Search Results (113)

Focal task-specific dystonia (FTSD) is an isolated dystonia in which abnormal muscle contractions occur only during a particular motor task while most other movements remain relatively spared. In this hypothesis article, we propose that FTSD arises within a task-specific motor synergy (TSMS) in primary motor cortex (M1), a local excitatory–inhibitory ensemble supporting a specific movement component of the affected task. We hypothesize that excitatory synapses within the affected TSMS become disproportionately strong relative to parvalbumin (PV)-centered inhibitory circuitry, creating a hyperexcitable dystonic synergy recruited when attempted task intensity exceeds the capacity of the residual functional synergy. A change in movement coordination is proposed to reduce the capacity of a previously established TSMS, producing a state of task-specific output limitation, termed true weakness, at higher intensities. Repeated overreaching beyond this reduced capacity may then favor excitatory over inhibitory strengthening, thereby driving the emergence and progressive consolidation of the dystonic synergy and generating the symptom-threshold phenomenon. Under the imposed architecture and parameterization, a spiking neural network exhibited an input-dependent crossover in the relative firing rates of specified functional and E/I-imbalanced model populations. We interpret these results as supporting an E/I-balance mechanism for the crossover, while recognizing that other parameter combinations can produce the same behavior, consistent with degeneracy. Structural contributions require further investigation to distinguish these possibilities. Finally, we propose below- or at-threshold retraining (BATR), in which symptom-free practice may promote inhibitory rebalancing and raise the symptom-threshold. This framework offers an experimentally testable M1-centered account of FTSD. Full article

The primary motor cortex (M1) controls voluntary movements through coordinated interactions between excitatory pyramidal neurons and inhibitory parvalbumin-expressing interneurons (PV-INs). Although PV-INs are critical to regulating motor output and motor coordination, their role in age-related motor decline remains unclear. Here, we investigated how aging alters PV-IN-associated regulation of corticospinal tract (CST) output in mice. Aged mice (14–24 months) exhibited selective motor impairments, including deficits in balance and hindlimb-supported performance, while general locomotor activity remained largely preserved. We combined optogenetics, ex vivo electrophysiology, retrograde tracing, and in vivo electromyographic (EMG) recordings. In aged M1 slices, optogenetic stimulation of the PV-IN-targeted network produced small extracellular-like voltage deflections recorded with a loose-apposed, non-sealed pipette configuration. These responses persisted during GABA_A receptor blockade but were abolished by DNQX and APV, indicating engagement of an ionotropic glutamate receptor-dependent network mechanism. Whole-cell recordings obtained in separate experiments demonstrated that conventional inhibitory PV-IN-to-pyramidal transmission remained detectable during repetitive stimulation. In vivo, PV-IN activation increased M1-evoked hindlimb EMG responses in aged mice but had little effect in young animals. Together, these findings identify an age-dependent reorganization of PV-IN-associated motor-cortical network function that alters the recruitment of glutamatergic mechanisms and corticospinal motor output. The present data do not establish the precise synaptic topology of this network response or whether the reorganization is compensatory or maladaptive. Full article

Parkinson’s disease (PD) is characterized by progressive dopaminergic degeneration and maladaptive motor cortical plasticity. However, the cellular pathways underlying cortical surface activity in the primary motor cortex (M1) remain unclear, despite serving as a potential target for electrotherapy. We investigated the excitatory–inhibitory (E-I) balance and synaptic plasticity of superficial M1 circuits in a unilateral 6-hydroxydopamine (6-OHDA)-induced rat model of PD. Using extracellular local field potential and whole-cell patch recordings from the contralateral and ipsilateral M1 hemispheres of hemi-parkinsonian rats, we observed a significantly elevated field excitatory postsynaptic potential (fEPSP) input–output function but unchanged intrinsic neuronal excitability in the M1 superficial layer. An altered relative contribution between alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)- and N-methyl-D-aspartate receptor (NMDAR)-mediated transmission was reflected by a significantly increased AMPA/NMDA ratio. Markedly reduced inhibitory synaptic tone was also evidenced by the decreased amplitude and frequency of spontaneous inhibitory postsynaptic currents (sIPSCs), supporting an E-I imbalance favoring excitation in PD. Furthermore, group I metabotropic glutamate receptor (mGluR_1/5)-dependent long-term depression (LTD) was abolished in the ipsilateral PD hemisphere, whereas NMDAR-dependent LTD remained intact. In summary, dopamine depletion appears to enhance network excitation and disrupt mGluR_1/5-mediated control of M1 surface circuitry. Our findings identify altered cortical surface mGluR-dependent plasticity in the hemi-parkinsonian model; however, the relationship between these electrophysiological alterations and individual motor outcomes remains to be determined. Full article

