bioRxiv Subject Collection: Neuroscience's Journal

SNCA-targeted epigenome therapy for Parkinsons disease alleviates pathological and behavioral perturbations in a mouse model
Alpha-synuclein (SNCA) overexpression is implicated in Parkinsons disease (PD) pathogenesis, making SNCA downregulation a promising therapeutic strategy. We developed a SNCA-targeted epigenome therapy using an all-in-one lentiviral vector (LV) carrying deactivated CRISPR/(d)Cas9, gRNA targeted at SNCA-intron1, and either the catalytic domain of DNA-methyltransferase3A (DNMT3A), or a synthetic repressor molecule of Kruppel-associated box (KRAB)/ methyl CpG binding protein 2 transcription repression domain (MeCp2-TRD). Therapeutic efficacy was evaluated in a new PD mouse model, generated with an adeno-associated viral vector carrying an engineered minigene comprised of the human (h)A53T-SNCA expressed via the human native regulatory region. Both therapeutic vectors reduced expression of -synuclein in the substantia nigra (SN), with LV/dSaCas9-KRAB-MeCP2(TRD) demonstrating greater repression. LV/dSaCas9-KRAB-MeCP2(TRD) also significantly reduced pathological -synuclein aggregation and phosphorylation (Ser129), and preserved tyrosine hydroxylase expression in the SN and the striatum. Behavioral analysis following LV/dSaCas9-KRAB-MeCP2(TRD) injection, showed significant improvement in motor deficits characteristic of our PD-mouse model. Safety assessments found normal blood counts, serum chemistry, and weights. Collectively, we provide in vivo proof-of-concept for our SNCA-targeted epigenome therapy in a PD-mouse model. Our results support the systems therapeutic potential for PD and related synucleinopathies and establish the foundation for further preclinical studies toward investigational new drug enablement.

Alpha-synuclein overexpression without vocalization deficits in a mouse model of parkinsonism.
Voice deficits are common in Parkinsons disease (PD) and significantly impact quality of life by increasing stress, social isolation, and caregiver burden. However, despite this impact, there are currently no treatments that target the underlying pathophysiology of PD in the vocalization system. The goal of this study was to examine the effect of one possible underlying mechanism responsible for the complex voice deficits that exist in PD; overexpression of the protein alpha-synuclein. Results show that overexpression of alpha-synuclein, prior to the development of alpha-synuclein aggregate pathology, does not result in significant vocalization deficits. A small but statistically significant increase in the total number of complex vocalizations was found in mice overexpressing alpha-synuclein compared to wildtype mice, but there were no differences in complexity ratio or any of the other specific vocalization parameters tested. Results provide a critical foundational understanding of the impact of overexpression versus aggregation of alpha-synuclein on voice deficits in PD. Future work will focus on manipulation of alpha-synuclein aggregate pathology, and not overexpression alone, to reduce or eliminate the burden of PD specific voice disorders.

Summary StatementThis study shows that overexpression of alpha-synuclein alone does not result in significant vocalization deficits, indicating that alpha-synuclein aggregate pathology within the vocalization system is required to induce vocalization deficits.

Robust functional ultrasound imaging in the awake and behaving brain: a systematic framework for motion artifact removal
Functional ultrasound imaging (fUSI) is a promising tool for studying brain activity in awake and behaving animals, offering insights into neural dynamics that are more naturalistic than those obtained under anesthesia. However, motion artifacts pose a significant challenge, introducing biases that can compromise the integrity of the data. This study provides a comprehensive evaluation and benchmarking of strategies for detecting and removing motion artifacts in transcranial fUSI acquisitions of awake mice. We evaluated 792 denoising strategies across four datasets, focusing on clutter filtering, scrubbing, frequency filtering, and confound regression methods. Our findings highlight the superior performance of adaptive clutter filtering and aCompCor confound regression in mitigating motion artifacts while preserving functional connectivity patterns. We also demonstrate that high-pass filtering is generally more effective than band-pass filtering in the presence of motion artifacts. Additionally, we show that with effective clutter filtering, scrubbing may become optional, which is particularly beneficial for experimental designs where motion correlates with conditions of interest. Based on these insights, we propose four optimized denoising paradigms tailored to different experimental constraints, providing practical recommendations for enhancing the reliability and reproducibility of fUSI data. Our findings challenge current practices in the field and have immediate practical implications for existing fUSI analysis workflows, paving the way for more sophisticated applications of fUSI in studying complex brain functions and dysfunctions in awake experimental paradigms.

