Search

Children with autism often show atypical brain lateralization for speech and language processing, however, it is unclear what linguistic component contributes to this phenomenon. Here we measured event-related potential (ERP) responses in 21 school-age autistic children and 25 age-matched neurotypical (NT) peers during listening to word-level prosodic stimuli. We found that both groups displayed larger late negative response (LNR) amplitude to native prosody than to nonnative prosody; however, unlike the NT group exhibiting left-lateralized LNR distinction of prosodic phonology, the autism group showed no evidence of LNR lateralization. Moreover, in both groups, the LNR effects were only present for prosodic phonology but not for phoneme-free prosodic acoustics. These results extended the findings of inadequate neural specialization for language in autism to sub-lexical prosodic structures. [ABSTRACT FROM AUTHOR]

Although consistent evidence has revealed that cognitive impairment is a common sequela in patients withmild stroke, few studies have focused on it, nor the impact of lesion location on cognitive function. Evidence on the neural mechanisms underlying the effects of mild stroke and lesion location on cognitive function is limited. This prompted us to conduct a comprehensive and quantitative study of functional brain network properties in mild stroke patients with different lesion locations. Specifically, an empirical approach was introduced in the present work to explore the impact of mild stroke-induced cognitive alterations on functional brain network reorganization during cognitive tasks (i.e., visual and auditory oddball). Electroencephalogram functional connectivity was estimated from three groups (i.e., 40 patients with cortical infarctions, 48 patients with subcortical infarctions, and 50 healthy controls). Using graph theoretical analysis, we quantitatively investigated the topological reorganization of functional brain networks at both global and nodal levels. Results showed that both patient groups had significantly worse behavioral performance on both tasks, with significantly longer reaction times and reduced response accuracy. Furthermore, decreased global and local efficiency were found in both patient groups, indicating a mild stroke-related disruption in information processing efficiency that is independent of lesion location. Regarding the nodal level, both divergent and convergent node strength distribution patterns were revealed between both patient groups, implying thatmild stroke with different lesion locations would lead to complex regional alterations during visual and auditory information processing, while certain robust cognitive processes were independent of lesion location. These findings provide some of the first quantitative insights into the complex neural mechanisms of mild stroke-induced cognitive impairment and extend our understanding of underlying alterations in cognition-related brain networks induced by different lesion locations, which may help to promote post-stroke management and rehabilitation. [ABSTRACT FROM AUTHOR]

• We observed facilitation for Homophonous primes but interference for Tonal primes in naming latencies of Mandarin words; • The tonal relatedness effect emerged alone before the syllabic relatedness effect in early stimulus-locked ERPs; • An interaction effect between tonal and syllabic relatedness was found in later ERPs; • The ERP data support a two-stage model: an early independent retrieval of tone and a later tone-to-syllable integration. Lexical tone is an important phonological property in tonal languages, but its encoding process in speech production remains unclear. We conducted two electroencephalographic (EEG) experiments to investigate the time course of tonal encoding relative to that of syllabic encoding in Mandarin Chinese disyllabic and monosyllabic word production respectively. We employed a phonologically primed picture naming task and orthogonally manipulated the tonal and syllabic overlap between the prime and the target word. In both experiments, the ERP data revealed that the main effect of tonal relatedness began to emerge alone in an early time window before that of syllabic relatedness, indicating an early independent retrieval process for lexical tone. Moreover, we observed a significant interaction between tonal and syllabic relatedness in later ERP time window(s) and onset latencies, indicating a later tone-to-syllable integration process. These results support the two-stage model of tonal encoding in Mandarin word production and offer implications for current speech production models. [ABSTRACT FROM AUTHOR]

