A nanofluidic spiking synapse.

Currently, the nanofluidic synapse can only perform basic neuromorphic pulse patterns. One immediate problem that needs to be addressed to further its capability of brain-like computing is the realization of a nanofluidic spiking device. Here, we report the use of a poly(3,4-ethylenedioxythiophene) polystyrene sulfonate membrane to achieve bionic ionic current-induced spiking. In addition to the simulation of various electrical pulse patterns, our synapse could produce transmembrane ionic current-induced spiking, which is highly analogous to biological action potentials with similar phases and excitability. Moreover, the spiking properties could be modulated by ions and neurochemicals. We expect that this work could contribute to biomimetic spiking computing in solution.

Repeated stimulation of feeding mechanoafferents in Aplysia generates responses consistent with the release of food.

How does repeated stimulation of mechanoafferents affect feeding motor neurons? Monosynaptic connections from a mechanoafferent population in the Aplysia buccal ganglia to five motor followers with different functions were examined during repeated stimulus trains. The mechanoafferents produced both fast and slow synaptic outputs, which could be excitatory or inhibitory. In contrast, other Aplysia mechanoafferents produce only fast excitation on their followers. In addition, patterns of synaptic connections were different to the different motor followers. Some followers received both fast excitation and fast inhibition, whereas others received exclusively fast excitation. All followers showed strong decreases in fast postsynaptic potential (PSP) amplitude within a stimulus train. Fast and slow synaptic connections were of net opposite signs in some followers but not in others. For one follower, synaptic contacts were not uniform from all subareas of the mechanoafferent cluster. Differences in properties of the buccal ganglia mechanoafferents and other Aplysia mechanoafferents may arise because the buccal ganglia neurons innervate the interior of the feeding apparatus, rather than an external surface, and connect to motor neurons for muscles with different motor functions. Fast connection patterns suggest that these synapses may be activated when food slips, biasing the musculature to release food. The largest slow inhibitory synaptic PSPs may contribute to a delay in the onset of the next behavior. Additional functions are also possible.

Direct and indirect pathways for heterosynaptic interaction underlying developmental synapse elimination in the mouse cerebellum.

Developmental synapse elimination is crucial for shaping mature neural circuits. In the neonatal mouse cerebellum, Purkinje cells (PCs) receive excitatory synaptic inputs from multiple climbing fibers (CFs) and synapses from all but one CF are eliminated by around postnatal day 20. Heterosynaptic interaction between CFs and parallel fibers (PFs), the axons of cerebellar granule cells (GCs) forming excitatory synapses onto PCs and molecular layer interneurons (MLIs), is crucial for CF synapse elimination. However, mechanisms for this heterosynaptic interaction are largely unknown. Here we show that deletion of AMPA-type glutamate receptor functions in GCs impairs CF synapse elimination mediated by metabotropic glutamate receptor 1 (mGlu1) signaling in PCs. Furthermore, CF synapse elimination is impaired by deleting NMDA-type glutamate receptors from MLIs. We propose that PF activity is crucial for CF synapse elimination by directly activating mGlu1 in PCs and indirectly enhancing the inhibition of PCs through activating NMDA receptors in MLIs.

From hidden hearing loss to supranormal auditory processing by neurotrophin 3-mediated modulation of inner hair cell synapse density.

Loss of synapses between spiral ganglion neurons and inner hair cells (IHC synaptopathy) leads to an auditory neuropathy called hidden hearing loss (HHL) characterized by normal auditory thresholds but reduced amplitude of sound-evoked auditory potentials. It has been proposed that synaptopathy and HHL result in poor performance in challenging hearing tasks despite a normal audiogram. However, this has only been tested in animals after exposure to noise or ototoxic drugs, which can cause deficits beyond synaptopathy. Furthermore, the impact of supernumerary synapses on auditory processing has not been evaluated. Here, we studied mice in which IHC synapse counts were increased or decreased by altering neurotrophin 3 (Ntf3) expression in IHC supporting cells. As we previously showed, postnatal Ntf3 knockdown or overexpression reduces or increases, respectively, IHC synapse density and suprathreshold amplitude of sound-evoked auditory potentials without changing cochlear thresholds. We now show that IHC synapse density does not influence the magnitude of the acoustic startle reflex or its prepulse inhibition. In contrast, gap-prepulse inhibition, a behavioral test for auditory temporal processing, is reduced or enhanced according to Ntf3 expression levels. These results indicate that IHC synaptopathy causes temporal processing deficits predicted in HHL. Furthermore, the improvement in temporal acuity achieved by increasing Ntf3 expression and synapse density suggests a therapeutic strategy for improving hearing in noise for individuals with synaptopathy of various etiologies.

