Search Results (92)

Gliomas are the most common malignant primary brain tumors in adults. The treatment of high-grade gliomas is very limited due to their diffuse infiltration, high plasticity, and resistance to conventional therapies. Although they were long considered passive massive lesions, they are now regarded as functionally integrated components of neural circuits, as they form authentic electrochemical synapses with neurons. This allows them to mimic neuronal activity to drive tumor growth and invasion. Ultrastructural studies show presynaptic vesicles in neurons and postsynaptic densities in glioma cell membranes, while electrophysiological recordings detect postsynaptic currents in tumor cells. Tumor microtubules (TMs), dynamic cytoplasmic protrusions enriched in AMPA receptors, are the structures responsible for glioma–glioma and glioma–neuron connectivity, also contributing to treatment resistance and tumor network integration. In these connections, neurons release glutamate that mainly activates their AMPA receptors in glioma cells, while gliomas release excess glutamate, causing excitotoxicity, altering the local excitatory-inhibitory balance, and promoting a hyperexcitable and pro-tumorigenic microenvironment. In addition, certain gliomas, such as diffuse midline gliomas, have altered chloride homeostasis, which makes GABAergic signaling depolarizing and growth promoting. Synaptogenic factors, such as neuroligin-3 and BDNF, further enhance glioma proliferation and synapse formation. These synaptic and paracrine interactions contribute to cognitive impairment, epileptogenesis, and resistance to surgical and pharmacological interventions. High functional connectivity within gliomas correlates with shorter patient survival. Therapies such as AMPA receptor antagonists (perampanel), glutamate release modulators (riluzole or sulfasalazine), and chloride cotransporter inhibitors (NKCC1 blockers) aim to improve outcomes for patients. Full article

Given the limited efficacy of current interventions and the complexity of chronic pain, identifying perpetuating factors is crucial for uncovering new mechanistic pathways and treatment targets. The oral and gut microbiome has emerged as a potential modulator of pain through immune, metabolic, and neural mechanisms. Contemporary evidence indicates that chronic pain populations exhibit altered oral and gut microbiota, characterized by reduced short-chain fatty acid (SCFA)-producing taxa and an overrepresentation of pro-inflammatory species. These compositional changes affect metabolites such as SCFAs, bile acids, and microbial cell wall components, which interact with host receptors to promote peripheral and central sensitization. Microbiota-derived metabolites modulate peripheral sensitization by altering nociceptive neuron excitability and stimulating immune cells to release pro-inflammatory cytokines that increase blood–brain barrier permeability, activate microglia, and amplify neuroinflammation. Activated microglia further disrupt the balance between excitatory and inhibitory neurotransmission by enhancing glutamatergic activity and weakening GABAergic signaling, thereby contributing to the induction and maintenance of central sensitization. While observational studies establish associations between dysbiosis and chronic pain, animal models and early human fecal microbiota transplantation studies suggest a potential causal role of dysbiosis in pain, although human evidence remains preliminary and influenced by diet, lifestyle, and comorbidities. Overall, microbiota appears to regulate pain via peripheral and central mechanisms, and targeting it through specific interventions, such as dietary modulation to enhance SCFA production, alongside broader lifestyle measures like sleep, physical activity, stress management, and oral hygiene, may represent a new therapeutic strategy for the management of chronic pain. Full article

Background: Repetitive transcranial magnetic stimulation (rTMS) is an established neuromodulatory method, yet its multiscale neurophysiological effects in autism spectrum disorder (ASD) remain insufficiently characterized. Recent EEG analytic advances—such as spectral parameterization, long-range temporal correlation (LRTC) assessment, and connectivity modeling—enable quantitative evaluation of excitation–inhibition (E/I) balance and network organization. Objective: This study aimed to examine whether an eight-session, EEG-guided mixed-frequency rTMS protocol—combining inhibitory 1 Hz and excitatory 10 Hz trains individualized to quantitative EEG (qEEG) abnormalities—produces measurable changes in spectral dynamics, temporal correlations, and functional connectivity in a pediatric ASD case. Methods: An 11-year-old right-handed female with ASD (DSM-5-TR, ADOS-2) underwent resting-state EEG one week before and four months after intervention. Preprocessing used a validated automated pipeline, followed by spectral parameterization (FOOOF), detrended fluctuation analysis (DFA), and connectivity analyses (phase-lag index and Granger causality) in MATLAB (2023b). No inferential statistics were applied due to the single-case design. The study was conducted at Cosmos Healthcare (London, UK) with in-kind institutional support and approved by the Atlantic International University IRB (AIU-IRB-22-101). Results: Post-rTMS EEG showed (i) increased delta and reduced theta/alpha/beta power over central regions; (ii) steeper aperiodic slope and higher offset, maximal at Cz, suggesting increased inhibitory tone; (iii) reduced Hurst exponents (1–10 Hz) at Fz, Cz, and Pz, indicating decreased long-range temporal correlations; (iv) reorganization of hubs away from midline with marked Cz decoupling; and (v) strengthened parietal-to-central directional connectivity (Pz→Cz) with reduced Cz→Pz influence. Conclusions: Mixed-frequency, EEG-guided rTMS produced convergent changes across spectral, aperiodic, temporal, and connectivity measures consistent with modulation of cortical E/I balance and network organization. Findings are preliminary and hypothesis-generating. The study was supported by in-kind resources from Cosmos Healthcare, whose authors participated as investigators but had no influence on analysis or interpretation. Controlled trials are warranted to validate these exploratory results. Full article

