The dialectic of Hebb and homeostasis

Neuronal guidance signaling in neurodegenerative diseases: Key regulators that function at neuron-glia and neuroimmune interfaces

The nervous system processes a vast amount of information, performing computations that underlie perception, cognition, and behavior. During development, neuronal guidance genes, which encode extracellular cues, their receptors, and downstream signal transducers, organize neural wiring to generate the complex architecture of the nervous system. It is now evident that many of these neuroguidance cues and their receptors are active during development and are also expressed in the adult nervous system. This suggests that neuronal guidance pathways are critical not only for neural wiring but also for ongoing function and maintenance of the mature nervous system. Supporting this view, these pathways continue to regulate synaptic connectivity, plasticity, and remodeling, and overall brain homeostasis throughout adulthood. Genetic and transcriptomic analyses have further revealed many neuronal guidance genes to be associated with a wide range of neurodegenerative and neuropsychiatric disorders. Although the precise mechanisms by which aberrant neuronal guidance signaling drives the pathogenesis of these diseases remain to be clarified, emerging evidence points to several common themes, including dysfunction in neurons, microglia, astrocytes, and endothelial cells, along with dysregulation of neuron-microglia-astrocyte, neuroimmune, and neurovascular interactions. In this review, we explore recent advances in understanding the molecular and cellular mechanisms by which aberrant neuronal guidance signaling contributes to disease pathogenesis through altered cell-cell interactions. For instance, recent studies have unveiled two distinct semaphorin-plexin signaling pathways that affect microglial activation and neuroinflammation. We discuss the challenges ahead, along with the therapeutic potentials of targeting neuronal guidance pathways for treating neurodegenerative diseases. Particular focus is placed on how neuronal guidance mechanisms control neuron-glia and neuroimmune interactions and modulate microglial function under physiological and pathological conditions. Specifically, we examine the crosstalk between neuronal guidance signaling and TREM2, a master regulator of microglial function, in the context of pathogenic protein aggregates. It is well-established that age is a major risk factor for neurodegeneration. Future research should address how aging and neuronal guidance signaling interact to influence an individual's susceptibility to various late-onset neurological diseases and how the progression of these diseases could be therapeutically blocked by targeting neuronal guidance pathways.

GluA2-containing AMPA receptors form a continuum of Ca2+-permeable channels

Fast excitatory neurotransmission in the mammalian brain is mediated by cation-selective AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) receptors (AMPARs)1. AMPARs are critical for the learning and memory mechanisms of Hebbian plasticity2 and glutamatergic synapse homeostasis3, with recent work establishing that AMPAR missense mutations can cause autism and intellectual disability4-7. AMPARs have been grouped into two functionally distinct tetrameric assemblies based on the inclusion or exclusion of the GluA2 subunit that determines Ca2+ permeability through RNA editing8,9. GluA2-containing AMPARs are the most abundant in the central nervous system and considered to be Ca2+ impermeable10. Here we show this is not the case. Contrary to conventional understanding, GluA2-containing AMPARs form a continuum of polyamine-insensitive ion channels with varying degrees of Ca2+ permeability. Their ability to transport Ca2+ is shaped by the subunit composition of AMPAR tetramers as well as the spatial orientation of transmembrane AMPAR regulatory proteins and cornichon auxiliary subunits. Ca2+ crosses the ion-conduction pathway by docking to an extracellular binding site that helps funnel divalent ions into the pore selectivity filter. The dynamic range in Ca2+ permeability, however, arises because auxiliary subunits primarily modify the selectivity filter. Taken together, our work proposes a broader role for AMPARs in Ca2+ signalling in the mammalian brain and offers mechanistic insight into the pathogenic nature of missense mutations.

Regulation of PV interneuron plasticity by neuropeptide-encoding genes

Neuronal activity must be regulated in a narrow permissive band for the proper operation of neural networks. Changes in synaptic connectivity and network activity-for example, during learning-might disturb this balance, eliciting compensatory mechanisms to maintain network function1-3. In the neocortex, excitatory pyramidal cells and inhibitory interneurons exhibit robust forms of stabilizing plasticity. However, although neuronal plasticity has been thoroughly studied in pyramidal cells4-8, little is known about how interneurons adapt to persistent changes in their activity. Here we describe a critical cellular process through which cortical parvalbumin-expressing (PV+) interneurons adapt to changes in their activity levels. We found that changes in the activity of individual PV+ interneurons drive bidirectional compensatory adjustments of the number and strength of inhibitory synapses received by these cells, specifically from other PV+ interneurons. High-throughput profiling of ribosome-associated mRNA revealed that increasing the activity of a PV+ interneuron leads to upregulation of two genes encoding multiple secreted neuropeptides: Vgf and Scg2. Functional experiments demonstrated that VGF is critically required for the activity-dependent scaling of inhibitory PV+ synapses onto PV+ interneurons. Our findings reveal an instructive role for neuropeptide-encoding genes in regulating synaptic connections among PV+ interneurons in the adult mouse neocortex.

The interplay between Hebbian and homeostatic plasticity in the adult visual cortex

Homeostatic and Hebbian plasticity co-operate during the critical period, refining neuronal circuits; however, the interaction between these two forms of plasticity is still unclear, especially in adulthood. Here, we directly investigate this issue in adult humans using two consolidated paradigms to elicit each form of plasticity in the visual cortex: the long-term potentiation-like change of the visual evoked potential (VEP) induced by high-frequency stimulation (HFS) and the shift of ocular dominance induced by short-term monocular deprivation (MD). We tested homeostatic and Hebbian plasticity independently, then explored how they interacted by inducing them simultaneously in a group of adult healthy volunteers. We successfully induced both forms of plasticity: 60 min of MD induced a reliable change in ocular dominance and HFS reliably modulated the amplitude of the P1 component of the VEP. Importantly, we found that, across participants, homeostatic and Hebbian plasticity were negatively correlated, indicating related neural mechanisms, potentially linked to intracortical excitation/inhibition balance. On the other hand, we did not find an interaction when the two forms of plasticity were induced simultaneously. Our results indicate a largely preserved plastic potential in the visual cortex of the adult brain, for both short-term homeostatic and Hebbian plasticity. Crucially, we show for the first time a direct relationship between these two forms of plasticity in the adult human visual cortex, which could inform future research and treatment protocols for neurological diseases. KEY POINTS: Homeostatic and Hebbian plasticity co-operate during the critical period to refine neuronal circuits in the visual cortex. The interaction between these two forms of plasticity is still unknown, especially after the closure of the critical periods and in humans. We directly investigate the interplay between Hebbian and homeostatic visual plasticity in adult humans using non-invasive paradigms. We found a negative correlation between these forms of plasticity showing for the first time a direct relationship between Hebbian and homeostatic plasticity. Our results could inform future research and treatment protocols for neurological diseases.

Adaptive Synaptic Scaling in Spiking Networks for Continual Learning and Enhanced Robustness

Synaptic plasticity plays a critical role in the expression power of brain neural networks. Among diverse plasticity rules, synaptic scaling presents indispensable effects on homeostasis maintenance and synaptic strength regulation. In the current modeling of brain-inspired spiking neural networks (SNN), backpropagation through time is widely adopted because it can achieve high performance using a small number of time steps. Nevertheless, the synaptic scaling mechanism has not yet been well touched. In this work, we propose an experience-dependent adaptive synaptic scaling mechanism (AS-SNN) for spiking neural networks. The learning process has two stages: First, in the forward path, adaptive short-term potentiation or depression is triggered for each synapse according to afferent stimuli intensity accumulated by presynaptic historical neural activities. Second, in the backward path, long-term consolidation is executed through gradient signals regulated by the corresponding scaling factor. This mechanism shapes the pattern selectivity of synapses and the information transfer they mediate. We theoretically prove that the proposed adaptive synaptic scaling function follows a contraction map and finally converges to an expected fixed point, in accordance with state-of-the-art results in three tasks on perturbation resistance, continual learning, and graph learning. Specifically, for the perturbation resistance and continual learning tasks, our approach improves the accuracy on the N-MNIST benchmark over the baseline by 44% and 25%, respectively. An expected firing rate callback and sparse coding can be observed in graph learning. Extensive experiments on ablation study and cost evaluation evidence the effectiveness and efficiency of our nonparametric adaptive scaling method, which demonstrates the great potential of SNN in continual learning and robust learning.

