets were considered and applied. Furthermore, the robustness of each coding scheme to the non-ideality-induced synaptic noise and fault in analog neuromorphic systems was studied and compared. Our results show that TTFS coding is the best choice in achieving the highest computational performance with very low hardware implementation overhead. TTFS coding requires 4x/7.5x lower processing latency and 3.5x/6.5x fewer SOPs than rate coding during the training/inference process. Phase coding is the most resilient scheme to input noise. Burst coding offers the highest network compression efficacy and the best overall robustness to hardware non-idealities for both training and inference processes. The study presented in this paper reveals the design space created by the choice of each coding scheme, allowing designers to frame each scheme in terms of its strength and weakness given a designs’ constraints and considerations in neuromorphic systems.

Analysis of extracellular spike waveforms and associated receptive fields of neurons in cat primary visual cortex.

Extracellular spikes recorded in the visual cortex (Area 17/18, V1) are commonly classified into either regular-spiking (RS) or fast-spiking (FS). Using multi-electrode arrays positioned in cat V1 and a broadband stimulus, we show that there is also a distinct class with positive-spiking (PS) waveforms. PS units were associated mainly with non-oriented receptive fields while RS and FS units had orientation-selective receptive fields. We suggest that PS units are recordings of axons originating from the thalamus. This conclusion was reinforced by our finding that we could record PS units after cortical silencing, but not record RS and FS units. The importance of our findings is that we were able to correlate spike shapes with receptive field characteristics with high precision using multi-electrode extracellular recording techniques. This allows considerable increases in the amount of information that can be extracted from future cortical experiments. Extracellular spike waveforms from recordings in the visual cortex have been classified into either regular-spiking (RS) or fast-spiking (FS) units. While both these types of spike waveforms are negative-dominant, we show that there are also distinct classes of spike waveforms in visual Area 17/18 (V1) of anaesthetised cats with positive-dominant waveforms, which are not regularly reported. The spatial receptive fields (RFs) of these different spike waveform types were estimated, which objectively revealed the existence of oriented and non-oriented RFs. We found that units with positive-dominant spikes, which have been associated with recordings from axons in the literature, had mostly non-oriented RFs (84%), which are similar to the centre-surround RFs observed in the dorsal lateral geniculate nucleus (dLGN). Thus, we hypothesise that these positive-dominant waveforms may be recordings from dLGN afferents. We recorded from V1 before and after the application of muscimol (a cortical silencer) and found that the positive-dominant spikes (PS) remained while the RS and FS cells did not. We also noted that the PS units had spiking characteristics normally associated with dLGN units (i.e. higher response spike rates, lower response latencies and higher proportion of burst spikes). Our findings show quantitatively that it is possible to correlate the RF properties of cortical neurons with particular spike waveforms. This has implications for how extracellular recordings should be interpreted and complex experiments can now be contemplated that would have been very challenging previously, such as assessing the feedforward connectivity between brain areas in the same location of cortical tissue.

Spike bursting in a dragonfly target-detecting neuron

Dragonflies visually detect prey and conspecifics, rapidly pursuing these targets via acrobatic flights. Over many decades, studies have investigated the elaborate neuronal circuits proposed to underlie this rapid behaviour. A subset of dragonfly visual neurons exhibit exquisite tuning to small, moving targets even when presented in cluttered backgrounds. In prior work, these neuronal responses were quantified by computing the rate of spikes fired during an analysis window of interest. However, neuronal systems can utilize a variety of neuronal coding principles to signal information, so a spike train’s information content is not necessarily encapsulated by spike rate alone. One example of this is burst coding, where neurons fire rapid bursts of spikes, followed by a period of inactivity. Here we show that the most studied target-detecting neuron in dragonflies, CSTMD1, responds to moving targets with a series of spike bursts. This spiking activity differs from those in other identified visual neurons in the dragonfly, indicative of different physiological mechanisms underlying CSTMD1’s spike generation. Burst codes present several advantages and disadvantages compared to other coding approaches. We propose functional implications of CSTMD1’s burst coding activity and show that spike bursts enhance the robustness of target-evoked responses.

