Mechanisms Of Synaptic Plasticity Research Articles

Synaptic reorganization of synchronized neuronal networks with synaptic weight and structural plasticity.

Abnormally strong neural synchronization may impair brain function, as observed in several brain disorders. We computationally study how neuronal dynamics, synaptic weights, and network structure co-emerge, in particular, during (de)synchronization processes and how they are affected by external perturbation. To investigate the impact of different types of plasticity mechanisms, we combine a network of excitatory integrate-and-fire neurons with different synaptic weight and/or structural plasticity mechanisms: (i) only spike-timing-dependent plasticity (STDP), (ii) only homeostatic structural plasticity (hSP), i.e., without weight-dependent pruning and without STDP, (iii) a combination of STDP and hSP, i.e., without weight-dependent pruning, and (iv) a combination of STDP and structural plasticity (SP) that includes hSP and weight-dependent pruning. To accommodate the diverse time scales of neuronal firing, STDP, and SP, we introduce a simple stochastic SP model, enabling detailed numerical analyses. With tools from network theory, we reveal that structural reorganization may remarkably enhance the network's level of synchrony. When weaker contacts are preferentially eliminated by weight-dependent pruning, synchrony is achieved with significantly sparser connections than in randomly structured networks in the STDP-only model. In particular, the strengthening of contacts from neurons with higher natural firing rates to those with lower rates and the weakening of contacts in the opposite direction, followed by selective removal of weak contacts, allows for strong synchrony with fewer connections. This activity-led network reorganization results in the emergence of degree-frequency, degree-degree correlations, and a mixture of degree assortativity. We compare the stimulation-induced desynchronization of synchronized states in the STDP-only model (i) with the desynchronization of models (iii) and (iv). The latter require stimuli of significantly higher intensity to achieve long-term desynchronization. These findings may inform future pre-clinical and clinical studies with invasive or non-invasive stimulus modalities aiming at inducing long-lasting relief of symptoms, e.g., in Parkinson's disease.

Unveiling serotonergic dysfunction of obsessive-compulsive disorder on prefrontal network dynamics: a computational perspective.

Serotonin (5-HT) regulates working memory within the prefrontal cortex network, which is crucial for understanding obsessive-compulsive disorder. However, the mechanisms how network dynamics and serotonin interact in obsessive-compulsive disorder remain elusive. Here, we incorporate 5-HT receptors (5-HT1A, 5-HT2A) and dopamine receptors into a multistable prefrontal cortex network model, replicating the experimentally observed inverted U-curve phenomenon. We show how the two 5-HT receptors antagonize neuronal activity and modulate network multistability. Reduced binding of 5-HT1A receptors increases global firing, while reduced binding of 5-HT2A receptors deepens attractors. The obtained results suggest reward-dependent synaptic plasticity mechanisms may attenuate 5-HT related network impairments. Integrating serotonin-mediated dopamine release into circuit, we observe that decreased serotonin concentration triggers the network into a deep attractor state, expanding the domain of attraction of stable nodes with high firing rate, potentially causing aberrant reverse learning. This suggests a hypothesis wherein elevated dopamine concentrations in obsessive-compulsive disorder might result from primary deficits in serotonin levels. Findings of this work underscore the pivotal role of serotonergic dysregulation in modulating synaptic plasticity through dopamine pathways, potentially contributing to learned obsessions. Interestingly, serotonin reuptake inhibitors and antidopaminergic potentiators can counteract the over-stable state of high-firing stable points, providing new insights into obsessive-compulsive disorder treatment.

Artificial cerebellum on FPGA: realistic real-time cerebellar spiking neural network model capable of real-world adaptive motor control.

