Neural activities differentiating bodies versus non-body stimuli have been identified in the occipitotemporal cortex of both humans and nonhuman primates. However, the neural mechanisms of coding the similarity of different individuals' bodies of the same species to support their categorical representations remain unclear. Using electroencephalography (EEG) and magnetoencephalography (MEG), we investigated the temporal and spatial characteristics of neural processes shared by different individual body silhouettes of the same species by quantifying the repetition suppression of neural responses to human and animal (chimpanzee, dog, and bird) body silhouettes showing different postures. Our EEG results revealed significant repetition suppression of the amplitudes of early frontal/central activity at 180-220 ms (P2) and late occipitoparietal activity at 220-320 ms (P270) in response to animal (but not human) body silhouettes of the same species. Our MEG results further localized the repetition suppression effect related to animal body silhouettes in the left supramarginal gyrus and left frontal cortex at 200-440 ms after stimulus onset. Our findings suggest two neural processes that are involved in spontaneous categorical representations of animal body silhouettes as a cognitive basis of human-animal interactions.
Humans ; Animals ; Male ; Electroencephalography ; Magnetoencephalography ; Female ; Young Adult ; Adult ; Pattern Recognition, Visual/physiology* ; Brain Mapping ; Photic Stimulation ; Brain/physiology* ; Dogs

Depressive disorder is a chronic, recurring, and potentially life-endangering neuropsychiatric disease. According to a report by the World Health Organization, the global population suffering from depression is experiencing a significant annual increase. Despite its prevalence and considerable impact on people, little is known about its pathogenesis. One major reason is the scarcity of reliable animal models due to the absence of consensus on the pathology and etiology of depression. Furthermore, the neural circuit mechanism of depression induced by various factors is particularly complex. Considering the variability in depressive behavior patterns and neurobiological mechanisms among different animal models of depression, a comparison between the neural circuits of depression induced by various factors is essential for its treatment. In this review, we mainly summarize the most widely used behavioral animal models and neural circuits under different triggers of depression, aiming to provide a theoretical basis for depression prevention.
Animals ; Disease Models, Animal ; Depressive Disorder/psychology* ; Humans ; Behavior, Animal/physiology* ; Nerve Net/physiopathology* ; Brain/physiopathology* ; Neural Pathways/physiopathology*

Rhythm, as a prominent characteristic of auditory experiences such as speech and music, is known to facilitate attention, yet its contribution to working memory (WM) remains unclear. Here, human participants temporarily retained a 12-tone sequence presented rhythmically or arrhythmically in WM and performed a pitch change-detection task. Behaviorally, while having comparable accuracy, rhythmic tone sequences showed a faster response time and lower response boundaries in decision-making. Electroencephalographic recordings revealed that rhythmic sequences elicited enhanced non-phase-locked beta-band (16 Hz-33 Hz) and theta-band (3 Hz-5 Hz) neural oscillations during sensory encoding and WM retention periods, respectively. Importantly, the two-stage neural signatures were correlated with each other and contributed to behavior. As beta-band and theta-band oscillations denote the engagement of motor systems and WM maintenance, respectively, our findings imply that rhythm facilitates auditory WM through intricate oscillation-based interactions between the motor and auditory systems that facilitate predictive attention to auditory sequences.
Humans ; Memory, Short-Term/physiology* ; Male ; Beta Rhythm/physiology* ; Female ; Theta Rhythm/physiology* ; Young Adult ; Auditory Perception/physiology* ; Adult ; Electroencephalography ; Acoustic Stimulation ; Reaction Time/physiology* ; Brain/physiology* ; Attention/physiology*

Stromal interaction molecules (STIM)s are Ca²⁺ sensors in internal Ca²⁺ stores of the endoplasmic reticulum. They activate the store-operated Ca²⁺ channels, which are the main source of Ca²⁺ entry in non-excitable cells. Moreover, STIM proteins interact with other Ca²⁺ channel subunits and active transporters, making STIMs an important intermediate molecule in orchestrating a wide variety of Ca²⁺ influxes into excitable cells. Nevertheless, little is known about the role of STIM proteins in brain functioning. Being involved in many signaling pathways, STIMs replenish internal Ca²⁺ stores in neurons and mediate synaptic transmission and neuronal excitability. Ca²⁺ dyshomeostasis is a signature of many pathological conditions of the brain, including neurodegenerative diseases, injuries, stroke, and epilepsy. STIMs play a role in these disturbances not only by supporting abnormal store-operated Ca²⁺ entry but also by regulating Ca²⁺ influx through other channels. Here, we review the present knowledge of STIMs in neurons and their involvement in brain pathology.
Neurons/metabolism* ; Animals ; Humans ; Calcium/metabolism* ; Stromal Interaction Molecules/metabolism* ; Calcium Signaling/physiology* ; Calcium Channels/metabolism* ; Brain/metabolism*

