Neuroscience最新文献

Memory consolidation is a complex process that transforms short-term memories into long-term memories, relying on the dynamic synergistic effects of the global neural oscillation network. This paper reviews the specific functions of neural oscillations at different frequencies in memory consolidation and their inter-regional interaction mechanisms. Specifically, memory consolidation during non-rapid eye movement (NREM) sleep mainly relies on the nested pattern of hippocampal sharp wave-ripples (SPW-Rs) with cortical slow oscillations (SOs) and sleep spindles, while during rapid eye movement (REM) sleep and wakefulness, it more depends on the theta-gamma coupling pattern between the hippocampus and prefrontal cortex. Both rely on the core mechanism of "oscillation-timed offline replay" to reactivate memory traces, depend on the synergistic integration of multiple brain regions, and use cross-frequency coupling as the core mode of inter-regional information transmission. The synergistic effects of these oscillations reflect the dynamic, context-dependent emergent properties of distributed neural systems, rather than a fixed hierarchical structure. Future research needs to further reveal the fine regulatory mechanisms of neural oscillations in different behavioral states and memory types, and explore therapeutic strategies for memory disorders based on neural oscillation modulation, providing a theoretical reference for brain-inspired computing and neural repair technologies.

Objective: The aim of this study was to investigate the effect of blood homocysteine (Hcy) levels on the Phase Lag Index (PLI) of electroencephalographic (EEG) resting-state networks (RSNs) in patients with epilepsy (PWEs).

Methods: Ninety-one patients with newly diagnosed focal epilepsy who had not taken anti-seizure medications (ASMs) were retrospectively included and divided into the Hcy-normal group (Hcy < 15 μmol/L, n = 57) and the Hcy-elevated group (Hcy > 15 μmol/L, n = 34). Nine clinical features were recorded, and 684 PLI features in four bands (α, β, δ, and θ) were calculated. Differences between the two groups of data were compared and correlation analyzed.

Results: There were significant differences between the two groups in the PLI features of α, β, and δ bands, with O1-Fz (left occipital region-mid frontal region), Fp2-Pz (right frontal pole region-parietal region), and F4-Pz (right frontal region-parietal region) differing significantly in all three bands, and α band was more significantly affected. Correlation analysis showed that α: C4-F8 (right central region-right frontotemporal region), α: T3-Pz (left middle temporal region-parietal region) and δ bands: F3-Fz (left frontal region-middle frontal region). The correlation coefficients were the largest and there was a positive correlation between all statistically significant features and Hcy.

Conclusion: The present study suggests that Hcy may affect epileptogenesis and seizures by influencing RSNs (especially α band) in specific brain regions, providing a new idea for the study of the Hcy-brain network interaction mechanism in epilepsy.

The global rise in sugar-rich diets is a major public health concern because excessive sugar intake can disrupt the brain's reward circuitry. This neurobiological dysfunction is considered a key factor leading to significant health complications, including obesity, sugar addiction, and neurological issues, which requires a deeper understanding of sugar's effects on the brain and behavior. This study investigated the impact of chronic consumption of sugar-enriched agar-based diet (SD) compared to a control diet (CD) in male C57BL/6Mlac mice. A T-maze task was used to assess reward-seeking behavior, while local field potential (LFP) recordings were obtained from neural circuit related with reward processing including the nucleus accumbens (NAc), dorsal hippocampus (HP), medial prefrontal cortex (mPFC), and olfactory bulb (OB) to evaluate neural dynamics. Mice in the SD-group exhibited a significant increase in body weight, indicating metabolic adaptation to chronic sugar intake. However, behavioral analysis revealed no significant differences between the SD- and CD-groups in terms of percent time preference or total traveled distance, suggesting that prolonged sugar consumption may not have overtly enhanced reward-seeking behavior in this paradigm. In contrast, neurophysiological data showed a significant reduction in the NAc theta-band (5-9 Hz) LFP power during the turning epoch. This dissociation between behavioral outcomes and neural activity points to the complexity of sugar's effects on the brain, possibly involving compensatory mechanisms in other regions of the reward circuitry. These findings highlight the sensitivity of the NAc to chronic sugar exposure and provide novel insights into the neural substrates underlying sugar-related decision-making.

Central post-stroke pain (CPSP) is a frequent complication following a stroke, significantly reducing the quality of life for stroke patients. The cause of CPSP remains unclear; consequently, effective treatment options are limited. Central neuronal hyperexcitability is a significant contributor to CPSP pathogenesis. Artesunate (Arte) reduces neuronal hyperexcitability by inhibiting mGluR5 expression. This study aimed to investigate whether artesunate could reduce CPSP by inhibiting mGluR5 expression. A thalamic hemorrhagic injury model was used to induce CPSP in adult male Sprague-Dawley rats. The paw mechanical withdrawal threshold (PMWT) and the paw thermal withdrawal latency (PTWL) were measured in each group before and after modeling. Western blot and Immunofluorescence revealed changes in the expression of mGluR5, TRPV1, and CGRP. In the CPSP group, the PMWT threshold decreased, whereas the PTWL remained unchanged. The expression of mGluR5, TRPV1, and CGRP increased. In the CPSP + Arte group, mGluR5 expression was inhibited by artesunate, which also reversed the reduction of the PMWT threshold in CPSP rats. By intraventricular injection of mGluR5 into the lateral ventricles of CPSP rats, MPEP, a specific inhibitor of mGluR5, inhibits mGluR5 expression and increases the PMWT threshold.