Repetitive magnetic stimulation with iTBS600 induces persistent structural and functional plasticity in mouse organotypic slice cultures

Background

Repetitive transcranial magnetic stimulation (rTMS) is well known for its ability to induce synaptic plasticity, yet its impact on structural and functional remodeling within stimulated networks remains unclear. This study investigates the cellular and network-level mechanisms of rTMS-induced plasticity using a clinically approved 600-pulse intermittent theta burst stimulation (iTBS600) protocol applied to organotypic brain tissue cultures.

Methods

We applied iTBS600 to entorhino-hippocampal organotypic tissue cultures and conducted a 24-hour analysis using c-Fos immunostaining, whole-cell patch-clamp recordings, time-lapse imaging of dendritic spines, and calcium imaging.

Results

We observed long-term potentiation (LTP) of excitatory synapses in dentate granule cells, characterized by increased mEPSC frequencies and spine remodeling over time. c-Fos expression in the dentate gyrus was transient and exhibited a clear sensitivity to the orientation of the induced electric field, suggesting a direction-dependent induction of plasticity. Structural remodeling of dendritic spines was temporally linked to enhanced synaptic strength, while spontaneous firing rates remained stable during the early phase in the dentate gyrus, indicating the engagement of homeostatic mechanisms. Despite the widespread electric field generated by rTMS, its effects were spatially and temporally precise, driving Hebbian plasticity and region-specific spine dynamics.

Conclusions

These findings provide mechanistic insights into how rTMS-induced LTP promotes targeted plasticity while preserving network stability. Understanding these interactions may help refine stimulation protocols to optimize therapeutic outcomes.

Increased robustness and adaptation to simultaneous temperature and elevated extracellular potassium in the pyloric rhythm of the crab, Cancer borealis

Animals must deal with numerous perturbations, oftentimes concurrently. In this study, we examine the effects of two perturbations, high extracellular potassium and elevated temperature, on the resilience of the pyloric rhythm of the crab, Cancer borealis. At control temperatures (11°C), high potassium saline (2.5× K+) depolarizes the neurons of the stomatogastric ganglion (STG), and the pyloric rhythm becomes quiescent. Over minutes, while remaining depolarized in high potassium, the pyloric network neurons adapt, and resume their spiking and bursting activity. We compared adaptation to high potassium applications at 20°C to those seen at 11°C. At 20°C, the intracellular waveforms of the neuronal activity seen in high potassium more closely resemble activity in control saline, and adaptation and recovery occur more rapidly. Spike and burst thresholds were measured using slow ramps of injected current from hyperpolarized to depolarized values of membrane potential in the presence of high potassium and at both temperatures. The maximal burst frequencies in control saline were higher at 20°C and subthreshold bursts occurred at a more hyperpolarized membrane potential at 20°C. In high potassium, subthreshold bursts were seen at 20°C, but not at 11°C, whereas spike thresholds were similar at the two temperatures. At both temperatures, a second application of high potassium showed substantially more rapid adaptation than did the first application. Together, these data show that the adaptation to high potassium saline is enhanced by high temperature.NEW & NOTEWORTHY Multiple applications of high potassium saline to the pyloric rhythm of the crab, Cancer borealis show a history-dependent adaptation process that is enhanced at high temperatures.

Regulation of presynaptic homeostatic plasticity by glial signalling in Alzheimer's disease

Alzheimer's disease (AD), the most common form of dementia among the elderly, affects numerous individuals worldwide. Despite advances in understanding the molecular underpinnings of AD pathology, effective treatments to prevent or cure the disease remain elusive. AD is characterized not only by pathological hallmarks such as amyloid plaques and neurofibrillary tangles but also by impairments in synaptic physiology, circuit activity and cognitive function. Synaptic homeostatic plasticity plays a vital role in maintaining the stability of synaptic and neural functions amid genetic and environmental disturbances. A key component of this regulation is presynaptic homeostatic potentiation, where increased presynaptic neurotransmitter release compensates for reduced postsynaptic glutamate receptor functionality, thereby stabilizing neuronal excitability. The role of presynaptic homeostatic plasticity in synapse stabilization in AD, however, remains unclear. Moreover, recent advances in transcriptomics have illuminated the complex roles of glial cells in regulating synaptic function in ageing brains and in the progression of neurodegenerative diseases. Yet, the impact of AD-related abnormalities in glial signalling on synaptic homeostatic plasticity has not been fully delineated. This review discusses recent findings on how glial dysregulation in AD affects presynaptic homeostatic plasticity. There is increasing evidence that disrupted glial signalling, particularly through aberrant histone acetylation and transcriptomic changes in glia, compromises this plasticity in AD. Notably, the sphingosine signalling pathway has been identified as being protective in stabilizing synaptic physiology through epigenetic and homeostatic mechanisms, presenting potential therapeutic targets for treating neurodegenerative disorders.

Boosting Psychotherapy With Noninvasive Brain Stimulation: The Whys and Wherefores of Modulating Neural Plasticity to Promote Therapeutic Change

The phenomenon of neural plasticity pertains to the intrinsic capacity of neurons to undergo structural and functional reconfiguration through learning and experiential interaction with the environment. These changes could manifest themselves not only as a consequence of various life experiences but also following therapeutic interventions, including the application of noninvasive brain stimulation (NIBS) and psychotherapy. As standalone therapies, both NIBS and psychotherapy have demonstrated their efficacy in the amelioration of psychiatric disorders' symptoms, with a certain variability in terms of effect sizes and duration. Consequently, scholars suggested the convenience of integrating the two interventions into a multimodal treatment to boost and prolong the therapeutic outcomes. Such an approach is still in its infancy, and the physiological underpinnings substantiating the effectiveness and utility of combined interventions are still to be clarified. Therefore, this opinion paper aims to provide a theoretical framework consisting of compelling arguments as to why adding NIBS to psychotherapy can promote therapeutic change. Namely, we will discuss the physiological effects of the two interventions, thus providing a rationale to explain the potential advantages of a combined approach.

Efficient value synthesis in the orbitofrontal cortex explains how loss aversion adapts to the ranges of gain and loss prospects

Is irrational behavior the incidental outcome of biological constraints imposed on neural information processing? In this work, we consider the paradigmatic case of gamble decisions, where gamble values integrate prospective gains and losses. Under the assumption that neurons have a limited firing response range, we show that mitigating the ensuing information loss within artificial neural networks that synthetize value involves a specific form of self-organized plasticity. We demonstrate that the ensuing efficient value synthesis mechanism induces value range adaptation. We also reveal how the ranges of prospective gains and/or losses eventually determine both the behavioral sensitivity to gains and losses and the information content of the network. We test these predictions on two fMRI datasets from the OpenNeuro.org initiative that probe gamble decision-making but differ in terms of the range of gain prospects. First, we show that peoples' loss aversion eventually adapts to the range of gain prospects they are exposed to. Second, we show that the strength with which the orbitofrontal cortex (in particular: Brodmann area 11) encodes gains and expected value also depends upon the range of gain prospects. Third, we show that, when fitted to participant's gambling choices, self-organizing artificial neural networks generalize across gain range contexts and predict the geometry of information content within the orbitofrontal cortex. Our results demonstrate how self-organizing plasticity aiming at mitigating information loss induced by neurons' limited response range may result in value range adaptation, eventually yielding irrational behavior.

