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Behavioural experiences interact with regenerative responses to shape patterns of neural reorganization after stroke. This review is focused on the competitive nature of these behavioural experience effects. Interactions between learning‐related plasticity and regenerative reactions have been found to underlie the establishment of new compensatory behaviours and the efficacy of motor rehabilitative training in rodent stroke models. Learning in intact brains depends on competitive and cooperative mechanisms of synaptic plasticity. Synapses are added in response to learning and selectively maintained and strengthened via activity‐dependent competition. Long‐term memories for experiences that occur closely in time can be weakened or enhanced by competitive or cooperative interactions in the time‐dependent process of stabilizing synaptic changes. Rodent stroke model findings suggest that compensatory reliance on the non‐paretic hand after stroke can shape and stabilize synaptic reorganization patterns in both hemispheres, to compete with the capacity for experiences of the paretic side to do so. However, the competitive edge of the non‐paretic side can be countered by overlapping experiences of the paretic hand, and might even be shifted in a cooperative direction with skilfully coordinated bimanual experience. Advances in the basic understanding of learning‐related synaptic competition are helping to inform the basis of experience‐dependent variations in stroke outcome. [ABSTRACT FROM AUTHOR]

Mounting evidence indicates that a physiological function of amyloid-β (Aβ) is to mediate neural activity-dependent homeostatic and competitive synaptic plasticity in the brain. I have previously summarized the lines of evidence supporting this hypothesis and highlighted the similarities between Aβ and anti-microbial peptides in mediating cell/synapse competition. In cell competition, anti-microbial peptides deploy a multitude of mechanisms to ensure both self-protection and competitor elimination. Here I review recent studies showing that similar mechanisms are at play in Aβ-mediated synapse competition and perturbations in these mechanisms underpin Alzheimer's disease (AD). Specifically, I discuss evidence that Aβ and ApoE, two crucial players in AD, co-operate in the regulation of synapse competition. Glial ApoE promotes self-protection by increasing the production of trophic monomeric Aβ and inhibiting its assembly into toxic oligomers. Conversely, Aβ oligomers, once assembled, promote the elimination of competitor synapses via direct toxic activity and amplification of "eat-me" signals promoting the elimination of weak synapses. I further summarize evidence that neuronal ApoE may be part of a gene regulatory network that normally promotes competitive plasticity, explaining the selective vulnerability of ApoE expressing neurons in AD brains. Lastly, I discuss evidence that sleep may be key to Aβ-orchestrated plasticity, in which sleep is not only induced by Aβ but is also required for Aβ-mediated plasticity, underlining the link between sleep and AD. Together, these results strongly argue that AD is a disease of competitive synaptic plasticity gone awry, a novel perspective that may promote AD research. [ABSTRACT FROM AUTHOR]

Although Hebbian LTP has an important role in memory formation, the properties of Hebbian LTP cannot fully account for, and in some cases seem incompatible with, fundamental properties of associative learning. Importantly, findings from computational and neurophysiological studies suggest that burst-dependent forms of plasticity, where dendritic spikes and bursts of action potentials provide the postsynaptic depolarization needed for LTP induction, may overcome some of the limitations of conventional Hebbian LTP. Thus, I investigated how excitatory synapses onto CA1 pyramidal cells interact during the induction of complex spike (CS) burst-dependent LTP in hippocampal slices from male mice. Consistent with previous findings, theta-frequency trains of synaptic stimulation induce a Hebbian form of plasticity where postsynaptic CS bursts provide the depolarization needed for NMDAR activation and LTP induction. However, in contrast to conventional Hebbian plasticity, where cooperative LTP induction requires coactivation of synapses on a timescale of tens of milliseconds, cooperative interactions between synapses activated several seconds apart can induce CS burst-dependent LTP. A novel, retroactive form of heterosynaptic plasticity, where activation of one group of synapses triggers LTP induction at other synapses that were active seconds earlier, also contributes to cooperativity in CS burst-dependent LTP. Moreover, competitive synaptic interactions that emerge during prolonged bouts of postsynaptic CS bursting potently regulate CS burst-dependent LTP. Together, the unusual properties of synaptic cooperativity and competition in CS burst-dependent LTP enable Hebbian synapses to operate and interact on behavioral timescales.SIGNIFICANCE STATEMENT While EPSP-evoked complex spike (CS) bursting induces LTP at excitatory synapses onto hippocampal CA1 pyramidal cells, the properties of synaptic interactions during the induction of CS burst-dependent LTP have not been investigated. Here I report that interactions between independent synaptic inputs during the induction of CS burst-dependent LTP exhibit a number of novel, computationally relevant properties. Unlike conventional Hebbian LTP, the induction of CS burst-dependent LTP is regulated by proactive and retroactive cooperative interactions between synapses activated several seconds apart. Moreover, activity-dependent, competitive interactions between synapses allow strongly activated synapses to suppress LTP induction at more weakly activated synapses. Thus, CS burst-dependent LTP exhibits a number of the unique properties that overcome significant limitations of standard Hebbian plasticity rules.

