Burst firing in sensory systems

Network motifs in cellular neurophysiology

Concepts from network science and graph theory, including the framework of network motifs, have been frequently applied in studying neuronal networks and other biological complex systems. Network-based approaches can also be used to study the functions of individual neurons, where cellular elements such as ion channels and membrane voltage are conceptualized as nodes within a network, and their interactions are denoted by edges. Network motifs in this context provide functional building blocks that help to illuminate the principles of cellular neurophysiology. In this review we build a case that network motifs operating within neurons provide tools for defining the functional architecture of single-neuron physiology and neuronal adaptations. We highlight the presence of such computational motifs in the cellular mechanisms underlying action potential generation, neuronal oscillations, dendritic integration, and neuronal plasticity. Future work applying the network motifs perspective may help to decipher the functional complexities of neurons and their adaptation during health and disease.

Dorsal root ganglion: a key to understanding the therapeutic effects of the erector spinae plane (ESP) and other intertransverse process blocks?

Since its description in 2016, the erector spinae plane block (ESPB) has become a widely employed regional anesthetic technique and kindled interest in a range of related techniques, collectively termed intertransverse process blocks. There has been ongoing controversy over mechanism of action of the ESPB, mainly due to incongruities between results of cutaneous sensory testing, clinical efficacy studies, and investigations into the neural structures that are reached by injected local anesthetic (LA). This paper reviews the spread of LA to the paravertebral and epidural space and the cutaneous anesthesia in ESPB, with specific emphasis on the dorsal root ganglion (DRG). We hypothesize that the DRG, due to its unique and complex microarchitecture, represents a key therapeutic target for modulation of nociceptive signaling in regional anesthesia. This paper discusses how the anatomical and physiological characteristics of the DRG may be one of the factors underpinning the clinical analgesia observed in ESPB and other intertransverse process blocks.

Individualized temporal patterns dominate cortical upstate and sleep depth in driving human sleep spindle timing

Sleep spindles are critical for memory consolidation and strongly linked to neurological disease and aging. Despite their significance, the relative influences of factors like sleep depth, cortical up/down states, and spindle temporal patterns on individual spindle production remain poorly understood. Moreover, spindle temporal patterns are typically ignored in favor of an average spindle rate. Here, we analyze spindle dynamics in 1008 participants from the Multi-Ethnic Study of Atherosclerosis using a point process framework. Results reveal fingerprint-like temporal patterns, characterized by a refractory period followed by a period of increased spindle activity, which are highly individualized yet consistent night-to-night. We observe increased timing variability with age and distinct gender/age differences. Strikingly, and in contrast to the prevailing notion, individualized spindle patterns are the dominant determinant of spindle timing, accounting for over 70% of the statistical deviance explained by all of the factors we assessed, surpassing the contribution of slow oscillation (SO) phase (~14%) and sleep depth (~16%). Furthermore, we show spindle/SO coupling dynamics with sleep depth are preserved across age, with a global negative shift towards the SO rising slope. These findings offer novel mechanistic insights into spindle dynamics with direct experimental implications and applications to individualized electroencephalography biomarker identification.

Neonatal di-(2-ethylhexyl)phthalate exposure induces permanent alterations in secretory CRH neuron characteristics in the hypothalamus paraventricular region of adult male rats

Corticotrophin-releasing hormone (CRH) neurons in the hypothalamic paraventricular nucleus (PVN) play a critical role in the modulation of the hypothalamic-pituitary-adrenal (HPA) axis. Early-life exposure to di-(2-ethylhexyl) phthalate (DEHP) has been associated with an increased risk of developing psychiatric disorders in adulthood. The present work was designed to explore the impact of neonatal exposure to DEHP on adult PVN CRH neuronal activity. DEHP or vehicle was given to male rat pups from PND16 to PND22. Then, anxiety-like behaviors, serum corticosterone and testosterone, immunohistochemistry, western blotting, fluorescence in situ hybridization and acute ex vivo slice electrophysiological recordings were used to evaluate the influence of DEHP on adult PVN secretory CRH neurons. Neonatal DEHP-exposed rats exhibited enhanced anxiety-like behaviors in adults, with an increase in CORT. Secretory CRH neurons showed higher spontaneous firing activity but could be inhibited by GABAAR blockers. CRH neurons displayed fewer firing spikes, prolonged first-spike latency, depolarizing shifts in GABA reversal potential and strengthened GABAergic inputs, as indicated by increases in the frequency and amplitude of sIPSCs. Enhancement of GABAergic transmission was accompanied by upregulated expression of GAD67 and downregulated expression of GABABR1, KCC2 and GAT1. These findings suggest that neonatal exposure to DEHP permanently altered the characteristics of secretory CRH neurons in the PVN, which may contribute to the development of psychiatric disorders later in life.

Holistic bursting cells store long-term memory in auditory cortex

The sensory neocortex has been suggested to be a substrate for long-term memory storage, yet which exact single cells could be specific candidates underlying such long-term memory storage remained neither known nor visible for over a century. Here, using a combination of day-by-day two-photon Ca2+ imaging and targeted single-cell loose-patch recording in an auditory associative learning paradigm with composite sounds in male mice, we reveal sparsely distributed neurons in layer 2/3 of auditory cortex emerged step-wise from quiescence into bursting mode, which then invariably expressed holistic information of the learned composite sounds, referred to as holistic bursting (HB) cells. Notably, it was not shuffled populations but the same sparse HB cells that embodied the behavioral relevance of the learned composite sounds, pinpointing HB cells as physiologically-defined single-cell candidates of an engram underlying long-term memory storage in auditory cortex.

Silences, spikes and bursts: Three-part knot of the neural code

When a neuron breaks silence, it can emit action potentials in a number of patterns. Some responses are so sudden and intense that electrophysiologists felt the need to single them out, labelling action potentials emitted at a particularly high frequency with a metonym - bursts. Is there more to bursts than a figure of speech? After all, sudden bouts of high-frequency firing are expected to occur whenever inputs surge. The burst coding hypothesis advances that the neural code has three syllables: silences, spikes and bursts. We review evidence supporting this ternary code in terms of devoted mechanisms for burst generation, synaptic transmission and synaptic plasticity. We also review the learning and attention theories for which such a triad is beneficial.

Self-Organization of Nonlinearly Coupled Neural Fluctuations Into Synergistic Population Codes

Neural activity in the brain exhibits correlated fluctuations that may strongly influence the properties of neural population coding. However, how such correlated neural fluctuations may arise from the intrinsic neural circuit dynamics and subsequently affect the computational properties of neural population activity remains poorly understood. The main difficulty lies in resolving the nonlinear coupling between correlated fluctuations with the overall dynamics of the system. In this study, we investigate the emergence of synergistic neural population codes from the intrinsic dynamics of correlated neural fluctuations in a neural circuit model capturing realistic nonlinear noise coupling of spiking neurons. We show that a rich repertoire of spatial correlation patterns naturally emerges in a bump attractor network and further reveals the dynamical regime under which the interplay between differential and noise correlations leads to synergistic codes. Moreover, we find that negative correlations may induce stable bound states between two bumps, a phenomenon previously unobserved in firing rate models. These noise-induced effects of bump attractors lead to a number of computational advantages including enhanced working memory capacity and efficient spatiotemporal multiplexing and can account for a range of cognitive and behavioral phenomena related to working memory. This study offers a dynamical approach to investigating realistic correlated neural fluctuations and insights to their roles in cortical computations.

