Enhanced cerebral blood flow similarity of the somatomotor network in chronic insomnia: Transcriptomic decoding, gut microbial signatures and phenotypic roles.

Chronic insomnia (CI) is a complex disease involving multiple factors including genetics, gut microbiota, and brain structure and function. However, there lacks a unified framework to elucidate how these factors interact in CI. By combining data of clinical assessment, sleep behavior recording, cognitive test, multimodal MRI (structural, functional, and perfusion), gene, and gut microbiota, this study demonstrated that enhanced cerebral blood flow (CBF) similarities of the somatomotor network (SMN) acted as a key mediator to link multiple factors in CI. Specifically, we first demonstrated that only CBF but not morphological or functional networks exhibited alterations in patients with CI, characterized by increases within the SMN and between the SMN and higher-order associative networks. Moreover, these findings were highly reproducible and the CBF similarity method was test-retest reliable. Further, we showed that transcriptional profiles explained 60.4 % variance of the pattern of the increased CBF similarities with the most correlated genes enriched in regulation of cellular and protein localization and material transport, and gut microbiota explained 69.7 % inter-individual variance in the increased CBF similarities with the most contributions from Negativicutes and Lactobacillales. Finally, we found that the increased CBF similarities were correlated with clinical variables, accounted for sleep behaviors and cognitive deficits, and contributed the most to the patient-control classification (accuracy = 84.4 %). Altogether, our findings have important implications for understanding the neuropathology of CI and may inform ways of developing new therapeutic strategies for the disease.

Top-down modulation and cortical-AMG/HPC interaction in familiar face processing.

Humans can accurately recognize familiar faces in only a few hundred milliseconds, but the underlying neural mechanism remains unclear. Here, we recorded intracranial electrophysiological signals from ventral temporal cortex (VTC), superior/middle temporal cortex (STC/MTC), medial parietal cortex (MPC), and amygdala/hippocampus (AMG/HPC) in 20 epilepsy patients while they viewed faces of famous people and strangers as well as common objects. In posterior VTC and MPC, familiarity-sensitive responses emerged significantly later than initial face-selective responses, suggesting that familiarity enhances face representations after they are first being extracted. Moreover, viewing famous faces increased the coupling between cortical areas and AMG/HPC in multiple frequency bands. These findings advance our understanding of the neural basis of familiar face perception by identifying the top-down modulation in local face-selective response and interactions between cortical face areas and AMG/HPC.

DeepHPV: a deep learning model to predict human papillomavirus integration sites.

Human papillomavirus (HPV) integrating into human genome is the main cause of cervical carcinogenesis. HPV integration selection preference shows strong dependence on local genomic environment. Due to this theory, it is possible to predict HPV integration sites. However, a published bioinformatic tool is not available to date. Thus, we developed an attention-based deep learning model DeepHPV to predict HPV integration sites by learning environment features automatically. In total, 3608 known HPV integration sites were applied to train the model, and 584 reviewed HPV integration sites were used as the testing dataset. DeepHPV showed an area under the receiver-operating characteristic (AUROC) of 0.6336 and an area under the precision recall (AUPR) of 0.5670. Adding RepeatMasker and TCGA Pan Cancer peaks improved the model performance to 0.8464 and 0.8501 in AUROC and 0.7985 and 0.8106 in AUPR, respectively. Next, we tested these trained models on independent database VISDB and found the model adding TCGA Pan Cancer performed better (AUROC: 0.7175, AUPR: 0.6284) than the model adding RepeatMasker peaks (AUROC: 0.6102, AUPR: 0.5577). Moreover, we introduced attention mechanism in DeepHPV and enriched the transcription factor binding sites including BHLHA15, CHR, COUP-TFII, DMRTA2, E2A, HIC1, INR, NPAS, Nr5a2, RARa, SCL, Snail1, Sox10, Sox3, Sox4, Sox6, STAT6, Tbet, Tbx5, TEAD, Tgif2, ZNF189, ZNF416 near attention intensive sites. Together, DeepHPV is a robust and explainable deep learning model, providing new insights into HPV integration preference and mechanism. Availability: DeepHPV is available as an open-source software and can be downloaded from https://github.com/JiuxingLiang/DeepHPV.git, Contact: huzheng1998@163.com, liangjiuxing@m.scnu.edu.cn, lizheyzy@163.com.