Glutamate Signaling and Neuroligin/Neurexin Adhesion Play Opposing Roles That Are Mediated by Major Histocompatibility Complex I Molecules in Cortical Synapse Formation

Although neurons release neurotransmitter before contact, the role for this release in synapse formation remains unclear. Cortical synapses do not require synaptic vesicle release for formation (Verhage et al., 2000; Sando et al., 2017; Sigler et al., 2017; Held et al., 2020), yet glutamate clearly regulates glutamate receptor trafficking (Roche et al., 2001; Nong et al., 2004) and induces spine formation (Engert and Bonhoeffer, 1999; Maletic-Savatic et al., 1999; Toni et al., 1999; Kwon and Sabatini, 2011; Oh et al., 2016). Using rat and murine culture systems to dissect molecular mechanisms, we found that glutamate rapidly decreases synapse density specifically in young cortical neurons in a local and calcium-dependent manner through decreasing N-methyl-d-aspartate receptor (NMDAR) transport and surface expression as well as cotransport with neuroligin (NL1). Adhesion between NL1 and neurexin 1 protects against this glutamate-induced synapse loss. Major histocompatibility I (MHCI) molecules are required for the effects of glutamate in causing synapse loss through negatively regulating NL1 levels in both sexes. Thus, like acetylcholine at the neuromuscular junction, glutamate acts as a dispersal signal for NMDARs and causes rapid synapse loss unless opposed by NL1-mediated trans-synaptic adhesion. Together, glutamate, MHCI, and NL1 mediate a novel form of homeostatic plasticity in young neurons that induces rapid changes in NMDARs to regulate when and where nascent glutamatergic synapses are formed.

KATP channel mutation disrupts hippocampal network activity and nocturnal gamma shifts

ATP-sensitive potassium (KATP) channels couple cell metabolism to cellular electrical activity. Humans affected by severe activating mutations in KATP channels suffer from developmental delay, epilepsy and neonatal diabetes (DEND syndrome). While the aetiology of diabetes in DEND syndrome is well understood, the pathophysiology of the neurological symptoms remains unclear. We hypothesized that impaired activity of parvalbumin-positive interneurons (PV-INs) may result in seizures and cognitive problems. We found, by performing electrophysiological experiments, that expressing the DEND mutation Kir6.2-V59M selectively in mouse PV-INs reduced intrinsic gamma frequency preference and short-term depression as well as disturbed cognition-associated gamma oscillations and hippocampal sharp waves. Furthermore, the risk of seizures was increased and the day-night shift in gamma activity disrupted. Blocking KATP channels with tolbutamide partially rescued the network oscillations. The non-reversible part may, to some extent, result from observed altered PV-IN dendritic branching and PV-IN arrangement within CA1. In summary, PV-INs play a key role in DEND syndrome, and this provides a framework for establishing treatment options.

Homeostatic regulation of brain activity: from endogenous mechanisms to homeostatic nanomachines

After the initial concepts of the constancy of the internal milieu or homeostasis, put forward by Claude Bernard and Walter Cannon, homeostasis emerged as a mechanism to control oscillations of biologically meaningful variables within narrow physiological ranges. This is a primary need in the central nervous system that is continuously subjected to a multitude of stimuli from the internal and external environments that affect its function and structure, allowing to adapt the individual to the ever-changing daily conditions. Preserving physiological levels of activity despite disturbances that could either depress neural computation or excessively stimulate neural activity is fundamental, and failure of these homeostatic mechanisms can lead to brain diseases. In this review, we cover the role and main mechanisms of homeostatic plasticity involving the regulation of excitability and synaptic strength from the single neuron to the network level. We analyze the relationships between homeostatic and Hebbian plasticity and the conditions under which the preservation of the excitatory/inhibitory balance fails, triggering epileptogenesis and eventually epilepsy. Several therapeutic strategies to cure epilepsy have been designed to strengthen homeostasis when endogenous homeostatic plasticity mechanisms have become insufficient or ineffective to contrast hyperactivity. We describe "on demand" gene therapy strategies, including optogenetics, chemogenetics, and chemo-optogenetics, and particularly focus on new closed loop sensor-actuator strategies mimicking homeostatic plasticity that can be endogenously expressed to strengthen the homeostatic defenses against brain diseases.

Age-Related Homeostatic Plasticity at Rodent Neuromuscular Junctions

Motor ability decline remains a major threat to the quality of life of the elderly. Although the later stages of aging co-exist with degenerative pathologies, the long process of aging is more complicated than a simple and gradual degeneration. To combat senescence and the associated late-stage degeneration of the neuromuscular system, it is imperative to examine changes that occur during the long process of aging. Prior to late-stage degeneration, age-induced changes in the neuromuscular system trigger homeostatic plasticity. This unique phenomenon may be important for the maintenance of the neuromuscular system during the early stages of aging. In this review, we will focus on age-induced changes in neurotransmission at the neuromuscular junction, providing the potential mechanisms responsible for these changes. The goal is to highlight these key elements and their role in regulating neurotransmission, facilitating future research efforts to combat late-stage degeneration in the neuromuscular system by preserving the functional and structural integrity of these elements prior to the late stage of aging.

The synaptic vesicle cluster as a controller of pre- and postsynaptic structure and function

The synaptic vesicle cluster (SVC) is an essential component of chemical synapses, which provides neurotransmitter-loaded vesicles during synaptic activity, at the same time as also controlling the local concentrations of numerous exo- and endocytosis cofactors. In addition, the SVC hosts molecules that participate in other aspects of synaptic function, from cytoskeletal components to adhesion proteins, and affects the location and function of organelles such as mitochondria and the endoplasmic reticulum. We argue here that these features extend the functional involvement of the SVC in synapse formation, signalling and plasticity, as well as synapse stabilization and metabolism. We also propose that changes in the size of the SVC coalesce with changes in the postsynaptic compartment, supporting the interplay between pre- and postsynaptic dynamics. Thereby, the SVC could be seen as an 'all-in-one' regulator of synaptic structure and function, which should be investigated in more detail, to reveal molecular mechanisms that control synaptic function and heterogeneity.

Daily light-induced transcription in visual cortex neurons drives downward firing rate homeostasis and stabilizes sensory processing

Balancing plasticity and stability in neural circuits is essential for an animal's ability to learn from its environment while preserving proper processing and perception of sensory information. However, unlike the mechanisms that drive plasticity in neural circuits, the activity-induced molecular mechanisms that convey functional stability remain poorly understood. Focusing on the visual cortex of adult mice and combining transcriptomics, electrophysiology, and in vivo calcium imaging, we find that the daily appearance of light induces, in excitatory neurons, a large gene program along with rapid and transient increases in the ratio of excitation and inhibition (E/I ratio) and neural activity. Furthermore, we find that the light-induced transcription factor NPAS4 drives these daily normalizations of the E/I ratio and neural activity rates and that it stabilizes the neurons' response properties. These findings indicate that daily sensory-induced transcription normalizes the E/I ratio and drives downward firing rate homeostasis to maintain proper sensory processing and perception.

Keeping Your Brain in Balance: Homeostatic Regulation of Network Function

To perform computations with the efficiency necessary for animal survival, neocortical microcircuits must be capable of reconfiguring in response to experience, while carefully regulating excitatory and inhibitory connectivity to maintain stable function. This dynamic fine-tuning is accomplished through a rich array of cellular homeostatic plasticity mechanisms that stabilize important cellular and network features such as firing rates, information flow, and sensory tuning properties. Further, these functional network properties can be stabilized by different forms of homeostatic plasticity, including mechanisms that target excitatory or inhibitory synapses, or that regulate intrinsic neuronal excitability. Here we discuss which aspects of neocortical circuit function are under homeostatic control, how this homeostasis is realized on the cellular and molecular levels, and the pathological consequences when circuit homeostasis is impaired. A remaining challenge is to elucidate how these diverse homeostatic mechanisms cooperate within complex circuits to enable them to be both flexible and stable.