The principle of constraint-induced therapy is widely practiced in rehabilitation. In hemiplegic cerebral palsy (CP) with impaired contralateral corticospinal projection due to unilateral injury, function improves after imposing a temporary constraint on limbs from the less affected hemisphere. This type of partially-reversible impairment in motor control by early brain injury bears a resemblance to the experience-dependent plastic acquisition and modification of neuronal response selectivity in the visual cortex. Previously, such mechanism was modeled within the framework of BCM (Bienenstock-Cooper-Munro) theory, a rate-based synaptic modification theory. Here, we demonstrate a minimally complex yet sufficient neural network model which provides a fundamental explanation for inter-hemispheric competition using a simplified spike-based model of information transmission and plasticity. We emulate the restoration of function in hemiplegic CP by simulating the competition between cells of the ipsilateral and contralateral corticospinal tracts. We use a high-speed hardware neural simulation to provide realistic numbers of spikes and realistic magnitudes of synaptic modification. We demonstrate that the phenomenon of constraint-induced partial reversal of hemiplegia can be modeled by simplified neural descending tracts with 2 layers of spiking neurons and synapses with spike-timing-dependent plasticity (STDP). We further demonstrate that persistent hemiplegia following unilateral cortical inactivation or deprivation is predicted by the STDP-based model but is inconsistent with BCM model. Although our model is a highly simplified and limited representation of the corticospinal system, it offers an explanation of how constraint as an intervention can help the system to escape from a suboptimal solution. This is a display of an emergent phenomenon from the synaptic competition.

Synapses change their weights in response to neuronal activity and in turn, neuronal networks alter their response properties and ultimately allow the brain to store information as memories. As for memories, not all events are maintained over time. Maintenance of synaptic plasticity depends on the interplay between functional changes at synapses and the synthesis of plasticity-related proteins that are involved in stabilizing the initial functional changes. Different forms of synaptic plasticity coexist in time and across the neuronal dendritic area. Thus, homosynaptic plasticity refers to activity-dependent synaptic modifications that are input-specific, whereas heterosynaptic plasticity relates to changes in non-activated synapses. Heterosynaptic forms of plasticity, such as synaptic cooperation and competition allow neurons to integrate events that occur separated by relatively large time windows, up to one hour. Here, we show that activation of Cdc42, a Rho GTPase that regulates actin cytoskeleton dynamics, is necessary for the maintenance of long-term potentiation (LTP) in a time-dependent manner. Inhibiting Cdc42 activation does not alter the time-course of LTP induction and its initial expression but blocks its late maintenance. We show that Cdc42 activation is involved in the phosphorylation of cofilin, a protein involved in modulating actin filaments and that weak and strong synaptic activation leads to similar levels on cofilin phosphorylation, despite different levels of LTP expression. We show that Cdc42 activation is required for synapses to interact by cooperation or competition, supporting the hypothesis that modulation of the actin cytoskeleton provides an activity-dependent and time-restricted permissive state of synapses allowing synaptic plasticity to occur. We found that under competition, the sequence in which synapses are activated determines the degree of LTP destabilization, demonstrating that competition is an active destabilization process. Taken together, we show that modulation of actin cytoskeleton by Cdc42 activation is necessary for the expression of homosynaptic and heterosynaptic forms of plasticity. Determining the temporal and spatial rules that determine whether synapses cooperate or compete will allow us to understand how memories are associated. [Display omitted] • Cdc42 is required for the maintenance of homosynaptic synaptic plasticity. • Weak and strong stimulation modulate actin by cofilin phosphorylation. • Cdc42 activation is necessary for heterosynaptic cooperation and competition. • Synaptic competition is an active destabilization process. • The time-window of synaptic cooperation and competition is activity dependent. [ABSTRACT FROM AUTHOR]

Although Hebbian LTP has an important role in memory formation, the properties of Hebbian LTP cannot fully account for, and in some cases seem incompatible with, fundamental properties of associative learning. Importantly, findings from computational and neurophysiological studies suggest that burst-dependent forms of plasticity, where dendritic spikes and bursts of action potentials provide the postsynaptic depolarization needed for LTP induction, may overcome some of the limitations of conventional Hebbian LTP. Thus, I investigated how excitatory synapses onto CA1 pyramidal cells interact during the induction of complex spike (CS) burst-dependent LTP in hippocampal slices from male mice. Consistent with previous findings, theta-frequency trains of synaptic stimulation induce a Hebbian form of plasticity where postsynaptic CS bursts provide the depolarization needed for NMDAR activation and LTP induction. However, in contrast to conventional Hebbian plasticity, where cooperative LTP induction requires coactivation of synapses on a timescale of tens of milliseconds, cooperative interactions between synapses activated several seconds apart can induce CS burst-dependent LTP. A novel, retroactive form of heterosynaptic plasticity, where activation of one group of synapses triggers LTP induction at other synapses that were active seconds earlier, also contributes to cooperativity in CS burst-dependent LTP. Moreover, competitive synaptic interactions that emerge during prolonged bouts of postsynaptic CS bursting potently regulate CS burst-dependent LTP. Together, the unusual properties of synaptic cooperativity and competition in CS burst-dependent LTP enable Hebbian synapses to operate and interact on behavioral timescales. [ABSTRACT FROM AUTHOR]