Toward human-like adaptability in robotics through a retention-engineered synaptic control system.

Although advanced robots can adeptly mimic human movement and aesthetics, they are still unable to adapt or evolve in response to external experiences. To address this limitation, we propose an innovative approach that uses parallel-processable retention-engineered synaptic devices in the control system. This approach aims to simulate a human-like learning system without necessitating complex computational systems. The retention properties of the synaptic devices were modulated by adjusting the amount of Ag/AgCl ink sprayed. This changed the voltage drop across the interface between the gate electrode and the electrolyte. Furthermore, the unrestricted movement of ions in the electrolyte enhanced the signal multiplexing capability of the ion gel, enabling device-level parallel processing. By integrating the unique characteristics of the synaptic devices with actuators, we successfully emulated a human-like workout process that includes feedback between acute and chronic responses. The proposed control system offers an innovative approach to reducing system complexity and achieving a human-like learning system in the field of biomimicry.

Skewing information flow through pre- and postsynaptic plasticity in the mushroom bodies of Drosophila.

Animal brains need to store information to construct a representation of their environment. Knowledge of what happened in the past allows both vertebrates and invertebrates to predict future outcomes by recalling previous experience. Although invertebrate and vertebrate brains share common principles at the molecular, cellular, and circuit-architectural levels, there are also obvious differences as exemplified by the use of acetylcholine versus glutamate as the considered main excitatory neurotransmitters in the respective central nervous systems. Nonetheless, across central nervous systems, synaptic plasticity is thought to be a main substrate for memory storage. Therefore, how brain circuits and synaptic contacts change following learning is of fundamental interest for understanding brain computations tied to behavior in any animal. Recent progress has been made in understanding such plastic changes following olfactory associative learning in the mushroom bodies (MBs) of Drosophila A current framework of memory-guided behavioral selection is based on the MB skew model, in which antagonistic synaptic pathways are selectively changed in strength. Here, we review insights into plasticity at dedicated Drosophila MB output pathways and update what is known about the plasticity of both pre- and postsynaptic compartments of Drosophila MB neurons.

Functional Dynamics and Selectivity of Two Parallel Corticocortical Pathways from Motor Cortex to Layer 5 Circuits in Somatosensory Cortex.

In the rodent whisker system, active sensing and sensorimotor integration are mediated in part by the dynamic interactions between the motor cortex (M1) and somatosensory cortex (S1). However, understanding these dynamic interactions requires knowledge about the synapses and how specific neurons respond to their input. Here, we combined optogenetics, retrograde labeling, and electrophysiology to characterize the synaptic connections between M1 and layer 5 (L5) intratelencephalic (IT) and pyramidal tract (PT) neurons in S1 of mice (both sexes). We found that M1 synapses onto IT cells displayed modest short-term depression, whereas synapses onto PT neurons showed robust short-term facilitation. Despite M1 inputs to IT cells depressing, their slower kinetics resulted in summation and a response that increased during short trains. In contrast, summation was minimal in PT neurons due to the fast time course of their M1 responses. The functional consequences of this reduced summation, however, were outweighed by the strong facilitation at these M1 synapses, resulting in larger response amplitudes in PT neurons than IT cells during repetitive stimulation. To understand the impact of facilitating M1 inputs on PT output, we paired trains of inputs with single backpropagating action potentials, finding that repetitive M1 activation increased the probability of bursts in PT cells without impacting the time dependence of this coupling. Thus, there are two parallel but dynamically distinct systems of M1 synaptic excitation in L5 of S1, each defined by the short-term dynamics of its synapses, the class of postsynaptic neurons, and how the neurons respond to those inputs.

Deletion of VPS50 protein in mouse brain impairs synaptic function and behavior.