Brain Representations of Natural Sound Statistics
Natural sound textures, such as rain or crackling fire, are defined by time-averaged summary statistics that shape their perceptual identity. Variations in these statistics provide a controlled means to examine how the human brain processes complex auditory structure. In this study, we investigated how such statistics are represented along the ascending auditory pathway, within auditory cortex, and in high-level regions involved in natural pattern analysis. Using fMRI, we measured brain responses to synthetic sound textures in which higher-order statistical structure was systematically degraded while preserving the overall texture category. Participants listened to sounds with varying levels of naturalness, defined by their statistical fidelity to real-world textures, and performed a perceptual comparison task, judging whether two sequentially presented sounds matched in naturalness. We observed that increasing naturalness elicited stronger BOLD responses across bilateral auditory cortex for both reference and test sounds. Activity in medial temporal lobe regions, including the entorhinal cortex and hippocampus, was modulated by naturalness in a position-dependent manner. The entorhinal cortex activity was modulated only during the test sound, suggesting a role in perceptual-mnemonic comparison. The hippocampal connectivity with auditory cortex increased when reference textures were more degraded or less natural, indicating top-down inference under uncertainty. Together, these findings highlight the interplay between bottom-up encoding and memory-based mechanisms in supporting judgments of auditory realism based on summary statistics.

HIPPOCAMPAL THETA OSCILLATIONS DURING CONTROLLED SPEED RUNS ON A TREADMILL
Hippocampal theta (6-12 Hz) oscillations coordinate neural activity during spatial navigation and are strongly related to locomotion speed. However, recent research has yielded conflicting evidence on whether theta rhythms are primarily modulated by acceleration or instantaneous speed. Moreover, the role of movement transitions--at locomotion onset and offset--has often been overlooked, despite potentially involving distinct dynamics not explained by speed or acceleration alone. Previous studies have rarely controlled for locomotion timing and speed, limiting our ability to dissociate the contributions of speed, acceleration, and movement transitions. To address this, we used a computer-controlled treadmill to induce rat locomotion under three distinct conditions: (a) movement transitions, (b) steady running at constant speed, and (c) locomotion with continuous acceleration. This setup allowed precise spectral analysis of hippocampal theta oscillations across conditions. We found that treadmill-triggered movement transitions produced sustained increases in theta power and transient increases in theta frequency. Upon treadmill stop, theta power decreased slowly, whereas theta frequency dropped rapidly. Steady running elevated both theta power and frequency relative to rest. During constant-speed trials, both metrics increased with speed and remained stable over time. Notably, the acceleration rate itself had no effect on theta power or frequency. Instead, during accelerating trials, theta frequency increased progressively with instantaneous speed, underscoring speed as the primary modulator. In summary, our results show that movement transitions induce distinct, sustained changes in theta power and transient changes in theta frequency, while instantaneous speed--not acceleration--governs hippocampal theta frequency.

Significance statementThe precise contributions of movement transitions, speed, and acceleration to hippocampal theta oscillations remain unclear due to confounding factors in freely moving paradigms. To resolve this, we employed a computer-controlled treadmill to systematically isolate each locomotor variable under tightly controlled conditions. Our results demonstrate that movement transitions induce distinct changes in theta power and frequency, and that instantaneous speed--not acceleration--robustly modulates theta frequency across hippocampal subregions. These findings clarify an ongoing debate and refine our understanding of how specific locomotor dynamics shape hippocampal activity during navigation.