BACKGROUND: Ischemic stroke is a common type of stroke associated with reorganization of functional network of the brain. OBJECTIVE: This pilot study aimed to investigate the characteristics of functional brain networks based on EEG in patients with acute ischemic stroke. METHODS: Seven patients with ischemic stroke within 72 hours of onset and seven healthy controls were enrolled in the study. Dynamic EEG monitoring and clinical information were repeatedly collected within 72 hours (T1), on the 5th day (T2), and on the 7th day (T3) of stroke onset. A directed transfer function was employed to construct functional brain connection patterns. Graph theoretical analysis was performed to evaluate the characteristics of functional brain networks. RESULTS: First, we found that the brain networks of ischemic stroke patients were quite different from the healthy controls. The clustering coefficient (0.001 < Threshold < 0.2) in Delta, Theta, and Alpha bands for the patients were significantly lower (P < 0.01) and the shortest path length in all bands (0.001 < Threshold < 0.2) for the patients were significantly longer (P < 0.01). Moreover, the peaks of the shortest path length for the patients seemed to be higher in all bands with larger thresholds. Secondly, the brain networks for the patients showed a characterized time-variation pattern. The clustering coefficient (0.001 < Threshold < 0.2) of T1 was higher than that of T2 in alpha band (P < 0.01). The shortest path length (0.001 < Threshold < 0.2) of T3 was shorter than that of T2 (P < 0.01) in all bands, and the peak of T3 was numerically higher than that of T2 in all bands with narrower thresholds. CONCLUSION: Functional brain networks in patients with acute ischemic stroke showed impaired global functional integration and decreased efficiency of information transmission compared with healthy subjects. The shortening of the shortest path length during the recovery indicates neural plasticity and reorganization. [ABSTRACT FROM AUTHOR]

The indoor public spaces of most elderly facilities in China have a monotonous space form, which, thus, causes low comprehensive performance and is less likely to satisfy participants' various requirements. This study proposes an optimization design method of "In-Between Area" for a space form operation to improve the performance of indoor public spaces. First, two models were established: Model A to reflect current indoor public spaces and Model B to represent the indoor public spaces designed by using the "In-Between Area" method. Second, a walk-through video was created from each model, with a duration of 196 s. Subjective assessment (STAI) data and objective physiological data (HRV and EEG), were collected from 40 participants while they were watching walk-through videos. The comparison analysis showed statistically significant differences between Model A and Model B. The results of STAI, HRV and EEG proved that the "In-Between Area" method, as an optimization design method, created a more pleasant and comfortable environment for the elderly and improved the overall efficiency of the indoor space. [ABSTRACT FROM AUTHOR]

Most of the current soundscape research content is limited to the discussion of the restoration effect of single-element soundscapes, but it is the combination of sounds that is common in outdoor activities, and there is no evidence that the restoration of natural soundscapes is better with multi-element combinations. In this study, the Zhangjiajie National Forest Park in China was used as the research object, and the physiological indices of the subjects were collected through electroencephalogram signals, and the POMS short-form psychological scale was used to understand the subjective psychological responses of the subjects to the soundscape. The results showed that (1) The psychophysiological restorative ability of the natural soundscape of the National Forest Park was confirmed, and the subjects' psychological and physiological indices changed significantly and positively after listening to each section of the natural soundscape (p = 0.001). (2) The restorative effect of the multi-natural sound combination was ranked first in the overall ranking of the five natural soundscapes, and the multi-natural sound combination did indeed provide better restorative effects than the single-element sounds. (3) Gender does not usually have a significant effect on the restoration effect, and only Windy Sound among the four single-element nature sound landscapes and one multi-element combination of nature sound landscapes showed a significant gender difference, so in general, the effect of gender on the restoration effect of nature sound landscapes is not significant. In terms of research methodology, this study used cluster analysis to cluster the five types of natural soundscapes according to psychological and physiological recovery ability, and used ridge regression to construct mathematical models of the psychological and physiological recovery of each of the four natural soundscapes. The study of human physiological and psychological recovery from different types of natural soundscapes in China's national forest parks will provide a basis for soundscape planning, design, and policy formulation in national forest parks., (© 2024. The Author(s).)