Network motifs in cellular neurophysiology

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

Co-existence of synaptic plasticity and metastable dynamics in a spiking model of cortical circuits

Evidence for metastable dynamics and its role in brain function is emerging at a fast pace and is changing our understanding of neural coding by putting an emphasis on hidden states of transient activity. Clustered networks of spiking neurons have enhanced synaptic connections among groups of neurons forming structures called cell assemblies; such networks are capable of producing metastable dynamics that is in agreement with many experimental results. However, it is unclear how a clustered network structure producing metastable dynamics may emerge from a fully local plasticity rule, i.e., a plasticity rule where each synapse has only access to the activity of the neurons it connects (as opposed to the activity of other neurons or other synapses). Here, we propose a local plasticity rule producing ongoing metastable dynamics in a deterministic, recurrent network of spiking neurons. The metastable dynamics co-exists with ongoing plasticity and is the consequence of a self-tuning mechanism that keeps the synaptic weights close to the instability line where memories are spontaneously reactivated. In turn, the synaptic structure is stable to ongoing dynamics and random perturbations, yet it remains sufficiently plastic to remap sensory representations to encode new sets of stimuli. Both the plasticity rule and the metastable dynamics scale well with network size, with synaptic stability increasing with the number of neurons. Overall, our results show that it is possible to generate metastable dynamics over meaningful hidden states using a simple but biologically plausible plasticity rule which co-exists with ongoing neural dynamics.

Enhanced Synaptic Inhibition in the Dorsolateral Geniculate Nucleus in a Mouse Model of Glaucoma

Elevated intraocular pressure (IOP) triggers glaucoma by damaging the output neurons of the retina called retinal ganglion cells (RGCs). This leads to the loss of RGC signaling to visual centers of the brain such as the dorsolateral geniculate nucleus (dLGN), which is critical for processing and relaying information to the cortex for conscious vision. In response to altered levels of activity or synaptic input, neurons can homeostatically modulate postsynaptic neurotransmitter receptor numbers, allowing them to scale their synaptic responses to stabilize spike output. While prior work has indicated unaltered glutamate receptor properties in the glaucomatous dLGN, it is unknown whether glaucoma impacts dLGN inhibition. Here, using DBA/2J mice, which develop elevated IOP beginning at 6-7 months of age, we tested whether the strength of inhibitory synapses on dLGN thalamocortical relay neurons is altered in response to the disease state. We found an enhancement of feedforward disynaptic inhibition arising from local interneurons along with increased amplitude of quantal inhibitory synaptic currents. A combination of immunofluorescence staining for the γ-aminobutyric acid (GABA)A-α1 receptor subunit, peak-scaled nonstationary fluctuation analysis, and measures of homeostatic synaptic scaling pointed to an ∼1.4-fold increase in GABA receptors at postsynaptic inhibitory synapses, although several pieces of evidence indicate a nonuniform scaling across inhibitory synapses within individual relay neurons. Together, these results indicate an increase in inhibitory synaptic strength in the glaucomatous dLGN, potentially pointing toward homeostatic compensation for disruptions in network and neuronal function triggered by increased IOP.

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.

Co-existence of synaptic plasticity and metastable dynamics in a spiking model of cortical circuits

Evidence for metastable dynamics and its role in brain function is emerging at a fast pace and is changing our understanding of neural coding by putting an emphasis on hidden states of transient activity. Clustered networks of spiking neurons have enhanced synaptic connections among groups of neurons forming structures called cell assemblies; such networks are capable of producing metastable dynamics that is in agreement with many experimental results. However, it is unclear how a clustered network structure producing metastable dynamics may emerge from a fully local plasticity rule, i.e., a plasticity rule where each synapse has only access to the activity of the neurons it connects (as opposed to the activity of other neurons or other synapses). Here, we propose a local plasticity rule producing ongoing metastable dynamics in a deterministic, recurrent network of spiking neurons. The metastable dynamics co-exists with ongoing plasticity and is the consequence of a self-tuning mechanism that keeps the synaptic weights close to the instability line where memories are spontaneously reactivated. In turn, the synaptic structure is stable to ongoing dynamics and random perturbations, yet it remains sufficiently plastic to remap sensory representations to encode new sets of stimuli. Both the plasticity rule and the metastable dynamics scale well with network size, with synaptic stability increasing with the number of neurons. Overall, our results show that it is possible to generate metastable dynamics over meaningful hidden states using a simple but biologically plausible plasticity rule which co-exists with ongoing neural dynamics.

Noise-induced hearing loss alters potassium-chloride cotransporter KCC2 and GABA inhibition in the auditory centers

Homeostatic plasticity, the ability of neurons to maintain their averaged activity constant around a set point value, is thought to account for the central hyperactivity after hearing loss. Here, we investigated the putative role of GABAergic neurotransmission in this mechanism after a noise-induced hearing loss larger than 50 dB in high frequencies in guinea pigs. The effect of GABAergic inhibition is linked to the normal functioning of K + -Cl- co-transporter isoform 2 (KCC2) which maintains a low intracellular concentration of chloride. The expression of membrane KCC2 were investigated before and after noise trauma in the ventral and dorsal cochlear nucleus (VCN and DCN, respectively) and in the inferior colliculus (IC). Moreover, the effect of gabazine (GBZ), a GABA antagonist, was also studied on the neural activity in IC. We show that KCC2 is downregulated in VCN, DCN and IC 3 days after noise trauma, and in DCN and IC 30 days after the trauma. As expected, GBZ application in the IC of control animals resulted in an increase of spontaneous and stimulus-evoked activity. In the noise exposed animals, on the other hand, GBZ application decreased the stimulus-evoked activity in IC neurons. The functional implications of these central changes are discussed.

Nonuniform scaling of synaptic inhibition in the dorsolateral geniculate nucleus in a mouse model of glaucoma

Elevated intraocular pressure (IOP) triggers glaucoma by damaging the output neurons of the retina called retinal ganglion cells (RGCs). This leads to the loss of RGC signaling to visual centers of the brain such as the dorsolateral geniculate nucleus (dLGN), which is critical for processing and relaying information to the cortex for conscious vision. In response to altered levels of activity or synaptic input, neurons can homeostatically modulate postsynaptic neurotransmitter receptor numbers, allowing them to scale their synaptic responses to stabilize spike output. While prior work has indicated unaltered glutamate receptor properties in the glaucomatous dLGN, it is unknown whether glaucoma impacts dLGN inhibition. Here, using DBA/2J mice, which develop elevated IOP beginning at 6-7 months of age, we tested whether the strength of inhibitory synapses on dLGN thalamocortical relay neurons is altered in response to the disease state. We found an enhancement of feed-forward disynaptic inhibition arising from local interneurons along with increased amplitude of quantal inhibitory synaptic currents. A combination of immunofluorescence staining for the GABA A -α1 receptor subunit, peak-scaled nonstationary fluctuation analysis, and measures of homeostatic synaptic scaling indicated this was the result of an approximately 1.4-fold increase in GABA receptor number at post-synaptic inhibitory synapses, although several pieces of evidence strongly indicate a non-uniform scaling across inhibitory synapses within individual relay neurons. Together, these results indicate an increase in inhibitory synaptic strength in the glaucomatous dLGN, potentially pointing toward homeostatic compensation for disruptions in network and neuronal function triggered by increased IOP.