Parkinson’s disease (PD) is a multisystem disorder, with early changes extending beyond basal ganglia circuitries and involving non-dopaminergic pathways, including cerebellar networks. Whether cerebellar dysfunction reflects a compensatory mechanism or an intrinsic hallmark of disease progression remains unresolved. In this cross-sectional study, we examined how cerebellar γ-aminobutyric acid (GABA) and glutamate/glutamine (Glx) systems, as well as their excitatory/inhibitory (E/I) balance, are modulated along the disease course. As to ascertain how these mechanisms contribute to motor and non-motor features in the premotor and early stages of PD, 18 individuals with isolated REM sleep behavior disorder (iRBD), 20 de novo, drug-naïve PD (dnPD), and 18 matched healthy controls underwent clinical, cognitive, and neuropsychiatric assessments alongside cerebellar magnetic resonance spectroscopy (MRS, MEGA-PRESS, 3T). While cerebellar neurotransmitter levels did not differ significantly across groups, dnPD patients exhibited a shift toward hyperexcitability in the E/I ratio, without correlation to clinical or cognitive measures. In contrast, in iRBD, an inverse relationship between heightened GABAergic activity and neuropsychiatric symptoms emerged. These findings suggest an early, dynamic cerebellar involvement, potentially reflecting compensatory modulation of altered basal ganglia output. Our results support cerebellar GABA MRS as a promising biomarker and open perspectives for targeting non-dopaminergic pathways in PD. Full article

The optimal computing ability of spiking neural networks (SNNs) mainly depends on the connection weights of their synapses and the thresholds that control the spiking. In order to realize the optimization calculation of different objective functions, it is necessary to modify the connection weights adaptively and make the thresholds dynamically self-learning. However, it is very difficult to construct an adaptive learning algorithm for spiking neural networks due to the discontinuity of neuron spike sending process, which is also a fatal problem in this field. In this paper, an efficient adaptive learning algorithm for spiking neural networks is proposed, which adjusts the weights of synaptic connections by a learning factor adaptively and adjusts the probability of spike sending by the self-organizing learning method of the dynamic threshold, so as to achieve the goal of automatic global search optimization. The algorithm is applied to the learning task of global optimization, and the experimental results show that this algorithm has good stability and learning ability, and is effective in dealing with complex multi-objective optimization problems of spatiotemporal spike mode. Moreover, the proposed framework explicitly leverages problem and model symmetries. In Traveling Salesman Problems, distance symmetry (d(i, j) = d(j, i)) and tour permutation symmetry are preserved by our spike-train-based similarity and energy updates, which do not depend on node labels. Together with the homogeneous neuron dynamics and balanced excitatory–inhibitory populations, these symmetry-aware properties reduce the effective search space and enhance the convergence stability. Full article

Depression is one of the most disabling of all disorders across the community, yet many aspects of the disorder remain contentious. Psychosocial and biological perspectives are often placed in opposition to one another, which in part reflects a failure of our explanatory frameworks. The active inference account of brain function breaks down this dualism, demonstrating that bodily processes are deeply integrated with the social world. It shows us that there is no contradiction in understanding depression as a product of the social environment at the same time as having a brain basis and manifesting in biological symptoms. From an active inference perspective, depression can be thought of as a synaptopathy: a disorder that arises from alterations to the excitatory-inhibitory balance enacted at the synapse, reflecting the interoceptive precision-weightings that have changed in the context of psychosocial instability. Therapies that alleviate depressive symptoms act at different levels of the active inference framework to re-weight precision estimates and the confidence we have in our predictions: this is true for psychotherapies, lifestyle interventions and antidepressant medications. Their effectiveness is often only partial, and while different treatment modalities can complement one another, there is a need for continued development of new and better treatment options. Full article