Synaptic plasticity rules with physiological calcium levels

Spike-timing-dependent plasticity (STDP) is considered as a primary mechanism underlying formation of new memories during learning. Despite the growing interest in activity-dependent plasticity, it is still unclear whether synaptic plasticity rules inferred from in vitro experiments are correct in physiological conditions. The abnormally high calcium concentration used in in vitro studies of STDP suggests that in vivo plasticity rules may differ significantly from in vitro experiments, especially since STDP depends strongly on calcium for induction. We therefore studied here the influence of extracellular calcium on synaptic plasticity. Using a combination of experimental (patch-clamp recording and Ca2+ imaging at CA3-CA1 synapses) and theoretical approaches, we show here that the classic STDP rule in which pairs of single pre- and postsynaptic action potentials induce synaptic modifications is not valid in the physiological Ca2+ range. Rather, we found that these pairs of single stimuli are unable to induce any synaptic modification in 1.3 and 1.5 mM calcium and lead to depression in 1.8 mM. Plasticity can only be recovered when bursts of postsynaptic spikes are used, or when neurons fire at sufficiently high frequency. In conclusion, the STDP rule is profoundly altered in physiological Ca2+, but specific activity regimes restore a classical STDP profile.

Variable but not random: temporal pattern coding in a songbird brain area necessary for song modification.

Practice of a complex motor gesture involves motor exploration to attain a better match to target, but little is known about the neural code for such exploration. We examine spiking in a premotor area of the songbird brain critical for song modification and quantify correlations between spiking and time in the motor sequence. While isolated spikes code for time in song during performance of song to a female bird, extended strings of spiking and silence, particularly bursts, code for time in song during undirected (solo) singing, or "practice." Bursts code for particular times in song with more information than individual spikes, and this spike-spike synergy is significantly higher during undirected singing. The observed pattern information cannot be accounted for by a Poisson model with a matched time-varying rate, indicating that the precise timing of spikes in both bursts in undirected singing and isolated spikes in directed singing code for song with a temporal code. Temporal coding during practice supports the hypothesis that lateral magnocellular nucleus of the anterior nidopallium neurons actively guide song modification at local instances in time.NEW & NOTEWORTHY This paper shows that bursts of spikes in the songbird brain during practice carry information about the output motor pattern. The brain's code for song changes with social context, in performance versus practice. Synergistic combinations of spiking and silence code for time in the bird's song. This is one of the first uses of information theory to quantify neural information about a motor output. This activity may guide changes to the song.

Interspike intervals within retinal spike bursts combinatorially encode multiple stimulus features.

Neurons in various regions of the brain generate spike bursts. While the number of spikes within a burst has been shown to carry information, information coding by interspike intervals (ISIs) is less well understood. In particular, a burst with k spikes has k-1 intraburst ISIs, and these k-1 ISIs could theoretically encode k-1 independent values. In this study, we demonstrate that such combinatorial coding occurs for retinal bursts. By recording ganglion cell spikes from isolated salamander retinae, we found that intraburst ISIs encode oscillatory light sequences that are much faster than the light intensity modulation encoded by the number of spikes. When a burst has three spikes, the two intraburst ISIs combinatorially encode the amplitude and phase of the oscillatory sequence. Analysis of trial-to-trial variability suggested that intraburst ISIs are regulated by two independent mechanisms responding to orthogonal oscillatory components, one of which is common to bursts with a different number of spikes. Therefore, the retina encodes multiple stimulus features by exploiting all degrees of freedom of burst spike patterns, i.e., the spike number and multiple intraburst ISIs.

Neural control of rapid binocular eye movements: Saccade-vergence burst neurons

During normal viewing, we direct our eyes between objects in three-dimensional (3D) space many times a minute. To accurately fixate these objects, which are usually located in different directions and at different distances, we must generate eye movements with appropriate versional and vergence components. These combined saccade-vergence eye movements result in disjunctive saccades with a vergence component that is much faster than that generated during smooth, symmetric vergence eye movements. The neural control of disjunctive saccades is still poorly understood. Recent anatomical studies suggested that the central mesencephalic reticular formation (cMRF), located lateral to the oculomotor nucleus, contains premotor neurons potentially involved in the neural control of these eye movements. We have therefore investigated the role of the cMRF in the control of disjunctive saccades in trained rhesus monkeys. Here, we describe a unique population of cMRF neurons that, during disjunctive saccades, display a burst of spikes that are highly correlated with vergence velocity. Importantly, these neurons show no increase in activity for either conjugate saccades or symmetric vergence. These neurons are termed saccade-vergence burst neurons (SVBNs) to maintain consistency with modeling studies that proposed that such a class of neuron exists to generate the enhanced vergence velocities observed during disjunctive saccades. Our results demonstrate the existence and characteristics of SVBNs whose activity is correlated solely with the vergence component of disjunctive saccades and, based on modeling studies, are critically involved in the generation of the disjunctive saccades required to view objects in our 3D world.

