Spike timing and reliability in cortical pyramidal neurons: effects of EPSC kinetics, input synchronization and background noise on spike timing

Physiological noise facilitates multiplexed coding of vibrotactile-like signals in somatosensory cortex

Neurons can use different aspects of their spiking to simultaneously represent (multiplex) different features of a stimulus. For example, some pyramidal neurons in primary somatosensory cortex (S1) use the rate and timing of their spikes to, respectively, encode the intensity and frequency of vibrotactile stimuli. Doing so has several requirements. Because they fire at low rates, pyramidal neurons cannot entrain 1:1 with high-frequency (100 to 600 Hz) inputs and, instead, must skip (i.e., not respond to) some stimulus cycles. The proportion of skipped cycles must vary inversely with stimulus intensity for firing rate to encode stimulus intensity. Spikes must phase-lock to the stimulus for spike times (intervals) to encode stimulus frequency, but, in addition, skipping must occur irregularly to avoid aliasing. Using simulations and in vitro experiments in which mouse S1 pyramidal neurons were stimulated with inputs emulating those induced by vibrotactile stimuli, we show that fewer cycles are skipped as stimulus intensity increases, as required for rate coding, and that intrinsic or synaptic noise can induce irregular skipping without disrupting phase locking, as required for temporal coding. This occurs because noise can modulate the reliability without disrupting the precision of spikes evoked by small-amplitude, fast-onset signals. Specifically, in the fluctuation-driven regime associated with sparse spiking, rate and temporal coding are both paradoxically improved by the strong synaptic noise characteristic of the intact cortex. Our results demonstrate that multiplexed coding by S1 pyramidal neurons is not only feasible under in vivo conditions, but that background synaptic noise is actually beneficial.

Variations in Commissural Input Processing Across Different Types of Cortical Projection Neurons

To understand how incoming cortical inputs are processed by different types of cortical projection neurons in the medial prefrontal cortex, we compared intrinsic physiological properties of and commissural excitatory/inhibitory influences on layer 5 intratelencephalic (IT), layer 5 pyramidal tract (PT), and layers 2/3 IT projection neurons. We found that intrinsic physiological properties and commissural synaptic transmission varied across the three types of projection neurons. The rank order of intrinsic excitability was layer 5 PT > layer 5 IT > layers 2/3 IT neurons. Commissural connectivity was higher in layers 2/3 than layer 5 projection neurons, but commissural excitatory influence was stronger on layer 5 than layers 2/3 pyramidal neurons. Paired-pulse ratio was also greater in PT than IT neurons. These results indicate that commissural inputs activate deep layer PT neurons most preferentially and superficial layer IT neurons least preferentially. Deep layer PT neurons might faithfully transmit cortical input signals to downstream subcortical structures for reliable control of behavior, whereas superficial layer IT neurons might integrate cortical input signals from diverse sources in support of higher-order cognitive functions.

Intracellular Properties of Deep-Layer Pyramidal Neurons in Frontal Eye Field of Macaque Monkeys

Although many details remain unknown, several positive statements can be made about the laminar distribution of primate frontal eye field (FEF) neurons with different physiological properties. Most certainly, pyramidal neurons in the deep layer of FEF that project to the brainstem carry movement and fixation signals but clear evidence also support that at least some deep-layer pyramidal neurons projecting to the superior colliculus carry visual responses. Thus, deep-layer neurons in FEF are functionally heterogeneous. Despite the useful functional distinctions between neuronal responses in vivo, the underlying existence of distinct cell types remain uncertain, mostly due to methodological limitations of extracellular recordings in awake behaving primates. To substantiate the functionally defined cell types encountered in the deep layer of FEF, we measured the biophysical properties of pyramidal neurons recorded intracellularly in brain slices issued from macaque monkey biopsies. Here, we found that biophysical properties recorded in vitro permit us to distinguish two main subtypes of regular-spiking neurons, with, respectively, low-resistance and low excitability vs. high-resistance and strong excitability. These results provide useful constraints for cognitive models of visual attention and saccade production by indicating that at least two distinct populations of deep-layer neurons exist.

Somatostatin-expressing parafacial neurons are CO2/H+ sensitive and regulate baseline breathing

Glutamatergic neurons in the retrotrapezoid nucleus (RTN) function as respiratory chemoreceptors by regulating breathing in response to tissue CO2/H+. The RTN and greater parafacial region may also function as a chemosensing network composed of CO2/H+-sensitive excitatory and inhibitory synaptic interactions. In the context of disease, we showed that loss of inhibitory neural activity in a mouse model of Dravet syndrome disinhibited RTN chemoreceptors and destabilized breathing (Kuo et al., 2019). Despite this, contributions of parafacial inhibitory neurons to control of breathing are unknown, and synaptic properties of RTN neurons have not been characterized. Here, we show the parafacial region contains a limited diversity of inhibitory neurons including somatostatin (Sst)-, parvalbumin (Pvalb)-, and cholecystokinin (Cck)-expressing neurons. Of these, Sst-expressing interneurons appear uniquely inhibited by CO2/H+. We also show RTN chemoreceptors receive inhibitory input that is withdrawn in a CO2/H+-dependent manner, and chemogenetic suppression of Sst+ parafacial neurons, but not Pvalb+ or Cck+ neurons, increases baseline breathing. These results suggest Sst-expressing parafacial neurons contribute to RTN chemoreception and respiratory activity.