The organization of consciousness is described through increasingly rich theoretical models. We review evidence that working memory capacity—essential to generating consciousness in the cerebral cortex—is supported by dual limbic memory systems. These dorsal (Papez) and ventral (Yakovlev) limbic networks provide the basis for mnemonic processing and prediction in the dorsal and ventral divisions of the human neocortex. Empirical evidence suggests that the dorsal limbic division is (i) regulated preferentially by excitatory feedforward control, (ii) consolidated by REM sleep, and (iii) controlled in waking by phasic arousal through lemnothalamic projections from the pontine brainstem reticular activating system. The ventral limbic division and striatum, (i) organizes the inhibitory neurophysiology of NREM to (ii) consolidate explicit memory in sleep, (iii) operating in waking cognition under the same inhibitory feedback control supported by collothalamic tonic activation from the midbrain. We propose that (i) these dual (excitatory and inhibitory) systems alternate in the stages of sleep, and (ii) in waking they must be balanced—at criticality—to optimize the active inference that generates conscious experiences. Optimal Bayesian belief updating rests on balanced feedforward (excitatory predictive) and feedback (inhibitory corrective) control biases that play the role of prior and likelihood (i.e., sensory) precision. Because the excitatory (E) phasic arousal and inhibitory (I) tonic activation systems that regulate these dual limbic divisions have distinct affective properties, varying levels of elation for phasic arousal (E) and anxiety for tonic activation (I), the dual control systems regulate sleep and consciousness in ways that are adaptively balanced—around the entropic nadir of E–I criticality—for optimal self-regulation of consciousness and psychological health. Because they are emotive as well as motive control systems, these dual systems have unique qualities of feeling that may be registered as subjective experience. Full article

A balanced excitatory/inhibitory (E/I) tone is crucial for proper brain function, and disruptions can lead to neurological disorders. This review explores the role of astrocytes in maintaining a balanced E/I tone in the brain, which is crucial for proper functioning. It highlights the potential for dysfunctional astrocyte metabolism to disrupt E/I balance, leading to neuronal dysfunction and potentially causing neurological disease pathogenesis. The review focuses on glucose, lactate shuttling, and glutamate metabolism. This review synthesizes findings from in vitro, in vivo, and human studies examining the interplay between astrocyte metabolism, neuronal activity, and E/I balance. Literature searches were conducted using keywords including “astrocyte metabolism”, “excitatory/inhibitory balance”, “glutamate”, “lactate shuttle”, “neurometabolic coupling”, and “neurological disorders” in databases such as PubMed and Web of Science. Disruptions in astrocyte glucose uptake or glycolysis can impair lactate production, reducing neuronal energy supply and affecting neuronal excitability. Impaired glutamate uptake and conversion to glutamine within astrocytes leads to elevated extracellular glutamate, promoting excitotoxicity. Altered glycogen metabolism and other metabolic impairments within astrocytes can also affect neuronal health and contribute to imbalances between excitation and inhibition. Dysfunctional astrocyte metabolism represents a significant contributor to E/I imbalance in the brain. Understanding the specific metabolic vulnerabilities of astrocytes and their impact on neuronal function provides potential therapeutic targets for neurological disorders characterized by E/I dysregulation. Targeting astrocyte metabolism may offer a novel approach to restoring E/I balance and improving neurological outcomes. Full article

This study examined spontaneous activity in children aged 3–11 years with specific language impairment (SLI) using an electroencephalogram (EEG). We compared SLI-diagnosed children with a normo-development group (ND). The signal complexity, multiscale entropy (MSE) and parameterized power spectral density (FOOOF) were analyzed, decomposing the PSD into its aperiodic (AP, proportional to 1/fx) and periodic (P) components. The results showed increases in complexity across scales in both groups. Although the topographic distributions were similar, children with SLI exhibited an increased AP component over a broad frequency range (13–45 Hz) in the medial regions. The P component showed differences in brain activity according to the frequency and region. At 9–12 Hz, ND presented greater central–anterior activity, whereas, in SLI, this was seen for posterior–central. At 33–36 Hz, anterior activity was greater in SLI than in ND. At 37–45 Hz, SLI showed greater activity than ND, with a specific increase in the left, medial and right regions at 41–45 Hz. These findings suggest alterations in the excitatory–inhibitory balance and impaired intra- and interhemispheric connectivity, indicating difficulties in neuronal modulation possibly associated with the cognitive and linguistic characteristics of SLI. Full article