BACKGROUND: The VPS50 protein functions in synaptic and dense core vesicle acidification, and perturbations of VPS50 function produce behavioral changes in Caenorhabditis elegans. Patients with mutations in VPS50 show severe developmental delay and intellectual disability, characteristics that have been associated with autism spectrum disorders (ASDs). The mechanisms that link VPS50 mutations to ASD are unknown. RESULTS: To examine the role of VPS50 in mammalian brain function and behavior, we used the CRISPR/Cas9 system to generate knockouts of VPS50 in both cultured murine cortical neurons and living mice. In cultured neurons, KO of VPS50 did not affect the number of synaptic vesicles but did cause mislocalization of the V-ATPase V1 domain pump and impaired synaptic activity, likely as a consequence of defects in vesicle acidification and vesicle content. In mice, mosaic KO of VPS50 in the hippocampus altered synaptic transmission and plasticity and generated robust cognitive impairments. CONCLUSIONS: We propose that VPS50 functions as an accessory protein to aid the recruitment of the V-ATPase V1 domain to synaptic vesicles and in that way plays a crucial role in controlling synaptic vesicle acidification. Understanding the mechanisms controlling behaviors and synaptic function in ASD-associated mutations is pivotal for the development of targeted interventions, which may open new avenues for therapeutic strategies aimed at ASD and related conditions.

Conductance-based dendrites perform Bayes-optimal cue integration.

A fundamental function of cortical circuits is the integration of information from different sources to form a reliable basis for behavior. While animals behave as if they optimally integrate information according to Bayesian probability theory, the implementation of the required computations in the biological substrate remains unclear. We propose a novel, Bayesian view on the dynamics of conductance-based neurons and synapses which suggests that they are naturally equipped to optimally perform information integration. In our approach apical dendrites represent prior expectations over somatic potentials, while basal dendrites represent likelihoods of somatic potentials. These are parametrized by local quantities, the effective reversal potentials and membrane conductances. We formally demonstrate that under these assumptions the somatic compartment naturally computes the corresponding posterior. We derive a gradient-based plasticity rule, allowing neurons to learn desired target distributions and weight synaptic inputs by their relative reliabilities. Our theory explains various experimental findings on the system and single-cell level related to multi-sensory integration, which we illustrate with simulations. Furthermore, we make experimentally testable predictions on Bayesian dendritic integration and synaptic plasticity.

Quantification of Microglial Engulfment of Synaptic Material Using Flow Cytometry.

Microglia play a pivotal role in synaptic refinement in the brain. Analysis of microglial engulfment of synapses is essential for comprehending this process; however, currently available methods for identifying microglial engulfment of synapses, such as immunohistochemistry (IHC) and imaging, are laborious and time-intensive. To address this challenge, herein we present in vitro and in vivo* assays that allow fast and high-throughput quantification of microglial engulfment of synapses using flow cytometry. In the in vivo* approach, we performed intracellular vGLUT1 staining following fresh cell isolation from adult mouse brains to quantify engulfment of vGLUT1+ synapses by microglia. In the in vitro synaptosome engulfment assay, we used freshly isolated cells from the adult mouse brain to quantify the engulfment of pHrodo Red-labeled synaptosomes by microglia. These protocols together provide a time-efficient approach to quantifying microglial engulfment of synapses and represent promising alternatives to labor-intensive image analysis-based methods. By streamlining the analysis, these assays can contribute to a better understanding of the role of microglia in synaptic refinement in different disease models.

Hebbian priming of human motor learning.

Motor learning relies on experience-dependent plasticity in relevant neural circuits. In four experiments, we provide initial evidence and a double-blinded, sham-controlled replication (Experiment I-II) demonstrating that motor learning involving ballistic index finger movements is improved by preceding paired corticospinal-motoneuronal stimulation (PCMS), a human model for exogenous induction of spike-timing-dependent plasticity. Behavioral effects of PCMS targeting corticomotoneuronal (CM) synapses are order- and timing-specific and partially bidirectional (Experiment III). PCMS with a 2 ms inter-arrival interval at CM-synapses enhances learning and increases corticospinal excitability compared to control protocols. Unpaired stimulations did not increase corticospinal excitability (Experiment IV). Our findings demonstrate that non-invasively induced plasticity interacts positively with experience-dependent plasticity to promote motor learning. The effects of PCMS on motor learning approximate Hebbian learning rules, while the effects on corticospinal excitability demonstrate timing-specificity but not bidirectionality. These findings offer a mechanistic rationale to enhance motor practice effects by priming sensorimotor training with individualized PCMS.

A neural network model for online one-shot storage of pattern sequences.