Significance Statement

Elevated eye pressure in glaucoma leads to loss of retinal outputs to the dorsolateral geniculate nucleus (dLGN), which is critical for relaying information to the cortex for conscious vision. Alterations in neuronal activity, as could arise from excitatory synapse loss, can trigger homeostatic adaptations to synaptic function that attempt to maintain activity within a meaningful dynamic range, although whether this occurs uniformly at all synapses within a given neuron or is a non-uniform process is debated. Here, using a mouse model of glaucoma, we show that dLGN inhibitory synapses undergo non-uniform upregulation due to addition of post-synaptic GABA receptors. This is likely to be a neuronal adaptation to glaucomatous pathology in an important sub-cortical visual center.

Glutamate signaling and neuroligin/neurexin adhesion play opposing roles that are mediated by major histocompatibility complex I molecules in cortical synapse formation

Although neurons release neurotransmitter before contact, the role for this release in synapse formation remains unclear. Cortical synapses do not require synaptic vesicle release for formation 1-4 , yet glutamate clearly regulates glutamate receptor trafficking 5,6 and induces spine formation 7-11 . Using a culture system to dissect molecular mechanisms, we found that glutamate rapidly decreases synapse density specifically in young cortical neurons in a local and calcium-dependent manner through decreasing NMDAR transport and surface expression as well as co-transport with neuroligin (NL1). Adhesion between NL1 and neurexin 1 protects against this glutamate-induced synapse loss. Major histocompatibility I (MHCI) molecules are required for the effects of glutamate in causing synapse loss through negatively regulating NL1 levels. Thus, like acetylcholine at the NMJ, glutamate acts as a dispersal signal for NMDARs and causes rapid synapse loss unless opposed by NL1-mediated trans-synaptic adhesion. Together, glutamate, MHCI and NL1 mediate a novel form of homeostatic plasticity in young neurons that induces rapid changes in NMDARs to regulate when and where nascent glutamatergic synapses are formed.

Converging synaptic and network dysfunctions in distinct autoimmune encephalitis

Psychiatric and neurological symptoms, as well as cognitive deficits, represent a prominent phenotype associated with variable forms of autoimmune encephalitis, regardless of the neurotransmitter receptor targeted by autoantibodies. The mechanistic underpinnings of these shared major neuropsychiatric symptoms remain however unclear. Here, we investigate the impacts of patient-derived monoclonal autoantibodies against the glutamatergic NMDAR (NMDAR mAb) and inhibitory GABAaR (GABAaR mAb) signalling in the hippocampal network. Unexpectedly, both excitatory and inhibitory synaptic receptor membrane dynamics, content and transmissions are altered by NMDAR or GABAaR mAb, irrespective of the affinity or antagonistic effect of the autoantibodies. The effect of NMDAR mAb on inhibitory synapses and GABAaR mAb on excitatory synapses requires neuronal activity and involves protein kinase signalling. At the cell level, both autoantibodies increase the excitation/inhibition balance of principal cell inputs. Furthermore, NMDAR or GABAaR mAb leads to hyperactivation of hippocampal networks through distinct alterations of principal cell and interneuron properties. Thus, autoantibodies targeting excitatory NMDAR or inhibitory GABAaR trigger convergent network dysfunctions through a combination of shared and distinct mechanisms.

NSF DARE-transforming modeling in neurorehabilitation: a patient-in-the-loop framework

In 2023, the National Science Foundation (NSF) and the National Institute of Health (NIH) brought together engineers, scientists, and clinicians by sponsoring a conference on computational modelling in neurorehabiilitation. To facilitate multidisciplinary collaborations and improve patient care, in this perspective piece we identify where and how computational modelling can support neurorehabilitation. To address the where, we developed a patient-in-the-loop framework that uses multiple and/or continual measurements to update diagnostic and treatment model parameters, treatment type, and treatment prescription, with the goal of maximizing clinically-relevant functional outcomes. This patient-in-the-loop framework has several key features: (i) it includes diagnostic and treatment models, (ii) it is clinically-grounded with the International Classification of Functioning, Disability and Health (ICF) and patient involvement, (iii) it uses multiple or continual data measurements over time, and (iv) it is applicable to a range of neurological and neurodevelopmental conditions. To address the how, we identify state-of-the-art and highlight promising avenues of future research across the realms of sensorimotor adaptation, neuroplasticity, musculoskeletal, and sensory & pain computational modelling. We also discuss both the importance of and how to perform model validation, as well as challenges to overcome when implementing computational models within a clinical setting. The patient-in-the-loop approach offers a unifying framework to guide multidisciplinary collaboration between computational and clinical stakeholders in the field of neurorehabilitation.

Versatile Endogenous Editing of GluRIIA in Drosophila melanogaster

Glutamate receptors at the postsynaptic side translate neurotransmitter release from presynapses into postsynaptic excitation. They play a role in many forms of synaptic plasticity, e.g., homeostatic scaling of the receptor field, activity-dependent synaptic plasticity and the induction of presynaptic homeostatic potentiation (PHP). The latter process has been extensively studied at Drosophila melanogaster neuromuscular junctions (NMJs). The genetic removal of the glutamate receptor subunit IIA (GluRIIA) leads to an induction of PHP at the synapse. So far, mostly imprecise knockouts of the GluRIIA gene have been utilized. Furthermore, mutated and tagged versions of GluRIIA have been examined in the past, but most of these constructs were not expressed under endogenous regulatory control or involved the mentioned imprecise GluRIIA knockouts. We performed CRISPR/Cas9-assisted gene editing at the endogenous locus of GluRIIA. This enabled the investigation of the endogenous expression pattern of GluRIIA using tagged constructs with an EGFP and an ALFA tag for super-resolution immunofluorescence imaging, including structured illumination microscopy (SIM) and direct stochastic optical reconstruction microscopy (dSTORM). All GluRIIA constructs exhibited full functionality and PHP could be induced by philanthotoxin at control levels. By applying hierarchical clustering algorithms to analyze the dSTORM data, we detected postsynaptic receptor cluster areas of ~0.15 µm2. Consequently, our constructs are suitable for ultrastructural analyses of GluRIIA.

Transforming modeling in neurorehabilitation: clinical insights for personalized rehabilitation

Practicing clinicians in neurorehabilitation continue to lack a systematic evidence base to personalize rehabilitation therapies to individual patients and thereby maximize outcomes. Computational modeling- collecting, analyzing, and modeling neurorehabilitation data- holds great promise. A key question is how can computational modeling contribute to the evidence base for personalized rehabilitation? As representatives of the clinicians and clinician-scientists who attended the 2023 NSF DARE conference at USC, here we offer our perspectives and discussion on this topic. Our overarching thesis is that clinical insight should inform all steps of modeling, from construction to output, in neurorehabilitation and that this process requires close collaboration between researchers and the clinical community. We start with two clinical case examples focused on motor rehabilitation after stroke which provide context to the heterogeneity of neurologic injury, the complexity of post-acute neurologic care, the neuroscience of recovery, and the current state of outcome assessment in rehabilitation clinical care. Do we provide different therapies to these two different patients to maximize outcomes? Asking this question leads to a corollary: how do we build the evidence base to support the use of different therapies for individual patients? We discuss seven points critical to clinical translation of computational modeling research in neurorehabilitation- (i) clinical endpoints, (ii) hypothesis- versus data-driven models, (iii) biological processes, (iv) contextualizing outcome measures, (v) clinical collaboration for device translation, (vi) modeling in the real world and (vii) clinical touchpoints across all stages of research. We conclude with our views on key avenues for future investment (clinical-research collaboration, new educational pathways, interdisciplinary engagement) to enable maximal translational value of computational modeling research in neurorehabilitation.