Development of spiking neural networks (SNNs) controlling mobile robots is one of the modern challenges in computational neuroscience and artificial intelligence. Such networks, being replicas of biological ones, are expected to have a higher computational potential than traditional artificial neural networks (ANNs). The critical problem is in the design of robust learning algorithms aimed at building a “living computer” based on SNNs. Here, we propose a simple SNN equipped with a Hebbian rule in the form of spike-timing-dependent plasticity (STDP). The SNN implements associative learning by exploiting the spatial properties of STDP. We show that a LEGO robot controlled by the SNN can exhibit classical and operant conditioning. Competition of spike-conducting pathways in the SNN plays a fundamental role in establishing associations of neural connections. It replaces the irrelevant associations by new ones in response to a change in stimuli. Thus, the robot gets the ability to relearn when the environment changes. The proposed SNN and the stimulation protocol can be further enhanced and tested in developing neuronal cultures, and also admit the use of memristive devices for hardware implementation.

Activity‐dependent plasticity of synaptic connections is a hallmark of the mammalian brain and represents a key mechanism for rewiring neural circuits during development, experience‐dependent plasticity, and brain disorders. Cellular models of memory, such as long‐term potentiation and long‐term depression, share common principles to memory consolidation. As for memory, the maintenance of synaptic plasticity is dependent on the synthesis of de novo protein synthesis. The synaptic‐tagging and capture hypothesis states that the maintenance of synaptic plasticity is dependent on the interplay between input‐specific synaptic tags and the allocation or capture of plasticity‐related proteins (PRPs) at activated synapses. The setting of the synaptic tag and the capture of PRPs are independent processes that can occur separated in time and different groups of activated synapses. How are these two processes orchestrated in time and space? Here, we discuss the synaptic‐tagging and capture hypothesis in the light of neuronal compartmentalization models and address the role of actin as a putative synaptic tag. If different groups of synapses interact by synaptic‐tagging and capture mechanisms, understanding the spatial rules of such interaction is key to define the relevant neuronal compartment. We also discuss how actin modulation can allow an input‐specific capture of PRPs and try to conciliate the temporal dynamics of synaptic actin with the maintenance of plasticity. Understanding how multiple synapses interact in time and space is fundamental to predict how neurons integrate information and ultimately how memory is acquired. [ABSTRACT FROM AUTHOR]

We propose a model for synaptic plasticity based on a calcium signaling cascade. The model simplifies the full signaling pathways from a calcium influx to the phosphorylation (potentiation) and dephosphorylation (depression) of glutamate receptors that are gated by fictive C 1 and C 2 catalysts, respectively. This model is based on tangible chemical reactions, including fictive catalysts, for long-term plasticity rather than the conceptual theories commonplace in various models, such as preset thresholds of calcium concentration. Our simplified model successfully reproduced the experimental synaptic plasticity induced by different protocols such as (i) a synchronous pairing protocol and (ii) correlated presynaptic and postsynaptic action potentials (APs). Further, the ocular dominance plasticity (or the experimental verification of the celebrated Bienenstock—Cooper—Munro theory) was reproduced by two model synapses that compete by means of back-propagating APs (bAPs). The key to this competition is synapse-specific bAPs with reference to bAP-boosting on the physiological grounds. [ABSTRACT FROM AUTHOR]

Development of spiking neural networks (SNNs) controlling mobile robots is one of the modern challenges in computational neuroscience and artificial intelligence. Such networks, being replicas of biological ones, are expected to have a higher computational potential than traditional artificial neural networks (ANNs). The critical problem is in the design of robust learning algorithms aimed at building a "living computer" based on SNNs. Here, we propose a simple SNN equipped with a Hebbian rule in the form of spike-timing-dependent plasticity (STDP). The SNN implements associative learning by exploiting the spatial properties of STDP. We show that a LEGO robot controlled by the SNN can exhibit classical and operant conditioning. Competition of spike-conducting pathways in the SNN plays a fundamental role in establishing associations of neural connections. It replaces the irrelevant associations by new ones in response to a change in stimuli. Thus, the robot gets the ability to relearn when the environment changes. The proposed SNN and the stimulation protocol can be further enhanced and tested in developing neuronal cultures, and also admit the use of memristive devices for hardware implementation. [ABSTRACT FROM AUTHOR]

