Complex Spike Research Articles

Cholinergic regulation of dendritic Ca2+ spikes controls firing mode of hippocampal CA3 pyramidal neurons

Active dendritic integrative mechanisms such as regenerative dendritic spikes enrich the information processing abilities of neurons and fundamentally contribute to behaviorally relevant computations. Dendritic Ca2+ spikes are generally thought to produce plateau-like dendritic depolarization and somatic complex spike burst (CSB) firing, which can initiate rapid changes in spatial coding properties of hippocampal pyramidal cells (PCs). However, here we reveal that a morpho-topographically distinguishable subpopulation of rat and mouse hippocampal CA3PCs exhibits compound apical dendritic Ca2+ spikes with unusually short duration that do not support the firing of sustained CSBs. These Ca2+ spikes are mediated by L-type Ca2+ channels and their time course is restricted by A- and M-type K+ channels. Cholinergic activation powerfully converts short Ca2+ spikes to long-duration forms, and facilitates and prolongs CSB firing. We propose that cholinergic neuromodulation controls the ability of a CA3PC subtype to generate sustained plateau potentials, providing a state-dependent dendritic mechanism for memory encoding and retrieval.

Pathogenesis, Replication, Advance Genetic Variants and Major Organ Effects of COVID-19 Infection. A Literature Review

The COVID-19 (corona virus disease-19) infection has been spread in whole and become a global threat effecting every nation throughout the world. The COVID-19 virus has a complex spike like structure and also exhibits a complex replication process. It can effect different organs of body such as brain, kidneys, lungs, eyes and also induce psychological effects in patients which may lead to serious complications even death. With the passage of time it's genetic makeup is also changing and the new COVID-19 strains are more resistant because of unique flexibility in it’s genetic makeup. A number of genetic variants have been identified by researchers to date but no specific treatment has been available against any variant. The aim of our study is to explore the pathogenicity, replication process, major organ effects and different genetic strains of COVID-19 virus that has been identified by researchers currently.

Multi-compartmental diversification of neutralizing antibody lineages dissected in SARS-CoV-2 spike-immunized macaques

The continued evolution of SARS-CoV-2 underscores the need to understand qualitative aspects of the humoral immune response elicited by spike immunization. Here, we combine monoclonal antibody (mAb) isolation with deep B cell receptor (BCR) repertoire sequencing of rhesus macaques immunized with prefusion-stabilized spike glycoprotein. Longitudinal tracing of spike-sorted B cell lineages in multiple immune compartments demonstrates increasing somatic hypermutation and broad dissemination of vaccine-elicited B cells in draining and non-draining lymphoid compartments, including the bone marrow, spleen and, most notably, periaortic lymph nodes. Phylogenetic analysis of spike-specific monoclonal antibody lineages identified through deep repertoire sequencing delineates extensive intra-clonal diversification that shaped neutralizing activity. Structural analysis of the spike in complex with a broadly neutralizing mAb provides a molecular basis for the observed differences in neutralization breadth between clonally related antibodies. Our findings highlight that immunization leads to extensive intra-clonal B cell evolution where members of the same lineage can both retain the original epitope specificity and evolve to recognize additional spike variants not previously encountered.

Decoding state-dependent cortical-cerebellar cellular functional connectivity in the mouse brain

The cortex and cerebellum form multi-synaptic reciprocal connections. We investigate the functional connectivity between single spiking cerebellar neurons and the population activity of the mouse dorsal cortex using mesoscale imaging. Cortical representations of individual cerebellar neurons vary significantly across different brain states but are drawn from a common set of cortical networks. These cortical-cerebellar connectivity features are observed in mossy fibers and Purkinje cells as well as neurons in different cerebellar lobules, albeit with variations across cell types and regions. Complex spikes of Purkinje cells preferably associate with the sensorimotor cortex, whereas simple spikes display more diverse cortical connectivity patterns. The spontaneous functional connectivity patterns align with cerebellar neurons' functional responses to external stimuli in a modality-specific manner. The tuning properties of subsets of cerebellar neurons differ between anesthesia and awake states, mirrored by state-dependent changes in their long-range functional connectivity patterns with mesoscale cortical activity.