Oligodendrocyte lineage cells, including oligodendrocyte precursor cells (OPCs) and oligodendrocytes (OLs), are essential in establishing and maintaining brain circuits. Autophagy is a conserved process that keeps the quality of organelles and proteostasis. The role of autophagy in oligodendrocyte lineage cells remains unclear. The present study shows that autophagy is required to maintain the number of OPCs/OLs and myelin integrity during brain aging. Inactivation of autophagy in oligodendrocyte lineage cells increases the number of OPCs/OLs in the developing brain while exaggerating the loss of OPCs/OLs with brain aging. Inactivation of autophagy in oligodendrocyte lineage cells impairs the turnover of myelin basic protein (MBP). It causes MBP to accumulate in the cytoplasm as multimeric aggregates and fails to be incorporated into integral myelin, which is associated with attenuated endocytic recycling. Inactivation of autophagy in oligodendrocyte lineage cells impairs myelin integrity and causes demyelination. Thus, this study shows autophagy is required to maintain myelin quality during aging by controlling the turnover of myelin components.
Animals ; Autophagy/physiology* ; Oligodendroglia/metabolism* ; Myelin Sheath/physiology* ; Aging/pathology* ; Myelin Basic Protein/metabolism* ; Cell Lineage/physiology* ; Mice ; Oligodendrocyte Precursor Cells ; Mice, Inbred C57BL ; Brain/cytology* ; Cells, Cultured ; Cell Count

General anesthesia, pivotal for surgical procedures, requires precise depth monitoring to mitigate risks ranging from intraoperative awareness to postoperative cognitive impairments. Traditional assessment methods, relying on physiological indicators or behavioral responses, fall short of accurately capturing the nuanced states of unconsciousness. This study introduces a machine learning-based approach to decode anesthesia depth, leveraging EEG data across different anesthesia states induced by propofol and esketamine in rats. Our findings demonstrate the model's robust predictive accuracy, underscored by a novel intra-subject dataset partitioning and a 5-fold cross-validation method. The research diverges from conventional monitoring by utilizing anesthetic infusion rates as objective indicators of anesthesia states, highlighting distinct EEG patterns and enhancing prediction accuracy. Moreover, the model's ability to generalize across individuals suggests its potential for broad clinical application, distinguishing between anesthetic agents and their depths. Despite relying on rat EEG data, which poses questions about real-world applicability, our approach marks a significant advance in anesthesia monitoring.
Animals ; Machine Learning ; Electroencephalography/methods* ; Ketamine/administration & dosage* ; Rats ; Male ; Propofol/administration & dosage* ; Rats, Sprague-Dawley ; Anesthesia, General/methods* ; Brain/physiology* ; Intraoperative Neurophysiological Monitoring/methods*

The ability to localize sound sources rapidly allows human beings to efficiently understand the surrounding environment. Previous studies have suggested that there is an auditory "where" pathway in the cortex for processing sound locations. The neural activation in regions along this pathway encodes sound locations by opponent hemifield coding, in which each unilateral region is activated by sounds coming from the contralateral hemifield. However, it is still unclear how these regions interact with each other to form a unified representation of the auditory space. In the present study, we investigated whether functional connectivity in the auditory "where" pathway encoded sound locations during passive listening. Participants underwent functional magnetic resonance imaging while passively listening to sounds from five distinct horizontal locations (-90°, -45°, 0°, 45°, 90°). We were able to decode sound locations from the functional connectivity patterns of the "where" pathway. Furthermore, we found that such neural representation of sound locations was primarily based on the coding of sound lateralization angles to the frontal midline. In addition, whole-brain analysis indicated that functional connectivity between occipital regions and the primary auditory cortex also encoded sound locations by lateralization angles. Overall, our results reveal a lateralization-angle-based representation of sound locations encoded by functional connectivity patterns, which could add on the activation-based opponent hemifield coding to provide a more precise representation of the auditory space.
Humans ; Sound Localization/physiology* ; Male ; Female ; Magnetic Resonance Imaging ; Young Adult ; Functional Laterality/physiology* ; Adult ; Brain Mapping ; Auditory Cortex/physiology* ; Acoustic Stimulation ; Auditory Pathways/physiology* ; Brain/physiology*