Early visual exposure primes future cross-modal specialization of the fusiform face area in tactile face processing in the blind.

The fusiform face area (FFA) is a core cortical region for face information processing. Evidence suggests that its sensitivity to faces is largely innate and tuned by visual experience. However, how experience in different time windows shape the plasticity of the FFA remains unclear. In this study, we investigated the role of visual experience at different time points of an individual's early development in the cross-modal face specialization of the FFA. Participants (n = 74) were classified into five groups: congenital blind, early blind, late blind, low vision, and sighted control. Functional magnetic resonance imaging data were acquired when the participants haptically processed carved faces and other objects. Our results showed a robust and highly consistent face-selective activation in the FFA region in the early blind participants, invariant to size and level of abstraction of the face stimuli. The cross-modal face activation in the FFA was much less consistent in other groups. These results suggest that early visual experience primes cross-modal specialization of the FFA, and even after the absence of visual experience for more than 14 years in early blind participants, their FFA can engage in cross-modal processing of face information.

Development of neural specialization for print: Evidence for predictive coding in visual word recognition.

How a child's brain develops specialization for print is poorly understood. One longstanding account is selective neuronal tuning to regularity of visual-orthographic features, which predicts a monotonically increased neural activation for inputs with higher regularity during development. However, we observed a robust interaction between a stimulus' orthographic regularity (bottom-up input) and children's lexical classification ability (top-down prediction): N1 response, which is the first negative component of the event-related potential (ERP) occurring at posterior electrodes, was stronger to lower-regularity stimuli, but only in children who were less efficient in lexically classifying these stimuli (high prediction error). In contrast, N1 responses were reduced to lower-regularity stimuli in children who showed high efficiency of lexical classification (low prediction error). The modulation of children's lexical classification efficiency on their neural responses to orthographic stimuli supports the predictive coding account of neural processes of reading.

Higher-order sensorimotor circuit of the brain's global network supports human consciousness.

Consciousness is a mental characteristic of the human mind, whose exact neural features remain unclear. We aimed to identify the critical nodes within the brain's global functional network that support consciousness. To that end, we collected a large fMRI resting state dataset with subjects in at least one of the following three consciousness states: preserved (including the healthy awake state, and patients with a brain injury history (BI) that is fully conscious), reduced (including the N1-sleep state, and minimally conscious state), and lost (including the N3-sleep state, anesthesia, and unresponsive wakefulness state). We also included a unique dataset of subjects in rapid eye movement sleep state (REM-sleep) to test for the presence of consciousness with minimum movements and sensory input. To identify critical nodes, i.e., hubs, within the brain's global functional network, we used a graph-theoretical measure of degree centrality conjoined with ROI-based functional connectivity. Using these methods, we identified various higher-order sensory and motor regions including the supplementary motor area, bilateral supramarginal gyrus (part of inferior parietal lobule), supragenual/dorsal anterior cingulate cortex, and left middle temporal gyrus, that could be important hubs whose degree centrality was significantly reduced when consciousness was reduced or absent. Additionally, we identified a sensorimotor circuit, in which the functional connectivity among these regions was significantly correlated with levels of consciousness across the different groups, and remained present in the REM-sleep group. Taken together, we demonstrated that regions forming a higher-order sensorimotor integration circuit are involved in supporting consciousness within the brain's global functional network. That offers novel and more mechanism-guided treatment targets for disorders of consciousness.

Neural network correlates of high-altitude adaptive genetic variants in Tibetans: A pilot, exploratory study.