One of the modern trends in the design of human–machine interfaces (HMI) is to involve the so called spiking neuron networks (SNNs) in signal processing. The SNNs can be trained by simple and efficient biologically inspired algorithms. In particular, we have shown that sensory neurons in the input layer of SNNs can simultaneously encode the input signal based both on the spiking frequency rate and on varying the latency in generating spikes. In the case of such mixed temporal-rate coding, the SNN should implement learning working properly for both types of coding. Based on this, we investigate how a single neuron can be trained with pure rate and temporal patterns, and then build a universal SNN that is trained using mixed coding. In particular, we study Hebbian and competitive learning in SNN in the context of temporal and rate coding problems. We show that the use of Hebbian learning through pair-based and triplet-based spike timing-dependent plasticity (STDP) rule is accomplishable for temporal coding, but not for rate coding. Synaptic competition inducing depression of poorly used synapses is required to ensure a neural selectivity in the rate coding. This kind of competition can be implemented by the so-called forgetting function that is dependent on neuron activity. We show that coherent use of the triplet-based STDP and synaptic competition with the forgetting function is sufficient for the rate coding. Next, we propose a SNN capable of classifying electromyographical (EMG) patterns using an unsupervised learning procedure. The neuron competition achieved via lateral inhibition ensures the “winner takes all” principle among classifier neurons. The SNN also provides gradual output response dependent on muscular contraction strength. Furthermore, we modify the SNN to implement a supervised learning method based on stimulation of the target classifier neuron synchronously with the network input. In a problem of discrimination of three EMG patterns, the SNN with supervised learning shows median accuracy 99.5% that is close to the result demonstrated by multi-layer perceptron learned by back propagation of an error algorithm. [ABSTRACT FROM AUTHOR]

One of the modern trends in the design of human−machine interfaces (HMI) is to involve the so called spiking neuron networks (SNNs) in signal processing. The SNNs can be trained by simple and efficient biologically inspired algorithms. In particular, we have shown that sensory neurons in the input layer of SNNs can simultaneously encode the input signal based both on the spiking frequency rate and on varying the latency in generating spikes. In the case of such mixed temporal-rate coding, the SNN should implement learning working properly for both types of coding. Based on this, we investigate how a single neuron can be trained with pure rate and temporal patterns, and then build a universal SNN that is trained using mixed coding. In particular, we study Hebbian and competitive learning in SNN in the context of temporal and rate coding problems. We show that the use of Hebbian learning through pair-based and triplet-based spike timing-dependent plasticity (STDP) rule is accomplishable for temporal coding, but not for rate coding. Synaptic competition inducing depression of poorly used synapses is required to ensure a neural selectivity in the rate coding. This kind of competition can be implemented by the so-called forgetting function that is dependent on neuron activity. We show that coherent use of the triplet-based STDP and synaptic competition with the forgetting function is sufficient for the rate coding. Next, we propose a SNN capable of classifying electromyographical (EMG) patterns using an unsupervised learning procedure. The neuron competition achieved via lateral inhibition ensures the “winner takes all” principle among classifier neurons. The SNN also provides gradual output response dependent on muscular contraction strength. Furthermore, we modify the SNN to implement a supervised learning method based on stimulation of the target classifier neuron synchronously with the network input. In a problem of discrimination of three EMG patterns, the SNN with supervised learning shows median accuracy 99.5% that is close to the result demonstrated by multi-layer perceptron learned by back propagation of an error algorithm.

In developing brains, activity-dependent remodeling facilitates the formation of precise neuronal connectivity. Synaptic competition is known to facilitate synapse elimination; however, it has remained unknown how different synapses compete with one another within a post-synaptic cell. Here, we investigate how a mitral cell in the mouse olfactory bulb prunes all but one primary dendrite during the developmental remodeling process. We find that spontaneous activity generated within the olfactory bulb is essential. We show that strong glutamatergic inputs to one dendrite trigger branch-specific changes in RhoA activity to facilitate the pruning of the remaining dendrites: NMDAR-dependent local signals suppress RhoA to protect it from pruning; however, the subsequent neuronal depolarization induces neuron-wide activation of RhoA to prune non-protected dendrites. NMDAR-RhoA signals are also essential for the synaptic competition in the mouse barrel cortex. Our results demonstrate a general principle whereby activity-dependent lateral inhibition across synapses establishes a discrete receptive field of a neuron. [Display omitted] • Spontaneous neuronal activity is required for dendrite pruning of mitral cells • Glutamatergic inputs via NMDARs locally suppress RhoA to protect winner dendrites • Glutamatergic inputs via NMDARs activate RhoA in remote loser dendrites for pruning • Activity-dependent lateral inhibition mediates synaptic competition in general Fujimoto, Leiwe, Aihara, et al. show that strong glutamatergic inputs to a dendrite trigger local protection and lateral inhibition via NMDARs and RhoA, leading to the pruning of all but just one primary dendrite during mitral cell remodeling. Local protection and lateral inhibition comprise a general strategy for synaptic competition during development. [ABSTRACT FROM AUTHOR]

In many parts of the nervous system, signals pass across multiple synaptic relays on their way to a destination, but little is known about how these relays form and the function they serve. To get some insight into this question we ask how the connectivity patterns are organized at two successive synaptic relays in a simple, cholinergic efferent pathway. We found that the organization at successive relays in the parasympathetic nervous system strongly resemble each other despite the different embryological origin and physiological properties of the pre- and postsynaptic cells. Additionally, we found a similar developmental synaptic pruning and elaboration strategy is used at both sites to generate their adult organizations. The striking parallels in adult innervation and developmental mechanisms at the relays argue that a general strategy is in operation. We discuss why from a functional standpoint this structural organization may amplify central signals while at the same time maintaining positional targeting.