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social interactions, communication deficits, and excessive repetitive behaviors. While ASD has a strong genetic basis, growing evidence suggests that epileptic seizures may serve as environmental risk factors for ASD development. The high comorbidity between epilepsy and ASD (20–30%) suggests potential shared neurobiological mechanisms, yet the causal relationship remains poorly understood. To investigate the causal role of seizures in the development of ASD-like pathology, we exposed adolescent mice (3 weeks old) to electroconvulsive seizures (ECS) for 10 consecutive days. This repeated ECS exposure led to the emergence of autistic-like behaviors including significantly decreased sociability, increased repetitive self-grooming, enhanced marble burying behavior, and anxiety-like behaviors, without affecting general locomotor activity. Additionally, repeated exposure to ECS induced significant changes in glutamatergic neurotransmission in the mice’s prefrontal cortex and hippocampus, brain regions critically involved in social cognition and behavioral regulation. Interestingly, these changes occurred without alterations in other excitatory/inhibitory neuronal markers, suggesting a specific impact on glutamate receptor expression rather than a general disruption of excitatory/inhibitory balance. These findings suggest that repeated seizures may contribute to ASD-like symptoms by specifically affecting key glutamatergic neurotransmitter systems, providing insights into the neurobiological mechanisms underlying the comorbidity between epilepsy and autism. In addition, repeated ECS differentially regulated histone deacetylase (HDAC) transcripts in a region-specific manner and produced seizure-intensity-dependent transcriptomic signatures. Full article

Background: The cerebellum integrates sensory information to maintain balance and posture, allowing movement guidance. Perinatal damage to this brain region correlates with an increased incidence of Autism Spectrum Disorder (ASD), a major neurodevelopmental condition where poor motor performance in eye–hand coordination, balance and gait is observed. The cerebellum of ASD individuals is affected by reduced GABAergic signaling that leads to an excitatory/inhibitory imbalance. Methods: Motor coordination behavior were tested and Western blot essays performed to study the developmental expression of GABAergic signaling proteins, namely GABA_A receptor (α1, α2 and β1) subunits and glutamate decarboxylase 67 (GAD67), in CD1 mice prenatally exposed to valproic acid (VPA), a preclinical model of ASD. Results: The VPA group exhibited motor coordination deficits on postnatal day 30 (P30) compared to the control. The expression profiles for the control group revealed that GABA_A-α1 increased linearly, while GABA_A-β1 displayed the opposite pattern and GABA_A-α2 presented one peak of expression (P8). GAD67 decreased from embryonic day 16 (E16) to P8 but increased linearly after the first week of postnatal development (P8-P30). The developmental expression profile for all these proteins was disrupted by prenatal exposure to VPA. Conclusions: Motor coordination deficits correlate with a downregulated expression of GABA_A (α1, α2 and β1) subunits and GAD67 through cerebellar development in individuals that were prenatally exposed to VPA. Full article

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition characterized by impairments in social communication, restricted and repetitive behaviors, sensory dysregulation, and frequent psychiatric comorbidities. Increasing attention has been directed toward acupuncture as a complementary neuro-modulatory intervention; however, its underlying molecular mechanisms remain incompletely understood. This review synthesizes evidence from preclinical, clinical, and molecular studies published between 2015 and 2025 to examine how acupuncture influences neurobiological pathways relevant to ASD. Current evidence indicates that acupuncture modulates multiple neurotransmitter systems, including glutamatergic, GABAergic, dopaminergic, serotonergic, and noradrenergic signaling, while also influencing neurotrophin-mediated plasticity, neuroinflammatory responses, and synaptic function. Studies conducted directly in ASD models demonstrate regulation of excitatory/inhibitory balance, monoaminergic signaling, neurotrophin pathways, and ASD-associated behavioral outcomes, whereas evidence from related neuropsychiatric conditions provides complementary mechanistic support for these pathways. Collectively, the findings suggest that acupuncture may act through coordinated modulation of interconnected neurotransmitter and neuroplasticity networks rather than a single molecular target. However, direct mechanistic evidence in ASD-specific models and clinical populations remains limited, and considerable heterogeneity exists among acupuncture protocols and outcome measures. Future studies integrating standardized stimulation paradigms with molecular, electrophysiological, neuroimaging, and behavioral assessments will be essential to validate the proposed mechanisms and clarify the translational potential of acupuncture in ASD. Full article