Diverging from the Norm: Reevaluating What Miniature Excitatory Postsynaptic Currents Tell Us about Homeostatic Synaptic Plasticity

The idea that the nervous system maintains a set point of network activity and homeostatically returns to that set point in the face of dramatic disruption-during development, after injury, in pathologic states, and during sleep/wake cycles-is rapidly becoming accepted as a key plasticity behavior, placing it alongside long-term potentiation and depression. The dramatic growth in studies of homeostatic synaptic plasticity of miniature excitatory synaptic currents (mEPSCs) is attributable, in part, to the simple yet elegant mechanism of uniform multiplicative scaling proposed by Turrigiano and colleagues: that neurons sense their own activity and globally multiply the strength of every synapse by a single factor to return activity to the set point without altering established differences in synaptic weights. We have recently shown that for mEPSCs recorded from control and activity-blocked cultures of mouse cortical neurons, the synaptic scaling factor is not uniform but is close to 1 for the smallest mEPSC amplitudes and progressively increases as mEPSC amplitudes increase, which we term divergent scaling. Using insights gained from simulating uniform multiplicative scaling, we review evidence from published studies and conclude that divergent synaptic scaling is the norm rather than the exception. This conclusion has implications for hypotheses about the molecular mechanisms underlying synaptic scaling.

A fractional-order Wilson-Cowan formulation of cortical disinhibition

This work presents a fractional-order Wilson-Cowan model derivation under Caputo's formalism, considering an order of 0 < α ≤ 1 . To that end, we propose memory-dependent response functions and average neuronal excitation functions that permit us to naturally arrive at a fractional-order model that incorporates past dynamics into the description of synaptically coupled neuronal populations' activity. We then shift our focus on a particular example, aiming to analyze the fractional-order dynamics of the disinhibited cortex. This system mimics cortical activity observed during neurological disorders such as epileptic seizures, where an imbalance between excitation and inhibition is present, which allows brain dynamics to transition to a hyperexcited activity state. In the context of the first-order mathematical model, we recover traditional results showing a transition from a low-level activity state to a potentially pathological high-level activity state as an external factor modifies cortical inhibition. On the other hand, under the fractional-order formulation, we establish novel results showing that the system resists such transition as the order is decreased, permitting the possibility of staying in the low-activity state even with increased disinhibition. Furthermore, considering the memory index interpretation of the fractional-order model motivation here developed, our results establish that by increasing the memory index, the system becomes more resistant to transitioning towards the high-level activity state. That is, one possible effect of the memory index is to stabilize neuronal activity. Noticeably, this neuronal stabilizing effect is similar to homeostatic plasticity mechanisms. To summarize our results, we present a two-parameter structural portrait describing the system's dynamics dependent on a proposed disinhibition parameter and the order. We also explore numerical model simulations to validate our results.

Prediction error drives associative learning and conditioned behavior in a spiking model of Drosophila larva

Predicting reinforcement from sensory cues is beneficial for goal-directed behavior. In insect brains, underlying associations between cues and reinforcement, encoded by dopaminergic neurons, are formed in the mushroom body. We propose a spiking model of the Drosophila larva mushroom body. It includes a feedback motif conveying learned reinforcement expectation to dopaminergic neurons, which can compute prediction error as the difference between expected and present reinforcement. We demonstrate that this can serve as a driving force in learning. When combined with synaptic homeostasis, our model accounts for theoretically derived features of acquisition and loss of associations that depend on the intensity of the reinforcement and its temporal proximity to the cue. From modeling olfactory learning over the time course of behavioral experiments and simulating the locomotion of individual larvae toward or away from odor sources in a virtual environment, we conclude that learning driven by prediction errors can explain larval behavior.

Ketamine and the neurobiology of depression: Toward next-generation rapid-acting antidepressant treatments

Ketamine has emerged as a transformative and mechanistically novel pharmacotherapy for depression. Its rapid onset of action, efficacy for treatment-resistant symptoms, and protection against relapse distinguish it from prior antidepressants. Its discovery emerged from a reconceptualization of the neurobiology of depression and, in turn, insights from the elaboration of its mechanisms of action inform studies of the pathophysiology of depression and related disorders. It has been 25 y since we first presented our ketamine findings in depression. Thus, it is timely for this review to consider what we have learned from studies of ketamine and to suggest future directions for the optimization of rapid-acting antidepressant treatment.

Age-related dysregulation of homeostatic control in neuronal microcircuits

Neuronal homeostasis prevents hyperactivity and hypoactivity. Age-related hyperactivity suggests homeostasis may be dysregulated in later life. However, plasticity mechanisms preventing age-related hyperactivity and their efficacy in later life are unclear. We identify the adult cortical plasticity response to elevated activity driven by sensory overstimulation, then test how plasticity changes with age. We use in vivo two-photon imaging of calcium-mediated cellular/synaptic activity, electrophysiology and c-Fos-activity tagging to show control of neuronal activity is dysregulated in the visual cortex in late adulthood. Specifically, in young adult cortex, mGluR5-dependent population-wide excitatory synaptic weakening and inhibitory synaptogenesis reduce cortical activity following overstimulation. In later life, these mechanisms are downregulated, so that overstimulation results in synaptic strengthening and elevated activity. We also find overstimulation disrupts cognition in older but not younger animals. We propose that specific plasticity mechanisms fail in later life dysregulating neuronal microcircuit homeostasis and that the age-related response to overstimulation can impact cognitive performance.

Noise-Induced Hearing Loss Alters Potassium-Chloride CoTransporter KCC2 and GABA Inhibition in the auditory centers

Homeostatic plasticity, the ability of neurons to maintain their averaged activity constant around a set point value, is thought to account for the central hyperactivity after hearing loss. Here, we investigated the putative role of GABAergic neurotransmission in this mechanism after a noise-induced hearing loss larger than 50 dB in high frequencies in guinea pigs. The effect of GABAergic inhibition is linked to the normal functioning of K+-Cl- co-transporter isoform 2 (KCC2) which maintains a low intracellular concentration of chloride. The expression of membrane KCC2 were investigated before after noise trauma in the ventral and dorsal cochlear nucleus (VCN and DCN, respectively) and in the inferior colliculus (IC). Moreover, the effect of gabazine (GBZ), a GABA antagonist, was also studied on the neural activity in IC. We show that KCC2 is downregulated in VCN, DCN and IC 3 days after noise trauma, and in DCN and IC 30 days after the trauma. As expected, GBZ application in the IC of control animals resulted in an increase of spontaneous and stimulus-evoked activity. In the noise exposed animals, on the other hand, GBZ application decreased the stimulus-evoked activity in IC neurons. The functional implications of these central changes are discussed.

Electrophysiological properties of layer 2/3 pyramidal neurons in the primary visual cortex of a retinitis pigmentosa mouse model (rd10)

Retinal degeneration is one of the main causes of visual impairment and blindness. One group of retinal degenerative diseases, leading to the loss of photoreceptors, is collectively termed retinitis pigmentosa. In this group of diseases, the remaining retina is largely spared from initial cell death making retinal ganglion cells an interesting target for vision restoration methods. However, it is unknown how downstream brain areas, in particular the visual cortex, are affected by the progression of blindness. Visual deprivation studies have shown dramatic changes in the electrophysiological properties of visual cortex neurons, but changes on a cellular level in retinitis pigmentosa have not been investigated yet. Therefore, we used the rd10 mouse model to perform patch-clamp recordings of pyramidal neurons in layer 2/3 of the primary visual cortex to screen for potential changes in electrophysiological properties resulting from retinal degeneration. Compared to wild-type C57BL/6 mice, we only found an increase in intrinsic excitability around the time point of maximal retinal degeneration. In addition, we saw an increase in the current amplitude of spontaneous putative inhibitory events after a longer progression of retinal degeneration. However, we did not observe a long-lasting shift in excitability after prolonged retinal degeneration. Together, our results provide evidence of an intact visual cortex with promising potential for future therapeutic strategies to restore vision.