Complement C3aR deletion does not attenuate neurodegeneration in a tauopathy model or alter acute inflammation-induced gene expression changes in the brain
Aberrant activation of the classical complement pathway in the brain is implicated in contributing to synapse loss and neurodegeneration in various neurodegenerative conditions. Given that C3aR is a druggable target in the complement pathway, we evaluated the potential of C3aR KO to rescue neurodegeneration in a tauopathy model and neuroinflammatory responses in an acute endotoxemia model. We found that C3aR KO did not rescue tau pathology, microglia activation markers, neurodegeneration, or behavioral abnormalities in tauopathy model mice. While we found that endotoxemia resulted in numerous transcriptional changes including distinct alterations in subpopulations of microglia, astrocytes and oligodendrocytes, C3aR KO did not impact these alterations. Together, our results suggest that the beneficial effects of blocking the complement classical pathway in neurodegeneration models is likely independent of C3aR activation and raise questions about the rationale for therapeutically targeting C3aR for neurodegenerative disease.

Behavioural, biochemical and functional phenotyping of chronic exposure to chlordecone in mice
BackgroundChlordecone (CLD) is a persistent organochloride pesticide formerly used against banana weevil. It is detectable in blood samples from a large proportion of the population in the French Caribbean Islands. Several experimental studies have demonstrated acute neurotoxicity of CLD, but the effect of a subchronic exposure to CLD remains to be studied.

MethodsYoung adult male mice were injected intraperitoneally with 3 mg/kg CLD (n=34) or vehicle (n=22), twice a week, for eight weeks. Behavior, regional brain accumulation, and effects on the dopaminergic system were studied. In addition, functional ultrasound imaging (fUSi) was used to probe the visual, somatosensory and dopaminergic pathways.

ResultsCLD was detected in all brain regions (5-15 mg/kg) after two-month exposure, without any marked impact on behavior (anxiety, motor coordination, memory). The dopaminergic system was mostly unaffected, despite slight decreases in the number of TH-positive neurons and the expression of VMAT2, quantified in a subset of animals. fUSi highlighted a decreased response to the visual stimulation in CLD-exposed animals, in contrast to the sensorimotor response, which was found unaltered.

ConclusionThe two-month-long, systemic, exposure to an intermediate dose of CLD resulted in a mostly unaffected phenotype, with a normal behavior and a largely intact dopaminergic system. Interestingly, functional ultrasound imaging was able to detect an altered visual response, which has also been noted in Parkinsons disease. This study position functional ultrasound imaging as a promising technique to capture early signs of neurotoxicity, opening up opportunities for "toxico-fUS" in the field of neurotoxicology.

HighlightsHigh CLD neurotropism confirmed in mice by LC-MS/MS.

Sub-chronic chlordecone exposure suggests possible early signs of parkinsonism. Functional UltraSound reveals impairment of brain areas linked to vision and hearing.

Minocycline treatment affects astrocyte - microglia - neuron interaction and functional compensation of motor deficits in rat model of combined fluorocitrate and 6-OHDA lesion and early Parkinson's disease
Prolonged nervous system inflammation and glia activation are among hallmarks of Parkinsons disease. There are no therapies slowing pathology. Microglia and astrocytes are considered targets for disease modifying strategies. Nigrostriatal neurodegeneration causes locomotor dysfunction but at early stages can be compensated. Interaction between neurons, microglia and astrocytes could be essential for this functional adaptation and neuronal survival in long-term.

The aim was to check how microglia activation inhibition affects neuron and astrocyte cell death caused by selective toxins and how it affects locomotion and potential for spontaneous functional compensation of motor deficits at the early stages of Parkinsons disease.

In a rat model of fluorocitrate (FC)-induced astrocyte death and microglia activation combined with 6-OHDA selective dopaminergic system neurodegeneration we analyzed anti-inflammatory effect of minocycline on each of the cell type and on functional behavioral output.