Depression is increasingly prevalent among adolescents and can profoundly impact their lives. However, the early detection of depression is often hindered by the time-consuming diagnostic process and the absence of objective biomarkers. In this study, we propose a novel approach for depression detection based on an affective brain-computer interface (aBCI) and the resting-state electroencephalogram (EEG). By fusing EEG features associated with both emotional and resting states, our method captures comprehensive depression-related information. The final depression detection model, derived through decision fusion with multiple independent models, further enhances detection efficacy. Our experiments involved 40 adolescents with depression and 40 matched controls. The proposed model achieved an accuracy of 86.54% on cross-validation and 88.20% on the independent test set, demonstrating the efficiency of multimodal fusion. In addition, further analysis revealed distinct brain activity patterns between the two groups across different modalities. These findings hold promise for new directions in depression detection and intervention.
Humans ; Male ; Female ; Adolescent ; Case-Control Studies ; Depression/diagnosis* ; Early Diagnosis ; Rest ; Electroencephalography/methods* ; Brain-Computer Interfaces ; Models, Psychological ; Reproducibility of Results ; Affect/physiology* ; Photic Stimulation/methods* ; Video Recording ; Brain/physiopathology*

Closed-loop neuromodulation, especially using the phase of the electroencephalography (EEG) rhythm to assess the real-time brain state and optimize the brain stimulation process, is becoming a hot research topic. Because the EEG signal is non-stationary, the commonly used EEG phase-based prediction methods have large variances, which may reduce the accuracy of the phase prediction. In this study, we proposed a machine learning-based EEG phase prediction network, which we call EEG phase prediction network (EPN), to capture the overall rhythm distribution pattern of subjects and map the instantaneous phase directly from the narrow-band EEG data. We verified the performance of EPN on pre-recorded data, simulated EEG data, and a real-time experiment. Compared with widely used state-of-the-art models (optimized multi-layer filter architecture, auto-regress, and educated temporal prediction), EPN achieved the lowest variance and the greatest accuracy. Thus, the EPN model will provide broader applications for EEG phase-based closed-loop neuromodulation.
Humans ; Electroencephalography/methods* ; Brain/physiology* ; Machine Learning ; Signal Processing, Computer-Assisted ; Male ; Adult ; Neural Networks, Computer ; Brain Waves/physiology*

Iron metabolism is a critical factor in tumorigenesis and development. Although TP53 mutations are prevalent in glioblastoma (GBM), the mechanisms by which TP53 regulates iron metabolism remain elusive. We reveal an imbalance iron homeostasis in GBM via TCGA database analysis. TP53 mutations disrupted iron homeostasis in GBM, characterized by elevated total iron levels and reduced ferritin (FTH). The gain-of-function effect triggered by TP53 mutations upregulates itchy E3 ubiquitin-protein ligase (ITCH) protein expression in astrocytes, leading to FTH degradation and an increase in free iron levels. TP53-mut astrocytes were more tolerant to the high iron environment induced by exogenous ferric ammonium citrate (FAC), but the increase in intracellular free iron made them more sensitive to Erastin-induced ferroptosis. Interestingly, we found that Erastin combined with FAC treatment significantly increased ferroptosis. These findings provide new insights for drug development and therapeutic modalities for GBM patients with TP53 mutations from iron metabolism perspectives.
Ferroptosis/drug effects* ; Humans ; Iron/metabolism* ; Glioblastoma/metabolism* ; Tumor Suppressor Protein p53/metabolism* ; Homeostasis/physiology* ; Ferritins/metabolism* ; Brain Neoplasms/genetics* ; Mutation ; Astrocytes/drug effects* ; Cell Line, Tumor ; Piperazines/pharmacology* ; Quaternary Ammonium Compounds/pharmacology* ; Ferric Compounds