Frmpd3 (FERM and PDZ Domain Containing 3), a scaffold protein potentially involved in excitatory synaptic function, has not been thoroughly characterized in terms of its expression and functional role in vivo. Here, we investigated the distribution of Frmpd3 in the central nervous system and its potential regulatory role in epilepsy, a neurological disorder characterized by disrupted excitatory–inhibitory balance. The distribution of Frmpd3 throughout the mouse brain was investigated by immunofluorescence. Western blotting was conducted to examine potential alterations in Frmpd3 protein expression in the hippocampus of a pentylenetetrazol (PTZ)-induced chronic epilepsy model. Using stereotaxic techniques, we delivered Frmpd3 siRNA-AAV9 into the hippocampal CA1 region to achieve targeted protein knockdown. Then, the functional consequences of Frmpd3 depletion were assessed through behavioral observations and electrophysiological recordings in PTZ-treated mice. Finally, protein–protein interactions were investigated using immunoprecipitation and Western blot analysis. Immunofluorescence analysis revealed Frmpd3 expression in cortical, hypothalamic, cerebellar, and hippocampal neurons of adult mice. Subcellular localization studies demonstrated predominant distribution of Frmpd3 in the excitatory postsynaptic density (PSD) of hippocampal CA1 neurons, with additional expression in inhibitory neurons. Quantitative analysis showed significantly elevated Frmpd3 protein levels in the hippocampus of PTZ-induced epileptic mice compared to controls. Frmpd3 knockdown in the CA1 region resulted in the following: (1) reduced seizure frequency, (2) prolonged seizure latency, and (3) decreased incidence of PTZ-induced generalized seizures. Local field potential (LFP) recordings demonstrated that seizure amplitude tended to be reduced, and epileptic discharge durations tended to be shorter in Frmpd3-depleted mice compared to controls. Furthermore, we observed decreased membrane expression of the AMPA receptor GluA2 subunit in the hippocampus of Frmpd3 knockdown mice. Molecular interaction studies revealed that Frmpd3 forms complexes with glutamate receptor-interacting protein (GRIP) and GluA2. Our findings identify Frmpd3 as a novel regulatory scaffold protein that modulates epileptic susceptibility through molecular interactions with GRIP and GluA2. The underlying mechanism appears to involve Frmpd3-mediated regulation of GluA2 trafficking from the cytoplasm to the membrane, ultimately enhancing neuronal excitability through increased membrane expression of GluA2-containing AMPA receptors. Full article

The precise regulation of synaptic function by targeted protein degradation is fundamental to learning and memory, yet the roles of many brain-enriched E3 ubiquitin ligases in this process remain elusive. Here, we uncover a critical and previously unappreciated role for the E3 ubiquitin ligase PRAJA1 in orchestrating synaptic plasticity and hippocampus-dependent memory. Utilizing C57BL/6 and 5xFAD male mice and employing a multi-faceted approach including protein biochemistry, molecular biology, in vitro electrophysiology, and behavioral assays, we demonstrate that long-term potentiation (LTP) induction triggers a rapid, proteasome-dependent downregulation of PRAJA1 within the CA1 region of the hippocampus. Critically, selective knockdown of PRAJA1 in vivo profoundly enhanced both object recognition and spatial memory, while disrupting normal exploratory behavior. Mechanistically, we reveal that PRAJA1 acts as a key regulator of synaptic architecture and transmission: its downregulation leads to a reduction in key synaptic proteins and spine density, influencing the excitatory/inhibitory balance and facilitating synaptic plasticity. Conversely, increased PRAJA1 expression potentiates GABAergic transmission. Furthermore, we identify spinophilin as a novel substrate of PRAJA1, suggesting a direct molecular link between PRAJA1 and synaptic remodeling. Strikingly, our findings implicate dysregulation of PRAJA1 in the pathogenesis of Alzheimer’s disease, positioning PRAJA1 as a potential therapeutic target for cognitive enhancement in neurodegenerative conditions. These results unveil PRAJA1 as a critical molecular brake on synaptic plasticity and memory formation, offering a promising new avenue for understanding and potentially treating memory impairment. Full article