In result, reduced microglia activation by minocycline probably prevented part of astrocytes from FC-induced cell death. Microglia inhibition caused non-dopaminergic neurodegeneration in a group treated by both neurotoxins but still enhanced compensatory potential to functionally improve walking deficits caused by dopaminergic lesion.

It seems that activation of microglia by dying astrocytes vs dying neurons induced varied mechanisms. Inhibition of strong microglia activation could be protective for astrocytes but microglia is also important for neuronal adaptation, therefore suppression of its activation perturbs structural rebuilding during progressive neurodegeneration affecting functional outcome.

Understanding the relationship between neuronal death, astrocyte loss of function and microglial response could help to identify new, non-neuronal pharmacological target for healing various neurodegenerative diseases.

HighlightsO_LIAstrocyte death affected neuron function but neurodegeneration did not affect astrocyte survival.
C_LIO_LIMicroglia was differentially activated by death of astrocytes than by neuron degeneration.
C_LIO_LIMinocycline treatment decreased morphological signs of microglia activation, probably protected some astrocytes but negatively affected astrocytes in 6-OHDA lesion group.
C_LIO_LIMinocycline treatment despite inducing non-dopaminergic neurodegeneration still enhanced compensatory potential to functionally improve walking after combined 6-OHDA lesion and fluorocitrate-induced astrocyte death.
C_LI

A confound-free method to manipulate pupil size in psychological experiments
Those who study visual perception and visuo-spatial attention are increasingly paying interest to the ways in which these processes are influenced by the size of the pupil. However, this realm of research is complicated by the pupils notorious susceptibility to confounders and difficulties in disentangling cause and effect. Recent studies have sought a solution in the exploitation of intrinsically photosensitive retinal ganglion cells (ipRGCs), which trigger pupil constrictions upon detecting blue light. Experiments typically present stimuli against blue versus red backgrounds of equal perceived luminance, to effectuate systematically smaller pupils in the former than in the latter condition. Here we provide a further validation of this method, by testing a scenario of potential concern. Via retino-hypothalamic pathways, ipRGC activation modulates alertness and arousal. Blue and red backgrounds may therefore differentially impact behavior in addition to the pupil, potentially confounding inferences about the pupils impact on cognition. This was investigated with an auditory task in which participants responded as quickly as possible to sequences of randomly timed beeps while looking at blue versus red displays. Each participant was tested with an easy and a difficult version of the auditory task. Results suggest that the ipRGC method is good to go: in the presence of effects of task difficulty on both pupil size and task performance, the display color exclusively influenced pupil size without affecting task performance.

Emergence of multifrequency activity in a laminar neural mass model
Neural mass models (NMMs) aim to capture the principles underlying mesoscopic neural activity representing the average behavior of large neural populations in the brain. Recently, a biophysically grounded laminar NMM (LaNMM) has been proposed, capable of generating coupled slow and fast oscillations resulting from interactions between different cortical layers. This concurrent oscillatory activity provides a mechanistic framework for studying information processing mechanisms and various disease-related oscillatory dysfunctions. We show that this model can exhibit periodic, quasiperiodic, and chaotic oscillations. Additionally we demonstrate, through bifurcation analysis and numerical simulations, the emergence of rhythmic activity and various frequency couplings in the model, including delta-gamma, theta-gamma, and alpha-gamma couplings. We also examine how alterations linked with Alzheimers disease impair the models ability to display multifrequency activity. Furthermore, we show that the model remains robust when coupled to another neural mass. Together, our results offer a dynamical systems perspective of the laminar NMM model, thereby providing a foundation for future modeling studies and investigations into cognitive processes that depend on cross-frequency coupling.