Purpose: To analyze the electroclinical features of patients with developmental and/or epileptic encephalopathy with spike-and-wave activation in sleep (DEE/EE-SWAS) and study the efficacy of different therapies on seizure control, electroencephalogram (EEG) improvements of electrical status epilepticus during sleep (ESES), and cognition outcomes., Methods: Patients with DEE/EE-SWAS who underwent at least one follow-up EEG 3 months after therapy were retrospectively enrolled. The demographic and clinical characteristics of the patients were analyzed. Variables that influenced the outcomes were evaluated using logistic regression models., Results: In total, 87 patients (47 males) were included. The median age at ESES recognition was 81.0 months (IQR 64.0, 96.0). Forty-six patients were diagnosed with self-limited focal epilepsies (SeLFEs) before ESES recognition, 24 with developmental and epileptic encephalopathies with spike-and-wave activation in sleep (DEE-SWAS), and 17 with other epilepsies. Steroids, benzodiazepines, and antiseizure medications (ASMs) were the initial treatment options for ESES. Patients with structural etiologies or slow EEG backgrounds at the time of ESES recognition were less likely to respond to treatment than other patients. However, only children with slow EEG backgrounds had lower odds of response in logistic regression models. Children with clinical or EEG response showed improvements in cognition., Conclusion: Steroids, benzodiazepines, and ASMs are effective treatments for patients with DEE/EE-SWAS. Children with structural etiologies or slow EEG backgrounds at the time of ESES recognition may have a poor long-term prognosis. The efficacy of seizure reduction and EEG improvement is associated with cognitive improvement., Competing Interests: Declaration of competing interest None of the authors has any conflict of interest to disclose., (Copyright © 2024. Published by Elsevier Ltd.)

• These guidelines provide orientation to perform clinical neurophysiological studies during COVID-19 pandemic. • Guide to perform protective procedures for healthcare personal doing clinical neurophysiological studies. • Offer a protocol for the disinfection of equipment and supplies in clinical neurophysiological studies. On 31st December 2019, China notified the World Health Organization of an outbreak of atypical pneumonia from patients at a local seafood market in Wuhan, Hubei, China, responsible for a new coronavirus called Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that caused COVID-19 disease, which spread rapidly around the world. WHO declared a state of pandemic (11th March, 2020), which has caused more than 1 million infected and more than 110,000 deaths; it was observed that up to 29% of those infected were health care personnel. The main route of transmission of SARS-CoV2 is through respiratory secretions and direct contact with contaminated surfaces and material. The pandemic induced an international saturation of health care services and a rupture in the supply chain of protective equipment for healthcare personnel, which poses a high occupational risk to all. Based on the different healthcare systems, human resources, infrastructure and medical emergencies that will warrant the conduct of clinical neurophysiology studies and the lack of a guide for the management of the situation, it was decided by an expert task force of the Latin American Chapter of the International Federation of Clinical Neurophysiology to carry out these guidelines for the protection of patient and healthcare professionals conducting clinical neurophysiological studies. [ABSTRACT FROM AUTHOR]

Objective . To analyze the EEG features of four subacute sclerosing panencephalitis cases in North China. Methods . We retrospectively analyzed the EEG features in four patients with subacute sclerosing panencephalitis and 12 patients in control group from North China. Results. The periodic long-interval diffuse discharges were found in all of the four cases with subacute sclerosing panencephalitis. The morphology and component of periodic complexes were varied in different patients and different wakefulness states. Some EEG parameter settings help to identify periodic long-interval diffuse discharges including the slowed sweep speed, decreased sensitivity and reduced number of montages. In each patient with subacute sclerosing panencephalitis, the periodic long-interval diffuse discharges associated with two types of brief episodes (1:1) during awake period were found and none of the patients in the control group had this EEG pattern. The score system based on the periodic discharges and brief episodes also shows that all the patients with SSPE reached score 5 while none of the patients in the control group has a score greater than 3, which suggests that this EEG pattern may have diagnostic value. Conclusions. In subacute sclerosing panencephalitis, the morphology and component of periodic long-interval diffuse discharges were varied in different patients and different wakefulness states. Specific EEG parameter settings help to identify periodic long-interval diffuse discharges. Periodic long-interval diffuse discharges associated with two types of brief episodes (1:1) during awake period may strongly suggest the diagnosis of subacute sclerosing panencephalitis., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Emotion recognition plays an essential role in human-human interaction since it is a key to understanding the emotional states and reactions of human beings when they are subject to events and engagements in everyday life. Moving towards human-computer interaction, the study of emotions becomes fundamental because it is at the basis of the design of advanced systems to support a broad spectrum of application areas, including forensic, rehabilitative, educational, and many others. An effective method for discriminating emotions is based on ElectroEncephaloGraphy (EEG) data analysis, which is used as input for classification systems. Collecting brain signals on several channels and for a wide range of emotions produces cumbersome datasets that are hard to manage, transmit, and use in varied applications. In this context, the paper introduces the Empátheia system, which explores a different EEG representation by encoding EEG signals into images prior to their classification. In particular, the proposed system extracts spatio-temporal image encodings, or atlases, from EEG data through the Processing and transfeR of Interaction States and Mappings through Image-based eNcoding (PRISMIN) framework, thus obtaining a compact representation of the input signals. The atlases are then classified through the Empátheia architecture, which comprises branches based on convolutional, recurrent, and transformer models designed and tuned to capture the spatial and temporal aspects of emotions. Extensive experiments were conducted on the Shanghai Jiao Tong University (SJTU) Emotion EEG Dataset (SEED) public dataset, where the proposed system significantly reduced its size while retaining high performance. The results obtained highlight the effectiveness of the proposed approach and suggest new avenues for data representation in emotion recognition from EEG signals.