Glioblastoma (GBM) is an aggressive brain tumor with a poor prognosis, yet its molecular mechanisms remain incompletely understood. Olfactomedin 1 (OLFM1), a member of the olfactomedin-domain-containing protein family, is known for roles in neurodevelopment and is dysregulated in several cancers; however, its function in GBM is unclear. This study aimed to elucidate the potential role of OLFM1 in GBM progression and to explore its underlying molecular mechanisms. Through artificial neural networks, Mendelian randomization, transcriptomic analysis, and experimental validation, we identified OLFM1 as a potential tumor suppressor, with high expression predicting better survival in GBM. The immune infiltration analysis suggested a potential role of OLFM1 in inhibiting macrophage polarization from the M0 to M2 phenotype. Gene set enrichment analysis (GSEA) revealed that high OLFM1 expression is associated with downregulation of the JAK-STAT3 signaling pathway. Experimental assays confirmed that OLFM1 overexpression downregulates JAK-STAT3 signaling. Additionally, drug prediction using DSigDB and molecular docking suggested rosuvastatin as a candidate OLFM1-related GBM inhibitor with strong binding affinity to key pathway proteins. Collectively, our findings indicate OLFM1 as a potential prognostic biomarker and therapeutic target.

The integration of game-based cognitive training with electroencephalography (EEG)-based brain-computer interaction (BCI) has demonstrated potential for enhancing attention among individuals with attention-deficit hyperactivity disorder (ADHD). However, existing systems often lack adaptive difficulty regulation and rely solely on single-modal assessments, thereby limiting personalization and sustained engagement. This study developed and assessed an adaptive, multi-task EEG-BCI training system that combines real-time neurofeedback with machine learning-driven customization to bolster attentional capabilities. Fifty participants (25 with ADHD and 25 controls) completed attention-enhancement sessions utilizing SkiSport, a Unity-based skiing game that adjusts difficulty levels according to EEG-derived attention metrics obtained from the NeuroSky TGAM sensor. Support Vector Regression, XGBoost, and Multi-Layer Perceptron models were trained on behavioral and EEG data to predict optimal difficulty parameters. Attention and behavioural metrics were compared before and after personalisation. The findings indicated that EEG attention scores increased by an average of 15% (7.85% in controls, 21.5% in ADHD participants). The adaptive multi-task games yielded an additional 10% increase following personalization. Behavioral indices on reaction accuracy, game score, and completion time showed an overall improvement of 19%. XGBoost achieved the highest predictive accuracy on a held-out test set (R² value of 0.9826, RMSE of 0.8560, and MAE of 0.6417) for within-subject, window-level attention prediction. The proposed EEG-BCI game facilitated short-term enhancements in attention-related metrics among individuals with ADHD. The incorporation of machine learning-driven personalization into serious games offers a scalable, non-pharmacological strategy for short-term cognitive training and attentional modulation.

The thalamic reticular nucleus (TRN) is the principal inhibitory source of thalamus, it consists of GABAergic neurons that receive collateral projections from the thalamus and cortex but send their inhibition only to the thalamus, playing a key role in thalamocortical (TC) network modulation. TRN participates in generating thalamocortical slow waves and sleep spindles, as well as in attention, memory and sensory filtering, through different firing patterns. Maturation of the TRN-thalamus complex during early postnatal development is critical for the emergence of TC function. Although functional development of the TRN has been explored, an extensive characterization of firing patterns maturation across the first postnatal weeks was still lacking, as well as an integral analysis of developmental trajectories. Using whole-cell patch-clamp recordings in mice across five developmental stages, we provide a systematic electrophysiological profile of TRN maturation during the first three postnatal weeks. Our data show a protracted developmental trajectory of TRN, encompassing passive membrane and action potential properties, as well as tonic and burst firing patterns, the latter essential for sleep wave generation in the mature thalamocortical network. Passive membrane properties stabilize by P10, action potentials reach adult-like characteristics at P14, and tonic and burst firing patterns continue to mature until P21. Spontaneous excitatory postsynaptic currents evolve in parallel and largely stabilize at P14. Together, these findings identify critical periods in the development of thalamic inhibitory pathways and provide a framework for understanding how altered maturation trajectories may contribute to neurodevelopmental disorders.