Bidirectional learning in upbound and downbound microzones of the cerebellum

Over the past several decades, theories about cerebellar learning have evolved. A relatively simple view that highlighted the contribution of one major form of heterosynaptic plasticity to cerebellar motor learning has given way to a plethora of perspectives that suggest that many different forms of synaptic and non-synaptic plasticity, acting at various sites, can control multiple types of learning behaviour. However, there still seem to be contradictions between the various hypotheses with regard to the mechanisms underlying cerebellar learning. The challenge is therefore to reconcile these different views and unite them into a single overall concept. Here I review our current understanding of the changes in the activity of cerebellar Purkinje cells in different 'microzones' during various forms of learning. I describe an emerging model that indicates that the activity of each microzone is bound to either increase or decrease during the initial stages of learning, depending on the directional and temporal demands of its downstream circuitry and the behaviour involved.

Minimal Number of Required Inputs for Temporally Precise Action Potential Generation in Auditory Brainstem Nuclei

The auditory system relies on temporal precise information transfer, requiring an interplay of synchronously activated inputs and rapid postsynaptic integration. During late postnatal development synaptic, biophysical, and morphological features change to enable mature auditory neurons to perform their appropriate function. How the number of minimal required input fibers and the relevant EPSC time course integrated for action potential generation changes during late postnatal development is unclear. To answer these questions, we used in vitro electrophysiology in auditory brainstem structures from pre-hearing onset and mature Mongolian gerbils of either sex. Synaptic and biophysical parameters changed distinctively during development in the medial nucleus of the trapezoid body (MNTB), the medial superior olive (MSO), and the ventral and dorsal nucleus of the lateral lemniscus (VNLL and DNLL). Despite a reduction in input resistance in most cell types, all required fewer inputs in the mature stage to drive action potentials. Moreover, the EPSC decay time constant is a good predictor of the EPSC time used for action potential generation in all nuclei but the VNLL. Only in MSO neurons, the full EPSC time course is integrated by the neuron’s resistive element, while otherwise, the relevant EPSC time matches only 5–10% of the membrane time constant, indicating membrane charging as a dominant role for output generation. We conclude, that distinct developmental programs lead to a general increase in temporal precision and integration accuracy matched to the information relaying properties of the investigated nuclei.

Axonopathy and Reduction of Membrane Resistance: Key Features in a New Murine Model of Human GM1-Gangliosidosis

G_M1-gangliosidosis is caused by a reduced activity of β-galactosidase (Glb1), resulting in intralysosomal accumulations of G_M1. The aim of this study was to reveal the pathogenic mechanisms of G_M1-gangliosidosis in a new Glb1 knockout mouse model. Glb1^−/− mice were analyzed clinically, histologically, immunohistochemically, electrophysiologically and biochemically. Morphological lesions in the central nervous system were already observed in two-month-old mice, whereas functional deficits, including ataxia and tremor, did not start before 3.5-months of age. This was most likely due to a reduced membrane resistance as a compensatory mechanism. Swollen neurons exhibited intralysosomal storage of lipids extending into axons and amyloid precursor protein positive spheroids. Additionally, axons showed a higher kinesin and lower dynein immunoreactivity compared to wildtype controls. Glb1^−/− mice also demonstrated loss of phosphorylated neurofilament positive axons and a mild increase in non-phosphorylated neurofilament positive axons. Moreover, marked astrogliosis and microgliosis were found, but no demyelination. In addition to the main storage material G_M1, G_A1, sphingomyelin, phosphatidylcholine and phosphatidylserine were elevated in the brain. In summary, the current Glb1^−/− mice exhibit a so far undescribed axonopathy and a reduced membrane resistance to compensate the functional effects of structural changes. They can be used for detailed examinations of axon–glial interactions and therapy trials of lysosomal storage diseases.

Rhythms of the body, rhythms of the brain: Respiration, neural oscillations, and embodied cognition

In spite of its importance as a life-defining rhythmic movement and its constant rhythmic contraction and relaxation of the body, respiration has not received attention in Embodied Cognition (EC) literature. Our paper aims to show that (1) respiration exerts significant and unexpected influence on cognitive processes, and (2) it does so by modulating neural synchronization that underlies specific cognitive processes. Then, (3) we suggest that the particular example of respiration may function as a model for a general mechanism through which the body influences cognitive functioning. Finally, (4) we work out the implications for EC, draw a parallel to the role of gesture, and argue that respiration sometimes plays a double, pragmatic and epistemic, role, which reduces the cognitive load. In such cases, consistent with EC, the overall cognitive activity includes a loop-like interaction between neural and non-neural elements.