PPy/SWCNTs-Modified Microelectrode Array for Learning and Memory Model Construction through Electrical Stimulation and Detection of In Vitro Hippocampal Neuronal Network

The learning and memory functions of the brain remain unclear, which are in urgent need for the detection of both a single cell signal with high spatiotemporal resolution and network activities with high throughput. Here, an in vitro microelectrode array (MEA) was fabricated and further modified with polypyrrole/carboxylated single-walled carbon nanotubes (PPy/SWCNTs) nanocomposites as the interface between biological and electronic systems. The deposition of the nanocomposites significantly improved the performance of microelectrodes including low impedance (60.3 ± 28.8 k Ω), small phase delay (-32.8 ± 4.4°), and good biocompatibility. Then the modified MEA was used to apply learning training and test on hippocampal neuronal network cultured for 21 days through electrical stimulation, and multichannel electrophysiological signals were recorded simultaneously. During the process of learning training, the stimulus/response ratio of the hippocampal learning population gradually increased and the response time gradually decreased. After training, the mean spikes in burst, number of bursts, and mean burst duration increased by 53%, 191%, and 52%, respectively, and the correlation of neurons in the network was significantly enhanced from 0.45 ± 0.002 to 0.78 ± 0.002. In addition, the neuronal network basically retained these characteristics for at least 5 h. These results indicated that we have successfully constructed a learning and memory model of hippocampal neurons on the in vitro MEA, contributing to understanding learning and memory based on synaptic plasticity. The proposed PPy/SWCNTs-modified in vitro MEA will provide a promising platform for the exploration of learning and memory mechanism and their applications in vitro.

Differential Effects of Clozapine and Haloperidol on the 40 Hz Auditory Steady State Response-mediated Phase Resetting in the Prefrontal Cortex of the Female Sprague Dawley Rat

BACKGROUND

Neural synchrony at gamma frequency (~40 Hz) is important for information processing and is disrupted in schizophrenia. From a drug development perspective, molecules that can improve local gamma synchrony are promising candidates for therapeutic development.

HYPOTHESIS

Given their differentiated clinical profile, clozapine, and haloperidol may have distinct effects on local gamma synchrony engendered by 40 Hz click trains, the so-called auditory steady-state response (ASSR).

STUDY DESIGN

Clozapine and haloperidol at doses known to mimic clinically relevant D2 receptor occupancy were evaluated using the ASSR in separate cohorts of female SD rats.

RESULTS

Clozapine (2.5-10 mg/kg, sc) robustly increased intertrial phase coherence (ITC), across all doses. Evoked response increased but less consistently. Background gamma activity, unrelated to the stimulus, showed a reduction at all doses. Closer scrutiny of the data indicated that clozapine accelerated gamma phase resetting. Thus, clozapine augmented auditory information processing in the gamma frequency range by reducing the background gamma, accelerating the gamma phase resetting and improving phase precision and signal power. Modest improvements in ITC were seen with Haloperidol (0.08 and 0.24 mg/kg, sc) without accelerating phase resetting. Evoked power was unaffected while background gamma was reduced at high doses only, which also caused catalepsy.

CONCLUSIONS

Using click-train evoked gamma synchrony as an index of local neural network function, we provide a plausible neurophysiological basis for the superior and differentiated profile of clozapine. These observations may provide a neurophysiological template for identifying new drug candidates with a therapeutic potential for treatment-resistant schizophrenia.

Information Encoding in Bursting Spiking Neural Network Modulated by Astrocytes

We investigated a mathematical model composed of a spiking neural network (SNN) interacting with astrocytes. We analysed how information content in the form of two-dimensional images can be represented by an SNN in the form of a spatiotemporal spiking pattern. The SNN includes excitatory and inhibitory neurons in some proportion, sustaining the excitation-inhibition balance of autonomous firing. The astrocytes accompanying each excitatory synapse provide a slow modulation of synaptic transmission strength. An information image was uploaded to the network in the form of excitatory stimulation pulses distributed in time reproducing the shape of the image. We found that astrocytic modulation prevented stimulation-induced SNN hyperexcitation and non-periodic bursting activity. Such homeostatic astrocytic regulation of neuronal activity makes it possible to restore the image supplied during stimulation and lost in the raster diagram of neuronal activity due to non-periodic neuronal firing. At a biological point, our model shows that astrocytes can act as an additional adaptive mechanism for regulating neural activity, which is crucial for sensory cortical representations.

Sparse spike trains and the limitation of rate codes underlying rapid behaviours

Animals live in dynamic worlds where they use sensorimotor circuits to rapidly process information and drive behaviours. For example, dragonflies are aerial predators that react to movements of prey within tens of milliseconds. These pursuits are likely controlled by identified neurons in the dragonfly, which have well-characterized physiological responses to moving targets. Predominantly, neural activity in these circuits is interpreted in context of a rate code, where information is conveyed by changes in the number of spikes over a time period. However, such a description of neuronal activity is difficult to achieve in real-world, real-time scenarios. Here, we contrast a neuroscientists' post-hoc view of spiking activity with the information available to the animal in real-time. We describe how performance of a rate code is readily overestimated and outline a rate code's significant limitations in driving rapid behaviours.

Calbindin-Expressing CA1 Pyramidal Neurons Encode Spatial Information More Efficiently

Hippocampal pyramidal neurons (PNs) are traditionally conceptualized as homogeneous population. For the past few years, cumulating evidence has revealed the structural and functional heterogeneity of hippocampal pyramidal neurons. But the in vivo neuronal firing pattern of molecularly identified pyramidal neuron subclasses is still absent. In this study, we investigated the firing patterns of hippocampal PNs based on different expression profile of Calbindin (CB) during a spatial shuttle task in free moving male mice. We found that CB+ place cells can represent spatial information more efficiently than CB- place cells, albeit lower firing rates during running epochs. Furthermore, a subset of CB+ PNs shifted their theta firing phase during rapid-eye movement (REM) sleep states compared with running states. Although CB- PNs are more actively engaged in ripple oscillations, CB+ PNs showed stronger ripple modulation during slow-wave sleep (SWS). Our results pointed out the heterogeneity in neuronal representation between hippocampal CB+ and CB- PNs. Particularly, CB+ PNs encode spatial information more efficiently, which might be contributed by stronger afferents from the lateral entorhinal cortex to CB+ PNs.

Dynamical properties of neuromorphic Josephson junctions

Neuromorphic computing exploits the dynamical analogy between many physical systems and neuron biophysics. Superconductor systems, in particular, are excellent candidates for neuromorphic devices due to their capacity to operate at great speeds and with low energy dissipation compared to their silicon counterparts. In this paper, we revisit a prior work on Josephson Junction-based neurons to identify the exact dynamical mechanisms underlying the system's neuronlike properties and reveal complex behaviors which are relevant for neurocomputation and the design of superconducting neuromorphic devices. Our paper lies at the intersection of superconducting physics and theoretical neuroscience, both viewed under a common framework-that of nonlinear dynamics theory.