The cerebellum plays a central role in motor control and learning. Its neuronal network architecture, firing characteristics of component neurons, and learning rules at their synapses have been well understood in terms of anatomy and physiology. A realistic artificial cerebellum with mimetic network architecture and synaptic plasticity mechanisms may allow us to analyze cerebellar information processing in the real world by applying it to adaptive control of actual machines. Several artificial cerebellums have previously been constructed, but they require high-performance hardware to run in real-time for real-world machine control. Presently, we implemented an artificial cerebellum with the size of 104 spiking neuron models on a field-programmable gate array (FPGA) which is compact, lightweight, portable, and low-power-consumption. In the implementation three novel techniques are employed: (1) 16-bit fixed-point operation and randomized rounding, (2) fully connected spike information transmission, and (3) alternative memory that uses pseudo-random number generators. We demonstrate that the FPGA artificial cerebellum runs in real-time, and its component neuron models behave as those in the corresponding artificial cerebellum configured on a personal computer in Python. We applied the FPGA artificial cerebellum to the adaptive control of a machine in the real world and demonstrated that the artificial cerebellum is capable of adaptively reducing control error after sudden load changes. This is the first implementation and demonstration of a spiking artificial cerebellum on an FPGA applicable to real-world adaptive control. The FPGA artificial cerebellum may provide neuroscientific insights into cerebellar information processing in adaptive motor control and may be applied to various neuro-devices to augment and extend human motor control capabilities.

Cyclic nucleotide-induced bidirectional long-term synaptic plasticity in Drosophila mushroom body.

Activation of the cAMP pathway is one of the common mechanisms underlying long-term potentiation (LTP). In the Drosophila mushroom body, simultaneous activation of odour-coding Kenyon cells (KCs) and reinforcement-coding dopaminergic neurons activates adenylyl cyclase in KC presynaptic terminals, which is believed to trigger synaptic plasticity underlying olfactory associative learning. However, learning induces long-term depression (LTD) at these synapses, contradicting the universal role of cAMP as a facilitator of transmission. Here, we developed a system to electrophysiologically monitor both short-term and long-term synaptic plasticity at KC output synapses and demonstrated that they are indeed an exception in which activation of the cAMP-protein kinase A pathway induces LTD. Contrary to the prevailing model, our cAMP imaging found no evidence for synergistic action of dopamine and KC activity on cAMP synthesis. Furthermore, we found that forskolin-induced cAMP increase alone was insufficient for plasticity induction; it additionally required simultaneous KC activation to replicate the presynaptic LTD induced by pairing with dopamine. On the other hand, activation of the cGMP pathway paired with KC activation induced slowly developing LTP, proving antagonistic actions of the two second-messenger pathways predicted by behavioural study. Finally, KC subtype-specific interrogation of synapses revealed that different KC subtypes exhibit distinct plasticity duration even among synapses on the same postsynaptic neuron. Thus, our work not only revises the role of cAMP in synaptic plasticity by uncovering the unexpected convergence point of the cAMP pathway and neuronal activity, but also establishes the methods to address physiological mechanisms of synaptic plasticity in this important model. KEY POINTS: Although presynaptic cAMP increase generally facilitates synapses, olfactory associative learning in Drosophila, which depends on dopamine and cAMP signalling genes, induces long-term depression (LTD) at the mushroom body output synapses. By combining electrophysiology, pharmacology and optogenetics, we directly demonstrate that these synapses are an exception where activation of the cAMP-protein kinase A pathway leads to presynaptic LTD. Dopamine- or forskolin-induced cAMP increase alone is not sufficient for LTD induction; neuronal activity, which has been believed to trigger cAMP synthesis in synergy with dopamine input, is required in the downstream pathway of cAMP. In contrast to cAMP, activation of the cGMP pathway paired with neuronal activity induces presynaptic long-term potentiation, which explains behaviourally observed opposing actions of transmitters co-released by dopaminergic neurons. Our work not only revises the role of cAMP in synaptic plasticity, but also provides essential methods to address physiological mechanisms of synaptic plasticity in this important model system.

Structure, biophysics, and circuit function of a "giant" cortical presynaptic terminal.