Acoustical Enrichment during Early Development Improves Response Reliability in the Adult Auditory Cortex of the Rat

It is well known that auditory experience during early development shapes response properties of auditory cortex (AC) neurons, influencing, for example, tonotopical arrangement, response thresholds and strength, or frequency selectivity. Here, we show that rearing rat pups in a complex acoustically enriched environment leads to an increased reliability of responses of AC neurons, affecting both the rate and the temporal codes. For a repetitive stimulus, the neurons exhibit a lower spike count variance, indicating a more stable rate coding. At the level of individual spikes, the discharge patterns of individual neurons show a higher degree of similarity across stimulus repetitions. Furthermore, the neurons follow more precisely the temporal course of the stimulus, as manifested by improved phase-locking to temporally modulated sounds. The changes are persistent and present up to adulthood. The results document that besides basic alterations of receptive fields presented in our previous study, the acoustic environment during the critical period of postnatal development also leads to a decreased stochasticity and a higher reproducibility of neuronal spiking patterns.

Predicting the response of striatal spiny neurons to sinusoidal input

Spike-timing effects of small-amplitude sinusoidal currents were measured in mouse striatal spiny neurons firing repetitively. Spike-timing reliability varied with the stimulus frequency. For frequencies near the cell's firing rate, the cells altered firing rate to match the stimulus and became phase locked to it. The stimulus phase of firing during lock depended on the stimulus frequency relative to the cell's unperturbed firing rate. Interspike intervals during sinusoidal stimulation were predicted using an iterative map constructed from the cells' phase-resetting curve. Variability of interspike intervals was reduced by stimulation at all frequencies higher than about half the cell's unperturbed rate, and interspike intervals were accurately predicted by the map. Long sequences of spike times were predicted by iterating on the map. The accuracy of that prediction varied with frequency. Spike time predictability was highest near and during phase lock. The map predicted the phase of firing on the input and its dependence on stimulus frequency. Prediction errors, when they occurred, were of two kinds: unpredicted variation in interspike interval from intrinsic cell noise and accumulation of prediction errors from previous interspike intervals. Each type of prediction error arose from a different mechanism, and their impact was also predicted from the phase model. When two oscillatory input currents were presented simultaneously, striatal neurons responded selectively to only one of them, the one closest in frequency to the cell's unperturbed firing rate. Their spike times encoded the frequency and phase of that single oscillatory input.NEW & NOTEWORTHY During repetitive firing, the timing of action potentials is determined by the interaction between the input and voltage-sensitive currents throughout the interspike interval. This interaction is encapsulated in the neuron's phase-resetting curve. The phase-resetting curve predicted spike timing to small sinusoidal currents over a wide range of stimulus frequencies. Firing patterns were most sensitive to oscillatory components near the cell's own firing rate, even in the presence of noise and other inputs.

Regulation of Cortical Dynamic Range by Background Synaptic Noise and Feedforward Inhibition

The cortex encodes a broad range of inputs. This breadth of operation requires sensitivity to weak inputs yet non-saturating responses to strong inputs. If individual pyramidal neurons were to have a narrow dynamic range, as previously claimed, then staggered all-or-none recruitment of those neurons would be necessary for the population to achieve a broad dynamic range. Contrary to this explanation, we show here through dynamic clamp experiments in vitro and computer simulations that pyramidal neurons have a broad dynamic range under the noisy conditions that exist in the intact brain due to background synaptic input. Feedforward inhibition capitalizes on those noise effects to control neuronal gain and thereby regulates the population dynamic range. Importantly, noise allows neurons to be recruited gradually and occludes the staggered recruitment previously attributed to heterogeneous excitation. Feedforward inhibition protects spike timing against the disruptive effects of noise, meaning noise can enable the gain control required for rate coding without compromising the precise spike timing required for temporal coding.

Single mechanically-gated cation channel currents can trigger action potentials in neocortical and hippocampal pyramidal neurons

The mammalian brain is a mechanosensitive organ that responds to different mechanical forces ranging from intrinsic forces implicated in brain morphogenesis to extrinsic forces that can cause concussion and traumatic brain injury. However, little is known of the mechanosensors that transduce these forces. In this study we use cell-attached patch recording to measure single mechanically-gated (MG) channel currents and their affects on spike activity in identified neurons in neonatal mouse brain slices. We demonstrate that both neocortical and hippocampal pyramidal neurons express stretch-activated MG cation channels that are activated by suctions of ~25mm Hg, have a single channel conductance for inward current of 50-70pS and show weak selectivity for alkali metal cations (i.e., Na(+)<K(+)<Cs(+)). Significantly, single MG channel currents activated on the soma trigger spiking/action potentials in both neocortical and hippocampal pyramidal neurons. Not all neuron types studied here expressed MG channel currents. In particular, locus coeruleus and cerebellar Purkinje neurons showed no detectable MG channel activity. Moreover their robust rhythmic spike activity was resistant to mechanical modulation. Our observation that a single MG channel current can trigger spiking predicates the need for reassessment of the long held view that the impulse output of central neurons depends only upon their intrinsic voltage-gated channels and/or their integrated synaptic input.