Psilocybin reduces low frequency oscillatory power and neuronal phase-locking in the anterior cingulate cortex of awake rodents

Psilocybin is a hallucinogenic compound that is showing promise in the ability to treat neurological conditions such as depression and post-traumatic stress disorder. There have been several investigations into the neural correlates of psilocybin administration using non-invasive methods, however, there has yet to be an invasive study of the mechanism of action in awake rodents. Using multi-unit extracellular recordings, we recorded local field potential and spiking activity from populations of neurons in the anterior cingulate cortex of awake mice during the administration of psilocybin (2 mg/kg). The power of low frequency bands in the local field potential was found to significantly decrease in response to psilocybin administration, whilst gamma band activity trended towards an increase. The population firing rate was found to increase overall, with just under half of individual neurons showing a significant increase. Psilocybin significantly decreased the level of phase modulation of cells with each neural frequency band except high-gamma oscillations, consistent with a desynchronization of cortical populations. Furthermore, bursting behavior was altered in a subset of cells, with both positive and negative changes in the rate of bursting. Neurons that increased their burst firing following psilocybin administration were highly likely to transition from a phase-modulated to a phase unmodulated state. Taken together, psilocybin reduces low frequency oscillatory power, increases overall firing rates and desynchronizes local neural activity. These findings are consistent with dissolution of the default mode network under psilocybin, and may be indicative of disruption of top-down processing in the acute psychedelic state.

The burst gap is a peripheral temporal code for pitch perception that is shared across audition and touch

When tactile afferents were manipulated to fire in periodic bursts of spikes, we discovered that the perceived pitch corresponded to the inter-burst interval (burst gap) in a spike train, rather than the spike rate or burst periodicity as previously thought. Given that tactile frequency mechanisms have many analogies to audition, and indications that temporal frequency channels are linked across the two modalities, we investigated whether there is burst gap temporal encoding in the auditory system. To link this putative neural code to perception, human subjects (n = 13, 6 females) assessed pitch elicited by trains of temporally-structured acoustic pulses in psychophysical experiments. Each pulse was designed to excite a fixed population of cochlear neurons, precluding place of excitation cues, and to elicit desired temporal spike trains in activated afferents. We tested periodicities up to 150 Hz using a variety of burst patterns and found striking deviations from periodicity-predicted pitch. Like the tactile system, the duration of the silent gap between successive bursts of neural activity best predicted perceived pitch, emphasising the role of peripheral temporal coding in shaping pitch. This suggests that temporal patterning of stimulus pulses in cochlear implant users might improve pitch perception.

State-dependent activity dynamics of hypothalamic stress effector neurons

The stress response necessitates an immediate boost in vital physiological functions from their homeostatic operation to an elevated emergency response. However, the neural mechanisms underlying this state-dependent change remain largely unknown. Using a combination of in vivo and ex vivo electrophysiology with computational modeling, we report that corticotropin releasing hormone (CRH) neurons in the paraventricular nucleus of the hypothalamus (PVN), the effector neurons of hormonal stress response, rapidly transition between distinct activity states through recurrent inhibition. Specifically, in vivo optrode recording shows that under non-stress conditions, CRH_PVN neurons often fire with rhythmic brief bursts (RB), which, somewhat counterintuitively, constrains firing rate due to long (~2 s) interburst intervals. Stressful stimuli rapidly switch RB to continuous single spiking (SS), permitting a large increase in firing rate. A spiking network model shows that recurrent inhibition can control this activity-state switch, and more broadly the gain of spiking responses to excitatory inputs. In biological CRH_PVN neurons ex vivo, the injection of whole-cell currents derived from our computational model recreates the in vivo-like switch between RB and SS, providing direct evidence that physiologically relevant network inputs enable state-dependent computation in single neurons. Together, we present a novel mechanism for state-dependent activity dynamics in CRH_PVN neurons.

Early lock-in of structured and specialised information flows during neural development

The brains of many organisms are capable of complicated distributed computation underpinned by a highly advanced information processing capacity. Although substantial progress has been made towards characterising the information flow component of this capacity in mature brains, there is a distinct lack of work characterising its emergence during neural development. This lack of progress has been largely driven by the lack of effective estimators of information processing operations for spiking data. Here, we leverage recent advances in this estimation task in order to quantify the changes in transfer entropy during development. We do so by studying the changes in the intrinsic dynamics of the spontaneous activity of developing dissociated neural cell cultures. We find that the quantity of information flowing across these networks undergoes a dramatic increase across development. Moreover, the spatial structure of these flows exhibits a tendency to lock-in at the point when they arise. We also characterise the flow of information during the crucial periods of population bursts. We find that, during these bursts, nodes tend to undertake specialised computational roles as either transmitters, mediators, or receivers of information, with these roles tending to align with their average spike ordering. Further, we find that these roles are regularly locked-in when the information flows are established. Finally, we compare these results to information flows in a model network developing according to a spike-timing-dependent plasticity learning rule. Similar temporal patterns in the development of information flows were observed in these networks, hinting at the broader generality of these phenomena.

The neural hierarchy of consciousness

The chief undertaking in the studies of consciousness is that of unravelling "the minimal set of neural processes that are together sufficient for the conscious experience of a particular content - the neural correlates of consciousness". To this day, this crusade remains at an impasse, with a clash of two main theories: consciousness may arise either in a graded and cortically-localised fashion, or in an all-or-none and widespread one. In spite of the long-lasting theoretical debates, neurophysiological theories of consciousness have been mostly dissociated from them. Herein, a theoretical review will be put forth with the aim to change that. In its first half, we will cover the hard available evidence on the neurophysiology of consciousness, whereas in its second half we will weave a series of considerations on both theories and substantiate a novel take on conscious awareness: the levels of processing approach, partitioning the conscious architecture into lower- and higher-order, graded and nonlinear.

An electrophysiological perspective on Parkinson's disease: symptomatic pathogenesis and therapeutic approaches

Parkinson's disease (PD), or paralysis agitans, is a common neurodegenerative disease characterized by dopaminergic deprivation in the basal ganglia because of neuronal loss in the substantia nigra pars compacta. Clinically, PD apparently involves both hypokinetic (e.g. akinetic rigidity) and hyperkinetic (e.g. tremor/propulsion) symptoms. The symptomatic pathogenesis, however, has remained elusive. The recent success of deep brain stimulation (DBS) therapy applied to the subthalamic nucleus (STN) or the globus pallidus pars internus indicates that there are essential electrophysiological abnormalities in PD. Consistently, dopamine-deprived STN shows excessive burst discharges. This proves to be a central pathophysiological element causally linked to the locomotor deficits in PD, as maneuvers (such as DBS of different polarities) decreasing and increasing STN burst discharges would decrease and increase the locomotor deficits, respectively. STN bursts are not so autonomous but show a "relay" feature, requiring glutamatergic synaptic inputs from the motor cortex (MC) to develop. In PD, there is an increase in overall MC activities and the corticosubthalamic input is enhanced and contributory to excessive burst discharges in STN. The increase in MC activities may be relevant to the enhanced beta power in local field potentials (LFP) as well as the deranged motor programming at the cortical level in PD. Moreover, MC could not only drive erroneous STN bursts, but also be driven by STN discharges at specific LFP frequencies (~ 4 to 6 Hz) to produce coherent tremulous muscle contractions. In essence, PD may be viewed as a disorder with deranged rhythms in the cortico-subcortical re-entrant loops, manifestly including STN, the major component of the oscillating core, and MC, the origin of the final common descending motor pathways. The configurations of the deranged rhythms may play a determinant role in the symptomatic pathogenesis of PD, and provide insight into the mechanism underlying normal motor control. Therapeutic brain stimulation for PD and relevant disorders should be adaptively exercised with in-depth pathophysiological considerations for each individual patient, and aim at a final normalization of cortical discharge patterns for the best ameliorating effect on the locomotor and even non-motor symptoms.