The olivary input to the cerebellum dissociates sensory events from movement plans

Neurons in the inferior olive are thought to anatomically organize the Purkinje cells (P-cells) of the cerebellum into computational modules, but what is computed by each module? Here, we designed a saccade task in marmosets that dissociated sensory events from motor events and then recorded the complex and simple spikes of hundreds of P-cells. We found that when a visual target was presented at a random location, the olive reported the direction of that sensory event to one group of P-cells, but not to a second group. However, just before movement onset, it reported the direction of the planned movement to both groups, even if that movement was not toward the target. At the end of the movement if the subject experienced an error but chose to withhold the corrective movement, only the first group received information about the sensory prediction error. We organized the P-cells based on the information content of their olivary input and found that in the group that received sensory information, the simple spikes were suppressed during fixation, then produced a burst before saccade onset in a direction consistent with assisting the movement. In the second group, the simple spikes were not suppressed during fixation but burst near saccade deceleration in a direction consistent with stopping the movement. Thus, the olive differentiated the P-cells based on whether they would receive sensory or motor information, and this defined their contributions to control of movements as well as holding still.

Climbing fibers provide essential instructive signals for associative learning

Supervised learning depends on instructive signals that shape the output of neural circuits to support learned changes in behavior. Climbing fiber (CF) inputs to the cerebellar cortex represent one of the strongest candidates in the vertebrate brain for conveying neural instructive signals. However, recent studies have shown that Purkinje cell stimulation can also drive cerebellar learning and the relative importance of these two neuron types in providing instructive signals for cerebellum-dependent behaviors remains unresolved. In the present study we used cell-type-specific perturbations of various cerebellar circuit elements to systematically evaluate their contributions to delay eyeblink conditioning in mice. Our findings reveal that, although optogenetic stimulation of either CFs or Purkinje cells can drive learning under some conditions, even subtle reductions in CF signaling completely block learning to natural stimuli. We conclude that CFs and corresponding Purkinje cell complex spike events provide essential instructive signals for associative cerebellar learning.

On interaction of proteinoids with simulated neural networks

Proteinoid-neuron networks combine biological neurons with spiking proteinoid microspheres, which are generated by thermal condensation of amino acids. Complex and dynamic spiking patterns in response to varied stimuli make these networks suitable for unconventional computing. This research examines the interaction of proteinoid-neuron networks with function-generator-artificial neural networks (ANN) that may create distinct electrical waveforms. Function-generator- artificial neural network (ANN) stimulates and modulates proteinoid-neuron network spiking activity and synchronisation to encode and decode information. We employ function-generator-ANN to study proteinoid-neuron network nonlinear dynamics and chaos and optimise their performance and energy efficiency. Function-generator-ANN improves proteinoid-neuron networks’ computational capacities and robustness and creates unique hybrid systems with electrical devices. We address the benefits as well as the drawbacks of employing proteinoid-neuron networks for unconventional computing with function-generator-ANN.

Efficient Estimation of Directed Connectivity in Nonlinear and Nonstationary Spiking Neuron Networks.