Although substantial progress has been made in the identification of genetic substrates underlying physiology, neuropsychology, and brain organization, the genotype-phenotype associations remain largely unknown in the context of high-altitude (HA) adaptation. Here, we related HA adaptive genetic variants in three gene loci (EGLN1, EPAS1, and PPARA) to interindividual variance in a set of physiological characteristics, neuropsychological tests, and topological attributes of large-scale structural and functional brain networks in 135 indigenous Tibetan highlanders. Analyses of individual HA adaptive single-nucleotide polymorphisms (SNPs) revealed that specific SNPs selectively modulated physiological characteristics (erythrocyte level, ratio between forced expiratory volume in the first second to forced vital capacity, arterial oxygen saturation, and heart rate) and structural network centrality (the left anterior orbital gyrus) with no effects on neuropsychology or functional brain networks. Further analyses of genetic adaptive scores, which summarized the overall degree of genetic adaptation to HA, revealed significant correlations only with structural brain networks with respect to local interconnectivity of the whole networks, intermodule communication between the right frontal and parietal module and the left occipital module, nodal centrality in several frontal regions, and connectivity strength of a subnetwork predominantly involving in intramodule edges in the right temporal and occipital module. Moreover, the associations were dependent on gene loci, weight types, or topological scales. Together, these findings shed new light on genotype-phenotype interactions under HA hypoxia and have important implications for developing new strategies to optimize organism and tissue responses to chronic hypoxia induced by extreme environments or diseases.

Investigating GABA concentrations measured with macromolecule suppressed and unsuppressed MEGA-PRESS MR spectroscopy and their relationship with BOLD responses in the occipital cortex.

BACKGROUND: A combination of magnetic resonance spectroscopy (MRS) and functional (f)MRI is a promising method for studying brain activity. Negative results have, however, produced uncertainty as to the validity of the approach. Using a MEGA-PRESS sequence adapted to suppress the macromolecule signal (GABA-) has been suggested as a key methodological improvement, but there is some doubt as to the relationship between such estimates and those from the standard sequence (GABA+), making interpretation difficult. PURPOSE: To investigate the relationship between GABA+ and GABA- estimates from the posterior cingulate and occipital cortices. The second aim was to test for a correlation between occipital GABA and blood oxygenation level-dependent (BOLD) responses in the visual cortex to establish which of the two MEGA-PRESS sequences was more related to the functional responses. STUDY TYPE: Prospective. SUBJECTS: Thirty-one healthy participants. FIELD STRENGTH/SEQUENCE: 3T/single-voxel 1 H-MRS and gradient-echo echo planar imaging (EPI). ASSESSMENT: GABA estimates were made using the Gannet toolbox. fMRI data were analyzed with FSL and Python scripts. STATISTICAL TEST: Relationships between different variables were tested with Pearson's correlation. RESULTS: GABA+ and GABA- concentrations were found to be correlated in both regions (r = 0.52, 95% confidence interval [CI] = 0.35 0.66, pFDR = 0.002). No relationship was found between either the GABA+ or the GABA- concentrations and the amplitude of the BOLD response in the occipital cortex (GABA+, r = -0.14, pFDR > 0.1; GABA-, r = -0.29, pFDR >0.1). However, adding these results to those of prior studies in a meta-analysis of correlation coefficients did provide overall support for a negative correlation between GABA and BOLD response amplitudes (r = -0.39, 95% CI = -0.15-0.64). DATA CONCLUSION: The current findings highlight potential methodological issues that continue to interfere with relating MRS GABA estimates with fMRI responses but, taken in sum, provide support for this general approach. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1285-1294.

Breakdown in the temporal and spatial organization of spontaneous brain activity during general anesthesia.