The application of wearable magnetoencephalography using optically-pumped magnetometers has drawn extensive attention in the field of neuroscience. Electroencephalogram system can cover the whole head and reflect the overall activity of a large number of neurons. The efficacy of optically-pumped magnetometer in detecting event-related components can be validated through electroencephalogram results. Multivariate pattern analysis is capable of tracking the evolution of neurocognitive processes over time. In this paper, we adopted a classical Chinese semantic congruity paradigm and separately collected electroencephalogram and optically-pumped magnetometer signals. Then, we verified the consistency of optically-pumped magnetometer and electroencephalogram in detecting N400 using mutual information index. Multivariate pattern analysis revealed the difference in decoding performance of these two modalities, which can be further validated by dynamic/stable coding analysis on the temporal generalization matrix. The results from searchlight analysis provided a neural basis for this dissimilarity at the magnetoencephalography source level and the electroencephalogram sensor level. This study opens a new avenue for investigating the brain's coding patterns using wearable magnetoencephalography and reveals the differences in sensitivity between the two modalities in reflecting neuron representation patterns., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Background: In China, Jin's three-needle acupuncture therapy has been widely used for stroke treatment. However, its mechanism remains unclear. The aim of this study was to investigate the effects of Jin's three-needle acupuncture therapy on stroke patients using multi-channel EEGs. Materials and methods: Fifty stroke patients participated and their EEG signals were recorded before, during, and after acupuncture. Results: Comparing with baseline before acupuncture, the alpha rhythm was significantly increased during the acupuncture needle retention stage and became stronger after removing the needles. The increase of alpha rhythm occurred when inserting and removing the needles, with its high amplitude remaining during retention and after removal of the needles. As the alpha rhythm was significantly correlated with patients' movement and daily-living abilities, the alteration of alpha rhythm during and after acupuncture suggests a possible electrophysiological mechanism of the curative effect of acupuncture for stroke rehabilitation. Conclusion: From the electrophysiological study, Jin's three-needle acupuncture therapy is efficient in stroke patients. [ABSTRACT FROM AUTHOR]

Language is a remarkable cognitive ability that can be expressed through visual (written language) or auditory (spoken language) modalities. When visual characters and auditory speech convey conflicting information, individuals may selectively attend to either one of them. However, the dominant modality in such a competing situation and the neural mechanism underlying it are still unclear. Here, we presented participants with Chinese sentences in which the visual characters and auditory speech convey conflicting information, while behavioral and electroencephalographic (EEG) responses were recorded. Results showed a prominent auditory dominance when audio-visual competition occurred. Specifically, higher accuracy (ACC), larger N400 amplitudes and more linkages in the posterior occipital-parietal areas were demonstrated in the auditory mismatch condition compared to that in the visual mismatch condition. Our research illustrates the superiority of the auditory speech over the visual characters, extending our understanding of the neural mechanisms of audio-visual competition in Chinese., Competing Interests: Conflict of interest All authors claim that there are no conflicts of interest., (Copyright © 2022 IBRO. Published by Elsevier Ltd. All rights reserved.)