Based on the CRISP theory (Content Representation, Intrinsic Sequences, and Pattern completion), we present a computational model of the hippocampus that allows for online one-shot storage of pattern sequences without the need for a consolidation process. In our model, CA3 provides a pre-trained sequence that is hetero-associated with the input sequence, rather than storing a sequence in CA3. That is, plasticity on a short timescale only occurs in the incoming and outgoing connections of CA3, not in its recurrent connections. We use a single learning rule named Hebbian descent to train all plastic synapses in the network. A forgetting mechanism in the learning rule allows the network to continuously store new patterns while forgetting those stored earlier. We find that a single cue pattern can reliably trigger the retrieval of sequences, even when cues are noisy or missing information. Furthermore, pattern separation in subregion DG is necessary when sequences contain correlated patterns. Besides artificially generated input sequences, the model works with sequences of handwritten digits and natural images. Notably, our model is capable of improving itself without external input, in a process that can be referred to as 'replay' or 'offline-learning', which helps in improving the associations and consolidating the learned patterns.

Synapse-type-specific competitive Hebbian learning forms functional recurrent networks.

Cortical networks exhibit complex stimulus-response patterns that are based on specific recurrent interactions between neurons. For example, the balance between excitatory and inhibitory currents has been identified as a central component of cortical computations. However, it remains unclear how the required synaptic connectivity can emerge in developing circuits where synapses between excitatory and inhibitory neurons are simultaneously plastic. Using theory and modeling, we propose that a wide range of cortical response properties can arise from a single plasticity paradigm that acts simultaneously at all excitatory and inhibitory connections-Hebbian learning that is stabilized by the synapse-type-specific competition for a limited supply of synaptic resources. In plastic recurrent circuits, this competition enables the formation and decorrelation of inhibition-balanced receptive fields. Networks develop an assembly structure with stronger synaptic connections between similarly tuned excitatory and inhibitory neurons and exhibit response normalization and orientation-specific center-surround suppression, reflecting the stimulus statistics during training. These results demonstrate how neurons can self-organize into functional networks and suggest an essential role for synapse-type-specific competitive learning in the development of cortical circuits.

Persistent spiking activity in neuromorphic circuits incorporating post-inhibitory rebound excitation.

Objective. This study introduces a novel approach for integrating the post-inhibitory rebound excitation (PIRE) phenomenon into a neuronal circuit. Excitatory and inhibitory synapses are designed to establish a connection between two hardware neurons, effectively forming a network. The model demonstrates the occurrence of PIRE under strong inhibitory input. Emphasizing the significance of incorporating PIRE in neuromorphic circuits, the study showcases generation of persistent activity within cyclic and recurrent spiking neuronal networks.Approach. The neuronal and synaptic circuits are designed and simulated in Cadence Virtuoso using TSMC 180 nm technology. The operating mechanism of the PIRE phenomenon integrated into a hardware neuron is discussed. The proposed circuit encompasses several parameters for effectively controlling multiple electrophysiological features of a neuron.Main results. The neuronal circuit has been tuned to match the response of a biological neuron. The efficiency of this circuit is evaluated by computing the average power dissipation and energy consumption per spike through simulation. The sustained firing of neural spikes is observed till 1.7 s using the two neuronal networks.Significance. Persistent activity has significant implications for various cognitive functions such as working memory, decision-making, and attention. Therefore, hardware implementation of these functions will require our PIRE-integrated model. Energy-efficient neuromorphic systems are useful in many artificial intelligence applications, including human-machine interaction, IoT devices, autonomous systems, and brain-computer interfaces.

GluN2A- and GluN2B-containing pre-synaptic N-methyl-d-aspartate receptors differentially regulate action potential-evoked Ca2+ influx via modulation of SK channels.

N-methyl-d-aspartate receptors (NMDARs) play a pivotal role in synaptic plasticity. While the functional role of post-synaptic NMDARs is well established, pre-synaptic NMDAR (pre-NMDAR) function is largely unexplored. Different pre-NMDAR subunit populations are documented at synapses, suggesting that subunit composition influences neuronal transmission. Here, we used electrophysiological recordings at Schaffer collateral-CA1 synapses partnered with Ca2+ imaging and glutamate uncaging at boutons of CA3 pyramidal neurones to reveal two populations of pre-NMDARs that contain either the GluN2A or GluN2B subunit. Activation of the GluN2B population decreases action potential-evoked Ca2+ influx via modulation of small-conductance Ca2+-activated K+ channels, while activation of the GluN2A population does the opposite. Critically, the level of functional expression of the subunits is subject to homeostatic regulation, bidirectionally affecting short-term facilitation, thus providing a capacity for a fine adjustment of information transfer. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

Synaptic correlates of the corticocortical circuit in motor learning.