Neuropathic pain is a chronic condition resulting from injury or dysfunction of the nervous system, characterized by hyperalgesia, allodynia, and persistent alterations in sensory perception. Neuroligins, a family of postsynaptic adhesion proteins essential for synapse formation and maturation, have emerged as critical regulators of neuronal plasticity and nociceptive circuit excitability. Recent evidence suggests that dysregulation of neuroligin expression and function can modulate synaptic transmission in pain pathways, contributing to the onset and maintenance of neuropathic pain. This review highlights some findings on the role of neuroligins in neuropathic pain pathophysiology, underscoring molecular mechanisms, interactions with glutamatergic and GABAergic receptors, and their potential as innovative therapeutic targets for chronic pain management. Full article

Hypercaloric diet and obesity are strongly associated with cardiovascular dysfunction, diabetes and hypertension development mediated by sympathetic nervous system hyperactivity. In addition to the adrenergic system, purinergic signaling has emerged as a relevant modulator of cardiovascular physiopathology. However, its role in hypercaloric diet-induced cardiovascular dysfunction remains incompletely understood. In this study, we investigated the effects of a hypercaloric diet on metabolic parameters, atrial purinergic modulation and vascular reactivity. Rats fed the hypercaloric diet consumed a diet with ~31% greater caloric density than control animals that received a standard (3.5 kcal/g) pellet diet for 8 weeks. Metabolic and cardiovascular parameters were measured, and isolated right atria (RA), left atria (LA) and thoracic aortic vessels were used to evaluate function, contractility and vascular responsiveness. A hypercaloric diet significantly increased body weight and visceral adiposity, with elevated systolic blood pressure (SBP) and cardiac hypertrophy, associated with alterations in glucose levels and insulin sensitivity. In isolated atria, a hypercaloric diet increased basal contractile force in the LA. Also, ATP induced a biphasic response characterized by an initial negative inotropic effect (NIE) followed by a positive inotropic effect (PIE). A hypercaloric diet reduced ATP-mediated NIE and enhanced PIE in both atria, suggesting an altered balance between inhibitory-P1 and excitatory-P2 purinergic signaling. At the vascular level, a hypercaloric diet impaired adenosine-mediated relaxation and increased contraction, indicating vascular hyperreactivity. Collectively, these findings suggest that a hypercaloric diet induces cardiometabolic dysfunction associated with alterations in cardiovascular function linked to impaired P1/P2 purinergic regulation, contributing to obesity-associated cardiovascular remodeling and hypertension. Full article

Recurrent neural networks are studied along two largely parallel tracks: as machine-learning models evaluated by task performance and as computational-neuroscience models of cortical circuits evaluated by dynamical realism. Reservoir computing offers a meeting point, yet the link between dynamical regime and computational performance has not been systematically mapped in biologically constrained spiking architectures. We treat the Brunel balanced excitatory–inhibitory network as a reservoir and characterize separation capacity (kernel quality) and transient memory (corrected linear memory capacity, validated by non-parametric mutual information) across the full phase diagram. The analysis uses a four-state Markov source whose Shannon entropy rate is set in closed form by a single parameter at fixed marginal entropy. Both capabilities increase monotonically with the inhibitory ratio g, remaining jointly highest in the asynchronous irregular regime, with diminishing increments consistent with eventual saturation; the synchronous irregular regime, despite a network timescale three orders of magnitude longer, supports neither. Memory further requires sparse input coupling: dense coupling collapses the driven timescale and erases memory in every regime. Inhibitory balance thus emerges as a unified architectural control parameter, providing a quantitative design criterion for cortical-circuit modeling and reservoir computing applications. Full article