Cortical Specializations Underlying Fast Computations

The time course of behaviorally relevant environmental events sets temporal constraints on neuronal processing. How does the mammalian brain make use of the increasingly complex networks of the neocortex, while making decisions and executing behavioral reactions within a reasonable time? The key parameter determining the speed of computations in neuronal networks is a time interval that neuronal ensembles need to process changes at their input and communicate results of this processing to downstream neurons. Theoretical analysis identified basic requirements for fast processing: use of neuronal populations for encoding, background activity, and fast onset dynamics of action potentials in neurons. Experimental evidence shows that populations of neocortical neurons fulfil these requirements. Indeed, they can change firing rate in response to input perturbations very quickly, within 1 to 3 ms, and encode high-frequency components of the input by phase-locking their spiking to frequencies up to 300 to 1000 Hz. This implies that time unit of computations by cortical ensembles is only few, 1 to 3 ms, which is considerably faster than the membrane time constant of individual neurons. The ability of cortical neuronal ensembles to communicate on a millisecond time scale allows for complex, multiple-step processing and precise coordination of neuronal activity in parallel processing streams, while keeping the speed of behavioral reactions within environmentally set temporal constraints.

Development and modulation of intrinsic membrane properties control the temporal precision of auditory brain stem neurons

Passive and active membrane properties determine the voltage responses of neurons. Within the auditory brain stem, refinements in these intrinsic properties during late postnatal development usually generate short integration times and precise action-potential generation. This developmentally acquired temporal precision is crucial for auditory signal processing. How the interactions of these intrinsic properties develop in concert to enable auditory neurons to transfer information with high temporal precision has not yet been elucidated in detail. Here, we show how the developmental interaction of intrinsic membrane parameters generates high firing precision. We performed in vitro recordings from neurons of postnatal days 9–28 in the ventral nucleus of the lateral lemniscus of Mongolian gerbils, an auditory brain stem structure that converts excitatory to inhibitory information with high temporal precision. During this developmental period, the input resistance and capacitance decrease, and action potentials acquire faster kinetics and enhanced precision. Depending on the stimulation time course, the input resistance and capacitance contribute differentially to action-potential thresholds. The decrease in input resistance, however, is sufficient to explain the enhanced action-potential precision. Alterations in passive membrane properties also interact with a developmental change in potassium currents to generate the emergence of the mature firing pattern, characteristic of coincidence-detector neurons. Cholinergic receptor-mediated depolarizations further modulate this intrinsic excitability profile by eliciting changes in the threshold and firing pattern, irrespective of the developmental stage. Thus our findings reveal how intrinsic membrane properties interact developmentally to promote temporally precise information processing.

Long-term temporal imprecision of information coding in the anterior cingulate cortex of mice with peripheral inflammation or nerve injury

Temporal properties of spike firing in the central nervous system (CNS) are critical for neuronal coding and the precision of information storage. Chronic pain has been reported to affect cognitive and emotional functions, in addition to trigger long-term plasticity in sensory synapses and behavioral sensitization. Less is known about the possible changes in temporal precision of cortical neurons in chronic pain conditions. In the present study, we investigated the temporal precision of action potential firing in the anterior cingulate cortex (ACC) by using both in vivo and in vitro electrophysiological approaches. We found that peripheral inflammation caused by complete Freund's adjuvant (CFA) increased the standard deviation (SD) of spikes latency (also called jitter) of ∼51% of recorded neurons in the ACC of adult rats in vivo. Similar increases in jitter were found in ACC neurons using in vitro brain slices from adult mice with peripheral inflammation or nerve injury. Bath application of glutamate receptor antagonists CNQX and AP5 abolished the enhancement of jitter induced by CFA injection or nerve injury, suggesting that the increased jitter depends on the glutamatergic synaptic transmission. Activation of adenylyl cyclases (ACs) by bath application of forskolin increased jitter, whereas genetic deletion of AC1 abolished the change of jitter caused by CFA inflammation. Our study provides strong evidence for long-term changes of temporal precision of information coding in cortical neurons after peripheral injuries and explains neuronal mechanism for chronic pain caused cognitive and emotional impairment.

Modulation of olfactory bulb network activity by serotonin: synchronous inhibition of mitral cells mediated by spatially localized GABAergic microcircuits

Although inhibition has often been proposed as a central mechanism for coordinating activity in the olfactory system, relatively little is known about how activation of different inhibitory local circuit pathways can generate coincident inhibition of principal cells. We used serotonin (5-HT) as a pharmacological tool to induce spiking in ensembles of mitral cells (MCs), a primary output neuron in the olfactory bulb, and recorded intracellularly from pairs of MCs to directly assay coincident inhibitory input. We find that 5-HT disynaptically depolarized granule cells (GCs) only slightly but robustly increased the frequency of inhibitory postsynaptic inhibitory currents in MCs. Serotonin also triggered more coincident IPSCs in pairs of nearby MCs than expected by chance, including in MCs with truncated apical dendrites that lack glomerular synapses. That serotonin-triggered coincident inhibition in the absence of elevated GC somatic firing rates suggested that synchronized MC inhibition arose from glutamate receptor-mediated depolarization of GC dendrites or other (non-GC) interneurons outside the glomerular layer. Tetanic stimulation of GCL afferents to GCs triggered robust GC spiking, coincident inhibition in pairs of MCs, and recruited large-amplitude IPSCs in MCs. Enhancing neurotransmission through NMDARs by lowering the external Mg²⁺ concentration also increased inhibitory tone onto MCs but failed to promote synchronized inhibition. These results demonstrate that coincident MC inhibition can occur through multiple circuit pathways and suggests that the functional coordination between different GABAergic synapses in individual GCs can be dynamically regulated.