Studying directed connectivity within spiking neuron networks can help understand neural mechanisms. Existing methods assume linear time-invariant neural dynamics with a fixed time lag in information transmission, while spiking networks usually involve complex dynamics that are nonlinear and nonstationary, and have varying time lags. We develop a Gated Recurrent Unit (GRU)-Point Process (PP) method to estimate directed connectivity within spiking networks. We use a GRU to describe the dependency of the target neuron's current firing rate on the source neurons' past spiking events and a PP to relate the target neuron's firing rate to its current 0-1 spiking event. The GRU model uses recurrent states and gate/activation functions to deal with varying time lags, nonlinearity, and nonstationarity in a parameter-efficient manner. We estimate the model using maximum likelihood and compute directed information as our measure of directed connectivity. We conduct simulations using artificial spiking networks and a biophysical model of Parkinson's disease to show that GRU-PP systematically addresses varying time lags, nonlinearity, and nonstationarity, and estimates directed connectivity with high accuracy and data efficiency. We also use a non-human-primate dataset to show that GRU-PP correctly identifies the biophysically-plausible stronger PMd-to-M1 connectivity than M1-to-PMd connectivity during reaching. In all experiments, the GRU-PP consistently outperforms state-of-the-art methods. The GRU-PP method efficiently estimates directed connectivity in varying time lag, nonlinear, and nonstationary spiking neuron networks. The proposed method can serve as a directed connectivity analysis tool for investigating complex spiking neuron network dynamics.

Sleep disrupts complex spiking dynamics in the neocortex and hippocampus

Sleep disrupts complex spiking dynamics in the neocortex and hippocampus

Spatio-temporal study of single and multi-wavelength quasi-continuous-wave generation regimes in an all-normal dispersion ring cavity

In this paper, we report a comprehensive experimental study of quasi-continuous-wave operation in an all-normal-dispersion ring cavity laser with nonlinear polarization rotation based saturable absorber action. Using the temporal mapping technique, we analyze in real time spiking dynamics, characterized by the existence of ephemeral spikes that continually emerge and decay amidst the background radiation. In particular, the effects of the pumping level and its direction of variation on the laser emission dynamics were analyzed. The overall behavior, in particular the well-defined pattern of spike evolution between their emergence until their vanishing, is found to be qualitatively invariant over a broad range of pump power, from 70 mW to 550 mW, albeit the values of spiking parameters vary widely over this range. The spiking phenomenon appears from low pumping powers, just above the laser threshold. A phenomenon of hysteresis was also discovered, as some emission parameters, in particular the optical spectrum, depend on whether pump power is being raised or decreased. 2D autocorrelation analysis also proved insightful, showing that each spike appears at random, having no connection with other spikes. Finally, high pump power settings and birefringence adjustments enabled the discovery of more complex spiking dynamics where emission at various wavelengths occur, some of the lines presenting additional slow dynamics at the millisecond scale. These results indicate that deterministic complexity is, together with stochasticity, an essential ingredient to take into account for a better understanding of the operational modes in fiber lasers far from the pulsed regime.

Rescue of sharp wave-ripples and prevention of network hyperexcitability in the ventral but not the dorsal hippocampus of a rat model of fragile X syndrome.

Fragile X syndrome (FXS) is a genetic neurodevelopmental disorder characterized by intellectual disability and is related to autism. FXS is caused by mutations of the fragile X messenger ribonucleoprotein 1 gene (Fmr1) and is associated with alterations in neuronal network excitability in several brain areas including hippocampus. The loss of fragile X protein affects brain oscillations, however, the effects of FXS on hippocampal sharp wave-ripples (SWRs), an endogenous hippocampal pattern contributing to memory consolidation have not been sufficiently clarified. In addition, it is still not known whether dorsal and ventral hippocampus are similarly affected by FXS. We used a Fmr1 knock-out (KO) rat model of FXS and electrophysiological recordings from the CA1 area of adult rat hippocampal slices to assess spontaneous and evoked neural activity. We find that SWRs and associated multiunit activity are affected in the dorsal but not the ventral KO hippocampus, while complex spike bursts remain normal in both segments of the KO hippocampus. Local network excitability increases in the dorsal KO hippocampus. Furthermore, specifically in the ventral hippocampus of KO rats we found an increased effectiveness of inhibition in suppressing excitation and an upregulation of α1GABAA receptor subtype. These changes in the ventral KO hippocampus are accompanied by a striking reduction in its susceptibility to induced epileptiform activity. We propose that the neuronal network specifically in the ventral segment of the hippocampus is reorganized in adult Fmr1-KO rats by means of balanced changes between excitability and inhibition to ensure normal generation of SWRs and preventing at the same time derailment of the neural activity toward hyperexcitability.