Synapses do not facilitate prion-like transfer of alpha-synuclein: a quantitative study in reconstructed unidirectional neural networks

Alpha-synuclein (aSyn) aggregation spreads between cells and underlies the progression of neuronal lesions in the brain of patients with synucleinopathies such as Parkinson's diseases. The mechanisms of cell-to-cell propagation of aggregates, which dictate how aggregation progresses at the network level, remain poorly understood. Notably, while prion and prion-like spreading is often simplistically envisioned as a "domino-like" spreading scenario where connected neurons sequentially propagate protein aggregation to each other, the reality is likely to be more nuanced. Here, we demonstrate that the spreading of preformed aSyn aggregates is a limited process that occurs through molecular sieving of large aSyn seeds. We further show that this process is not facilitated by synaptic connections. This was achieved through the development and characterization of a new microfluidic platform that allows reconstruction of binary fully oriented neuronal networks in vitro with no unwanted backward connections, and through the careful quantification of fluorescent aSyn aggregates spreading between neurons. While this allowed us for the first time to extract quantitative data of protein seeds dissemination along neural pathways, our data suggest that prion-like dissemination of proteinopathic seeding aggregates occurs very progressively and leads to highly compartmentalized pattern of protein seeding in neural networks.

Single genomic enhancers drive experience-dependent GABAergic plasticity to maintain sensory processing in the adult cortex

Experience-dependent plasticity of synapses modulates information processing in neural circuits and is essential for cognitive functions. The genome, via non-coding enhancers, was proposed to control information processing and circuit plasticity by regulating experience-induced transcription of genes that modulate specific sets of synapses. To test this idea, we analyze here the cellular and circuit functions of the genomic mechanisms that control the experience-induced transcription of Igf1 (insulin-like growth factor 1) in vasoactive intestinal peptide (VIP) interneurons (INs) in the visual cortex of adult mice. We find that two sensory-induced enhancers selectively and cooperatively drive the activity-induced transcription of Igf1 to thereby promote GABAergic inputs onto VIP INs and to homeostatically control the ratio between excitation and inhibition (E/I ratio)-in turn, this restricts neural activity in VIP INs and principal excitatory neurons and maintains spatial frequency tuning. Thus, enhancer-mediated activity-induced transcription maintains sensory processing in the adult cortex via homeostatic modulation of E/I ratio.

STDP-Driven Rewiring in Spiking Neural Networks under Stimulus-Induced and Spontaneous Activity

Mathematical and computer simulation of learning in living neural networks have typically focused on changes in the efficiency of synaptic connections represented by synaptic weights in the models. Synaptic plasticity is believed to be the cellular basis for learning and memory. In spiking neural networks composed of dynamical spiking units, a biologically relevant learning rule is based on the so-called spike-timing-dependent plasticity or STDP. However, experimental data suggest that synaptic plasticity is only a part of brain circuit plasticity, which also includes homeostatic and structural plasticity. A model of structural plasticity proposed in this study is based on the activity-dependent appearance and disappearance of synaptic connections. The results of the research indicate that such adaptive rewiring enables the consolidation of the effects of STDP in response to a local external stimulation of a neural network. Subsequently, a vector field approach is used to demonstrate the successive "recording" of spike paths in both functional connectome and synaptic connectome, and finally in the anatomical connectome of the network. Moreover, the findings suggest that the adaptive rewiring could stabilize network dynamics over time in the context of activity patterns' reproducibility. A universal measure of such reproducibility introduced in this article is based on similarity between time-consequent patterns of the special vector fields characterizing both functional and anatomical connectomes.

Neural waves and short-term memory in a neural net model

We show that recognizable neural waveforms are reproduced in the model described in previous work. In so doing, we reproduce close matches to certain observed, though filtered, EEG-like measurements in closed mathematical form, to good approximations. Such neural waves represent the responses of individual networks to external and endogenous inputs and are presumably the carriers of the information used to perform computations in actual brains, which are complexes of interconnected networks. Then, we apply these findings to a question arising in short-term memory processing in humans. Namely, we show how the anomalously small number of reliable retrievals from short-term memory found in certain trials of the Sternberg task is related to the relative frequencies of the neural waves involved. This finding justifies the hypothesis of phase-coding, which has been posited as an explanation of this effect.

Early alterations in the MCH system link aberrant neuronal activity and sleep disturbances in a mouse model of Alzheimer's disease

Early Alzheimer's disease (AD) is associated with hippocampal hyperactivity and decreased sleep quality. Here we show that homeostatic mechanisms transiently counteract the increased excitatory drive to CA1 neurons in App^NL-G-F mice, but that this mechanism fails in older mice. Spatial transcriptomics analysis identifies Pmch as part of the adaptive response in App^NL-G-F mice. Pmch encodes melanin-concentrating hormone (MCH), which is produced in sleep-active lateral hypothalamic neurons that project to CA1 and modulate memory. We show that MCH downregulates synaptic transmission, modulates firing rate homeostasis in hippocampal neurons and reverses the increased excitatory drive to CA1 neurons in App^NL-G-F mice. App^NL-G-F mice spend less time in rapid eye movement (REM) sleep. App^NL-G-F mice and individuals with AD show progressive changes in morphology of CA1-projecting MCH axons. Our findings identify the MCH system as vulnerable in early AD and suggest that impaired MCH-system function contributes to aberrant excitatory drive and sleep defects, which can compromise hippocampus-dependent functions.

Dendrites help mitigate the plasticity-stability dilemma

With Hebbian learning 'who fires together wires together', well-known problems arise. Hebbian plasticity can cause unstable network dynamics and overwrite stored memories. Because the known homeostatic plasticity mechanisms tend to be too slow to combat unstable dynamics, it has been proposed that plasticity must be highly gated and synaptic strengths limited. While solving the issue of stability, gating and limiting plasticity does not solve the stability-plasticity dilemma. We propose that dendrites enable both stable network dynamics and considerable synaptic changes, as they allow the gating of plasticity in a compartment-specific manner. We investigate how gating plasticity influences network stability in plastic balanced spiking networks of neurons with dendrites. We compare how different ways to gate plasticity, namely via modulating excitability, learning rate, and inhibition increase stability. We investigate how dendritic versus perisomatic gating allows for different amounts of weight changes in stable networks. We suggest that the compartmentalisation of pyramidal cells enables dendritic synaptic changes while maintaining stability. We show that the coupling between dendrite and soma is critical for the plasticity-stability trade-off. Finally, we show that spatially restricted plasticity additionally improves stability.

The gut-brain connection: Exploring the influence of the gut microbiota on neuroplasticity and neurodevelopmental disorders

Neuroplasticity refers to the ability of brain circuits to reorganize and change the properties of the network, resulting in alterations in brain function and behavior. It is traditionally believed that neuroplasticity is influenced by external stimuli, learning, and experience. Intriguingly, there is new evidence suggesting that endogenous signals from the body's periphery may play a role. The gut microbiota, a diverse community of microorganisms living in harmony with their host, may be able to influence plasticity through its modulation of the gut-brain axis. Interestingly, the maturation of the gut microbiota coincides with critical periods of neurodevelopment, during which neural circuits are highly plastic and potentially vulnerable. As such, dysbiosis (an imbalance in the gut microbiota composition) during early life may contribute to the disruption of normal developmental trajectories, leading to neurodevelopmental disorders. This review aims to examine the ways in which the gut microbiota can affect neuroplasticity. It will also discuss recent research linking gastrointestinal issues and bacterial dysbiosis to various neurodevelopmental disorders and their potential impact on neurological outcomes.