On how correlations between excitatory and inhibitory synaptic inputs maximize the information rate of neuronal firing

Cortical neurons receive barrages of excitatory and inhibitory inputs which are not independent, as network structure and synaptic kinetics impose statistical correlations. Experiments in vitro and in vivo have demonstrated correlations between inhibitory and excitatory synaptic inputs in which inhibition lags behind excitation in cortical neurons. This delay arises in feed-forward inhibition (FFI) circuits and ensures that coincident excitation and inhibition do not preclude neuronal firing. Conversely, inhibition that is too delayed broadens neuronal integration times, thereby diminishing spike-time precision and increasing the firing frequency. This led us to hypothesize that the correlation between excitatory and inhibitory synaptic inputs modulates the encoding of information of neural spike trains. We tested this hypothesis by investigating the effect of such correlations on the information rate (IR) of spike trains using the Hodgkin-Huxley model in which both synaptic and membrane conductances are stochastic. We investigated two different synaptic input regimes: balanced synaptic conductances and balanced currents. Our results show that correlations arising from the synaptic kinetics, τ, and millisecond lags, δ, of inhibition relative to excitation strongly affect the IR of spike trains. In the regime of balanced synaptic currents, for short time lags (δ ~ 1 ms) there is an optimal τ that maximizes the IR of the postsynaptic spike train. Given the short time scales for monosynaptic inhibitory lags and synaptic decay kinetics reported in cortical neurons under physiological contexts, we propose that FFI in cortical circuits is poised to maximize the rate of information transfer between cortical neurons. Our results also provide a possible explanation for how certain drugs and genetic mutations affecting the synaptic kinetics can deteriorate information processing in the brain.

Reliable neuronal systems: the importance of heterogeneity

For every engineer it goes without saying: in order to build a reliable system we need components that consistently behave precisely as they should. It is also well known that neurons, the building blocks of brains, do not satisfy this constraint. Even neurons of the same type come with huge variances in their properties and these properties also vary over time. Synapses, the connections between neurons, are highly unreliable in forwarding signals. In this paper we argue that both these fact add variance to neuronal processes, and that this variance is not a handicap of neural systems, but that instead predictable and reliable functional behavior of neural systems depends crucially on this variability. In particular, we show that higher variance allows a recurrently connected neural population to react more sensitively to incoming signals, and processes them faster and more energy efficient. This, for example, challenges the general assumption that the intrinsic variability of neurons in the brain is a defect that has to be overcome by synaptic plasticity in the process of learning.

The role of coincidence-detector neurons in the reliability and precision of subthreshold signal detection in noise

Subthreshold signal detection is an important task for animal survival in complex environments, where noise increases both the external signal response and the spontaneous spiking of neurons. The mechanism by which neurons process the coding of signals is not well understood. Here, we propose that coincidence detection, one of the ways to describe the functionality of a single neural cell, can improve the reliability and the precision of signal detection through detection of presynaptic input synchrony. Using a simplified neuronal network model composed of dozens of integrate-and-fire neurons and a single coincidence-detector neuron, we show how the network reads out the subthreshold noisy signals reliably and precisely. We find suitable pairing parameters, the threshold and the detection time window of the coincidence-detector neuron, that optimize the precision and reliability of the neuron. Furthermore, it is observed that the refractory period induces an oscillation in the spontaneous firing, but the neuron can inhibit this activity and improve the reliability and precision further. In the case of intermediate intrinsic states of the input neuron, the network responds to the input more efficiently. These results present the critical link between spiking synchrony and noisy signal transfer, which is utilized in coincidence detection, resulting in enhancement of temporally sensitive coding scheme.

The effect of neural noise on spike time precision in a detailed CA3 neuron model

Experimental and computational studies emphasize the role of the millisecond precision of neuronal spike times as an important coding mechanism for transmitting and representing information in the central nervous system. We investigate the spike time precision of a multicompartmental pyramidal neuron model of the CA3 region of the hippocampus under the influence of various sources of neuronal noise. We describe differences in the contribution to noise originating from voltage-gated ion channels, synaptic vesicle release, and vesicle quantal size. We analyze the effect of interspike intervals and the voltage course preceding the firing of spikes on the spike-timing jitter. The main finding of this study is the ranking of different noise sources according to their contribution to spike time precision. The most influential is synaptic vesicle release noise, causing the spike jitter to vary from 1 ms to 7 ms of a mean value 2.5 ms. Of second importance was the noise incurred by vesicle quantal size variation causing the spike time jitter to vary from 0.03 ms to 0.6 ms. Least influential was the voltage-gated channel noise generating spike jitter from 0.02 ms to 0.15 ms.