Burst control: Synaptic conditions for burst generation in cortical layer 5 pyramidal neurons

The output of neocortical layer 5 pyramidal cells (L5PCs) is expressed by a train of single spikes with intermittent bursts of multiple spikes at high frequencies. The bursts are the result of nonlinear dendritic properties, including Na+, Ca2+, and NMDA spikes, that interact with the ~10,000 synapses impinging on the neuron's dendrites. Output spike bursts are thought to implement key dendritic computations, such as coincidence detection of bottom-up inputs (arriving mostly at the basal tree) and top-down inputs (arriving mostly at the apical tree). In this study we used a detailed nonlinear model of L5PC receiving excitatory and inhibitory synaptic inputs to explore the conditions for generating bursts and for modulating their properties. We established the excitatory input conditions on the basal versus the apical tree that favor burst and show that there are two distinct types of bursts. Bursts consisting of 3 or more spikes firing at < 200 Hz, which are generated by stronger excitatory input to the basal versus the apical tree, and bursts of ~2-spikes at ~250 Hz, generated by prominent apical tuft excitation. Localized and well-timed dendritic inhibition on the apical tree differentially modulates Na+, Ca2+, and NMDA spikes and, consequently, finely controls the burst output. Finally, we explored the implications of different burst classes and respective dendritic inhibition for regulating synaptic plasticity.

A synaptic learning rule for exploiting nonlinear dendritic computation

Information processing in the brain depends on the integration of synaptic input distributed throughout neuronal dendrites. Dendritic integration is a hierarchical process, proposed to be equivalent to integration by a multilayer network, potentially endowing single neurons with substantial computational power. However, whether neurons can learn to harness dendritic properties to realize this potential is unknown. Here, we develop a learning rule from dendritic cable theory and use it to investigate the processing capacity of a detailed pyramidal neuron model. We show that computations using spatial or temporal features of synaptic input patterns can be learned, and even synergistically combined, to solve a canonical nonlinear feature-binding problem. The voltage dependence of the learning rule drives coactive synapses to engage dendritic nonlinearities, whereas spike-timing dependence shapes the time course of subthreshold potentials. Dendritic input-output relationships can therefore be flexibly tuned through synaptic plasticity, allowing optimal implementation of nonlinear functions by single neurons.

Neural burst codes disguised as rate codes

The burst coding hypothesis posits that the occurrence of sudden high-frequency patterns of action potentials constitutes a salient syllable of the neural code. Many neurons, however, do not produce clearly demarcated bursts, an observation invoked to rule out the pervasiveness of this coding scheme across brain areas and cell types. Here we ask how detrimental ambiguous spike patterns, those that are neither clearly bursts nor isolated spikes, are for neuronal information transfer. We addressed this question using information theory and computational simulations. By quantifying how information transmission depends on firing statistics, we found that the information transmitted is not strongly influenced by the presence of clearly demarcated modes in the interspike interval distribution, a feature often used to identify the presence of burst coding. Instead, we found that neurons having unimodal interval distributions were still able to ascribe different meanings to bursts and isolated spikes. In this regime, information transmission depends on dynamical properties of the synapses as well as the length and relative frequency of bursts. Furthermore, we found that common metrics used to quantify burstiness were unable to predict the degree with which bursts could be used to carry information. Our results provide guiding principles for the implementation of coding strategies based on spike-timing patterns, and show that even unimodal firing statistics can be consistent with a bivariate neural code.

Burst activity plays no role in the field-to-field variability and rate remapping of grid cells

Grid cells in rodent medial entorhinal cortex are thought to play a key role for spatial navigation. When the animal is freely moving in an open arena the firing fields of each grid cell tend to form a highly regular, hexagonal lattice spanning the environment. However, firing rates vary from field to field and change under contextual modifications, whereas the field locations shift at most by a small amount under such "rate remapping." The observed differences in firing rate could reflect overall activity changes or changes in the detailed spike-train statistics. As these two alternatives imply distinct neural coding schemes, we investigated whether temporal firing patterns vary from field to field and whether they change under rate remapping. Focusing on short time scales, we found that the proportion of bursts compared to all discharge events is similar in all firing fields of a given grid cell and does not change under rate remapping. For each cell, mean firing rates with bursts are proportional to mean firing rates without bursts. However, this ratio varies across cells. Additionally, we looked at how rate remapping relates to entorhinal theta-frequency oscillations. Theta-phase coding was preserved despite firing-rate changes from rate remapping but we did not observe differences between the first and second half of the theta cycle, as had been reported for CA1. Our results indicate that both, the heterogeneity between firing fields and rate remapping, are not due to altered firing patterns on short time scales but reflect location-specific changes at the firing-rate level.

Neurophysiological basis of the N400 deflection, from Mismatch Negativity to Semantic Prediction Potentials and late positive components

The first theoretical model on the neurophysiological basis of the N400: the deflection reflects layer I dendritic plateaus on a preparatory state of synaptic integration that precedes layer V somatic burst firing for conscious identification of the higher-order features of the stimulus (a late positive shift). Plateaus ensue from apical disinhibition by vasoactive intestinal polypeptide-positive interneurons (VIPs) through suppression of Martinotti cells, opening the gates for glutamatergic feedback to trigger dendritic regenerative potentials. Cholinergic transients contribute to these dynamics directly, holding a central role in the N400 deflection. The stereotypical timing of the (frontal) glutamatergic feedback and the accompanying cholinergic transients account for the enigmatic "invariability" of the peak latency in the face of a gamut of different stimuli and paradigms. The theoretical postulations presented here may bring about unprecedented level of detail for the N400 deflection to be used in the study of schizophrenia, Alzheimer's disease and other higher-order pathologies. The substrates of a late positive component, the Mismatch Negativity and the Semantic Prediction Potentials are also surveyed.