Unraveling viral drug targets: a deep learning-based approach for the identification of potential binding sites.

The coronavirus disease 2019 (COVID-19) pandemic has spurred a wide range of approaches to control and combat the disease. However, selecting an effective antiviral drug target remains a time-consuming challenge. Computational methods offer a promising solution by efficiently reducing the number of candidates. In this study, we propose a structure- and deep learning-based approach that identifies vulnerable regions in viral proteins corresponding to drug binding sites. Our approach takes into account the protein dynamics, accessibility and mutability of the binding site and the putative mechanism of action of the drug. We applied this technique to validate drug targeting toward severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein S. Our findings reveal a conformation- and oligomer-specific glycan-free binding site proximal to the receptor binding domain. This site comprises topologically important amino acid residues. Molecular dynamics simulations of Spike in complex with candidate drug molecules bound to the potential binding sites indicate an equilibrium shifted toward the inactive conformation compared with drug-free simulations. Small molecules targeting this binding site have the potential to prevent the closed-to-open conformational transition of Spike, thereby allosterically inhibiting its interaction with human angiotensin-converting enzyme 2 receptor. Using a pseudotyped virus-based assay with a SARS-CoV-2 neutralizing antibody, we identified a set of hit compounds that exhibited inhibition at micromolar concentrations.

Complex spikes perturb movements and reveal the sensorimotor map of Purkinje cells

Computations that are performed by the cerebellar cortex are transmitted via simple spikes of Purkinje cells (P-cells) to downstream structures, but because P-cells are many synapses away from muscles, we do not know the relationship between modulation of simple spikes and control of behavior. Here, we recorded the spiking activities of hundreds of P-cells in the oculomotor vermis of marmosets during saccadic eye movements and found that following the presentation of a visual stimulus, the olivary input to a P-cell coarsely described the direction and amplitude of the visual stimulus as well as the upcoming movement. Occasionally, the complex spike occurred just before saccade onset, suppressing the P-cell's simple spikes and disrupting its output during that saccade. Remarkably, this brief suppression of simple spikes altered the saccade's trajectory by pulling the eyes toward the part of the visual space that was preferentially encoded by the olivary input to that P-cell. Thus, there is an alignment between the sensory space encoded by the complex spikes and the behavior conveyed by the simple spikes: a reduction in simple spikes is a signal to bias the ongoing movement toward the part of the sensory space preferentially encoded by the olivary input to that P-cell.

Neuromorphic behaviors of VO2 memristor-based neurons

Neuromorphic computing has the potential to overcome the limitations of the von Neumann Bottleneck and Moore's Law. Memristors, characterized by nanoscale, adjustable resistance, low power consumption, and non-volatility, are considered as one of the best candidates for neuromorphic computing. This paper utilizes an accurate model of VO2 locally active memristor fabricated by HRL Labs to construct second-order and third-order neuronal circuits, which can exhibit 21 different types of neuromorphic behaviors. These behaviors include all or nothing firing, complex spiking, bursting, refractory period, accommodation, chaos, and others. Based on the theories of local activity and the Edge of Chaos (EoC), this paper analyzes the dynamics of the neuronal circuits, demonstrating the biological neurons operate at the EoC, and the neuromorphic behaviors emerge on or near the EoC, which reveals the generation mechanism of the action potential.