The hippocampal mossy fiber synapse, formed between axons of dentate gyrus granule cells and dendrites of CA3 pyramidal neurons, is a key synapse in the trisynaptic circuitry of the hippocampus. Because of its comparatively large size, this synapse is accessible to direct presynaptic recording, allowing a rigorous investigation of the biophysical mechanisms of synaptic transmission and plasticity. Furthermore, because of its placement in the very center of the hippocampal memory circuit, this synapse seems to be critically involved in several higher network functions, such as learning, memory, pattern separation, and pattern completion. Recent work based on new technologies in both nanoanatomy and nanophysiology, including presynaptic patch-clamp recording, paired recording, super-resolution light microscopy, and freeze-fracture and "flash-and-freeze" electron microscopy, has provided new insights into the structure, biophysics, and network function of this intriguing synapse. This brings us one step closer to answering a fundamental question in neuroscience: how basic synaptic properties shape higher network computations.

Fiber-based in vivo imaging: unveiling avenues for exploring mechanisms of synaptic plasticity and neuronal adaptations underlying behavior.

In recent decades, various subfields within neuroscience, spanning molecular, cellular, and systemic dimensions, have significantly advanced our understanding of the elaborate molecular and cellular mechanisms that underpin learning, memory, and adaptive behaviors. There have been notable advancements in imaging techniques, particularly in reaching superficial brain structures. This progress has led to their widespread adoption in numerous laboratories. However, essential physiological and cognitive processes, including sensory integration, emotional modulation of motivated behavior, motor regulation, learning, and memory consolidation, are intricately encoded within deeper brain structures. Hence, visualization techniques such as calcium imaging using miniscopes have gained popularity for studying brain activity in unrestrained animals. Despite its utility, miniscope technology is associated with substantial brain tissue damage caused by gradient refractive index lens implantation. Furthermore, its imaging capabilities are primarily confined to the neuronal somata level, thus constraining a comprehensive exploration of subcellular processes underlying adaptive behaviors. Consequently, the trajectory of neuroscience's future hinges on the development of minimally invasive optical fiber-based endo-microscopes optimized for cellular, subcellular, and molecular imaging within the intricate depths of the brain. In pursuit of this goal, select research groups have invested significant efforts in advancing this technology. In this review, we present a perspective on the potential impact of this innovation on various aspects of neuroscience, enabling the functional exploration of in vivo cellular and subcellular processes that underlie synaptic plasticity and the neuronal adaptations that govern behavior.

Learning what matters: Synaptic plasticity with invariance to second-order input correlations.

Cortical populations of neurons develop sparse representations adapted to the statistics of the environment. To learn efficient population codes, synaptic plasticity mechanisms must differentiate relevant latent features from spurious input correlations, which are omnipresent in cortical networks. Here, we develop a theory for sparse coding and synaptic plasticity that is invariant to second-order correlations in the input. Going beyond classical Hebbian learning, our learning objective explains the functional form of observed excitatory plasticity mechanisms, showing how Hebbian long-term depression (LTD) cancels the sensitivity to second-order correlations so that receptive fields become aligned with features hidden in higher-order statistics. Invariance to second-order correlations enhances the versatility of biologically realistic learning models, supporting optimal decoding from noisy inputs and sparse population coding from spatially correlated stimuli. In a spiking model with triplet spike-timing-dependent plasticity (STDP), we show that individual neurons can learn localized oriented receptive fields, circumventing the need for input preprocessing, such as whitening, or population-level lateral inhibition. The theory advances our understanding of local unsupervised learning in cortical circuits, offers new interpretations of the Bienenstock-Cooper-Munro and triplet STDP models, and assigns a specific functional role to synaptic LTD mechanisms in pyramidal neurons.

The sphingosine 1-phosphate analogue, FTY720, modulates the lipidomic signature of the mouse hippocampus.