Attention reduces the burstiness of V1 neurons involved in attended target enhancement

Attention-dependent reduction in the tendency for neurons to fire bursts (burstiness) is widely observed in the visual cortex. However, the underlying mechanism and the functional role of this phenomenon remain unclear. We recorded well-isolated single-unit activities in primary visual cortex (V1) from two primates (Macaca mulatta) while they performed a detection task engaging spatial attention with two levels of difficulty (hard/easy). We found that attention modulated burstiness of V1 neurons in a cell-type specific manner. For neurons whose net response enhanced with the increase of task difficulty (difficulty-enhanced neuron), representing their involvement in boosting the signal of the attended stimulus, attention led to a reduction in burstiness during hard task but not during easy task. In contrast, regardless of the level of task difficulty, attention-dependent reduction in burstiness was not observed in neurons that showed a net suppression in firing rate with the increase of task difficulty (difficulty-suppressed neuron), indicating their commitment in filtering out the interference of distractor. This differentiation in the effects of attentional modulation on burstiness among the cells with distinct functional roles in attention suggests that the reduction in burstiness by attention is linked to target enhancement and is not associated with distractor suppression.

Involvement of the thalamic reticular nucleus in prepulse inhibition of acoustic startle

Thalamic reticular nucleus (TRN) is a group of inhibitory neurons surrounding the thalamus. Due to its important role in sensory information processing, TRN is considered as the target nucleus for the pathophysiological investigation of schizophrenia and autism spectrum disorder (ASD). Prepulse inhibition (PPI) of acoustic startle response, a phenomenon that strong stimulus-induced startle reflex is reduced by a weaker prestimulus, is always found impaired in schizophrenia and ASD. But the role of TRN in PPI modulation remains unknown. Here, we report that parvalbumin-expressing (PV+) neurons in TRN are activated by sound stimulation of PPI paradigm. Chemogenetic inhibition of PV+ neurons in TRN impairs PPI performance. Further investigations on the mechanism suggest a model of burst-rebound burst firing in TRN-auditory thalamus (medial geniculate nucleus, MG) circuitry. The burst firing is mediated by T-type calcium channel in TRN, and rebound burst firing needs the participation of GABAB receptor in MG. Overall, these findings support the involvement of TRN in PPI modulation.

Involvement of NMDA and GABA(A) receptors in modulation of spontaneous activity in hippocampal culture: Interrelations between burst firing and intracellular calcium signal

Spontaneous burst firing is a hallmark attributed to the neuronal network activity. It is known to be accompanied by intracellular calcium [Са²⁺]_i oscillations within the bursting neurons. Studying mechanisms underlying regulation of burst firing is highly relevant, since impairment in neuronal bursting accompanies different neurological disorders. In the present study, the contribution of NMDA and GABA(A) receptors to the shape formation of spontaneous burst -was studied in cultured hippocampal neurons. A combination of inhibitory analysis with simultaneous registration of neuronal bursting by whole-cell patch clamp and calcium imaging was used to assess spontaneous burst firing and [Са²⁺]_i level. Using bicuculline and D-AP5 we showed that GABA(A) and NMDA receptors effectively modulate burst plateau phase and [Са²⁺]_i transient spike which can further affect action potential (AP) amplitudes and firing frequency within a burst. Bicuculline significantly elevated the amplitude and reduced the duration of both burst plateau phase and [Са²⁺]_i spike resulting in an increase of AP firing frequency and shortening of AP amplitudes within a burst. D-AP5 significantly decreases the amplitude of both plateau phase and [Са²⁺]_i spike along with a burst duration that correlated with an increase in AP amplitudes and reduced firing frequency within a burst. The effect of bicuculline was occluded by co-addition of D-AP5 revealing modulatory role of GABA(A) receptors to the NMDA receptor-mediated formation of the burst. Our results provide new evidence on importance of NMDA and GABA(A) receptors in shaping burst firing and Ca²⁺transient spikes in cultured hippocampal neurons.

Distinct burst properties contribute to the functional diversity of thalamic nuclei

Thalamic neurons fire spikes in two modes, burst and tonic. The function of burst firing is unclear, but the evidence suggests that bursts are more effective at activating cortical cells, and that postinhibition rebound bursting contributes to thalamocortical oscillations during sleep. Bursts are considered stereotyped signals; however, there is limited evidence regarding how burst properties compare across thalamic nuclei of different functional or anatomical organization. Here, we used whole-cell patch clamp recordings and compartmental modeling to investigate the properties of bursts in six sensory thalamic nuclei, to study the mechanisms that can lead to different burst properties, and to assess the implications of different burst properties for thalamocortical transmission and oscillatory functions. We found that bursts in higher-order cells on average had higher number of spikes and longer latency to the first spike. Additionally, burst features in first-order neurons were determined by sensory modality. Shifting the voltage-dependence and density of the T-channel conductance in a compartmental model replicates the burst properties from the intracellular recordings, pointing to molecular mechanisms that can generate burst diversity. Furthermore, the model predicts that bursts with higher number of spikes will drastically reduce the effectiveness of thalamocortical transmission. In addition, the latency to burst limited the rebound oscillatory frequency in modeled cells. These results demonstrate that burst properties vary according to the thalamocortical hierarchy and with sensory modality. The findings imply that, while in burst mode, thalamocortical transmission and firing frequency will be determined by the number of spikes and latency to burst.

The unknown but knowable relationship between Presaccadic Accumulation of activity and Saccade initiation

The goal of this short review is to call attention to a yawning gap of knowledge that separates two processes essential for saccade production. On the one hand, knowledge about the saccade generation circuitry within the brainstem is detailed and precise - push-pull interactions between gaze-shifting and gaze-holding processes control the time of saccade initiation, which begins when omnipause neurons are inhibited and brainstem burst neurons are excited. On the other hand, knowledge about the cortical and subcortical premotor circuitry accomplishing saccade initiation has crystalized around the concept of stochastic accumulation - the accumulating activity of saccade neurons reaching a fixed value triggers a saccade. Here is the gap: we do not know how the reaching of a threshold by premotor neurons causes the critical pause and burst of brainstem neurons that initiates saccades. Why this problem matters and how it can be addressed will be discussed. Closing the gap would unify two rich but curiously disconnected empirical and theoretical domains.

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.

3D high-density microelectrode array with optical stimulation and drug delivery for investigating neural circuit dynamics

Investigation of neural circuit dynamics is crucial for deciphering the functional connections among regions of the brain and understanding the mechanism of brain dysfunction. Despite the advancements of neural circuit models in vitro, technologies for both precisely monitoring and modulating neural activities within three-dimensional (3D) neural circuit models have yet to be developed. Specifically, no existing 3D microelectrode arrays (MEAs) have integrated capabilities to stimulate surrounding neurons and to monitor the temporal evolution of the formation of a neural network in real time. Herein, we present a 3D high-density multifunctional MEA with optical stimulation and drug delivery for investigating neural circuit dynamics within engineered 3D neural tissues. We demonstrate precise measurements of synaptic latencies in 3D neural networks. We expect our 3D multifunctional MEA to open up opportunities for studies of neural circuits through precise, in vitro investigations of neural circuit dynamics with 3D brain models.

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.