The formation of appropriate synaptic connections is critical for the proper functioning of the brain. Early in development, neurons form a surplus of immature synapses. To establish efficient, functional neural networks, neurons selectively stabilize active synapses and eliminate less active ones. This process is known as activity-dependent synapse refinement. Defects in this process have been implicated in neuropsychiatric disorders such as schizophrenia and autism. Here we review the manner and mechanisms by which synapse elimination is regulated through activity-dependent competition. We propose a theoretical framework for the molecular mechanisms of synapse refinement, in which three types of signals regulate the refinement. We then describe the identity of these signals and discuss how multiple molecular signals interact to achieve appropriate synapse refinement in the brain. • Neuronal activity-dependent competition instructs synapse refinement. • The winning synapses send a punishment signal to the losing synapses. • The elimination signal, JAK2, drives the elimination of losing synapses. • Many stabilization signals regulate various aspects of winning synapse maturation. • Neurons and microglia communicate via eat-me and don't-eat-me signals. [ABSTRACT FROM AUTHOR]

Binocular vision requires proper developmental wiring of eye-specific inputs to the brain. In the thalamus, axons from the two eyes initially overlap in the dorsal lateral geniculate nucleus and undergo activity-dependent competition to segregate into target domains. Here, we combine eye-specific tract tracing with volumetric super-resolution imaging to measure the nanoscale molecular reorganization of developing retinogeniculate eye-specific synapses in the mouse brain. We show there are eye-specific differences in presynaptic vesicle pool size and vesicle association with the active zone at the earliest stages of retinogeniculate refinement but find no evidence of eye-specific differences in subsynaptic domain number, size, or transsynaptic alignment across development. Genetic disruption of spontaneous retinal activity decreases retinogeniculate synapse density, delays the emergence eye-specific differences in vesicle organization, and disrupts subsynaptic domain maturation. These results suggest that activity-dependent eye-specific presynaptic maturation underlies synaptic competition in the mammalian visual system. [Display omitted] • Four-color volumetric super-resolution imaging of eye-specific synapse development • Eye-specific synapses show activity-dependent differences in presynaptic maturation • Abnormal retinal wave activity disrupts vesicle organization at the active zone • Subsynaptic domain alignment is independent of eye of origin and retinal activity Zhang et al. use volumetric single-molecule localization super-resolution microscopy to investigate eye-specific synaptic competition in the developing mammalian visual system. Retinogeniculate segregation involves eye-specific changes in synapse density, synapse size, and vesicle organization at the active zone that are disrupted in a genetic mutant with abnormal spontaneous retinal activity. [ABSTRACT FROM AUTHOR]

Evidence suggests that hippocampal adult neurogenesis is critical for discriminating considerably interfering memories. During adult neurogenesis, synaptic competition modifies the weights of synaptic connections nonlocally across neurons, thus providing a different form of unsupervised learning from Hebb's local plasticity rule. However, how synaptic competition achieves separating similar memories largely remains unknown. Here, we aim to link synaptic competition with such pattern separation. In synaptic competition, adult-born neurons are integrated into the existing neuronal pool by competing with mature neurons for synaptic connections from the entorhinal cortex. We show that synaptic competition and neuronal maturation play distinct roles in separating interfering memory patterns. Furthermore, we demonstrate that a feedforward neural network trained by a competition-based learning rule can outperform a multilayer perceptron trained by the backpropagation algorithm when only a small number of samples are available. Our results unveil the functional implications and potential applications of synaptic competition in neural computation., (© The Author(s) 2023. Published by Oxford University Press on behalf of National Academy of Sciences.)

Homeostatic plasticity is considered to maintain activity in neuronal circuits within a functional range. In the absence of homeostatic plasticity neuronal activity is prone to be destabilized because Hebbian plasticity mechanisms induce positive feedback change. Several studies on homeostatic plasticity assumed the existence of a process for monitoring neuronal activity on a time scale of hours and adjusting synaptic efficacy by scaling up and down. However, the underlying mechanism still remains unclear. Excitatory synaptic efficacy is associated with the size of the dendritic spine, and dendritic spine size fluctuates even after neuronal activity is silenced. These fluctuations could be a non-Hebbian form of synaptic plasticity that serves such a homeostatic function. This study proposed and analyzed a synaptic plasticity model incorporating random fluctuations and soft-bounded Hebbian plasticity at excitatory synapses, and found that the proposed model can prevent excessive changes in neuronal activity by scaling synaptic efficacy up and down. Soft-bounded Hebbian plasticity suppresses strong synapses, thereby scaling synapses down and preventing runaway excitation. Random fluctuations diffuse synaptic efficacy, thereby scaling synapses up and preventing neurons from falling silent. The proposed model acts as a form of homeostatic plasticity, regardless of neuronal activity monitoring. [ABSTRACT FROM AUTHOR]