Author SummaryUnderstanding how the brain generates and coordinates rhythms across different layers is essential for uncovering the mechanisms underlying perception, memory, and cognition. In this work, we analyze a previously developed model of mesoscopic brain activity that simulates the layered structure of the cortex and its ability to produce coupled slow and fast neural oscillations. Using tools from dynamical systems theory, we reveal how the model gives rise to a rich repertoire of dynamical patterns--including periodic, quasiperiodic, and chaotic activity--through the coexistence of multiple oscillatory modes. We also investigate how pathological changes, such as those linked to Alzheimers disease, alter the models dynamics and impair its capacity to sustain complex cross-frequency interactions. Finally, we show that the model remains stable when connected to another brain region, highlighting its robustness. Our findings provide a deeper understanding of how multifrequency neural rhythms may emerge, how they might break down in disease, and how this modeling framework can inform both future theoretical studies and the development of new brain models.

Alpha rhythm subharmonics underlie responsiveness to theta burst stimulation via calcium metaplasticity
Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive technique to modulate brain activity, often used in treating Major Depressive Disorder (MDD) by targeting fronto-limbic circuitry. Despite its clinical utility, optimizing rTMS protocols remains challenging due to the complex and variable effects of stimulation parameter changes on synaptic plasticity. Oscillatory brain activity, measurable via Electroencephalography (EEG), serves as a biomarker for functional circuits and treatment response. To better understand the impact of rTMS on brain oscillations and connectivity, we used computational modeling of corticothalamic circuits to explore the mechanisms of stimulus-induced plasticity. We integrated calcium-dependent plasticity (CaDP) with Bienenstock-Cooper-Munro (BCM) metaplasticity formulations in a neural population model of resting-state EEG. By varying protocol parameters, we simulated iTBS effects on spectral power, synaptic efficacy, and calcium concentrations. Our findings highlight a resonance between theta stimulation and individual resting-state alpha rhythms, enhancing incoming excitatory long-term depression (LTD) and inhibitory long-term potentiation (LTP), leading to corticothalamic feed-forward inhibition (FFI). Induced effects were encapsulated by a weakening of corticothalamic loops and enhancement of intrathalamic loops. This work offers a novel paradigm for individualizing iTBS treatments, provides insights into the neurophysiological basis of clinical responsiveness, and offers a framework with which to derive tailored protocols.

Noradrenaline and microglia maintain plasticity-rigidity balance to safeguard rapid emotional learning in the prefrontal cortex
Balancing plasticity and rigidity is essential for brain function. While the neocortex typically shifts toward rigidity during development to preserve circuit integrity, certain forms of socially acquired emotional learning involve rapid remodeling in the medial prefrontal cortex (mPFC), raising the question of how such flexibility is achieved without compromising pre-existing representations. We found that activity-dependent dendritic spine enlargement is actively suppressed by microglia via a humoral factor in the adolescent mPFC. Noradrenaline lifted this suppression through cAMP signaling in microglia, permitting spine enlargement. Disruption of this noradrenaline-dependent pathway in the mPFC impaired the rapid acquisition of socially learned fear. Conversely, localized microglial ablation enhanced learning efficiency but disrupted emotional boundaries, inducing social fear learning to alter pain sensitivity. These findings demonstrate that noradrenaline and microglia regulate the plasticity-rigidity balance within an optimal range in the mPFC, enabling rapid social learning while safeguarding the functional segregation of emotional circuits.

High throughput machine learning pipeline to characterize larval zebrafish motor behavior
Using machine learning, we developed models that rigorously detect and classify larval zebrafish spontaneous and stimulus-evoked behaviors in various well plate formats. Zebrafish are an ideal model system for investigating the neural substrates underlying behavior due to their simple nervous system and well-documented responses to environmental stimuli. To track movement, we utilized an 8 key point pose estimation model, allowing precise capture of zebrafish kinematics. Using this kinematic data, we trained two random forest classifiers in a semi-supervised learning framework to classify various discreet behavioral outputs including stationary, scoot, turn, acoustic-startle like behavior, and visual-startle like behavior. The classifiers were trained on a manually labeled dataset, and their accuracy was validated showing high precision. To validate our machine learning models, we analyzed behavioral outputs during various stimulus evoked responses and during spontaneous behavior. For additional validation, and to show the utility of our recording and analysis pipeline, we investigated the locomotor effects of several established drugs with well-defined impacts on neurophysiology. Here we show that machine learning model development, enabled by semi-supervised learning developed classification models, provide detailed insights into the behavioral phenotypes of zebrafish, offering a powerful, high throughput method for studying neural control of behavior.