The small-molecule drug, FTY720 (fingolimod), is a synthetic sphingosine 1-phosphate (S1P) analogue currently used to treat relapsing-remitting multiple sclerosis in both adults and children. FTY720 can cross the blood-brain barrier (BBB) and, over time, accumulate in lipid-rich areas of the central nervous system (CNS) by incorporating into phospholipid membranes. FTY720 has been shown to enhance cell membrane fluidity, which can modulate the functions of glial cells and neuronal populations involved in regulating behaviour. Moreover, direct modulation of S1P receptor-mediated lipid signalling by FTY720 can impact homeostatic CNS physiology, including neurotransmitter release probability, the biophysical properties of synaptic membranes, ion channel and transmembrane receptor kinetics, and synaptic plasticity mechanisms. The aim of this study was to investigate how chronic FTY720 treatment alters the lipid composition of CNS tissue in adolescent mice at a key stage of brain maturation. We focused on the hippocampus, a brain region known to be important for learning, memory, and the processing of sensory and emotional stimuli. Using mass spectrometry-based lipidomics, we discovered that FTY720 increases the fatty acid chain length of hydroxy-phosphatidylcholine (PCOH) lipids in the mouse hippocampus. It also decreases PCOH monounsaturated fatty acids (MUFAs) and increases PCOH polyunsaturated fatty acids (PUFAs). A total of 99 lipid species were up-regulated in the mouse hippocampus following 3 weeks of oral FTY720 exposure, whereas only 3 lipid species were down-regulated. FTY720 also modulated anxiety-like behaviours in young mice but did not affect spatial learning or memory formation. Our study presents a comprehensive overview of the lipid classes and lipid species that are altered in the hippocampus following chronic FTY720 exposure and provides novel insight into cellular and molecular mechanisms that may underlie the therapeutic or adverse effects of FTY720 in the central nervous system.

Contextual memory engrams, and the neuromodulatory influence of the locus coeruleus.

Here, we review the basis of contextual memory at a conceptual and cellular level. We begin with an overview of the philosophical foundations of traversing space, followed by theories covering the material bases of contextual representations in the hippocampus (engrams), exploring functional characteristics of the cells and subfields within. Next, we explore various methodological approaches for investigating contextual memory engrams, emphasizing plasticity mechanisms. This leads us to discuss the role of neuromodulatory inputs in governing these dynamic changes. We then outline a recent hypothesis involving noradrenergic and dopaminergic projections from the locus coeruleus (LC) to different subregions of the hippocampus, in sculpting contextual representations, giving a brief description of the neuroanatomical and physiological properties of the LC. Finally, we examine how activity in the LC influences contextual memory processes through synaptic plasticity mechanisms to alter hippocampal engrams. Overall, we find that phasic activation of the LC plays an important role in promoting new learning and altering mnemonic processes at the behavioral and cellular level through the neuromodulatory influence of NE/DA in the hippocampus. These findings may provide insight into mechanisms of hippocampal remapping and memory updating, memory processes that are potentially dysregulated in certain psychiatric and neurodegenerative disorders.

Mechanisms of Action of TMS in the Treatment of Depression.

Transcranial magnetic stimulation (TMS) is entering increasingly widespread use in treating depression. The most common stimulation target, in the dorsolateral prefrontal cortex (DLPFC), emerged from early neuroimaging studies in depression. Recently, more rigorous casual methods have revealed whole-brain target networks and anti-networks based on the effects of focal brain lesions and focal brain stimulation on depression symptoms. Symptom improvement during therapeutic DLPFC-TMS appears to involve directional changes in signaling between the DLPFC, subgenual and dorsal anterior cingulate cortex, and salience-network regions. However, different networks may be involved in the therapeutic mechanisms for other TMS targets in depression, such as dorsomedial prefrontal cortex or orbitofrontal cortex. The durability of therapeutic effects for TMS involves synaptic neuroplasticity, and specifically may depend upon dopamine acting at the D1 receptor family, as well as NMDA-receptor-dependent synaptic plasticity mechanisms. Although TMS protocols are classically considered 'excitatory' or 'inhibitory', the actual effects in individuals appear quite variable, and might be better understood at the level of populations of synapses rather than individual synapses. Synaptic meta-plasticity may provide a built-in protective mechanism to avoid runaway facilitation or inhibition during treatment, and may account for the relatively small number of patients who worsen rather than improve with TMS. From an ethological perspective, the antidepressant effects of TMS may involve promoting a whole-brain attractor state associated with foraging/hunting behaviors, centered on the rostrolateral periaqueductal gray and salience network, and suppressing an attractor state associated with passive threat defense, centered on the ventrolateral periaqueductal gray and default-mode network.