Objective. Cultures have essential influences on emotions. However, most studies on cultural influences on emotions are in the areas of psychology and neuroscience, while the existing affective models are mostly built with data from the same culture. In this paper, we identify the similarities and differences among Chinese, German, and French individuals in emotion recognition with electroencephalogram (EEG) and eye movements from an affective computing perspective. Approach. Three experimental settings were designed: intraculture subject dependent, intraculture subject independent, and cross-culture subject independent. EEG and eye movements are acquired simultaneously from Chinese, German, and French subjects while watching positive, neutral, and negative movie clips. The affective models for Chinese, German, and French subjects are constructed by using machine learning algorithms. A systematic analysis is performed from four aspects: affective model performance, neural patterns, complementary information from different modalities, and cross-cultural emotion recognition. Main results. From emotion recognition accuracies, we find that EEG and eye movements can adapt to Chinese, German, and French cultural diversities and that a cultural in-group advantage phenomenon does exist in emotion recognition with EEG. From the topomaps of EEG, we find that the γ and β bands exhibit decreasing activities for Chinese, while for German and French, θ and α bands exhibit increasing activities. From confusion matrices and attentional weights, we find that EEG and eye movements have complementary characteristics. From a cross-cultural emotion recognition perspective, we observe that German and French people share more similarities in topographical patterns and attentional weight distributions than Chinese people while the data from Chinese are a good fit for test data but not suitable for training data for the other two cultures. Significance. Our experimental results provide concrete evidence of the in-group advantage phenomenon, cultural influences on emotion recognition, and different neural patterns among Chinese, German, and French individuals., (© 2022 IOP Publishing Ltd.)

EEG network modularity, as a proxy for cognitive plasticity, has been proposed to be a more reliable neural marker than power and coherence in predicting learning outcomes. The present study examined the associations between resting state EEG network modularity and both L1 Chinese and L2 English literacy skills among 90 Hong Kong first to fifth graders. The modularity indices of different frequency bands were highly correlated with one another. An exploratory factor analysis, performed to extract a general modularity index, explained 77.1% of the total variance. The modularity index was positively associated with Chinese word reading, Chinese phonological awareness, Chinese morphological awareness, and Chinese reading comprehension but was not significantly correlated with English word reading or English morphological awareness. Findings suggest that resting state EEG network modularity is likely to serve as a reasonable, reliable, and cost-effective neural marker of the development of first language but not second language literacy skills., (Copyright © 2021. Published by Elsevier Inc.)

Perceived cues signaling others' pain induce empathy which in turn motivates altruistic behavior toward those who appear suffering. This perception-emotion-behavior reactivity is the core of human altruism but does not always occur in real-life situations. Here, by integrating behavioral and multimodal neuroimaging measures, we investigate neural mechanisms underlying modulations of empathy and altruistic behavior by beliefs of others' pain (BOP). We show evidence that lack of BOP reduces subjective estimation of others' painful feelings and decreases monetary donations to those who show pain expressions. Moreover, lack of BOP attenuates neural responses to their pain expressions within 200 ms after face onset and modulates neural responses to others' pain in the insular, post-central, and frontal cortices. Our findings suggest that BOP provide a cognitive basis of human empathy and altruism and unravel the intermediate neural mechanisms., Competing Interests: TW, SH No competing interests declared, (© 2021, Wu and Han.)

Research on what neural mechanisms facilitate word reading development in non-alphabetic scripts is relatively rare. The present study was among the first to adopt a multivariate pattern classification analysis to decode electroencephalographic signals recorded for primary school children (N = 236) while performing a Chinese character decision task. Chinese is an ideal script for studying the relationship between neural discriminability (i.e., decodability) of the orthography and behavioral word reading skills since the mapping from orthography to phonology is relatively arbitrary in Chinese. This was also among the first empirical attempts to examine the extent to which decoding performance can predict current and subsequent word reading skills using a longitudinal design. Results showed that neural activation patterns of real characters can be distinguished from activation patterns for pseudo-characters, non-characters, and random stroke combinations in both younger and older children. Topography of the transformed classifier weights revealed two distinct cognitive sub-processes underlying single character recognition, but temporal generalization analysis suggested common neural mechanisms between the distinct cognitive sub-processes. Suggestive evidence from correlational and hierarchical regression analyses showed that decoding performance, assessed on average 2 months before the year 2 behavioral testing, predicted both year 1 word reading performance and the development of word reading fluency over the year. Results demonstrate that decoding performance, one indicator of how the neural system is functionally organized in processing characters and character-like stimuli, can serve as a useful neural marker in predicting current word reading skills and the capacity to learn to read., (© 2020 John Wiley & Sons Ltd.)