Preclinical evaluation of CHDI-009R for quantification of mutant huntingtin aggregates
Huntingtons disease (HD) is a neurodegenerative disorder caused by an expanded trinucleotide repeat in the huntingtin gene (HTT) that subsequently leads to aggregation of the mutant huntingtin (mHTT) protein. Thus, lowering mHTT is a key therapeutic approach used by several candidate therapeutics currently under investigation. Visualization of the efficiency of these therapeutics through in vivo mHTT quantification rises in importance. For positron emission tomography (PET) imaging of mHTT aggregates, it is critical to characterize the in vivo kinetic profile of newly identified mHTT binders to assess their translational application. Here, we report the evaluation of [11C]CHDI-009R, a PET imaging radioligand with higher affinity and selectivity for mHTT aggregates than previously reported radioligands, in the heterozygous (HET) zQ175DN mouse model of HD wild-type (WT) littermates at 9 and 3 months of age.

[11C]CHDI-009R displayed high stability in plasma and brain, which was reflected in brain kinetics as demonstrated by rapid uptake followed by relatively slow elimination. Kinetic modeling and volume of distribution VT (IDIF) indicated the radioligands ability to quantify mHTT aggregation at 9 months of age with clear genotype differentiation (p<0.0001). [11C]CHDI-009R showed an excellent test-retest reliability in 9-month-old mice (intraclass correlation coefficient: 0.62 - 0.79). A phenotypic difference in mHTT aggregates was also observed in 3-month-old mice in several brain structures (p<0.05) and was confirmed with [3H]CHDI-009R autoradiography.

Overall, this study suggests [11C]CHDI-009R is a promising radioligand for the detection of cerebral mHTT aggregates in a mouse model of HD and supports its advance to clinical evaluation.

AAV gene therapy for GBA-PD and Gaucher Disease
Mutations in GBA1, the gene encoding glucocerebrosidase (GCase), are the most common risk factor for Parkinsons Disease (PD). GBA-PD patients are a genetic subpopulation of PD carrying heterozygous mutations in GBA1. Additionally, bi-allelic mutations in GBA1 cause Gaucher Disease (GD), a lysosomal storage disorder. Loss of GCase activity, a lysosomal enzyme leads to the accumulation of lipid substrates, disrupting lipid homeostasis and promoting cellular toxicity. Here, we report an AAV-mediated GBA1 replacement strategy to treat GD and GBA-PD by a one-time infusion via intravenous (GD Type 1) or intra-CSF (GBA-PD) route of administration. We engineered human GCase to be readily secretable to facilitate broad cross-correction. We developed CBE (conduritol {beta}-epoxide) induced lipid accumulation models to assess efficacy in mice and non-human primates (NHPs) to assess efficacy of our engineered constructs. Based on data across species, across different routes of administration, we nominated AAV.GMU01 SS3-GBA1 as our lead candidate. SS3-GBA1 is robustly secreted, cross-corrected across tissues and promotes lipid clearance. By comparing human GCase levels in AAV-treated NHP brains to healthy human donor brains, we demonstrate that AAV.GMU01 SS3-GBA1 replenishes the GCase deficit seen in GBA-PD patients, thus, restoring GCase to near-physiological levels Importantly, AAV.GMU01 SS3-GBA1 is well-tolerated with no adverse findings. Collectively, we establish a therapeutic strategy for the treatment of Gaucher Disease and GBA-PD with a single gene therapy product.

