European Journal of Neuroscience最新文献

Precision step control during gait initiation is essential for stable locomotion. This study examined the role of the central nervous system in this process. In Experiment 1, 14 healthy young adults (21.9 ± 0.9 years) performed a control task (normal gait initiation) and a precision task (targeted foot placement with the first step). Task movements were divided into three phases: planning, preparation, and swing. Event-related desynchronization (ERD) in the alpha and beta bands (α-ERD and β-ERD) was calculated at Fz, Cz, and Pz for each phase. Step accuracy was evaluated as the outcome measure. In Experiment 2, 10 healthy young adults (22.1 ± 0.8 years) received 30-Hz transcranial alternating current stimulation (tACS) targeting the primary motor cortex, using a randomized crossover design consisting of active and sham stimulation conditions, to modulate β-ERD. Δβ-ERD and Δstep accuracy were calculated as the difference between post- and pre-stimulation values. In Experiment 1, a significant interaction effect was observed for ERD. Greater β-ERD during the preparation phase of the precision task was observed compared with the control task. Reduced β-ERD at Cz was significantly correlated with better step accuracy. In Experiment 2, no significant stimulation × time interaction was observed for β-ERD or step accuracy, and no significant correlation was found between Δβ-ERD and Δstep accuracy following tACS. These results indicate a close relationship between β-ERD in the sensorimotor cortex and step accuracy, suggesting that beta-band cortical activity plays an important role in precision stepping.

Parkinson's Disease (PD) often results in motor and cognitive impairments, including gait dysfunction, particularly in patients with freezing of gait (FOG). Current detection methods are either subjective or reliant on specialized gait analysis tools. This study aims to develop an objective, data-driven, multi-modal classification model for FOG-specific classification, distinguishing PD patients with FOG (PDFOG+) from those without FOG (PDFOG–) and healthy controls using resting-state EEG signals combined with demographic and clinical variables. For our main analysis, we utilized a dataset of 124 participants: 42 PDFOG+, 41 PDFOG–, and 41 age-matched healthy controls. Features extracted from resting-state EEG and descriptive variables (age, education, disease duration) were used to train a novel Bi-cephalic Self-Attention Model (BiSAM). We tested three modalities: signal-only, descriptive-only, and multi-modal, across different EEG channel subsets (BiSAM-63, −16, −8, and −4 for primary analysis). For the main analysis, signal-only (BiSAM-4) and descriptive-only models showed limited performance, achieving a maximum accuracy of 55% and 68%, respectively. In contrast, the multi-modal models significantly outperformed both, with BiSAM-8 and BiSAM-4 achieving the highest classification accuracy of 88%. These results demonstrate the value of integrating EEG with objective descriptive features for robust PDFOG+ classification. This study introduces a multi-modal, attention-based architecture that objectively classifies PDFOG+ using minimal EEG channels and descriptive variables. This approach offers a scalable and efficient alternative to traditional assessments, with potential applications in routine clinical monitoring and early diagnosis of PD-related gait dysfunction.

Group decision-making is a cognitive and emotional process influenced by mental representations of the group in terms of ideal and real dimensions. This study explored how communication about these representations affects decision-making as well as neural and autonomic responses. Using an electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), and biofeedback (BIO) hyperscanning paradigm, 28 participants divided into dyads discussed group decisions while self-representing either an ideal (Phase 1) or a real (Phase 2) group. EEG bands (delta, theta, alpha, beta, and gamma bands), oxygenated (O₂Hb) and deoxygenated hemoglobin (HHb), and autonomic measures (i.e., heart rate variability [HRV]) were recorded for individual and dyadic analyses. Single-subject analyses showed increased frontal low-frequency EEG bands, suggesting emotional involvement in all communication exchanges. Higher beta/gamma bands and HHb levels while subjects self-represented the real group indicated greater cognitive and perspective-taking effort. Increased HRV when discussing a group decision while mentally self-representing the ideal compared to the real group suggested greater emotion regulation. Euclidean distance analyses revealed increased delta dissimilarity within dyads, indicating higher emotional and cognitive engagement regardless of group representation. Beta dissimilarity increased when discussing a group decision while mentally self-representing the real group, reflecting higher attentional and cognitive control demands. The multimodal hyperscanning paradigm (combining EEG/fNIRS/BIO) offers complementary insights into the study of communicative exchanges. These findings enhance the understanding of decision-making dynamics and support strategies to improve group communication.

Previous neuroimaging studies have revealed abnormal functional activity in multiple brain regions among individuals with alcohol use disorder (AUD). However, due to the heterogeneity in study designs, these findings lack consistency, leaving the core neuropathological mechanisms of AUD unclear to date. To address this, we conducted a quantitative whole-brain meta-analysis of relevant resting-state functional imaging data to identify persistent brain region characteristics in individuals with AUD. A systematic literature search was conducted across six databases from their inception to August 8, 2025. Subsequently, a meta-analysis employing the anomaly effect size-marked difference mapping (AES-SDM) method was performed to identify abnormal brain activity patterns in patients with AUD. This was supplemented by jackknife sensitivity analysis, heterogeneity testing, publication bias assessment, subgroup analysis, and meta-regression analysis. The results showed that a total of 16 articles (20 datasets) were included, involving 520 patients with AUD and 523 healthy controls (HCs). SDM meta-analysis revealed enhanced functional activity in the right pars opercularis of the inferior frontal gyrus of AUD patients compared to healthy controls, while reduced functional activity was observed in the bilateral postcentral gyrus and left precuneus. Sensitivity analyses and subgroup analyses demonstrated high robustness across all regions. Meta-regression analysis indicated that reduced activity in the left posterior central gyrus was significantly correlated with AUD severity and moderated by age. This study shows AUD patients have abnormal activity in brain regions linked to sensory processing, emotional regulation, and self-awareness, offering comprehensive insights into AUD's neuropathology.

Social withdrawal is a core negative symptom of schizophrenia and remains poorly understood at the molecular level. Dysregulation of the endocannabinoid system has been implicated in social behavior, yet its downstream signaling mechanisms are not fully characterized. In this context, this study examined the effects of the fatty acid amide hydrolase (FAAH) inhibitor, URB597, on CREB expression and its phosphorylation at serine 133 (pCREB) in saline-treated (1 mL/kg, i.p.) or phencyclidine-treated (PCP; 5 mg/kg, i.p., twice a day for 7 days) rats engaged in social interaction. CREB and pCREB expression was measured in six cortical regions selected for their established roles in social behavior: the prelimbic cortex (A32V), the cingulate cortex (A32D), the ventral orbital cortex (VO), the lateral orbital cortex (LO), the agranular insular cortex (AI), and the infralimbic cortex (A25). PCP-treated rats showed reduced social interaction, and URB597 reversed this deficit, whereas the same treatment decreased social interaction in saline controls. Across the six prefrontal and insular regions, CREB expression was largely unchanged, apart from a URB597-related reduction in the LO (main effect, p < 0.05) and an increase in the AI of PCP-treated rats. URB597 also reduced pCREB in VO (main effect, p < 0.05). In contrast, the AI showed clear group-specific effects: Both PCP-treated rats receiving vehicle and saline-treated rats receiving URB597 exhibited reduced pCREB relative to saline controls. Although URB597 did not significantly reverse the pCREB reduction in PCP-treated rats, pCREB levels in the AI positively correlated with time spent in social interaction (r = 0.43, p < 0.05). These findings identify the AI as a key neural substrate underlying social withdrawal in this model and suggest that targeting the endocannabinoid system within this region may represent a promising therapeutic strategy for alleviating the negative symptoms of schizophrenia.