Excitatory–inhibitory (E-I) local circuits play a central role in synaptic plasticity and neural coding, yet their multilayer learning dynamics remain poorly understood. We constructed a multilayer feedforward spiking neural network with intra-layer E-I connectivity, using Izhikevich neurons to model regular spiking (RS) and fast spiking (FS) cells, and examined cooperative learning under excitatory and inhibitory spike-timing-dependent plasticity (eSTDP and iSTDP). FS-mediated lateral inhibition alleviates the long-term depression bias arising from RS firing rate adaptation via winner-take-all competition, promoting heterogeneous E→E weight differentiation while preserving mean synaptic strength. A $12\times 12$ parameter grid scan shows that iSTDP expands the stable learning region in the E-I parameter space and reveals a sustained cooperative co-evolution of eSTDP and iSTDP during training. For sparse coding, RS adaptation is the primary driver of Lifetime Sparseness, with FS inhibition acting as a cooperative enhancer; the network exhibits low sparseness at the input layer, a rapid increase at the second layer, and a stable plateau in deeper layers. For temporal pattern learning, the selectivity index $d^{\prime }$ improved substantially after training, reaching approximately 1.90 times that of the FS-absent condition; both interval sensitivity and pattern generalization tests confirmed that this advantage is robust across biologically plausible inter-group delays and preserved under small temporal jitter. Mutual information analysis reveals a consistent tendency for intra-layer FS circuits to maintain higher stimulus-related information across deep layers, consistent with FS-mediated suppression of non-specific responses. These findings provide computational evidence, within the scope of the present model, for understanding cortical E-I cooperative plasticity and inform design principles for neuromorphic systems with adaptive inhibitory regulation. Full article

α-Synuclein (α-Syn) is a key presynaptic protein, primarily known for its role in the pathogenesis of Parkinson’s disease (PD) and other synucleinopathies, including dementia with Lewy bodies (DLB). Although much of the research has focused on the nigrostriatal dopamine (DA) pathway, there is growing recognition that the accumulation of misfolded α-Syn in the prefrontal cortex (PFC) is a critical driver of non-motor symptoms and cognitive deficits in PD and DLB. This review examines the dual role of α-Syn in the PFC circuitry, initially exploring its regulation of synaptic vesicle (SV) dynamics and recycling to maintain stable neurotransmission. We highlight its contribution to the modulation of glutamatergic (Glu) and GABAergic (γ-aminobutyric acid, GABA) synapses, which ensures the functional excitatory/inhibitory (E/I) balance of prefrontal circuits. Conversely, in PD and DLB, the transition of functional α-Syn monomers to pathological oligomers triggers a cascade of synaptic failures. We analyze how α-Syn aggregation causes pathology in dendritic spines, leads to a progressive reduction in the density of synaptic markers, and impairs cortical plasticity. Synthesizing evidence from neuroimaging studies, post-mortem human cortical samples, and animal models, this review emphasizes the PFC as a vulnerable brain region where α-Syn-mediated synaptic dysfunction translates into cognitive and emotional deficits. Deciphering these early synaptic alterations is essential for developing neuroprotective strategies that preserve cortical function in PD and DLB. Full article

Background/Objectives: A current debate addresses where syntactic Merge primarily resides: the left-hemisphere posterior inferior frontal gyrus (IFG) or the temporo-parietal cortex. For proponents of the former, the temporo-parietal cortex supports more effortful processing; for the latter, the IFG supports integration and conflict resolution. We examine aperiodic activity in processing wh-filler-gap dependencies in French for evidence from network dynamics addressing engagement in syntax across L1 and L2. Methods: We extracted aperiodic activity 1/f components (considering offsets as a reflection of neuronal spiking and exponents as a reflection of excitatory–inhibitory balance) out of power spectrum density at 0.5–40 Hz across occipital and bilateral frontal and temporo-parietal regions of interest (ROIs) in reading. Results: Greater exponents arose in temporo-parietal than frontal ROIs in L1 and L2, with strong spiking and regulation suggested by greater offsets and exponents in the occipital ROI in L2—unlike L1—and with potential modulation by L1–L2 representation overlaps. These patterns suggest distributed cell assemblies for L1 and L2 processing. Increased regulation in temporo-parietal ROIs across L1 and L2 cell assemblies might suggest a structural function across temporo-parietal cortices in syntactic processing. Conclusions: Aperiodic activity reflecting connectivity in L1 and L2 processing supports distinct L1 and L2 cell assemblies, with L2 patterns suggesting potential overlap between L1 and L2 circuit modules. Greater exponents in bilateral temporo-parietal ROIs across L1 and L2 indicate increased regulation, supporting the engagement of lateralized temporo-parietal cortices in computations. These effects are discussed by considering advances in syntactic theory and the biology of language readiness. Full article