Engrams of Fast Learning

Fast learning designates the behavioral and neuronal mechanisms underlying the acquisition of a long-term memory trace after a unique and brief experience. As such it is opposed to incremental, slower reinforcement or procedural learning requiring repetitive training. This learning process, found in most animal species, exists in a large spectrum of natural behaviors, such as one-shot associative, spatial, or perceptual learning, and is a core principle of human episodic memory. We review here the neuronal and synaptic long-term changes associated with fast learning in mammals and discuss some hypotheses related to their underlying mechanisms. We first describe the variety of behavioral paradigms used to test fast learning memories: those preferentially involve a single and brief (from few hundred milliseconds to few minutes) exposures to salient stimuli, sufficient to trigger a long-lasting memory trace and new adaptive responses. We then focus on neuronal activity patterns observed during fast learning and the emergence of long-term selective responses, before documenting the physiological correlates of fast learning. In the search for the engrams of fast learning, a growing body of evidence highlights long-term changes in gene expression, structural, intrinsic, and synaptic plasticities. Finally, we discuss the potential role of the sparse and bursting nature of neuronal activity observed during the fast learning, especially in the induction plasticity mechanisms leading to the rapid establishment of long-term synaptic modifications. We conclude with more theoretical perspectives on network dynamics that could enable fast learning, with an overview of some theoretical approaches in cognitive neuroscience and artificial intelligence.

Glutamate transmission rather than cellular pacemaking propels excitatory-inhibitory resonance for ictogenesis in amygdala

Epileptic seizures are automatic, excessive, and synchronized neuronal activities originating from many brain regions especially the amygdala, the allocortices and neocortices. This may reflect a shared principle for network organization and signaling in these telencephalic structures. In theory, the automaticity of epileptic discharges may stem from spontaneously active "oscillator" neurons equipped with intrinsic pacemaking conductances, or from a group of synaptically-connected collaborating "resonator" neurons. In the basolateral amygdalar (BLA) network of pyramidal-inhibitory (PN-IN) neuronal resonators, we demonstrated that rhythmogenic currents are provided by glutamatergic rather than the classic intrinsic or cellular pacemaking conductances (namely the h currents). The excitatory output of glutamatergic neurons such as PNs presumably propels a novel network-based "relay burst mode" of discharges especially in INs, which precondition PNs into a state prone to burst discharges and thus further glutamate release. Also, selective activation of unilateral PNs, but never INs, readily drives bilateral BLA networks into reverberating discharges which are fully synchronized with the behavioral manifestations of seizures (e.g. muscle contractions). Seizures originating in BLA and/or the other structures with similar PN-IN networks thus could be viewed as glutamate-triggered erroneous network oscillations that are normally responsible for information relay.

Delta-Frequency Augmentation and Synchronization in Seizure Discharges and Telencephalic Transmission

Epileptic seizures constitute a common neurological disease primarily diagnosed by characteristic rhythms or waves in the local field potentials (LFPs) of cerebral cortices or electroencephalograms. With a basolateral amygdala (BLA) kindling model, we found that the dominant frequency of BLA oscillations is in the delta range (1-5 Hz) in both normal and seizure conditions. Multi-unit discharges are increased with higher seizure staging but remain phase-locked to the delta waves in LFPs. Also, the change in synchrony precedes and outlasts the changes in discharging units as well as behavioral seizures. One short train of stimuli readily drives the pyramidal-inhibitory neuronal networks in BLA slices into prolonged reverberating activities, where the burst and interburst intervals may concurrently set a "natural wavelength" for delta frequencies. Seizures thus could be viewed as erroneous temporospatial continuums to normal oscillations in a system with a built-in synchronizing and resonating nature for information relay.

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.

Neurons in various regions of the brain generate spike bursts. Bursts are typically composed of a few spikes generated within dozens of milliseconds, and individual bursts are separated by much longer periods of silence (~hundreds of milliseconds). Recent evidence indicates that the number of spikes in a burst, the interspike intervals (ISIs), and the overall duration of a burst, as well as the timing of burst onset, encode information. However, it remains unknown whether multiple ISIs within a single burst encode multiple input features. Here we demonstrate that such combinatorial ISI coding occurs for spike bursts in the retina. We recorded ganglion cell spikes from isolated salamander retinae stimulated with computer-generated movies. Visual response analyses indicated that multiple ISIs within a single burst combinatorially encode the phase and amplitude of oscillatory light sequences, which are different from the stimulus feature encoded by the spike number. The result demonstrates that 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. Because synaptic transmission in the visual system is highly sensitive to ISIs, the combinatorial ISI coding must have a major impact on visual information processing.

Single-neuron representation of learned complex sounds in the auditory cortex

The sensory responses of cortical neuronal populations following training have been extensively studied. However, the spike firing properties of individual cortical neurons following training remain unknown. Here, we have combined two-photon Ca²⁺ imaging and single-cell electrophysiology in awake behaving mice following auditory associative training. We find a sparse set (~5%) of layer 2/3 neurons in the primary auditory cortex, each of which reliably exhibits high-rate prolonged burst firing responses to the trained sound. Such bursts are largely absent in the auditory cortex of untrained mice. Strikingly, in mice trained with different multitone chords, we discover distinct subsets of neurons that exhibit bursting responses specifically to a chord but neither to any constituent tone nor to the other chord. Thus, our results demonstrate an integrated representation of learned complex sounds in a small subset of cortical neurons.

Using a combination of two-photon imaging and single-cell electrophysiology, the authors discover that associative learning induces the emergence of a unique subset of neurons in the auditory cortex, exhibiting high-rate bursting responses to the learned complex sounds but not to any of the constituents.

Deuterated Glutamate-Mediated Neuronal Activity on Micro-Electrode Arrays

The excitatory synaptic transmission is mediated by glutamate in neuronal networks of the mammalian brain. In addition to the synaptic glutamate, extra-synaptic glutamate is known to modulate the neuronal activity. In neuronal networks, glutamate uptake is an important role of neurons and glial cells for lowering the concentration of extracellular glutamate and to avoid the excitotoxicity by glutamate. Monitoring the spatial distribution of intracellular glutamate is important to study the uptake of glutamate, but the approach has been hampered by the absence of appropriate glutamate analogs that report the localization of glutamate. Deuterium-labeled glutamate (GLU-D) is a promising tracer for monitoring the intracellular concentration of glutamate, but physiological properties of GLU-D have not been studied. Here we study the effects of extracellular GLU-D for the neuronal activity by using primary cultured rat hippocampal neurons that form neuronal networks on microelectrodes array. The frequency of firing in the spontaneous activity of neurons increased with the increasing concentration of extracellular GLU-D. The frequency of synchronized burst activity in neurons increased similarly as we observed in the spontaneous activity. These changes of the neuronal activity with extracellular GLU-D were suppressed by antagonists of glutamate receptors. These results suggest that GLU-D can be used as an analog of glutamate with equivalent effects for facilitating the neuronal activity. We anticipate GLU-D developing as a promising analog of glutamate for studying the dynamics of glutamate during neuronal activity.