Neural excitatory/inhibitory (E/I) imbalance plays a pivotal role in the aging process. However, despite its significant impact, the role of E/I imbalance in motor dysfunction and neurodegenerative diseases has not received sufficient attention. This review explores the mechanisms underlying motor aging through the lens of E/I balance, emphasizing genetic and molecular factors that contribute to this imbalance (such as SCN2A, CACNA1C, GABRB3, GRIN2A, SYT, BDNF…). Key regulatory genes, including REST, vps-34, and STXBP1, are examined for their roles in modulating synaptic activity and neuronal function during aging. With insights drawn from ALS, we discuss how disruptions in E/I balance contribute to the pathophysiology of age-related motor dysfunction. The genes discussed above exhibit a certain association with age-related motor neuron diseases (like ALS), a relationship that had not been previously recognized. Innovative genetic therapies, such as gene editing technology and optogenetic manipulation, are emerging as promising tools for restoring E/I balance, offering hope for ameliorating motor deficits in aging. This review explores the potential of these technologies to intervene in aging-related motor diseases, despite challenges in their direct application to human conditions. Full article

Interactions between excitatory and inhibitory neurons in the cerebral cortex give rise to different regimes of activity and modulate brain oscillations. A prominent regime in the cortex is the inhibition-stabilized network (ISN), defined by strong recurrent excitation balanced by inhibition. While theoretical models have captured the response of brain circuits in the ISN state, their connectivity is typically hard-wired, leaving unanswered how a network may self-organize to an ISN state and dynamically switch between ISN and non-ISN states to modulate oscillations. Here, we introduce a mean-rate model of coupled Wilson-Cowan equations, link ISN and non-ISN states to Kolmogorov-Sinai entropy, and demonstrate how homeostatic plasticity (HP) allows the network to express both states depending on its level of tonic activity. This mechanism enables the model to capture a broad range of experimental effects, including (i) a paradoxical decrease in inhibitory activity, (ii) a phase offset between excitation and inhibition, and (iii) damped gamma oscillations. Further, the model accounts for experimental work on asynchronous quenching, where an external input suppresses intrinsic oscillations. Together, findings show that oscillatory activity is modulated by the dynamical regime of the network under the control of HP, thus advancing a framework that bridges neural dynamics, entropy, oscillations, and synaptic plasticity. Full article

Most brain development occurs in the “first 1000 days”, a critical period from conception to a child’s second birthday. Critical brain processes that occur during this time include synaptogenesis, myelination, neural pruning, and the formation of functioning neuronal circuits. Perturbations during the first 1000 days likely contribute to later-life neurodegenerative disease, including sporadic amyotrophic lateral sclerosis (ALS). Neurodevelopment is determined by many events, including the maturation and colonization of the infant microbiome and its metabolites, specifically neurotransmitters, immune modulators, vitamins, and short-chain fatty acids. Successful microbiome maturation and gut–brain axis function depend on maternal factors (stress and exposure to toxins during pregnancy), mode of delivery, quality of the postnatal environment, diet after weaning from breast milk, and nutritional deficiencies. While the neonatal microbiome is highly plastic, it remains prone to dysbiosis which, once established, may persist into adulthood, thereby inducing the development of chronic inflammation and abnormal excitatory/inhibitory balance, resulting in neural excitation. Both are recognized as key pathophysiological processes in the development of ALS. Full article

Focal cortical dysplasia (FCD) is a leading cause of drug-resistant epilepsy; however, the mechanisms underlying hyperexcitability in the affected cortical regions remain poorly understood. In this study, we employed a freeze-induced neocortical malformation model in rats to investigate the electrophysiological properties of pyramidal neurons surrounding the microgyrus and to evaluate changes in synaptic transmission. Using whole-cell patch-clamp recordings, we analyzed passive and active membrane properties, synaptic responses, and epileptiform activity in brain slices from rats with FCD and sham-operated controls. Our results revealed that while the intrinsic biophysical properties of neurons remained largely unchanged, the summation of excitatory and inhibitory inputs was significantly enhanced. Notably, the balance of inhibitory and excitatory synaptic currents was shifted toward excitation, making the perilesional cortex more susceptible to seizure generation. In a model of epileptiform activity induced by GABA_A receptor blockade and reduced Mg²⁺ concentration, we observed early ictal activity originating in the microgyrus and spreading to adjacent regions. These findings demonstrate that synaptic perturbations, rather than alterations in intrinsic neuronal properties, are the primary drivers of hyperexcitability in this model. Our study highlights the importance of synaptic dysregulation in FCD-related epilepsy and suggests that targeting synaptic transmission may offer a promising therapeutic strategy for controlling seizures in patients with cortical malformations. Full article