One Sentence SummaryA novel gene therapy strategy for GBA1-PD and Gaucher disease with an engineered payload that robustly cross-corrects enhancing therapeutic footprint

JiSuJi, a virtual muscle for small animal simulations, accurately predicts force from naturalistic spike trains
Physics-based simulators for neuromechanical control of virtual animals have the potential to significantly enhance our understanding of intricate structure-function relationships in neuromuscular systems, their neural activity and motor control. However, a key challenge is the accurate prediction of the forces that muscle fibers produce based on their complex patterns of electrical activity ("spike trains") while preserving model simplicity for broader applicability. In this study, we present a chemomechanical, three-dimensional finite-element muscle model - JiSuJi (pronounced ji su j[i], meaning "ultrafast muscle" in Chinese) - that efficiently and accurately predicts muscle forces from naturalistic spike trains. The models performance is validated against songbird vocal muscles, a particularly fast and therefore challenging muscle type. Our results demonstrate that JiSuJi accurately predicts both isometric and non-isometric muscle forces across a variety of naturalistic neural activity patterns. JiSuJi furthermore outperforms state-of-the-art muscle simulators for accuracy, while maintaining computational efficiency. Simulating muscle behavior offers a promising approach for investigating the underlying mechanisms of neuro-muscular interactions and precise motor control, especially in the fast-contracting muscles of animal model systems.

Population-specific brain charts reveal Chinese-Western differences in neurodevelopmental trajectories
Human brain charts provide unprecedented opportunities for decoding neurodevelopmental milestones and establishing clinical benchmarks for precision brain medicine 1-7. However, current lifespan brain charts are primarily derived from European and North American cohorts, with Asian populations severely underrepresented. Here, we present the first population-specific brain charts for China, developed through the Chinese Lifespan Brain Mapping Consortium (Phase I) using neuroimaging data from 43,037 participants (aged 0-100 years) across 384 sites nationwide. We establish the lifespan normative trajectories for 296 structural brain phenotypes, encompassing global, subcortical, and cortical measures. Cross-population comparisons with Western brain charts (based on data from 56,339 participants aged 0-100 years) reveal distinct neurodevelopmental patterns in the Chinese population, including prolonged cortical and subcortical maturation, accelerated cerebellar growth, and earlier development of sensorimotor regions relative to paralimbic regions. Crucially, these Chinese-specific charts outperform Western-derived models in predicting healthy brain phenotypes and detecting pathological deviations in Chinese clinical cohorts. These findings highlight the urgent need for diverse, population-representative brain charts to advance equitable precision neuroscience and improve clinical validity across populations.

Internal Resonance Dynamics in a Delayed van der Pol Oscillator Modeling Basal Ganglia Oscillations
Movement disorders, like Parkinsons disease, happen because of unusual patterns in the connections between the cortex and basal ganglia, often caused by timing issues in feedback pathways. This study uses a two-delay nonlinear dynamic model, based on the delayed the van der Pol oscillator, to examine how delays in the feedback loops of the direct and indirect basal ganglia pathways lead to unusual movement patterns and resonance. A thorough analysis of resonance looks at how the ratios of delays and the time it takes to respond affect the systems frequency, showing when internal resonance occurs and how frequency stabilizes under different conditions. We examine how stable the system is by looking at changes in its behavior and measuring the Lyapunov exponent across distinct types of nonlinear feedback setups. Simulations demonstrate transitions from stable oscillations to chaos with varying delays and saturation strength. Our results reproduce symptoms of Parkinsons disease, such as resting tremor, dyskinesia, and freezing, demonstrating how delayed inhibition or hyperactivity destabilizes motor function. The discussion supports these findings, indicating that early problems start in the striatum, with complex effects in the globus pallidus that worsen motor symptoms. This model explains the temporal evolution of Parkinsons disease symptoms and highlights the timing of feedback and saturation as key therapeutic targets. Overall, this research offers a biological explanation for motor problems caused by delays and supports novel approaches for brain stimulation using flexible methods.