Etomidate Depresses Spontaneous Complex Spikes Activity of Cerebellar Purkinje Cells via Cannabinoid 1 Receptor in vivo in Mice

Introduction: Complex spikes (CSs) activity of cerebellar Purkinje cells plays critical roles in motor coordination and motor learning by transferring information to cerebellar cortex, which is an accessible and useful model for neurophysiological investigation. Etomidate is an ultrashort-acting nonbarbiturate intravenous anesthetic, which inhibits the spontaneous activity of cerebellar Purkinje cells through activation of GABA_A and glycine receptors in vivo in mice. However, the effect of etomidate on the spontaneous CSs activity of cerebellar Purkinje cells in living mouse is not clear. Methods: We here investigated the effects of etomidate on spontaneous CSs activity of cerebellar Purkinje cell in urethane-anesthetized mice by electrophysiology recording technique and pharmacological methods. Results: Our results showed that cerebellar surface perfusion of etomidate significantly depressed the activity of spontaneous CSs, which exhibited decreases in the number of spikelets and the area under curve (AUC) of the CSs. The etomidate-produced inhibition of CSs activity was persisted in the presence of GABA_A and glycine receptors antagonists. However, application of cannabinoid 1 (CB1) receptor antagonist, AM-251, completely blocked the etomidate-induced inhibition of CSs. Furthermore, application of the CB1 receptor agonist, WIN55212-2, induced a decrease of CSs. Moreover, in the presence of a specific protein kinase A (PKA) inhibitor, KT5720, etomidate failed to produce decreases in the spikelets number and the AUC of the spontaneous CSs. Conclusion: These results indicate that cerebellar surface application of etomidate facilitates CB1 receptor activity resulting in a depression of spontaneous CSs activity of Purkinje cells via PKA signaling pathway in mouse cerebellar cortex. Our present results suggest that the etomidate administration may impair the function of cerebellar cortical neuronal circuitry by inhibition of the climbing fiber – Purkinje cells synaptic transmission through activation of CB1 receptors in vivo in mice.

Sleep disrupts complex spiking dynamics in the neocortex and hippocampus.

Neuronal interactions give rise to complex dynamics in cortical networks, often described in terms of the diversity of activity patterns observed in a neural signal. Interestingly, the complexity of spontaneous electroencephalographic signals decreases during slow-wave sleep (SWS); however, the underlying neural mechanisms remain elusive. Here, we analyse in-vivo recordings from neocortical and hippocampal neuronal populations in rats and show that the complexity decrease is due to the emergence of synchronous neuronal DOWN states. Namely, we find that DOWN states during SWS force the population activity to be more recurrent, deterministic, and less random than during REM sleep or wakefulness, which, in turn, leads to less complex field recordings. Importantly, when we exclude DOWN states from the analysis, the recordings during wakefulness and sleep become indistinguishable: the spiking activity in all the states collapses to a common scaling. We complement these results by implementing a critical branching model of the cortex, which shows that inducing DOWN states to only a percentage of neurons is enough to generate a decrease in complexity that replicates SWS.

How inhibitory and excitatory inputs gate output of the inferior olive.

The inferior olive provides the climbing fibers to Purkinje cells in the cerebellar cortex, where they elicit all-or-none complex spikes and control major forms of plasticity. Given their important role in both short-term and long-term coordination of cerebellum-dependent behaviors, it is paramount to understand the factors that determine the output of olivary neurons. Here, we use mouse models to investigate how the inhibitory and excitatory inputs to the olivary neurons interact with each other, generating spiking patterns of olivary neurons that align with their intrinsic oscillations. Using dual color optogenetic stimulation and whole-cell recordings, we demonstrate how intervals between the inhibitory input from the cerebellar nuclei and excitatory input from the mesodiencephalic junction affect phase and gain of the olivary output at both the sub- and suprathreshold level. When the excitatory input is activated shortly (~50 ms) after the inhibitory input, the phase of the intrinsic oscillations becomes remarkably unstable and the excitatory input can hardly generate any olivary spike. Instead, when the excitatory input is activated one cycle (~150 ms) after the inhibitory input, the excitatory input can optimally drive olivary spiking, riding on top of the first cycle of the subthreshold oscillations that have been powerfully reset by the preceding inhibitory input. Simulations of a large-scale network model of the inferior olive highlight to what extent the synaptic interactions penetrate in the neuropil, generating quasi-oscillatory spiking patterns in large parts of the olivary subnuclei, the size of which also depends on the relative timing of the inhibitory and excitatory inputs.