Which temporal features that can characterize different brain states (i.e., consciousness or unconsciousness) is a fundamental question in the neuroscience of consciousness. Using resting-state functional magnetic resonance imaging (rs-fMRI), we investigated the spatial patterns of two temporal features: the long-range temporal correlations (LRTCs), measured by power-law exponent (PLE), and temporal variability, measured by standard deviation (SD) during wakefulness and anesthetic-induced unconsciousness. We found that both PLE and SD showed global reductions across the whole brain during anesthetic state comparing to wakefulness. Importantly, the relationship between PLE and SD was altered in anesthetic state, in terms of a spatial "decoupling." This decoupling was mainly driven by a spatial pattern alteration of the PLE, rather than the SD, in the anesthetic state. Our results suggest differential physiological grounds of PLE and SD and highlight the functional importance of the topographical organization of LRTCs in maintaining an optimal spatiotemporal configuration of the neural dynamics during normal level of consciousness. The central role of the spatial distribution of LRTCs, reflecting temporo-spatial nestedness, may support the recently introduced temporo-spatial theory of consciousness (TTC).

Is There a Nonadditive Interaction Between Spontaneous and Evoked Activity? Phase-Dependence and Its Relation to the Temporal Structure of Scale-Free Brain Activity.

The aim of our study was to use functional magnetic resonance imaging to investigate how spontaneous activity interacts with evoked activity, as well as how the temporal structure of spontaneous activity, that is, long-range temporal correlations, relate to this interaction. Using an extremely sparse event-related design (intertrial intervals: 52-60 s), a novel blood oxygen level-dependent signal correction approach (accounting for spontaneous fluctuations using pseudotrials) and phase analysis, we provided direct evidence for a nonadditive interaction between spontaneous and evoked activity. We demonstrated the discrepancy between the present and previous observations on why a linear superposition between spontaneous and evoked activity can be seen by using co-occurring signals from homologous brain regions. Importantly, we further demonstrated that the nonadditive interaction can be characterized by phase-dependent effects of spontaneous activity, which is closely related to the degree of long-range temporal correlations in spontaneous activity as indexed by both power-law exponent and phase-amplitude coupling. Our findings not only contribute to the understanding of spontaneous brain activity and its scale-free properties, but also bear important implications for our understanding of neural activity in general.

Functional organization of the face-sensitive areas in human occipital-temporal cortex.

Human occipital-temporal cortex features several areas sensitive to faces, presumably forming the biological substrate for face perception. To date, there are piecemeal insights regarding the functional organization of these regions. They have come, however, from studies that are far from homogeneous with regard to the regions involved, the experimental design, and the data analysis approach. In order to provide an overall view of the functional organization of the face-sensitive areas, it is necessary to conduct a comprehensive study that taps into the pivotal functional properties of all the face-sensitive areas, within the context of the same experimental design, and uses multiple data analysis approaches. In this study, we identified the most robustly activated face-sensitive areas in bilateral occipital-temporal cortices (i.e., AFP, aFFA, pFFA, OFA, pcSTS, pSTS) and systemically compared their regionally averaged activation and multivoxel activation patterns to 96 images from 16 object categories, including faces and non-faces. This condition-rich and single-image analysis approach critically samples the functional properties of a brain region, allowing us to test how two basic functional properties, namely face-category selectivity and face-exemplar sensitivity are distributed among these regions. Moreover, by examining the correlational structure of neural responses to the 96 images, we characterize their interactions in the greater face-processing network. We found that (1) r-pFFA showed the highest face-category selectivity, followed by l-pFFA, bilateral aFFA and OFA, and then bilateral pcSTS. In contrast, bilateral AFP and pSTS showed low face-category selectivity; (2) l-aFFA, l-pcSTS and bilateral AFP showed evidence of face-exemplar sensitivity; (3) r-OFA showed high overall response similarities with bilateral LOC and r-pFFA, suggesting it might be a transitional stage between general and face-selective information processing; (4) r-aFFA showed high face-selective response similarity with r-pFFA and r-OFA, indicating it was specifically involved in processing face information. Results also reveal two properties of these face sensitive regions across the two hemispheres: (1) the averaged left intra-hemispheric response similarity for the images was lower than the averaged right intra-hemispheric and the inter-hemispheric response similarity, implying convergence of face processing towards the right hemisphere, and (2) the response similarities between homologous regions in the two hemispheres decreased as information processing proceeded from the early, more posterior, processing stage (OFA), indicating an increasing degree of hemispheric specialization and right hemisphere bias for face information processing. This study contributes to an emerging picture of how faces are processed within the occipital and temporal cortex.