Synaptic connections in the nervous system are rearranged during development and in adulthood as a feature of growth, plasticity, aging, and disease. Glia are implicated as active participants in these changes. Here we investigated a signal that controls the participation of peripheral glia, the terminal Schwann cells (SCs), at the neuromuscular junction (NMJ) in mice. Transgenic manipulation of the levels of membrane-tethered neuregulin1 (NRG1-III), a potent activator of SCs normally presented on motor axons, alters the rate of loss of motor inputs at NMJs during developmental synapse elimination. In addition, NMJs of adult transgenic mice that expressed excess axonal NRG1-III exhibited continued remodeling, in contrast to the more stable morphologies of controls. In fact, synaptic SCs of these adult mice with NRG1-III overexpression exhibited behaviors evident in wild type neonates during synapse elimination, including an affinity for the postsynaptic myofiber surface and phagocytosis of nerve terminals. Given that levels of NRG1-III expression normally peak during the period of synapse elimination, our findings identify axon-tethered NRG1 as a molecular determinant for SC-driven neuromuscular synaptic plasticity. [ABSTRACT FROM AUTHOR]

The amygdala is known to modulate hippocampal synaptic plasticity. One role could be an immediate effect of basolateral amygdala (BLA) in priming synaptic plasticity in the hippocampus. Another role could be through associative synaptic co-operation and competition that triggers events involved in the maintenance of synaptic potentiation. We present evidence that the timing and activity level of BLA stimulation are important factors for the induction and maintenance of long-term potentiation (LTP) in ventral hippocampal area CA1. A 100 Hz BLA co-stimulation facilitated the induction of LTP, whereas 200 Hz co-stimulation attenuated induction. A 100 Hz BLA co-stimulation also caused enhanced persistence, sufficient to prevent synaptic competition. This maintenance effect is likely through translational mechanisms, as mRNA expression of primary response genes was unaffected, whereas protein level of plasticity-related products was increased. Further understanding of the neural mechanisms of amygdala modulation on hippocampus could provide insights into the mechanisms of emotional disorders., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Synaptic circuits are highly sensitive to sensory experience during a critical period in early development. The maturation of GABA inhibition in the visual cortex is suggested to be required for both the onset and closure of the critical period for ocular dominance (OD) plasticity, although the underlying mechanism is unclear. This study examines a model of a visual cortical cell to investigate the mechanism by which inhibitory pathway regulates OD plasticity, through the competition between the groups of correlated inputs from two eyes. We show that when feedforward inhibition is at a low level, the activity-dependent competition does not arise. In the lack of competition, synaptic dynamics are monostable, which prevents the sensory experience to be embedded into synaptic weights. When the feedforward inhibition becomes greater than a threshold, the competitive interaction segregates the input groups into dominant and recessive ones. In this case, the synaptic dynamics become bistable, which provides the synaptic pattern with the ability to reflect sensory experience, opening the critical period. When the feedforward inhibition is further increased, a strong stability of synaptic patterns makes it difficult to change according to input stimuli. Therefore, it becomes difficult again for the synaptic weights to reflect the information about sensory stimuli, closing the critical period. Our hypothesis suggests that the start and end of critical period plasticity may be explained by the competitive dynamics of synapses, which is modulated by the feedforward inhibition. [ABSTRACT FROM AUTHOR]

Abstract: It has been suggested that non-spatial and spatial pieces of information are transmitted to the dentate gyrus from entorhinal cortex layer II through the lateral and medial perforant paths (LPP and MPP), which establish synapses on granule cell dendrites in the outer and middle one-thirds of the dentate molecular layer, respectively. In the present paper, we first investigated cooperation and competition between MPP and LPP synapses being subject to STDP rules, using a four-compartmental granule cell model. MPP and LPP were stimulated simultaneously by periodic and random pulse trains, respectively. Both synapses were gradually enhanced by cooperation between those synapses in the early stage, and then either the MPP or the LPP synapse was rapidly enhanced through synaptic competition in the following stage, depending on their initial synaptic conductances. The dominant cause of synaptic competition is that the distance between the MPP synapse and the soma is shorter than that between the LPP synapse and the soma. These results suggest that the LPP and MPP synapses tend to be enhanced in the dentate supra- and infrapyramidal blades, respectively, taking account of the thickness of each of the LPP and MPP fiber laminae in the blades. The dentate gyrus may select spatial and non-spatial pieces of information through synaptic cooperation, and may open a gate for each piece of information through synaptic competition. Then we investigated the role of inhibitory local circuits in synaptic competition in the dentate gyrus. The feed-forward GABA B inhibition suppressed unusual high-frequency firing of the granule cell, and consequently prevented excessive synaptic depression due to synaptic competition through STDP. The feed-forward and feedback GABA A inhibitions tend to reduce synaptic conductance fluctuations resulting from large increments and decrements due to very small spike-timings happening occasionally. [Copyright &y& Elsevier]