Biomimetic integrated olfactory sensory and olfactory bulb systems in vitro based on a chip

A variety of mammalian or insect behaviors rely on the recognition of relevant odor stimuli. The olfactory system detects and translates complex olfactory stimuli (odors) through the unique and reproducible dynamic ensembles of neuronal activities. This process is involved in various types of neurons of olfactory parts, thereby encoding olfactory information or predicting progression in some neuropsychiatric diseases. In this paper, we constructed a biomimetic model including olfactory sensing system and olfactory bulb processing system to map olfactory-associated ensembles of neuronal activity. The olfactory receptor neurons (ORNs) and olfactory bulb (OB) neurons were primarily cultured and the immunofluorescence images were performed to identify the types of neurons. Diacetyl solution was used as an odor stimulus, and the spike bursts and random spike firing patterns of concentration-dependent excitatory responses were obtained from the ORNs network. The spike waveform and feature parameters were extracted including the spike number and interval in per burst to program the stimulation unit and sequences. The sequences containing odor information were applied to the OB neuronal network for the simulation of the primary olfactory processing. The response pattern and change rule of the OB neuronal network were consistent with the OB neurons affected by the neurotransmitter, which is the carrier of olfactory information transmission in vivo. This biomimetic integrated olfactory sensory and processing system can serve as a novel model for studying the physiological and pathological mechanisms of olfaction, and the pharmacological application in vitro.

Long-term potentiation of glycinergic synapses by semi-natural stimulation patterns during tonotopic map refinement

Before the onset of hearing, cochlea-generated patterns of spontaneous spike activity drive the maturation of central auditory circuits. In the glycinergic sound localization pathway from the medial nucleus of the trapezoid body (MNTB) to the lateral superior olive (LSO) this spontaneous activity guides the strengthening and silencing of synapses which underlies tonotopic map refinement. However, the mechanisms by which patterned activity regulates synaptic refinement in the MNTB-LSO pathway are still poorly understood. To address this question, we recorded from LSO neurons in slices from prehearing mice while stimulating MNTB afferents with stimulation patterns that mimicked those present in vivo. We found that these semi-natural stimulation patterns reliably elicited a novel form of long-term potentiation (LTP) of MNTB-LSO synapses. Stimulation patterns that lacked the characteristic high-frequency (200 Hz) component of prehearing spike activity failed to elicit potentiation. LTP was calcium dependent, required the activation of both g-protein coupled GABAB and metabotropic glutamate receptors and involved an increase in postsynaptic glycine receptor-mediated currents. Our results provide a possible mechanism linking spontaneous spike bursts to tonotopic map refinement and further highlight the importance of the co-release of GABA and glutamate from immature glycinergic MNTB terminals.

Direct translation of climbing fiber burst-mediated sensory coding into post-synaptic Purkinje cell dendritic calcium.

Climbing fibers (CFs) generate complex spikes (CS) and Ca2+ transients in cerebellar Purkinje cells (PCs), serving as instructive signals. The so-called 'all-or-none' character of CSs has been questioned since the CF burst was described. Although recent studies have indicated a sensory-driven enhancement of PC Ca2+ signals, how CF responds to sensory events and contributes to PC dendritic Ca2+ and CS remains unexplored. Here, single or simultaneous Ca2+ imaging of CFs and PCs in awake mice revealed the presynaptic CF Ca2+ amplitude encoded the sensory input's strength and directly influenced post-synaptic PC dendritic Ca2+ amplitude. The sensory-driven variability in CF Ca2+ amplitude depended on the number of spikes in the CF burst. Finally, the spike number of the CF burst determined the PC Ca2+ influx and CS properties. These results reveal the direct translation of sensory information-coding CF inputs into PC Ca2+, suggesting the sophisticated role of CFs as error signals.