Neuronal morphology enhances robustness to perturbations of channel densities

Biological neurons show significant cell-to-cell variability but have the striking ability to maintain their key firing properties in the face of unpredictable perturbations and stochastic noise. Using a population of multi-compartment models consisting of soma, neurites, and axon for the lateral pyloric neuron in the crab stomatogastric ganglion, we explore how rebound bursting is preserved when the 14 channel conductances in each model are all randomly varied. The coupling between the axon and other compartments is critical for the ability of the axon to spike during bursts and consequently determines the set of successful solutions. When the coupling deviates from a biologically realistic range, the neuronal tolerance of conductance variations is lessened. Thus, the gross morphological features of these neurons enhance their robustness to perturbations of channel densities and expand the space of individual variability that can maintain a desired output pattern.

Neuronal membrane proteasomes regulate neuronal circuit activity in vivo and are required for learning-induced behavioral plasticity

Protein degradation is critical for brain function through processes that remain incompletely understood. Here, we investigated the in vivo function of the 20S neuronal membrane proteasome (NMP) in the brain of Xenopus laevis tadpoles. With biochemistry, immunohistochemistry, and electron microscopy, we demonstrated that NMPs are conserved in the tadpole brain and preferentially degrade neuronal activity-induced newly synthesized proteins in vivo. Using in vivo calcium imaging in the optic tectum, we showed that acute NMP inhibition rapidly increased spontaneous neuronal activity, resulting in hypersynchronization across tectal neurons. At the circuit level, inhibiting NMPs abolished learning-dependent improvement in visuomotor behavior in live animals and caused a significant deterioration in basal behavioral performance following visual training with enhanced visual experience. Our data provide in vivo characterization of NMP functions in the vertebrate nervous system and suggest that NMP-mediated degradation of activity-induced nascent proteins may serve as a homeostatic modulatory mechanism in neurons that is critical for regulating neuronal activity and experience-dependent circuit plasticity.

Transsynaptic Signaling of Ephs in Synaptic Development, Plasticity, and Disease

Synapse formation between neurons is critical for proper circuit and brain function. Prior to activity-dependent refinement of connections between neurons, activity-independent cues regulate the contact and recognition of potential synaptic partners. Formation of a synapse results in molecular recognition events that initiate the process of synaptogenesis. Synaptogenesis requires contact between axon and dendrite, selection of correct and rejection of incorrect partners, and recruitment of appropriate pre- and postsynaptic proteins needed for the establishment of functional synaptic contact. Key regulators of these events are families of transsynaptic proteins, where one protein is found on the presynaptic neuron and the other is found on the postsynaptic neuron. Of these families, the EphBs and ephrin-Bs are required during each phase of synaptic development from target selection, recruitment of synaptic proteins, and formation of spines to regulation of synaptic plasticity at glutamatergic spine synapses in the mature brain. These roles also place EphBs and ephrin-Bs as important regulators of human neurological diseases. This review will focus on the role of EphBs and ephrin-Bs at synapses.

Rapid homeostatic plasticity and neuropsychiatric therapeutics

Neuronal and synaptic plasticity are widely used terms in the field of psychiatry. However, cellular neurophysiologists have identified two broad classes of plasticity. Hebbian forms of plasticity alter synaptic strength in a synapse specific manner in the same direction of the initial conditioning stimulation. In contrast, homeostatic plasticities act globally over longer time frames in a negative feedback manner to counter network level changes in activity or synaptic strength. Recent evidence suggests that homeostatic plasticity mechanisms can be rapidly engaged, particularly by fast-acting antidepressants such as ketamine to trigger behavioral effects. There is increasing evidence that several neuropsychoactive compounds either directly elicit changes in synaptic activity or indirectly tap into downstream signaling pathways to trigger homeostatic plasticity and subsequent behavioral effects. In this review, we discuss this recent work in the context of a wider paradigm where homeostatic synaptic plasticity mechanisms may provide novel targets for neuropsychiatric treatment advance.

Remembering and forgetting in sleep: Selective synaptic plasticity during sleep driven by scaling factors Homer1a and Arc

Sleep is a conserved and essential process that supports learning and memory. Synapses are a major target of sleep function and a locus of sleep need. Evidence in the literature suggests that the need for sleep has a cellular or microcircuit level basis, and that sleep need can accumulate within localized brain regions as a function of waking activity. Activation of sleep promoting kinases and accumulation of synaptic phosphorylation was recently shown to be part of the molecular basis for the localized sleep need. A prominent hypothesis in the field suggests that some benefits of sleep are mediated by a broad but selective weakening, or scaling-down, of synaptic strength during sleep in order to offset increased excitability from synaptic potentiation during wake. The literature also shows that synapses can be strengthened during sleep, raising the question of what molecular mechanisms may allow for selection of synaptic plasticity types during sleep. Here I describe mechanisms of action of the scaling factors Arc and Homer1a in selective plasticity and links with sleep need. Arc and Homer1a are induced in neurons in response to waking neuronal activity and accumulate with time spent awake. I suggest that during sleep, Arc and Homer1a drive broad weakening of synapses through homeostatic scaling-down, but in a manner that is sensitive to the plasticity history of individual synapses, based on patterned phosphorylation of synaptic proteins. Therefore, Arc and Homer1a may offer insights into the intricate links between a cellular basis of sleep need and memory consolidation during sleep.

Stability and learning in excitatory synapses by nonlinear inhibitory plasticity

Synaptic changes are hypothesized to underlie learning and memory formation in the brain. But Hebbian synaptic plasticity of excitatory synapses on its own is unstable, leading to either unlimited growth of synaptic strengths or silencing of neuronal activity without additional homeostatic mechanisms. To control excitatory synaptic strengths, we propose a novel form of synaptic plasticity at inhibitory synapses. Using computational modeling, we suggest two key features of inhibitory plasticity, dominance of inhibition over excitation and a nonlinear dependence on the firing rate of postsynaptic excitatory neurons whereby inhibitory synaptic strengths change with the same sign (potentiate or depress) as excitatory synaptic strengths. We demonstrate that the stable synaptic strengths realized by this novel inhibitory plasticity model affects excitatory/inhibitory weight ratios in agreement with experimental results. Applying a disinhibitory signal can gate plasticity and lead to the generation of receptive fields and strong bidirectional connectivity in a recurrent network. Hence, a novel form of nonlinear inhibitory plasticity can simultaneously stabilize excitatory synaptic strengths and enable learning upon disinhibition.

Functional impairment of cortical AMPA receptors in schizophrenia

Clinical and preclinical studies suggest that some of the behavioral alterations observed in schizophrenia (SZ) may be mechanistically linked to synaptic dysfunction of glutamatergic signaling. Recent genetic and proteomic studies suggest alterations of cortical glutamate receptors of the AMPA-type (AMPARs), which are the predominant ligand-gated ionic channels of fast transmission at excitatory synapses. The impact of gene and protein alterations on the electrophysiological activity of AMPARs is not known in SZ. In this proof of principle work, using human postmortem brain synaptic membranes isolated from the dorsolateral prefrontal cortex (DLPFC), we combined electrophysiological analysis from microtransplanted synaptic membranes (MSM) with transcriptomic (RNA-Seq) and label-free proteomics data in 10 control and 10 subjects diagnosed with SZ. We observed in SZ a reduction in the amplitude of AMPARs currents elicited by kainate, an agonist of AMPARs that blocks the desensitization of the receptor. This reduction was not associated with protein abundance but with a reduction in kainate's potency to activate AMPARs. Electrophysiologically-anchored dataset analysis (EDA) was used to identify synaptosomal proteins that linearly correlate with the amplitude of the AMPARs responses, gene ontology functional annotations were then used to determine protein-protein interactions. Protein modules associated with positive AMPARs current increases were downregulated in SZ, while protein modules that were upregulated in SZ were associated with decreased AMPARs currents. Our results indicate that transcriptomic and proteomic alterations, frequently observed in the DLPFC in SZ, converge at the synaptic level producing a functional electrophysiological impairment of AMPARs.