The maturation of cortical circuits is strongly influenced by sensory experience during a restricted critical period. The developmental alteration in the subunit composition of NMDA receptors (NMDARs) has been suggested to be involved in regulating the timing of such plasticity. However, this hypothesis does not explain the evidence that enhancing GABA inhibition triggers a critical period in the visual cortex. Here, to investigate how the NMDAR and GABA functions influence synaptic organization, we examine an spike-timing-dependent plasticity (STDP) model that incorporates the dynamic modulation of LTP, associated with the activity- and subunit-dependent desensitization of NMDARs, as well as the background inhibition by GABA. We show that the competitive interaction between correlated input groups, required for experience-dependent synaptic modifications, may emerge when both the NMDAR subunit expression and GABA inhibition reach a sufficiently mature state. This may suggest that the cooperative action of these two developmental mechanisms can contribute to embedding the spatiotemporal structure of input spikes in synaptic patterns and providing the trigger for experience-dependent cortical plasticity. [ABSTRACT FROM AUTHOR]

Spike-timing-dependent plasticity (STDP) induces competition among inputs, which is required for the construction of functional neuronal circuits, while maintaining the basic features of Hebbian plasticity. Here, we theoretically examine the competitive function of STDP incorporating a metaplastic activity-dependent feedback (ADFB) mechanism, wherein higher postsynaptic activity suppresses LTP, in cases where a neuron receives two groups of correlated inputs. We demonstrate that there are four distinct types of competitive properties depending on the relative input frequency between the different groups and the correlation time among the inputs within the same group. (1) Competition with a bi-stable synaptic weight distribution (for identical frequencies and brief correlation). (2) No competition (for identical frequencies and prolonged correlation). (3) Competition preferring strong input activity (for different frequencies and brief correlation).(4) Competition preferring weak input activity (for different frequencies and prolonged correlation). This may suggest that ADFB regulation can modulate the Hebbian competition properties associated with STDP to increase its ability to reflect input firing properties. [ABSTRACT FROM AUTHOR]

Abstract: Spike-timing-dependent plasticity (STDP) has been suggested to play a role in the development of functional neuronal connections. However, for STDP to contribute to the synaptic organization, its learning curve should satisfy a requirement that the magnitude of long-term potentiation (LTP) is approximately the same as that of long-term depression (LTD). Without such balance between LTP and LTD, all the synapses are potentiated toward the upper limit or depressed toward the lower limit. Therefore, in this study, we explore the mechanisms by which the LTP/LTD balance in STDP can be modulated adequately. We examine a plasticity model that incorporates an activity-dependent feedback (ADFB) mechanism, wherein LTP induction is suppressed by higher postsynaptic activity. In this model, strengthening an ADFB function gradually decreases the temporal average of the ratio of the magnitude of LTP to that of LTD, whereas enhancing background inhibition augments this ratio. Additionally, correlated inputs can be strengthened or weakened depending on whether the correlation time is shorter or longer than a threshold value, respectively, suggesting that STDP may lead to either Hebbian or anti-Hebbian plasticity outcomes. At an intermediate range of correlation times, the reversal between the two distinct plasticity regimes can occur by changing the level of ADFB modulation and inhibition, providing a physiological mechanism for neurons to select from functionally different forms of learning rules. [Copyright &y& Elsevier]

Abstract: The largest part of information passed among neurons in the brain occurs by the means of chemical synapses connecting the axons of presynaptic neurons to the dendritic tree of the postsynaptic ones. In the present paper, the most relevant open problems related to the mechanisms of control of the information passing among neurons by synaptic transmission will be shortly reviewed. The “cross talking” between synapses, their mutual interactions and the control of the information flow between different areas of the dendritic tree will be also considered. The threshold mechanism based on the “reversal potential” will be considered for its role in the control of information transfer among neurons and also for its contribution to the information flow among different areas of the dendritic tree and to the computational ability of the single neuron. The concept of “competition for plasticity” will be proposed as a mechanism of competition based on the synaptic activation time. [Copyright &y& Elsevier]

Differential classical conditioning of the gill-withdrawal response (GWR) in Aplysia can be elicited by training in which a conditioned stimulus (CS) delivered to one side of the siphon (the CS+) is paired with a noxious unconditioned stimulus (US; tail shock), while a second conditioned stimulus (the CS-), delivered to a different siphon site, is unpaired with the US. NMDA receptor (NMDAR) activation has been shown previously to be critical for nondifferential classical conditioning in Aplysia. Here, we used a semi-intact preparation to test whether differential classical conditioning of the GWR also depends on activation of NMDARs. Differential training produced conditioned enhancement of the reflexive response to the CS+ and a reduction in the response to the CS-. Comparison of the results after differential training with those after training in which only the two CSs were presented (CS-alone experiments) indicated that the decrement in the response to CS- after differential training was not caused by habituation. Surprisingly, differential training in the NMDAR antagonist APV (DL-2-amino-5-phosphonovalerate) blocked not only the conditioned enhancement of the GWR, but also the conditioning-induced depression of the GWR. We suggest that differential conditioning involves an NMDAR-dependent, competitive interaction between the separate neural pathways activated by the CS+ and CS-. [ABSTRACT FROM AUTHOR]