Rodents actively learn new motor skills for survival in reaction to changing environments. Despite the classic view of the primary motor cortex (M1) as a simple muscle relay region, it is now known to play a significant role in motor skill acquisition. The secondary motor cortex (M2) is reported to be a crucial region for motor learning as well as for its role in motor execution and planning. Although these two regions are known for the part they play in motor learning, the role of direct connection and synaptic correlates between these two regions remains elusive. Here, we confirm M2 to M1 connectivity with a series of tracing experiments. We also show that the accelerating rotarod task successfully induces motor skill acquisition in mice. For mice that underwent rotarod training, learner mice showed increased synaptic density and spine head size for synapses between activated cell populations of M2 and M1. Non-learner mice did not show these synaptic changes. Collectively, these data suggest the potential importance of synaptic plasticity between activated cell populations as a potential mechanism of motor learning. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

Equal levels of pre- and postsynaptic potentiation produce unequal outcomes.

Which proportion of the long-term potentiation (LTP) expressed in the bulk of excitatory synapses is postsynaptic and which presynaptic remains debatable. To understand better the possible impact of either LTP form, we explored a realistic model of a CA1 pyramidal cell equipped with known membrane mechanisms and multiple, stochastic excitatory axo-spinous synapses. Our simulations were designed to establish an input-output transfer function, the dependence between the frequency of presynaptic action potentials triggering probabilistic synaptic discharges and the average frequency of postsynaptic spiking. We found that, within the typical physiological range, potentiation of the postsynaptic current results in a greater overall output than an equivalent increase in presynaptic release probability. This difference grows stronger at lower input frequencies and lower release probabilities. Simulations with a non-hierarchical circular network of principal neurons indicated that equal increases in either synaptic fidelity or synaptic strength of individual connections also produce distinct changes in network activity, although the network phenomenology is likely to be complex. These observations should help to interpret the machinery of LTP phenomena documented in situ. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

The role of calcium stores in long-term potentiation and synaptic tagging and capture in mouse hippocampus.

The roles of Ca2+-induced calcium release in synaptic plasticity and metaplasticity are poorly understood. The present study has addressed the role of intracellular Ca2+ stores in long-term potentiation (LTP) and a form of heterosynaptic metaplasticity known as synaptic tagging and capture (STC) at CA1 synapses in mouse hippocampal slices. The effects of two compounds, ryanodine and cyclopiazonic acid (CPA), were examined on LTP induced by three distinct induction protocols: weak (w), compressed (c) and spaced (s) theta-burst stimulation (TBS). These compounds did not significantly affect LTP induced by the wTBS (one episode of TBS; 25 stimuli) or cTBS (three such episodes with a 10 s inter-episode interval (IEI); 75 stimuli) but substantially inhibited LTP induced by a sTBS (10 min IEI; 75 stimuli). Ryanodine and CPA also prevented a small heterosynaptic potentiation that was observed with the sTBS protocol. Interestingly, these compounds also prevented STC when present during either the sTBS or the subsequent wTBS, applied to an independent input. All of these effects of ryanodine and CPA were similar to that of a calcium-permeable AMPA receptor blocker. In conclusion, Ca2+ stores provide one way in which signals are propagated between synaptic inputs and, by virtue of their role in STC, may be involved in associative long-term memories. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

Src dependency of the regulation of LTP by alternative splicing of GRIN1 exon 5.

Alternative splicing of Grin1 exon 5 regulates induction of long-term potentiation (LTP) at Schaffer collateral-CA1 synapses: LTP in mice lacking the GluN1 exon 5-encoded N1 cassette (GluN1a mice) is significantly increased compared with that in mice compulsorily expressing this exon (GluN1b mice). The mechanism underlying this difference is unknown. Here, we report that blocking the non-receptor tyrosine kinase Src prevents induction of LTP in GluN1a mice but not in GluN1b. We find that activating Src enhances pharmacologically isolated synaptic N-methyl-d-aspartate receptor (NMDAR) currents in GluN1a mice but not in GluN1b. Moreover, we observe that Src activation increases the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor component of Schaffer collateral-evoked excitatory post-synaptic potentials in GluN1a mice, but this increase is prevented by blocking NMDARs. We conclude that at these synapses, NMDARs in GluN1a mice are subject to upregulation by Src that mediates induction of LTP, whereas NMDARs in GluN1b mice are not regulated by Src, leading to Src-resistance of LTP. Thus, we have uncovered that a key regulatory mechanism for synaptic potentiation is gated by differential splicing of exon 5 of Grin1. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.