Background: Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is an autoimmune nervous system disease that has become increasingly recognized. This retrospective study is aimed to analyze the relations between clinical manifestations and blood brain barrier (BBB) integrity in anti-NMDAR encephalitis patients., Methods: Anti-NMDAR encephalitis patients were admitted to the First Affiliated Hospital of Guangxi Medical University from April 2014 to April 2020. Patients were grouped by the normal BBB and damaged BBB groups according to the cerebrospinal fluid (CSF) albumin/serum albumin (QAlb). Neutrophil-to-lymphocyte ratio (NLR) in peripheral blood was used for estimating the inflammatory status. The modified Rankin Scale (mRS) was used to assess prognosis., Results: Seventy-three anti-NMDAR encephalitis patients were diagnosed based on the autoimmune encephalitis diagnosis criteria of 2016. Fifty-three (72.6%) patients were in the normal BBB group and twenty (27.4%) were in the BBB damaged group. There were no significant differences in gender, age, psychiatric disturbances, epilepsy, speech disorder, motor dysfunction, memory dysfunction, and autonomic dysfunction between the two groups (p>0.05). Nevertheless, the proportions of decreased consciousness, ICU admission, NLR, CSF protein and intrathecal IgG synthesis (IgGIF, IgGLoc) in the damaged BBB group were higher than that in the normal BBB group (p<0.05). Patients (79.2%) with normal BBB had good prognosis compared to patients with damaged BBB (50%) after 2 months follow-up. The median mRS before and after immunotherapy in the damaged BBB group were significantly higher than that in the normal BBB group (p<0.01, p<0.05, respectively). Additionally, QAlb increased was positively correlated with the quantitative intrathecal IgG synthesis (IgGLoc: r=0.66; IgGIF: r=0.433, all p<0.001)., Conclusion: The dysfunction of BBB can be helpful in evaluating its prognosis since QAlb showed associations with ICU admission, NLR, a higher CSF protein, intrathecal IgG synthesis (IgGLoc, IgGIF) and mRS score after 2 months follow-up., (Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.)

Electroencephalogram (EEG)-based emotion recognition is receiving significant attention in research on brain-computer interfaces (BCI) and health care. To recognize cross-subject emotion from EEG data accurately, a technique capable of finding an effective representation robust to the subject-specific variability associated with EEG data collection processes is necessary. In this paper, a new method to predict cross-subject emotion using time-series analysis and spatial correlation is proposed. To represent the spatial connectivity between brain regions, a channel-wise feature is proposed, which can effectively handle the correlation between all channels. The channel-wise feature is defined by a symmetric matrix, the elements of which are calculated by the Pearson correlation coefficient between two-pair channels capable of complementarily handling subject-specific variability. The channel-wise features are then fed to two-layer stacked long short-term memory (LSTM), which can extract temporal features and learn an emotional model. Extensive experiments on two publicly available datasets, the Dataset for Emotion Analysis using Physiological Signals (DEAP) and the SJTU (Shanghai Jiao Tong University) Emotion EEG Dataset (SEED), demonstrate the effectiveness of the combined use of channel-wise features and LSTM. Experimental results achieve state-of-the-art classification rates of 98.93% and 99.10% during the two-class classification of valence and arousal in DEAP, respectively, with an accuracy of 99.63% during three-class classification in SEED.

There is a close relationship between urban green space and the physical and mental health of individuals. Most previous studies have discussed the impact of the structure of green space and its elements. This study focused on the emotional changes caused by common behaviors in urban green space (walking and sitting). We recruited 40 college students and randomly assigned them to walking and sitting groups (20 students per group). The two groups performed the same 8-min high-pressure learning task indoors and then performed 8-min recovery activities in a simulated urban green space (a bamboo-lawn space). We used the Emotiv EPOC+ EEG headset to dynamically measure six neural emotional parameters: "engagement," "valence," "meditation," "frustration," "focus," and "excitement." We conducted a pretest and posttest and used analysis of covariance (ANCOVA) to analyze the posttest data (with the pretest data as covariates). The results of the comparison of the two behaviors showed that the "valence" and "meditation" values of the walking group were higher than those of the sitting group, which suggests that walking in urban green space is more favorable for stress reduction. The sitting group had a higher "focus" value than did the walking group, which suggests that sitting in urban green space is better for attention restoration. The results of this study can provide guidance for urban green space planning and design as well as health guidance for urban residents.