Male and female rats underwent unilateral naris occlusion or sham surgery on either post-natal day (PN) 1 or after PN30. Following at least 30 days of unilateral olfactory deprivation, rats were urethane anesthetized and recordings were made from anterior piriform cortex (aPCX). Shock stimulation of afferent fibers (lateral olfactory tract) and association/commissural fibers evoked field potentials in aPCX that were analyzed across groups and between ages. The results demonstrate that early-onset unilateral olfactory deprivation depresses field potentials evoked by stimulation of the deprived cortical afferent, while late-onset deprivation did not. In contrast, intracortical association fiber mediated field potentials in the deprived cortex were enhanced after both early-onset and late-onset deprivation. These results suggest differential developmental plasticity of afferent and association fiber pathways in paleocortex that mirrors that previously described in neocortical sensory systems. [Copyright &y& Elsevier]

The distribution of anterogradely transported radioactivity in the ipsilateral associational and commissural afferents to the dentate gyrus, after injections of H-proline into the hilar region, has been analyzed in light and electron microscopic autoradiographs of adjoining semi-thin and ultrathin sections, respectively. In the inner third of the molecular layer, in which the two classes of afferents terminate, between 57% and 69% of the label was found over fine preterminal axons and presynaptic profiles; the remaining radioactivity was about equally distributed between dendritic profiles and other tissue components (mainly glial processes). Estimates of the relative numbers of grains within the peak region of labeling over the molecular layer of the supra- and infrapyramidal blades in the LM and EM autoradiographs (what we have termed the supra: infrapyramidal ratio) are surprisingly close despite appreciable differences in the absolute number of grains in different experiments. This suggests that in selected systems grain density estimates of this type can provide an accurate indication of the relative numbers of axons and axon terminals derived from the labeled projection systems, at least if the analyses are carried out on the same autoradiographs. Our results provide evidence for the assumption underlying the so-called temporal competition hypothesis (Gottlieb and Cowan 1972) and the report of a re-organization that occurs in the distribution of the associational afferents after hippocampal comminssurotomy (O'Leary et al. 1980). [ABSTRACT FROM AUTHOR]

Following the injection of a small amount of a labeled amino acid into the hilar region of the dentate gyrus in normal rats, the numbers of silver grains over the supra- and infrapyramidal blades of the dentate gyrus seen in autoradiograms taken at more rostral levels (due to axonal transport in the ipsilateral hippocampo-dentate associational fibers to the inner part of the molecular layer) show a fairly consistent ratio of about 2:1. If the commissural fibers to the same zone (from the hilar region of the contralateral side) are prevented from reaching the dentate gyrus by ablating the contralateral hippocampus and fimbria on the day after birth the corresponding ratio of silver grains is close to 1:1. On the reasonable assumption that the relative numbers of silver grains observed in this type of experiment bear some constant relationship to the relative numbers of labeled axon terminals, these findings suggest that in the absence of commissural afferents, the associational fibers are distributed more-or-less uniformly throughout the 'hippocampal zone' of the molecular layer. The simplest interpretation of this is that the associational and commissural afferents normally compete with each other for the available synaptic sites in the hippocampal zone (and especially in the infrapyramidal blade of the dentate gyrus) as postulated by Gottlieb and Cowan (1972), and that when the associational afferents do not have to compete with the commissural fibers, they occupy all the available synaptic sites. [ABSTRACT FROM AUTHOR]

The acquisition of fear memories involves plasticity of the thalamic and cortical pathways to the lateral amygdala (LA). In turn, the maintenance of synaptic plasticity requires the interplay between input-specific synaptic tags and the allocation of plasticity-related proteins. Based on this interplay, weakly activated synapses can express long-lasting forms of synaptic plasticity by cooperating with strongly activated synapses. Increasing the number of activated synapses can shift cooperation to competition. Synaptic cooperation and competition can determine whether two events, separated in time, are associated or whether a particular event is selected for storage. The rules that determine whether synapses cooperate or compete are unknown. We found that synaptic cooperation and competition, in the LA, are determined by the temporal sequence of cortical and thalamic stimulation and that the strength of the synaptic tag is modulated by the endocannabinoid signaling. This modulation is particularly effective in thalamic synapses, supporting a critical role of endocannabinoids in restricting thalamic plasticity. Also, we found that the availability of synaptic proteins is activity-dependent, shifting competition to cooperation. Our data present the first evidence that presynaptic modulation of synaptic activation, by the cannabinoid signaling, functions as a temporal gating mechanism limiting synaptic cooperation and competition., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)