Neural mechanisms of motion perceptual learning in noise.

Practice improves our perceptual ability. However, the neural mechanisms underlying this experience-dependent plasticity in adult brain remain unclear. Here, we studied the long-term neural correlates of motion perceptual learning. Subjects' behavioral performance and BOLD signals were tracked before, immediately after, and 2 weeks after practicing a motion direction discrimination task in noise over six daily sessions. Parallel to the specificity and persistency of the behavioral learning effect, we found that training sharpened the cortical tuning in MT, and enhanced the connectivity strength from MT to the intraparietal sulcus (IPS, a motion decision-making area). In addition, the decoding accuracy for the trained motion direction was improved in IPS 2 weeks after training. The dual changes in the sensory and the high-level cortical areas suggest that learning refines the neural representation of the trained stimulus and facilitates the information transmission in the decision process. Our findings are consistent with the functional specialization in the visual cortex, and provide empirical evidence to the reweighting theory of perceptual learning at a large spatial scale. Hum Brain Mapp 38:6029-6042, 2017. © 2017 Wiley Periodicals, Inc.

Intrinsic Functional Connectivity Patterns Predict Consciousness Level and Recovery Outcome in Acquired Brain Injury.

For accurate diagnosis and prognostic prediction of acquired brain injury (ABI), it is crucial to understand the neurobiological mechanisms underlying loss of consciousness. However, there is no consensus on which regions and networks act as biomarkers for consciousness level and recovery outcome in ABI. Using resting-state fMRI, we assessed intrinsic functional connectivity strength (FCS) of whole-brain networks in a large sample of 99 ABI patients with varying degrees of consciousness loss (including fully preserved consciousness state, minimally conscious state, unresponsive wakefulness syndrome/vegetative state, and coma) and 34 healthy control subjects. Consciousness level was evaluated using the Glasgow Coma Scale and Coma Recovery Scale-Revised on the day of fMRI scanning; recovery outcome was assessed using the Glasgow Outcome Scale 3 months after the fMRI scanning. One-way ANOVA of FCS, Spearman correlation analyses between FCS and the consciousness level and recovery outcome, and FCS-based multivariate pattern analysis were performed. We found decreased FCS with loss of consciousness primarily distributed in the posterior cingulate cortex/precuneus (PCC/PCU), medial prefrontal cortex, and lateral parietal cortex. The FCS values of these regions were significantly correlated with consciousness level and recovery outcome. Multivariate support vector machine discrimination analysis revealed that the FCS patterns predicted whether patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%, and the most discriminative region was the PCC/PCU. These findings suggest that intrinsic functional connectivity patterns of the human posteromedial cortex could serve as a potential indicator for consciousness level and recovery outcome in individuals with ABI. SIGNIFICANCE STATEMENT: Varying degrees of consciousness loss and recovery are commonly observed in acquired brain injury patients, yet the underlying neurobiological mechanisms remain elusive. Using a large sample of patients with varying degrees of consciousness loss, we demonstrate that intrinsic functional connectivity strength in many brain regions, especially in the posterior cingulate cortex and precuneus, significantly correlated with consciousness level and recovery outcome. We further demonstrate that the functional connectivity pattern of these regions can predict patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%. Our study thus provides potentially important biomarkers of acquired brain injury in clinical diagnosis, prediction of recovery outcome, and decision making for treatment strategies for patients with severe loss of consciousness.

How are different neural networks related to consciousness?