Morphological, neurochemical and electrophysiological features of parvalbumin-expressing cells: a likely source of axo-axonic inputs in the mouse spinal dorsal horn

Perception of normal bodily sensations relies on the precise regulation of sensory information entering the dorsal horn of the spinal cord. Inhibitory, axoaxonic, synapses provide a mechanism for this regulation, but the source of these important inhibitory connections remains to be elucidated. This study shows that a subpopulation of spinal interneurons that expresses parvalbumin and have specific morphological, connectivity and functional characteristics are a likely source of the inhibitory inputs that selectivity regulate non-noxious tactile input in the spinal cord. Our findings suggest that a loss of normal function in parvalbumin positive dorsal horn neurons may result in the development of tactile allodynia, where non-painful stimuli gain the capacity to evoke the sensation of pain.

Late postnatal development of intrinsic and synaptic properties promotes fast and precise signaling in the dorsal nucleus of the lateral lemniscus

The dorsal nucleus of the lateral lemniscus (DNLL) is an auditory brain stem structure that generates a long-lasting GABAergic output, which is important for binaural processing. Despite its importance in binaural processing, little is known about the cellular physiology and the synaptic input kinetics of DNLL neurons. To assess the relevant physiological parameters of DNLL neurons, their late postnatal developmental profile was analyzed in acute brain slices of 9- to 26-day-old Mongolian gerbils. The observed developmental changes in passive membrane and action potential (AP) properties all point toward an improvement of fast and precise signal integration in these neurons. Accordingly, synaptic glutamatergic and GABAergic current kinetics accelerate with age. The changes in intrinsic and synaptic properties contribute nearly equally to reduce the latency and jitter in AP generation and thus enhance the temporal precision of DNLL neurons. Furthermore, the size of the synaptic NMDA current is developmentally downregulated. Despite this developmental reduction, DNLL neurons display an NMDA-dependent postsynaptic amplification of AP generation, known to support high firing rates, throughout this developmental period. Taken together, our findings indicate that during late postnatal development DNLL neurons are optimized for high firing rates with high temporal precision.

Visual cortical function in very low birth weight infants without retinal or cerebral pathology

PURPOSE

Preterm infants are at high risk of visual and neural developmental deficits. However, the development of visual cortical function in preterm infants with no retinal or neurologic morbidity has not been well defined. To determine whether premature birth itself alters visual cortical function, swept parameter visual evoked potential (sVEP) responses of healthy preterm infants were compared with those of term infants.

METHODS

Fifty-two term infants and 58 very low birth weight (VLBW) infants without significant retinopathy of prematurity or neurologic morbidities were enrolled. Recruited VLBW infants were between 26 and 33 weeks of gestational age, with birth weights of less than 1500 g. Spatial frequency, contrast, and vernier offset sweep VEP tuning functions were measured at 5 to 7 months' corrected age. Acuity and contrast thresholds were derived by extrapolating the tuning functions to 0 amplitude. These thresholds and suprathreshold response amplitudes were compared between groups.

RESULTS

Preterm infants showed increased thresholds (indicating decreased sensitivity to visual stimuli) and reductions in amplitudes for all three measures. These changes in cortical responsiveness were larger in the <30 weeks ' gestational age subgroup than in the ≥30 weeks' gestational age subgroup.

CONCLUSIONS

Preterm infants with VLBW had measurable and significant changes in cortical responsiveness that were correlated with gestational age. These results suggest that premature birth in the absence of identifiable retinal or neurologic abnormalities has a significant effect on visual cortical sensitivity at 5 to 7 months' of corrected age and that gestational age is an important factor in visual development.

Experimental analysis and computational modeling of interburst intervals in spontaneous activity of cortical neuronal culture

Rhythmic bursting is the most striking behavior of cultured cortical networks and may start in the second week after plating. In this study, we focus on the intervals between spontaneously occurring bursts, and compare experimentally recorded values with model simulations. In the models, we use standard neurons and synapses, with physiologically plausible parameters taken from literature. All networks had a random recurrent architecture with sparsely connected neurons. The number of neurons varied between 500 and 5,000. We find that network models with homogeneous synaptic strengths produce asynchronous spiking or stable regular bursts. The latter, however, are in a range not seen in recordings. By increasing the synaptic strength in a (randomly chosen) subset of neurons, our simulations show interburst intervals (IBIs) that agree better with in vitro experiments. In this regime, called weakly synchronized, the models produce irregular network bursts, which are initiated by neurons with relatively stronger synapses. In some noise-driven networks, a subthreshold, deterministic, input is applied to neurons with strong synapses, to mimic pacemaker network drive. We show that models with such "intrinsically active neurons" (pacemaker-driven models) tend to generate IBIs that are determined by the frequency of the fastest pacemaker and do not resemble experimental data. Alternatively, noise-driven models yield realistic IBIs. Generally, we found that large-scale noise-driven neuronal network models required synaptic strengths with a bimodal distribution to reproduce the experimentally observed IBI range. Our results imply that the results obtained from small network models cannot simply be extrapolated to models of more realistic size. Synaptic strengths in large-scale neuronal network simulations need readjustment to a bimodal distribution, whereas small networks do not require such changes.