Restoration of a paraventricular thalamo-accumbal behavioral suppression circuit prevents reinstatement of heroin seeking

Lack of behavioral suppression typifies substance use disorders, yet the neural circuit underpinnings of drug-induced behavioral disinhibition remain unclear. Here, we employ deep-brain two-photon calcium imaging in heroin self-administering mice, longitudinally tracking adaptations within a paraventricular thalamus to nucleus accumbens behavioral inhibition circuit from the onset of heroin use to reinstatement. We find that select thalamo-accumbal neuronal ensembles become profoundly hypoactive across the development of heroin seeking and use. Electrophysiological experiments further reveal persistent adaptations at thalamo-accumbal parvalbumin interneuronal synapses, whereas functional rescue of these synapses prevents multiple triggers from initiating reinstatement of heroin seeking. Finally, we find an enrichment of μ-opioid receptors in output- and cell-type-specific paraventricular thalamic neurons, which provide a mechanism for heroin-induced synaptic plasticity and behavioral disinhibition. These findings reveal key circuit adaptations that underlie behavioral disinhibition in opioid dependence and further suggest that recovery of this system would reduce relapse susceptibility.

The use of memristive devices in machine vision systems

The comparison results of processing units with memristive devices versus modern hardware accelerators of artificial neural networks (ANNs) based on traditional electronic components, as presented in the review [1], demonstrate numerous advantages across all major indicators such as throughput, energy efficiency, accuracy, and others. This report analyzes the current state of memristive devices in addressing machine vision issues. Special attention is paid to the concept of [2] neuromorphic machine vision systems (MVS) based on memristive devices. This concept’s distinct feature lies in its fully analog system, commencing from information input to its output. It encompasses sensory and neural components. The sensory part is responsible for gathering visual information and transferring it to the neural segment for processing through the ANN model algorithm. A specific instance for implementing the input channel of the sensor component involves connecting a photodiode (PD) and a memristor in a single circuit. When the circuit is flipped in reverse bias and light falls on the PD, a photocurrent flows through it from the cathode to the anode. Depending on the light intensity and exposure time, this photocurrent alters the resistance of the memristor, thereby converting illumination into resistance. If visual information doesn’t require encoding with memristor resistances, they can be replaced with a load resistance of the same nominal value for all channels. Irrespective of the input channel variant, the signal encoding visual information is fed into the neural part without digitization. Memristors act as synapses as part of the neural part. They can be used to implement synapses in both traditional formal ANN architectures, where input information is multiplied by a pre-programmed weight, and synapses for spiking neural networks, where a memristor exhibits synaptic plasticity mechanisms similar to those in biological neural networks [3]. If the output from the suggested MVS input channel variants is connected to a device that operates on the “integrate and fire” principle, the device can be deemed as not only an input for a structured ANN, but also a presynaptic neuron for a spiking ANN. The neuron’s frequency of spikes will depend on the light intensity; the brighter the light, the higher the frequency of spikes and vice versa. Faster charge accumulation occurs in channels with low resistance. The complete analog machine vision system will function as a spike neural network, without incorporating any analog-to-digital or digital-to-analog converters. Compared to digital machine vision systems, this approach will significantly decrease energy consumption while producing wearable and on-board electronics with distinct tactical and technical features. This design can be tailored to the size of modern matrices of photo and video fixation devices and employed as a hardware accelerator for the ANN models currently used to process images, and it can serve as a foundation for advancing this area.