The diagnosis of depression almost exclusively depends on doctor-patient communication and scale analysis, which have the obvious disadvantages such as patient denial, poor sensitivity, subjective biases and inaccuracy. An objective, automated method that predicts clinical outcomes in depression is essential for increasing the accuracy of depression recognition and treatments. This paper aims at better recognizing depression using the transformation of EEG features and machine learning methods. An experiment based on emotional face stimuli task was conducted, and twenty-eight subjects' EEG data were recorded from 128-channel HydroCel Geodesic Sensor Net (HCGSN) by Net Station software. The Mini International Neuropsychiatric Interview (MINI) was used by psychiatrists as the criterion for diagnosis of depression patients. The power spectral density and activity were respectively extracted as original features using Auto-regress model and Hjorth algorithm with different time windows. Two separate approaches processed the features: ensemble learning and deep learning. For the ensemble learning, a deep forest transformed the original features to new features that potentially improve feature engineering and a support vector machine (SVM) that was applied as classifier. For deep learning method, we added spatial information of EEG caps to both features by image conversion and adopted convolutional neural network (CNN) to recognize them. The performance of both methods was evaluated for separated and total frequency bands. As a result, the best accuracy obtained was 89.02% when we used the ensemble model and power spectral density. The best accuracy of deep learning method was 84.75% using the activity. These experimental results prove the efficiency of the proposed methods and show that EEG could be used as a reliable indicator for depression recognition, which makes it possible for EEG-based portable system design and application in auxiliary depression recognition in the future., (Copyright © 2019 Elsevier B.V. All rights reserved.)

To investigate whether coding pain expressions of own-race and other-race individuals engages overlapping or distinct neuronal populations, we recorded event-related brain potentials from Chinese and Caucasian adults when viewing an adaptor face (with pain or neutral expressions) and a target face (with only pain expression) presented in rapid succession. If distinct neuronal populations are engaged in coding pain expressions of different races, repetition suppression (RS) of neural activity to pain expressions, that is, decreased neural responses to target faces preceded by pain versus neutral adaptors, should occur when an adaptor and a target are of the same race but not when they are of different races. We found that neural responses to adaptor faces at 128-188 ms (P2) and 200-300 ms (N2) over the frontal/central areas were positively shifted by pain versus neutral expressions. Moreover, RS of neural responses to target faces in the P2/N2 windows occurred when an adaptor and a target were of the same race but not when their racial identities differed, and these effects were observed in both Chinese and Caucasian participants. Our results suggest that perception of pain expressions of different races may recruit distinct neuronal assemblies at a specific stage of the processing stream., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Purpose: To analyze the electroclinical features and evolution of patients diagnosed with convulsions with mild gastroenteritis (CwG) from southwest China., Methods: We reviewed and analyzed the medical records of 34 patients (13 males) diagnosed with CwG and followed-up for at least 12 months., Results: The age of onset was 6-29 months and the female/male ratio 1.62. Seizures were generalized in 32 cases. Single seizures in 15 cases were <5 min and multiple seizures 24-48 h after seizure onset were seen in 18 cases. Seizure duration was <1 min in 32.35%, between 1 and 5 min in 55.88%, and between 5 and 10 min in 8.82% of seizures. The average interval between the onset of gastroenteritis and seizures was 2.47 days. Rotavirus antigen was positive in stools in 26.47% of cases. During the acute phase, diazepam and phenobarbital as first-line treatment were effective in 25% and 83.33% of cases, respectively. Fourteen patients showed non-specific anomalies in the interictal electroencephalography. During 12-36 months follow-up, 33 cases showed normal psychomotor development and no seizures., Conclusions: CwG occurred mostly in toddlers. During the acute phase, phenobarbital is more effective in controlling seizures. For a good prognosis, it is unnecessary to administrate long-term anticonvulsants., (Copyright © 2013 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.)