Parallel optical control of spatiotemporal neuronal spike activity using high-speed digital light processing

Neurons in the mammalian neocortex receive inputs from and communicate back to thousands of other neurons, creating complex spatiotemporal activity patterns. The experimental investigation of these parallel dynamic interactions has been limited due to the technical challenges of monitoring or manipulating neuronal activity at that level of complexity. Here we describe a new massively parallel photostimulation system that can be used to control action potential firing in in vitro brain slices with high spatial and temporal resolution while performing extracellular or intracellular electrophysiological measurements. The system uses digital light processing technology to generate 2-dimensional (2D) stimulus patterns with >780,000 independently controlled photostimulation sites that operate at high spatial (5.4 μm) and temporal (>13 kHz) resolution. Light is projected through the quartz–glass bottom of the perfusion chamber providing access to a large area (2.76 mm × 2.07 mm) of the slice preparation. This system has the unique capability to induce temporally precise action potential firing in large groups of neurons distributed over a wide area covering several cortical columns. Parallel photostimulation opens up new opportunities for the in vitro experimental investigation of spatiotemporal neuronal interactions at a broad range of anatomical scales.

Inhibitory-excitatory synaptic balance is shifted toward increased excitation in magnocellular neurosecretory cells of heart failure rats

Despite the well-established contribution of neurohumoral activation to morbidity and mortality in heart failure (HF) patients, relatively little is known about the underlying central nervous system mechanisms. In this study, we aimed to determine whether changes in GABAergic inhibitory and glutamatergic excitatory synaptic function contribute to altered hypothalamic magnocellular neurosecretory cell (MNC) activity in HF rats. Patch-clamp recordings were obtained from MNCs in brain slices from sham and HF rats. Glutamate excitatory (EPSCs) and GABAergic inhibitory postsynaptic currents (IPSCs) were simultaneously recorded, and changes in their strengths, as well as their interactions, were evaluated. We found a diminished GABAergic synaptic strength in MNCs of HF rats, reflected as faster decaying IPSCs and diminished mean IPSC charge transfer. Opposite changes were observed in glutamate EPSC synaptic strength, resulting in a shift in the GABA-glutamate balance toward a relatively stronger glutamate influence in HF rats. The prolongation of glutamate EPSCs during HF was mediated, at least in part, by an enhanced contribution of AMPA receptor desensitization to the EPSC decay time course. EPSC prolongation, and consequently increased unitary strength, resulted in a stronger AMPA receptor-mediated excitatory drive to firing discharge in MNCs of HF rats. Blockade of GABA(A) synaptic activity diminished the EPSC waveform variability observed among events in sham rats, an effect that was blunted in HF rats. Together, our results suggest that opposing changes in postsynaptic properties of GABAergic and glutamatergic synaptic function contribute to enhanced magnocellular neurosecretory activity in HF rats.

Factors controlling the input-output relationship of spherical bushy cells in the gerbil cochlear nucleus

Despite the presence of large endbulb inputs, the spherical bushy cells (SBCs) of the rostral anteroventral cochlear nucleus do not function as simple auditory relays. We used the good signal-to-noise ratio of juxtacellular recordings to dissect the intrinsic and network mechanisms controlling the input-output relationship of SBCs in anesthetized gerbils. The SBCs generally operated close to action potential (AP) threshold and showed no evidence for synaptic depression, suggesting that the endbulbs of Held have low release probability in vivo. Analysis of the complex waveforms suggested that in the absence of auditory stimulation, postsynaptic spike depression and stochastic fluctuations in EPSP size were the main factors determining jitter and reliability of the endbulb synapse. During auditory stimulation, progressively larger EPSPs were needed to trigger APs at increasing sound intensities. Simulations suggested hyperpolarizing inhibition could explain the observed decrease in EPSP efficacy. Synaptic inhibition showed a delayed onset and generally had a higher threshold than excitatory inputs, but otherwise inhibition and excitation showed mostly overlapping frequency-response areas. The recruitment of synaptic inhibition caused postsynaptic spikes to be preferentially triggered by well-timed, large EPSPs, resulting in improved phase locking despite more variable EPSP-AP latencies. Our results suggest that the lack of synaptic depression, caused by low release probability, and the apparent absence of sound-evoked synaptic inhibition at low sound intensity maximize sensitivity of SBCs. At higher sound intensities, the recruitment of synaptic inhibition constrains their firing rate and optimizes their temporal precision.