Temporal lobe epilepsy (TLE) is a common drug-resistant epilepsy characterized by recurrent seizures, cognitive impairment, aberrant adult hippocampal neurogenesis, inhibitory circuit disruption, and persistent inflammatory remodeling. Current anti-seizure medications primarily offer symptomatic control and do not target the progressive structural and functional deterioration of epileptic hippocampal networks. Here, we investigated whether local nerve growth factor (NGF)-hydrogel delivery during the latent phase after status epilepticus could mitigate hippocampal pathological remodeling and improve long-term outcomes in a kainic acid (KA)-induced mouse model (utilizing C57BL/6J and Nestin-CreERT2 mice). Animals were randomly assigned to three groups: the saline control group, the untreated KA epilepsy group, and the KA + NGF-hydrogel treatment group. NGF-hydrogel was administered into hippocampal Cornu Ammonis 1 (CA1) beginning 3 days post-kainic acid and repeated every 15 days. Histological, immunofluorescence, circuit-tracing, electrophysiology, electroencephalography (EEG), and behavioral assessments were used to evaluate neurogenesis, microenvironment, circuit readouts, seizure burden, and cognition. NGF-hydrogel treatment was associated with preserved dentate gyrus neural stem cell populations, improved newborn granule cell localization and maturation, attenuated neuroinflammation and gliosis, and partial recovery of inhibitory interneuron markers. These changes were accompanied by improved hippocampal circuit readouts, reduced chronic spontaneous seizure burden, and enhanced recognition and spatial memory. Our findings indicate that local NGF-hydrogel delivery following status epilepticus is associated with improved hippocampal remodeling and functional outcomes, and suggest that biomaterial-based neurotrophic support may be a promising strategy for providing targeted neuroprotection and facilitating excitatory/inhibitory (E/I) balance reconstruction in the epileptic hippocampus. Full article

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition characterized by complex interactions among genetic, environmental, and biological factors. Increasing evidence suggests that immune system processes intersect with neurodevelopment in ways that may influence brain maturation, synaptic organization, and large-scale network function. However, existing literature is often fragmented across molecular, cellular, and systems levels, limiting the development of a coherent interpretive framework. In this review, we propose a developmental neuroimmune cascade model of ASD, in which early-life immune perturbations, arising from prenatal or perinatal factors, may interact with genetic susceptibility to influence cytokine signaling, microglial function, blood-brain barrier dynamics, and gut-immune communication. These processes may, in turn, affect synaptic pruning, excitatory-inhibitory balance, and the maturation of neural circuits, contributing to alterations in large-scale brain networks implicated in sensory processing, interoception, and social cognition. We synthesize evidence from observational human studies, postmortem analyses, and experimental animal models to examine how immune-related mechanisms may contribute to neurodevelopmental trajectories associated with ASD, while explicitly distinguishing associative findings from mechanistic inference. Particular attention is given to the role of distributed network vulnerability, including, but not limited to, insula-centered systems that integrate internal bodily states with affective and cognitive processing. Finally, we consider implications for biomarker development and stratified intervention approaches, emphasizing the importance of developmental timing, biological heterogeneity, and cautious interpretation of translational potential. Rather than positioning immune dysfunction as a singular cause of ASD, this model conceptualizes neuroimmune processes as modulators of developmental trajectories, offering a structured basis for future research linking immune signaling to circuit-level and behavioral outcomes. Full article

Epilepsy is a prevalent neurological disorder characterized by recurrent seizures, and electroencephalogram (EEG) signals provide a direct measure of brain activity for detection. Although deep learning achieves high accuracy, it often lacks physiological interpretability. We propose the Excitation/Inhibition Dynamic Polynomial Network (E/I-DynPolyNet), a biologically grounded framework for interpretable seizure detection. Specifically, E/I-DynPolyNet introduces a dual excitatory/inhibitory (E/I) pathway with sign-constrained synaptic weights, encouraging the learned activations to reflect latent E/I representations. Furthermore, a differentiable Wilson-Cowan (WC) module is embedded to govern the temporal evolution of E/I interactions, ensuring consistency with neurophysiological principles. A physics-informed optimization strategy integrates supervised learning with dynamical residual constraints and E/I balance regularization, guiding the model to learn physiologically consistent representations. Experimental results on the CHB-MIT and Bonn datasets demonstrate competitive accuracies of 95.81% and 98.5%, respectively. Crucially, E/I-DynPolyNet enables quantitative estimation of E/I imbalance, revealing that E/I ratios increase from 1.01 in the pre-ictal phase to 1.38 during seizures—a finding consistent with clinical observations of ictogenesis. These results indicate that E/I-DynPolyNet not only improves detection performance but also provides a mechanistic description of seizure dynamics, bridging the gap between data-driven learning and neurophysiological interpretation. Full article