OBJECTIVE: We aimed to investigate the roles of different resting-state networks in predicting both the actual level of consciousness and its recovery in brain injury patients. METHODS: We investigated resting-state functional connectivity within different networks in patients with varying levels of consciousness: unresponsive wakefulness syndrome (UWS; n = 56), minimally conscious state (MCS; n = 29), and patients with brain lesions but full consciousness (BL; n = 48). Considering the actual level of consciousness, we compared the strength of network connectivity among the patient groups. We then checked the presence of connections between specific regions in individual patients and calculated the frequency of this in the different patient groups. Considering the recovery of consciousness, we split the UWS group into 2 subgroups according to recovery: those who emerged from UWS (UWS-E) and those who remained in UWS (UWS-R). The above analyses were repeated on these 2 subgroups. RESULTS: Functional connectivity strength in salience network (SN), especially connectivity between the supragenual anterior cingulate cortex (SACC) and left anterior insula (LAI), was reduced in the unconscious state (UWS) compared to the conscious state (MCS and BL). Moreover, at the individual level, SACC-LAI connectivity was more present in MCS than in UWS. Default-mode network (DMN) connectivity strength, especially between the posterior cingulate cortex (PCC) and left lateral parietal cortex (LLPC), was reduced in UWS-R compared with UWS-E. Furthermore, PCC-LLPC connectivity was more present in UWS-E than in UWS-R. INTERPRETATION: Our findings show that SN (SACC-LAI) connectivity correlates with behavioral signs of consciousness, whereas DMN (PCC-LLPC) connectivity instead predicts recovery of consciousness.

Recollection reduces unitised familiarity effect.

Two types of encoding tasks have been employed in previous research to investigate the beneficial effect of unitisation on familiarity-based associative recognition (unitised familiarity effect), namely the compound task and the interactive imagery task. Here we show how these two tasks could differentially engage subsequent recollection-based associative recognition and consequently lead to the turn-on or turn-off of the unitised familiarity effect. In the compound task, participants studied unrelated word pairs as newly learned compounds. In the interactive imagery task, participants studied the same word pairs as interactive images. An associative recognition task was used in combination with the Remember/Know procedure to measure recollection-based and familiarity-based associative recognition. The results showed that the unitised familiarity effect was present in the compound task but was absent in the interactive imagery task. A comparison of the compound and the interactive imagery task revealed a dramatic increase in recollection-based associative recognition for the interactive imagery task. These results suggest that unitisation could benefit familiarity-based associative recognition; however, this effect will be eliminated when the memory trace formed is easily accessed by strong recollection without the need for a familiarity assessment.

A Stroop effect emerges in the processing of complex Chinese characters that contain a color-related radical.

Three experiments examined whether a Stroop effect emerges in the processing of complex Chinese characters that contain a color-related radical. In Experiment 1, a Stroop effect occurred when participants responded to the black or white color of the simple characters [Chinese character: see text] (black) and [Chinese character: see text] (white) by making a left or right keypress. For Experiment 2, in which the stimuli were complex characters whose meanings were unrelated to color but that contained [Chinese character: see text] or [Chinese character: see text] as a radical, a Stroop effect also occurred, although it was smaller than in Experiment 1. Furthermore, this Stroop effect as a function of radical meaning was shown again in Experiment 3 for low-frequency complex characters but not high-frequency ones. These results suggest that the semantic representations of the complex characters' color-related radicals are accessed in the context of a Stroop color word task, especially for low-frequency characters. Reduction of the Stroop effect in complex characters composed of one radical with color meaning and one without is similar to dilution of the Stroop effect that occurs when a color word is accompanied by a neutral word. Possible implications of the results for accounts of Stroop dilution are discussed.

Fine neural tuning for orthographic properties of words emerges early in children reading alphabetic script.

The left-lateralized N170 component of ERPs for words compared with various control stimuli is considered as an electrophysiological manifestation of visual expertise for written words. To understand the information sensitivity of the effect, researchers distinguish between coarse tuning for words (the N170 amplitude difference between words and symbol strings) and fine tuning for words (the N170 amplitude difference between words and consonant strings). Earlier developmental ERP studies demonstrated that the coarse tuning for words occurred early in children (8 years old), whereas the fine tuning for words emerged much later (10 years old). Given that there are large individual differences in reading ability in young children, these tuning effects may emerge earlier than expected in some children. This study measured N170 responses to words and control stimuli in a large group of 7-year-olds that varied widely in reading ability. In both low and high reading ability groups, we observed the coarse neural tuning for words. More interestingly, we found that a stronger N170 for words than consonant strings emerged in children with high but not low reading ability. Our study demonstrates for the first time that fine neural tuning for orthographic properties of words can be observed in young children with high reading ability, suggesting that the emergent age of this effect is much earlier than previously assumed. The modulation of this effect by reading ability suggests that fine tuning is flexible and highly related to experience. Moreover, we found a correlation between this tuning effect at left occipitotemporal electrodes and children's reading ability, suggesting that the fine tuning might be a biomarker of reading skills at the very beginning of learning to read.