Amyloid beta (1‐42) peptide suppression of macroscopic homomeric Kv1.2 and heteromeric Kv1.1/1.2 currents is calcium‐ and calcineurin‐dependent: Implications for Alzheimer’s disease

AbstractBackgroundThe roles of Aβ in the pathogenesis of Alzheimer ’s disease (AD) include disruption of: 1) Ca2+ homeostasis, 2) synaptic communication, and 3) learning‐ and memory‐related synaptic plasticity and neuronal excitability mechanisms. Exactly how these abnormalities arise is incompletely understood. Our lab has focused on the involvement of voltage‐gated potassium channels (VGKCs) in several of these processes. VGKCs are activated during an action potential and regulate Ca2+ influx. Inhibition of VGKCs can lead to synapto‐ and neuro‐toxicity. Kv1.x family subunits can assemble as functional homomers or select heteromers; Kv1.1 is often co‐expressed with Kv1.2. We’ve previously found that: 1) Aβ peptides suppress both Kv1.1 and Kv1.2 homomeric channel activities, as well as Kv1.1/1.2 heteromeric activity, 2) Aβ suppression of Kv1.1 was partially (∼ 50%) dependent on intracellular calcium [Ca2+]i, being reduced by exposure of cells to the calcium chelator BAPTA‐AM, as well as by cyclosporine A (CsA), an inhibitor of PP2B/calcineurin (CaN). Here we asked if Aβ‐suppression of Kv1.2 and Kv1.1/1.2 currents was similarly dependent on [Ca2+]i, and CaN in the case of Kv1.2.MethodsStage V/VI Xenopus laevis oocytes from Ecocyte Bioscience (Austin, TX) were injected with Kv1.2 cRNA for homomeric expression. Heteromeric expression was produced by co‐injection of Kv1.1 and 1.2 cRNAs. Macroscopic currents were measured 2‐3 days later using TEVC.ResultsBath application (1 μM) of Aβ(1‐42) produced significant suppression of Kv1.2 (46%, n = 10) and Kv1.1/1.2 (41%, n = 8), 30 min following Aβ application. These suppressions were significantly greater than those of DMSO‐exposed control cells: 2% for Kv1.2 (n = 15), p< .002; 11% (n = 7) for Kv1.1/1.2, p <.02. BAPTA‐AM treatment (n = 9; 50 μM for 1 hr, followed by 3X wash) greatly reduced Aβ‐suppression of Kv1.2 current (from 46% to 18%, p < .002). CsA exposure (n = 6, 10 μM for 12 hr) completely blocked Aβ suppression (from 46% to ‐4%, p < .0001). BAPTA‐AM (n = 5) also significantly attenuated suppression of Kv1.1/1.2 current (from 41% to 10%, p < .02).ConclusionOur results suggest that Aβ‐disruption of [Ca2+]i can lead to suppression of Kv1.1 and 1.2 activities through CaN activation, and thereby contribute to hyperexcitabilty phenotypes in AD.

Proteomic profiling of interferon-responsive reactive astrocytes in rodent and human.

Astrocytes are a heterogeneous population of central nervous system glial cells that respond to pathological insults and injury by undergoing a transformation called "reactivity." Reactive astrocytes exhibit distinct and context-dependent cellular, molecular, and functional state changes that can either support or disturb tissue homeostasis. We recently identified a reactive astrocyte sub-state defined by interferon-responsive genes like Igtp, Ifit3, Mx1, and others, called interferon-responsive reactive astrocytes (IRRAs). To further this transcriptomic definition of IRRAs, we wanted to define the proteomic changes that occur in this reactive sub-state. We induced IRRAs in immunopanned rodent astrocytes and human iPSC-differentiated astrocytes using TNF, IL1α, C1Q, and IFNβ and characterized their proteomic profile (both cellular and secreted) using unbiased quantitative proteomics. We identified 2335 unique cellular proteins, including IFIT2/3, IFITM3, OASL1/2, MX1/2/3, and STAT1. We also report that rodent and human IRRAs secrete PAI1, a serine protease inhibitor which may influence reactive states and functions of nearby cells. Finally, we evaluated how IRRAs are distinct from neurotoxic reactive astrocytes (NRAs). While NRAs are described by expression of the complement protein C3, it was not upregulated in IRRAs. Instead, we found ~90 proteins unique to IRRAs not identified in NRAs, including OAS1A, IFIT3, and MX1. Interferon signaling in astrocytes is critical for the antiviral immune response and for regulating synaptic plasticity and glutamate transport mechanisms. How IRRAs contribute to these functions is unknown. This study provides the basis for future experiments to define the functional roles of IRRAs in the context of neurodegenerative disorders.