Synchrony of Spontaneous Burst Firing between Retinal Ganglion Cells Across Species

Neurons communicate with other neurons in response to environmental changes. Their goal is to transmit information to their targets reliably. A burst, which consists of multiple spikes within a short time interval, plays an essential role in enhancing the reliability of information transmission through synapses. In the visual system, retinal ganglion cells (RGCs), the output neurons of the retina, show bursting activity and transmit retinal information to the lateral geniculate neuron of the thalamus. In this study, to extend our interest to the population level, the burstings of multiple RGCs were simultaneously recorded using a multi-channel recording system. As the first step in network analysis, we focused on investigating the pairwise burst correlation between two RGCs. Furthermore, to assess if the population bursting is preserved across species, we compared the synchronized bursting of RGCs between marmoset monkey (callithrix jacchus), one species of the new world monkeys and mouse (C57BL/6J strain). First, monkey RGCs showed a larger number of spikes within a burst, while the inter-spike interval, burst duration, and inter-burst interval were smaller compared with mouse RGCs. Monkey RGCs showed a strong burst synchronization between RGCs, whereas mouse RGCs showed no correlated burst firing. Monkey RGC pairs showed significantly higher burst synchrony and mutual information than mouse RGC pairs did. Comprehensively, through this study, we emphasize that two species have a different bursting activity of RGCs and different burst synchronization suggesting two species have distinctive retinal processing.

Temporal patterns in electrical nerve stimulation: Burst gap code shapes tactile frequency perception

We have previously described a novel temporal encoding mechanism in the somatosensory system, where mechanical pulses grouped into periodic bursts create a perceived tactile frequency based on the duration of the silent gap between bursts, rather than the mean rate or the periodicity. This coding strategy may offer new opportunities for transmitting information to the brain using various sensory neural prostheses and haptic interfaces. However, it was not known whether the same coding mechanisms apply when using electrical stimulation, which recruits a different spectrum of afferents. Here, we demonstrate that the predictions of the burst gap coding model for frequency perception apply to burst stimuli delivered with electrical pulses, re-emphasising the importance of the temporal structure of spike patterns in neural processing and perception of tactile stimuli. Reciprocally, the electrical stimulation data confirm that the results observed with mechanical stimulation do indeed depend on neural processing mechanisms in the central nervous system, and are not due to skin mechanical factors and resulting patterns of afferent activation.

Structural Correlates of CA2 and CA3 Pyramidal Cell Activity in Freely-Moving Mice

Plasticity within hippocampal circuits is essential for memory functions. The hippocampal CA2/CA3 region is thought to be able to rapidly store incoming information by plastic modifications of synaptic weights within its recurrent network. High-frequency spike-bursts are believed to be essential for this process, by serving as triggers for synaptic plasticity. Given the diversity of CA2/CA3 pyramidal neurons, it is currently unknown whether and how burst activity, assessed in vivo during natural behavior, relates to principal cell heterogeneity. To explore this issue, we juxtacellularly recorded the activity of single CA2/CA3 neurons from freely-moving male mice, exploring a familiar environment. In line with previous work, we found that spatial and temporal activity patterns of pyramidal neurons correlated with their topographical position. Morphometric analysis revealed that neurons with a higher proportion of distal dendritic length displayed a higher tendency to fire spike-bursts. We propose that the dendritic architecture of pyramidal neurons might determine burst-firing by setting the relative amount of distal excitatory inputs from the entorhinal cortex.SIGNIFICANCE STATEMENT High-frequency spike-bursts are thought to serve fundamental computational roles within neural circuits. Within hippocampal circuits, spike-bursts are believed to serve as potent instructive signals, which increase the efficiency of information transfer and induce rapid modifications of synaptic efficacies. In the present study, by juxtacellularly recording and labeling single CA2/CA3 neurons in freely-moving mice, we explored whether and how burst propensity relates to pyramidal cell heterogeneity. We provide evidence that, within the CA2/CA3 region, neurons with higher proportion of distal dendritic length display a higher tendency to fire spike-bursts. Thus, the relative amount of entorhinal inputs, arriving onto the distal dendrites, might determine the burst propensity of individual CA2/CA3 neurons in vivo during natural behavior.

Examination and characterisation of burst spinal cord stimulation on cerebrospinal fluid cellular and protein constituents in patient responders with chronic neuropathic pain - A Pilot Study

INTRODUCTION

Patients with neuropathic pain have altered proteomic and neuropeptide constituents in cerebrospinal fluid (CSF) compared to controls. Tonic spinal cord stimulation (SCS) has demonstrated differential expression of neuropeptides in CSF before and after treatment suggesting potential mechanisms of action. Burst-SCS is an evidence-based paraesthesia free waveform utilised for neuropathic pain with a potentially different mechanistic action to tonic SCS. This study examines the dynamic biological changes of CSF at a cellular and proteome level after Burst-SCS.

METHODS

Patients with neuropathic pain selected for SCS had CSF sampled prior to implant of SCS and following 8 weeks of continuous Burst-SCS. Baseline and 8-week pain scores with demographics were recorded. T cell frequencies were analysed by flow cytometry, proteome analysis was performed using mass spectrometry and secreted cytokines, chemokines and neurotrophins were measured by enzyme-linked immunosorbent assay (ELISA).

RESULTS

4 patients (2 females, 2 males) with a mean age of 51 years (+/-SEM 2.74, SD 5.48) achieved a reduction in pain of >50% following 8 weeks of Burst-SCS. Analysis of the CSF proteome indicated a significant alteration in protein expression most related to synapse assembly and immune regulators. There was significantly lower expression of the proteins: growth hormone A1 (PRL), somatostatin (SST), nucleobindin-2 (NUCB2), Calbindin (CALB1), acyl-CoA binding protein (DBI), proSAAS (PCSK1N), endothelin-3 (END3) and cholecystokinin (CCK) after Burst-SCS. The concentrations of secreted chemokines and cytokines and the frequencies of T cells were not significantly changed following Burst-SCS.

CONCLUSION

This study characterised the alteration in the CSF proteome in response to burst SCS in vivo. Functional analysis indicated that the alterations in the CSF proteome is predominately linked to synapse assembly and immune effectors. Individual protein analysis also suggests potential supraspinal mechanisms.

Neural Code for Ambient Heat Detection in Elaterid Beetles

Environmental thermal conditions play a major role at all levels of biological organization; however, there is little information on noxious high temperature sensation crucial in behavioral thermoregulation and survival of small ectothermic animals such as insects. So far, a capability to unambiguously encode heat has been demonstrated only for the sensory triad of the spike bursting thermo- and two bimodal hygro-thermoreceptor neurons located in the antennal dome-shaped sensilla (DSS) in a carabid beetle. We used extracellular single sensillum recording in the range of 20-45°C to demonstrate that a similar sensory triad in the elaterid Agriotes obscurus also produces high temperature-induced bursty spike trains. Several parameters of the bursts are temperature dependent, allowing the neurons in a certain order to encode different, but partly overlapping ranges of heat up to lethal levels in a graded manner. ISI in a burst is the most useful parameter out of six. Our findings consider spike bursting as a general, fundamental quality of the classical sensory triad of antennal thermo- and hygro-thermoreceptor neurons widespread in many insect groups, being a flexible and reliable mode of coding unfavorably high temperatures. The possible involvement of spike bursting in behavioral thermoregulation of the beetles is discussed. By contrast, the mean firing rate of the neurons in regular and bursty spike trains combined does not carry useful thermal information at the high end of noxious heat.