The self and its resting state in consciousness: an investigation of the vegetative state.

Recent studies have demonstrated resting-state abnormalities in midline regions in vegetative state/unresponsive wakefulness syndrome and minimally conscious state patients. However, the functional implications of these resting-state abnormalities remain unclear. Recent findings in healthy subjects have revealed a close overlap between the neural substrate of self-referential processing and the resting-state activity in cortical midline regions. As such, we investigated task-related neural activity during active self-referential processing and various measures of resting-state activity in 11 patients with disorders of consciousness (DOC) and 12 healthy control subjects. Overall, the results revealed that DOC patients exhibited task-specific signal changes in anterior and posterior midline regions, including the perigenual anterior cingulate cortex (PACC) and posterior cingulate cortex (PCC). However, the degree of signal change was significantly lower in DOC patients compared with that in healthy subjects. Moreover, reduced signal differentiation in the PACC predicted the degree of consciousness in DOC patients. Importantly, the same midline regions (PACC and PCC) in DOC patients also exhibited severe abnormalities in the measures of resting-state activity, that is functional connectivity and the amplitude of low-frequency fluctuations. Taken together, our results provide the first evidence of neural abnormalities in both the self-referential processing and the resting state in midline regions in DOC patients. This novel finding has important implications for clinical utility and general understanding of the relationship between the self, the resting state, and consciousness.

Cerebellum engages in automation of verb-generation skill.

Numerous studies have shown cerebellar involvement in item-specific association, a form of explicit learning. However, very few have demonstrated cerebellar participation in automation of non-motor cognitive tasks. Applying fMRI to a repeated verb-generation task, we sought to distinguish cerebellar involvement in learning of item-specific noun-verb association and automation of verb generation skill. The same set of nouns was repeated in six verb-generation blocks so that subjects practiced generating verbs for the nouns. The practice was followed by a novel block with a different set of nouns. The cerebellar vermis (IV/V) and the right cerebellar lobule VI showed decreased activation following practice; activation in the right cerebellar Crus I was significantly lower in the novel challenge than in the initial verb-generation task. Furthermore, activation in this region during well-practiced blocks strongly correlated with improvement of behavioral performance in both the well-practiced and the novel blocks, suggesting its role in the learning of general mental skills not specific to the practiced noun-verb pairs. Therefore, the cerebellum processes both explicit verbal associative learning and automation of cognitive tasks. Different cerebellar regions predominate in this processing: lobule VI during the acquisition of item-specific association, and Crus I during automation of verb-generation skills through practice.

Altered Cortical Information Interaction During Respiratory Events in Children with Obstructive Sleep Apnea-Hypopnea Syndrome.

Obstructive sleep apnea-hypopnea syndrome (OSAHS) significantly impairs children's growth and cognition. This study aims to elucidate the pathophysiological mechanisms underlying OSAHS in children, with a particular focus on the alterations in cortical information interaction during respiratory events. We analyzed sleep electroencephalography before, during, and after events, utilizing Symbolic Transfer Entropy (STE) for brain network construction and information flow assessment. The results showed a significant increase in STE after events in specific frequency bands during N2 and rapid eye movement (REM) stages, along with increased STE during N3 stage events. Moreover, a noteworthy rise in the information flow imbalance within and between hemispheres was found after events, displaying unique patterns in central sleep apnea and hypopnea. Importantly, some of these alterations were correlated with symptom severity. These findings highlight significant changes in brain region coordination and communication during respiratory events, offering novel insights into OSAHS pathophysiology in children.