Engram cell connectivity as a mechanism for information encoding and memory function

Information derived from experiences is incorporated into the brain as changes to ensembles of cells, termed engram cells, which allow memory storage and recall. The mechanism by which those changes hold specific information is unclear. Here, we test the hypothesis that the specific synaptic wiring between engram cells is the substrate of information storage. First, we monitor how learning modifies the connectivity pattern between engram cells at a monosynaptic connection involving the hippocampal ventral CA1 (vCA1) region and the amygdala. Then, we assess the functional significance of these connectivity changes by artificially activating or inhibiting its presynaptic and postsynaptic components, respectively. Finally, we identify a synaptic plasticity mechanism mediated by postsynaptic density protein 95 (PSD-95), which impacts the connectivity pattern among engram cells and contributes to the long-term stability of the memory. These findings impact our theory of learning and memory by helping us explain the translation of specific information into engram cells and how these connections shape brain function.

Theta Burst Stimulation of the Human Motor Cortex Modulates Secondary Hyperalgesia to Punctate Mechanical Stimuli

ObjectivesMany chronic pain conditions show evidence of dysregulated synaptic plasticity, including the development and maintenance of central sensitization. This provides a strong rationale for neuromodulation therapies for the relief of chronic pain. However, variability in responses and low fidelity across studies remain an issue for both clinical trials and pain management, demonstrating insufficient mechanistic understanding of effective treatment protocols. Materials and MethodsIn a randomized counterbalanced crossover designed study, we evaluated two forms of patterned repetitive transcranial magnetic stimulation, known as continuous theta burst stimulation (TBS) and intermittent TBS, during normal and central sensitization states. Secondary hyperalgesia (a form of use-dependent central sensitization) was induced using a well-established injury-free pain model and assessed by standardized quantitative sensory testing involving light touch and pinprick pain thresholds in addition to stimulus-response functions. ResultsWe found that continuous TBS of the human motor cortex has a facilitatory (pronociceptive) effect on the magnitude of perceived pain to secondary hyperalgesia, which may rely on induction and expression of neural plasticity through heterosynaptic long-term potentiation–like mechanisms. ConclusionsBy defining the underlying mechanisms of TBS-driven synaptic plasticity in the nociceptive system, we offer new insight into disease mechanisms and provide targets for promoting functional recovery and repair in chronic pain. For clinical applications, this knowledge is critical for development of more efficacious and mechanisms-based neuromodulation protocols, which are urgently needed to address the chronic pain and opioid epidemics.

Synaptic plasticity and the role of astrocytes in central metabolic circuits.

Neural circuits in the brain, primarily in the hypothalamus, are paramount to the homeostatic control of feeding and energy utilization. They integrate hunger, satiety, and body adiposity cues from the periphery and mediate the appropriate behavioral and physiological responses to satisfy the energy demands of the animal. Notably, perturbations in central homeostatic circuits have been linked to the etiology of excessive feeding and obesity. Considering the ever-changing energy requirements of the animal and required adaptations, it is not surprising that brain-feeding circuits remain plastic in adulthood and are subject to changes in synaptic strength as a consequence of nutritional status. Indeed, synapse density, probability of presynaptic transmitter release, and postsynaptic responses in hypothalamic energy balance centers are tailored to behavioral and physiological responses required to sustain survival. Mounting evidence supports key roles of astrocytes facilitating some of this plasticity. Here we discuss these synaptic plasticity mechanisms and the emerging roles of astrocytes influencing energy and glucose balance control in health and disease. This article is categorized under: Cancer > Molecular and Cellular Physiology Neurological Diseases > Molecular and Cellular Physiology.