Difference in response reliability predicted by spectrotemporal tuning in the cochlear nuclei of barn owls

The brainstem auditory pathway is obligatory for all aural information. Brainstem auditory neurons must encode the level and timing of sounds, as well as their time-dependent spectral properties, the fine structure, and envelope, which are essential for sound discrimination. This study focused on envelope coding in the two cochlear nuclei of the barn owl, nucleus angularis (NA) and nucleus magnocellularis (NM). NA and NM receive input from bifurcating auditory nerve fibers and initiate processing pathways specialized in encoding interaural time (ITD) and level (ILD) differences, respectively. We found that NA neurons, although unable to accurately encode stimulus phase, lock more strongly to the stimulus envelope than NM units. The spectrotemporal receptive fields (STRFs) of NA neurons exhibit a pre-excitatory suppressive field. Using multilinear regression analysis and computational modeling, we show that this feature of STRFs can account for enhanced across-trial response reliability, by locking spikes to the stimulus envelope. Our findings indicate a dichotomy in envelope coding between the time and intensity processing pathways as early as at the level of the cochlear nuclei. This allows the ILD processing pathway to encode envelope information with greater fidelity than the ITD processing pathway. Furthermore, we demonstrate that the properties of the STRFs of the neurons can be quantitatively related to spike timing reliability.

Synaptic and network mechanisms of sparse and reliable visual cortical activity during nonclassical receptive field stimulation

During natural vision, the entire visual field is stimulated by images rich in spatiotemporal structure. Although many visual system studies restrict stimuli to the classical receptive field (CRF), it is known that costimulation of the CRF and the surrounding nonclassical receptive field (nCRF) increases neuronal response sparseness. The cellular and network mechanisms underlying increased response sparseness remain largely unexplored. Here we show that combined CRF + nCRF stimulation increases the sparseness, reliability, and precision of spiking and membrane potential responses in classical regular spiking (RS(C)) pyramidal neurons of cat primary visual cortex. Conversely, fast-spiking interneurons exhibit increased activity and decreased selectivity during CRF + nCRF stimulation. The increased sparseness and reliability of RS(C) neuron spiking is associated with increased inhibitory barrages and narrower visually evoked synaptic potentials. Our experimental observations were replicated with a simple computational model, suggesting that network interactions among neuronal subtypes ultimately sharpen recurrent excitation, producing specific and reliable visual responses.

A selective interplay between aberrant EPSPKA and INaP reduces spike timing precision in dentate granule cells of epileptic rats

Spike timing precision is a fundamental aspect of neuronal information processing in the brain. Here we examined the temporal precision of input–output operation of dentate granule cells (DGCs) in an animal model of temporal lobe epilepsy (TLE). In TLE, mossy fibers sprout and establish recurrent synapses on DGCs that generate aberrant slow kainate receptor–mediated excitatory postsynaptic potentials (EPSP_KA) not observed in controls. We report that, in contrast to time-locked spikes generated by EPSP_AMPA in control DGCs, aberrant EPSP_KA are associated with long-lasting plateaus and jittered spikes during single-spike mode firing. This is mediated by a selective voltage-dependent amplification of EPSP_KA through persistent sodium current (I_NaP) activation. In control DGCs, a current injection of a waveform mimicking the slow shape of EPSP_KA activates I_NaP and generates jittered spikes. Conversely in epileptic rats, blockade of EPSP_KA or I_NaP restores the temporal precision of EPSP–spike coupling. Importantly, EPSP_KA not only decrease spike timing precision at recurrent mossy fiber synapses but also at perforant path synapses during synaptic integration through I_NaP activation. We conclude that a selective interplay between aberrant EPSP_KA and I_NaP severely alters the temporal precision of EPSP–spike coupling in DGCs of chronic epileptic rats.

Interacting stochastic oscillators

Stochastic coherence (SC) and self-induced stochastic resonance (SISR) are two distinct mechanisms of noise-induced coherent motion. For interacting SC and SISR oscillators, we find that whether or not phase synchronization is achieved depends sensitively on the coupling strength and noise intensities. Specifically, in the case of weak coupling, individual oscillators are insensitive to each other, whereas in the case of strong coupling, one fixed oscillator with optimal coherence can be entrained to the other, adjustable oscillator (i.e., its noise intensity is tunable), achieving phase-locking synchronization, as long as the tunable noise intensity is not beyond a threshold; such synchronization is lost otherwise. For an array lattice of SISR oscillators, except for coupling-enhanced coherence similar to that found in the case of coupled SC oscillators, there is an optimal network topology degree (i.e., number of coupled nodes), such that coherence and synchronization are optimally achieved, implying that the system-size resonance found in an ensemble of noise-driven bistable systems can occur in coupled SISR oscillators.

Optimal time scale for spike-time reliability: theory, simulations, and experiments

Use of spike timing to encode information requires that neurons respond with high temporal precision and with high reliability. Fast fluctuating stimuli are known to result in highly reproducible spike times across trials, whereas constant stimuli result in variable spike times. Here, we first studied mathematically how spike-time reliability depends on the rapidness of aperiodic stimuli. Then, we tested our theoretical predictions in computer simulations of neuron models (Hodgkin-Huxley and modified quadratic integrate-and-fire), as well as in patch-clamp experiments with real neurons (mitral cells in the olfactory bulb and pyramidal cells in the neocortex). As predicted by our theory, we found that for firing frequencies in the beta/gamma range, spike-time reliability is maximal when the time scale of the input fluctuations (autocorrelation time) is in the range of a few milliseconds (2-5 ms), coinciding with the time scale of fast synapses, and decreases substantially for faster and slower inputs. Finally, we comment how these findings relate to mechanisms causing neuronal synchronization.