Signal Propagation via Open-Loop Intrathalamic Architectures: A Computational Model

Propagation of signals across the cerebral cortex is a core component of many cognitive processes and is generally thought to be mediated by direct intracortical connectivity. The thalamus, by contrast, is considered to be devoid of internal connections and organized as a collection of parallel inputs to the cortex. Here, we provide evidence that "open-loop" intrathalamic pathways involving the thalamic reticular nucleus (TRN) can support propagation of oscillatory activity across the cortex. Recent studies support the existence of open-loop thalamo-reticulo-thalamic (TC-TRN-TC) synaptic motifs in addition to traditional closed-loop architectures. We hypothesized that open-loop structural modules, when connected in series, might underlie thalamic and, therefore cortical, signal propagation. Using a supercomputing platform to simulate thousands of permutations of a thalamocortical network based on physiological data collected in mice, rats, ferrets, and cats and in which select synapses were allowed to vary both by class and individually, we evaluated the relative capacities of closed-loop and open-loop TC-TRN-TC synaptic configurations to support both propagation and oscillation. We observed that (1) signal propagation was best supported in networks possessing strong open-loop TC-TRN-TC connectivity; (2) intrareticular synapses were neither primary substrates of propagation nor oscillation; and (3) heterogeneous synaptic networks supported more robust propagation of oscillation than their homogeneous counterparts. These findings suggest that open-loop, heterogeneous intrathalamic architectures might complement direct intracortical connectivity to facilitate cortical signal propagation.

Differential Roles of Hypothalamic AVPV and Arcuate Kisspeptin Neurons in Estradiol Feedback Regulation of Female Reproduction

Mammalian reproductive function includes puberty onset and completion, reproductive cyclicity, steroidogenesis, gametogenesis, fertilization, pregnancy, and lactation; all are indispensable to perpetuate species. Reproductive cycles are critical for providing the hormonal milieu needed for follicular development and maturation of eggs, but cycles, in and of themselves, do not guarantee ovulation will occur. Here, we review the roles in female reproductive neuroendocrine function of two hypothalamic populations that produce the neuropeptide kisspeptin, demonstrating distinct roles in maintaining cycles and ovulation.

Cell-Type Specific Burst Firing Interacts with Theta and Beta Activity in Prefrontal Cortex During Attention States

Population-level theta and beta band activity in anterior cingulate and prefrontal cortices (ACC/PFC) are prominent signatures of self-controlled, adaptive behaviors. But how these rhythmic activities are linked to cell-type specific activity has remained unclear. Here, we suggest such a cell-to-systems level linkage. We found that the rate of burst spiking events is enhanced particularly during attention states and that attention-specific burst spikes have a unique temporal relationship to local theta and beta band population-level activities. For the 5-10 Hz theta frequency range, bursts coincided with transient increases of local theta power relative to nonbursts, particularly for bursts of putative interneurons. For the 16-30 Hz beta frequency, bursts of putative interneurons phase synchronized stronger than nonbursts, and were associated with larger beta power modulation. In contrast, burst of putative pyramidal cells showed similar beta power modulation as nonbursts, but were accompanied by stronger beta power only when they occurred early in the beta cycle. These findings suggest that in the ACC/PFC during attention states, mechanisms underlying burst firing are intimately linked to narrow band population-level activities, providing a cell-type specific window into rhythmic inhibitory gating and the emergence of rhythmically coherent network states during goal directed behavior.

A Computational Modeling Reveals That Strength of Inhibitory Input, E/I Balance, and Distance of Excitatory Input Modulate Thalamocortical Bursting Properties

The thalamus is a brain structure known to modulate sensory information before relaying to the cortex. The unique ability of a thalamocortical (TC) neuron to switch between the high frequency burst firing and single spike tonic firing has been implicated to have a key role in sensory modulation including pain. Of the two firing modes, burst firing, especially maintaining certain burst firing properties, was suggested to be critical in controlling nociceptive behaviors. Therefore, understanding the factors that influence burst firing properties would offer important insight into understanding sensory modulation. Using computational modeling, we investigated how the balance of excitatory and inhibitory inputs into a TC neuron influence TC bursting properties. We found that intensity of inhibitory inputs and the timing of excitatory input delivery control the dynamics of bursting properties. Then, to reflect a more realistic model, excitatory inputs delivered at different dendritic locations—proximal, intermediate, or distal—of a TC neuron were also investigated. Interestingly, excitatory input delivered into a distal dendrite, despite the furthest distance, had the strongest influence in shaping burst firing properties, suggesting that not all inputs equally contribute to modulating TC bursting properties. Overall, the results provide computational insights in understanding the detailed mechanism of the factors influencing temporal pattern of thalamic bursts.

Novel Functions of Feedback in Electrosensory Processing

Environmental signals act as input and are processed across successive stages in the brain to generate a meaningful behavioral output. However, a ubiquitous observation is that descending feedback projections from more central to more peripheral brain areas vastly outnumber ascending feedforward projections. Such projections generally act to modify how sensory neurons respond to afferent signals. Recent studies in the electrosensory system of weakly electric fish have revealed novel functions for feedback pathways in that their transformation of the afferent input generates neural firing rate responses to sensory signals mediating perception and behavior. In this review, we focus on summarizing these novel and recently uncovered functions and put them into context by describing the more "classical" functions of feedback in the electrosensory system. We further highlight the parallels between the electrosensory system and other systems as well as outline interesting future directions.

Cluster burst synchronization in a scale-free network of inhibitory bursting neurons

We consider a scale-free network of inhibitory Hindmarsh-Rose (HR) bursting neurons, and make a computational study on coupling-induced cluster burst synchronization by varying the average coupling strength J 0 . For sufficiently small J 0 , non-cluster desynchronized states exist. However, when passing a critical point J c ∗ ( ≃ 0.16 ) , the whole population is segregated into 3 clusters via a constructive role of synaptic inhibition to stimulate dynamical clustering between individual burstings, and thus 3-cluster desynchronized states appear. As J 0 is further increased and passes a lower threshold J l ∗ ( ≃ 0.78 ) , a transition to 3-cluster burst synchronization occurs due to another constructive role of synaptic inhibition to favor population synchronization. In this case, HR neurons in each cluster make burstings every 3rd cycle of the instantaneous burst rate R w ( t ) of the whole population, and exhibit burst synchronization. However, as J 0 passes an intermediate threshold J m ∗ ( ≃ 5.2 ) , HR neurons fire burstings intermittently at a 4th cycle of R w ( t ) via burst skipping rather than at its 3rd cycle, and hence they begin to make intermittent hoppings between the 3 clusters. Due to such intermittent intercluster hoppings via burst skippings, the 3 clusters become broken up (i.e., the 3 clusters are integrated into a single one). However, in spite of such break-up (i.e., disappearance) of the 3-cluster states, (non-cluster) burst synchronization persists in the whole population, which is well visualized in the raster plot of burst onset times where bursting stripes (composed of burst onset times and indicating burst synchronization) appear successively. With further increase in J 0 , intercluster hoppings are intensified, and bursting stripes also become dispersed more and more due to a destructive role of synaptic inhibition to spoil the burst synchronization. Eventually, when passing a higher threshold J h ∗ ( ≃ 17.8 ) a transition to desynchronization occurs via complete overlap between the bursting stripes. Finally, we also investigate the effects of stochastic noise on both 3-cluster burst synchronization and intercluster hoppings.