A prefrontal cortex alpha/delta switch controls the transition from positive to negative affective states

Positive and negative emotional states in rats can be studied by investigating ultrasonic vocalizations (USVs). Positive affect in rats is indexed by 50 kHz hedonic USVs, and negative affect is indexed by 22 kHz aversive calls. We examined the relationship of emotional states in rats using medial prefrontal cortex (MPFC) quantitative electroencephalograms (qEEG) and found that hedonic USVs were associated with active wake qEEG (high alpha/low delta power), and aversive USVs occurred with groggy wake qEEG (low alpha/high delta). Further, alpha frequency electrical stimulation of the MPFC induces hedonic calls and reward-seeking behavior, whereas delta frequency stimulation produces aversive calls and avoidance behavior. The brain region responsible for generating motor output for USVs, the periaqueductal gray (PAG), shows a motor-evoked potential that is temporally locked to the alpha (hedonic) and delta (aversive) motor-evoked potential. Closed-loop alpha frequency electrical stimulation could prevent delta qEEG and aversive USVs. At the neuronal circuit level, the alpha rhythm was associated with synaptic long-term potentiation (LTP) in the cortex, whereas the delta rhythm was associated with synaptic depotentiation (LTD) in the cortex. At the pharmacological level, NMDAR and growth factor modulation regulated these forms of neuroplasticity. At the single neuron level, excitatory neurons show increased activity in response to alpha frequencies and decreased activity during delta frequencies. In humans, the feeling of joy increased alpha and decreased delta power in frontal scalp qEEG, and the opposite response was seen for sadness. Thus, the synchronization of alpha/delta oscillations through the neuronal circuit responsible for emotional expression coordinates emotional behavior, and the switch between active wake/positive affect and groggy wake/negative affect is under the control of an LTP- LTD synaptic plasticity mechanism.

Neuroprotective mechanism of walnut-derived peptide via C1q-mediated synaptic plasticity in HT22 cells

Synaptic dysfunction is a precursor of cognitive decline and memory impairment in neurodegenerative diseases. The complement component 1q (C1q), and complement pathway contribute to synaptic loss and plasticity, leading to nerve damage. The walnut-derived peptide TWLPLPR (TW-7) has beneficial effect on nerve protection. However, its specific mechanisms are still not fully understood, particularly in C1q-mediated synaptic plasticity. We investigated the neuroprotective effects of TW-7, and the mechanism of C1q-mediated synaptic plasticity in hydrogen peroxide (H2O2)-induced HT22 cells. Treatment with C1q gene plasmid overexpression in HT22 cells showed that TW-7 reduced C1q expression, thus decreasing complement three (C3) expression and increasing the presynaptic protein SYP and postsynaptic protein PSD95. Molecular docking confirmed that TW-7 binding to the recognition site of C1q and reduce synaptic loss. Furthermore, TW-7 inhibited local apoptosis and mediated the phosphoinositide 3-kinase/Programmable Logic Controller/IP3 receptor pathway to maintain intracellular Ca2+ homeostasis and improve synaptic plasticity. Our results suggest that TW-7 exerts a neuroprotective effect in HT22 cells by C1q-mediated synaptic plasticity.

Mechanistic Insights into Synaptic Plasticity Behaviors of Electrolyte-Gated Flexible Transistor Devices.

Biological synaptic function simulation using flexible electronic devices based on low-dimensional semiconductor materials is an emerging and rapidly evolving research field with promising applications in brain-like computers and artificial intelligence systems. In this work, we present the fabrication of solution compatible MoS2 thin-film transistors on the ultrathin polymethyl methacrylate substrates via layer-by-layer assembly followed by a one-step transfer printing method. The MoS2 transport channel is controlled by ionic liquid gating with 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, resulting in excellent synaptic performances for emulating memory and perception synapse functions. To investigate the synaptic behaviors, we conduct a series of synaptic spike-dependent experiments and propose an advanced model that delineates the long-term plasticity and short-term plasticity with separate characteristic factors. These findings provide insights into the fundamental mechanisms of synaptic plasticity in electric double-layer devices and contribute to a better understanding of their synaptic performances. In addition, we examine the effects of bending conditions on synaptic plasticity and synaptic weights, unveiling the synergistic interplay between mechanical deformation and synaptic behaviors. Our experimental results, combined with the developed model, are in good agreement and shed light on the influence of mechanical flexibility on the synaptic properties of the devices. In summary, this study establishes a solid foundation for further development of flexible synaptic devices from both practical and theoretical perspectives.