From period-doubling bursting to chaotic–periodic bursting in a modified Chua’s circuit

The aim of this paper is to reveal the dynamical mechanism of bursting oscillations in non-smooth dynamical systems, and the interest is focused on the effects of period-doubling bifurcation and chaotic attractor on the bursting oscillations. By modifying a fourth-order Chua’s circuit, a dynamical system possessing non-smooth switching manifold and multiple scale variables, is established. By taking the slow-varying variable as a bifurcation parameter, Subcritical non-smooth Hopf bifurcation, C-bifurcation, and period-doubling bifurcation are obtained in the fast subsystem. Further more, chaotic attractors, which are generated from a series of period-doubling bifurcations, are also observed. Based on the numerical simulations and bifurcation analysis of the fast subsystem, eight typical bursting patterns are obtained, and their dynamical mechanism is revealed. Study shows that period-2 limit cycle in the fast subsystem may cause the slow–fast system to oscillates in alternating small and large amplitudes; A complex spiking attractors made up of limit cycles and chaotic attractors may lead to spiking states changing from chaotic oscillations to periodic ones, and the trajectory may jump directly from a chaotic attractor to other stable one without undergoing any bifurcation of the fast subsystem.

Excitatory nucleo-olivary pathway shapes cerebellar outputs for motor control

The brain generates predictive motor commands to control the spatiotemporal precision of high-velocity movements. Yet, how the brain organizes automated internal feedback to coordinate the kinematics of such fast movements is unclear. Here we unveil a unique nucleo-olivary loop in the cerebellum and its involvement in coordinating high-velocity movements. Activating the excitatory nucleo-olivary pathway induces well-timed internal feedback complex spike signals in Purkinje cells to shape cerebellar outputs. Anatomical tracing reveals extensive axonal collaterals from the excitatory nucleo-olivary neurons to downstream motor regions, supporting integration of motor output and internal feedback signals within the cerebellum. This pathway directly drives saccades and head movements with a converging direction, while curtailing their amplitude and velocity via the powerful internal feedback mechanism. Our finding challenges the long-standing dogma that the cerebellum inhibits the inferior olivary pathway and provides a new circuit mechanism for the cerebellar control of high-velocity movements.

Reconfigurable Low-Power TiO2 Memristor for Integration of Artificial Synapse and Nociceptor

Bio-mimetic advanced electronic systems are emerging rapidly, engrossing their applications in neuromorphic computing, humanoid robotics, tactile sensors, and so forth. The biological synaptic and nociceptive functions are governed by intricate neurotransmitter dynamics that involve both short-term and long-term plasticity. To emulate the neuronal dynamics in an electronic device, an Ag/TiO2/Pt/SiO2/Si memristor is fabricated, exhibiting compliance current controlled reversible transition of volatile switching (VS) and non-volatile switching (NVS). The origin of the VS and NVS depends on the diameter of the conducting filament, which is explained using a field-induced nucleation theory and validated by temporal current response measurements. The switching delay of the device is used to determine the characteristic nociceptive behaviors such as threshold, relaxation, inadaptation, allodynia, and hyperalgesia. The short-term and long-term retention loss attributed to the VS and NVS, respectively, is used to emulate short-term memory and long-term memory of the biological brain in a single device. More importantly, synergistically modulating the VS-NVS transition, the complex spike rate-dependent (SRDP) and spike time-dependent plasticity (STDP) with a weight change of up to 600% is demonstrated in the same device, which is the highest reported so far for TiO2 memristors. Furthermore, the device exhibits very low power consumption, ∼3.76 pJ/spike, and can imitate synaptic and nociceptive functions. The consolidation of complex nociceptive and synaptic behavior in a single memristor facilitates low-power integration of scalable intelligent sensors and neuromorphic devices.