The aim was to investigate brain responses to non-painful tactile stimuli applied to the non-dominant hand during sleep. 21 healthy subjects participated in the study (11 female, mean age ± SD: 20.67 ± 1.91 years). A 40-channel polysomnography system and a pneumatic tactile stimulator unit were used. Stimuli were applied to the participants\' non-dominant hand. Evoked potential components of the CZ electrode were examined in four sleep stages (N1, N2, N3, and REM). Repeated measures ANOVA was used in statistical analyses. Brain responses, categorized as early (P50, N100, and P200), mid-early (N300, P450, and N550), and late (P900 and Nlate), were detected all sleep stages. No notable variances were found in the amplitude and latency of early brain responses when analyzed across different sleep stages. Differences in both amplitude and latency were observed across different sleep stages for the N300, P450, P900, and Nlate response components. This study presents a pioneering exploration into the responses of the non-dominant hand throughout all sleep stages, encompassing eight distinct response components. This novel investigation contributes to the existing literature by shedding light on previously unexplored aspects. The observed early responses are identified as sensory, while middle to late responses align with cognitive processes within the realm of sleep research. Notably, N300, P450, P900, and Nlate components display variations across diverse sleep stages, marked by alterations in both amplitude and latency. These findings offer valuable insights into the dynamic nature of hand responses throughout the sleep continuum.

UNASSIGNED: Operant conditioning of motor evoked torque (MEPTORQUE) can directly target the corticospinal pathway in patients with anterior cruciate ligament (ACL) reconstruction. However, it remains unclear whether operant conditioning can elicit short-term improvements in corticospinal excitability and whether these improvements are influenced by stimulus intensity.
UNASSIGNED: Quadriceps MEPTORQUE responses can be upconditioned in a single session and will elicit short-term adaptations in corticospinal excitability, with higher stimulus intensities eliciting greater effects.
UNASSIGNED: Randomized controlled laboratory study.
UNASSIGNED: Level 2.
UNASSIGNED: Thirty-six participants were assessed during a single session of an operant conditioning protocol. Participants were randomized into 1 of 3 groups for stimulus intensity used during operant conditioning based on the participant\'s active motor threshold (AMT: 100%, 120%, and 140%). Quadriceps MEPTORQUE amplitude was evaluated during a block of control transcranial magnetic stimulation trials (CTRL) to establish baseline corticospinal excitability, and 3 blocks of conditioning trials (COND) during which participants trained to upcondition their MEPTORQUE. MEPTORQUE recruitment curves were collected to evaluate the effect of operant conditioning on acute corticospinal adaptations.
UNASSIGNED: Participants with ACL reconstruction could upcondition their MEPTORQUE in a single session (P < 0.01; CTRL, 17.27 ± 1.28; COND, 21.35 ± 1.28 [mean ± standard error [SE] in N·m]), but this ability was not influenced by the stimulus intensity used during training (P = 0.84). Furthermore, significant improvements in corticospinal excitability were observed (P = 0.05; PRE, 687.91 ± 50.15; POST, 761.08 ± 50.15 [mean ± SE in N·m %AMT]), but stimulus intensity did not influence corticospinal adaptations (P = 0.67).
UNASSIGNED: Operant conditioning can elicit short-term neural adaptations in ACL-reconstructed patients. Future operant conditioning paradigms may effectively use any of the 3 stimulus intensities studied herein.
UNASSIGNED: Operant conditioning may be a feasible approach to improve corticospinal excitability after ACL reconstruction.

Each brain response to a stimulus is, to a large extent, unique. However this variability, our perceptual experience feels stable. Standard decoding models, which utilise information across several areas to tap into stimuli representation and processing, are fundamentally based on averages. Therefore, they can focus precisely on the features that are most stable across stimulus presentations. But which are these features exactly is difficult to address in the absence of a generative model of the signal. Here, I introduce genephys, a generative model of brain responses to stimulation publicly available as a Python package that, when confronted with a decoding algorithm, can reproduce the structured patterns of decoding accuracy that we observe in real data. Using this approach, I characterise how these patterns may be brought about by the different aspects of the signal, which in turn may translate into distinct putative neural mechanisms. In particular, the model shows that the features in the data that support successful decoding-and, therefore, likely reflect stable mechanisms of stimulus representation-have an oscillatory component that spans multiple channels, frequencies, and latencies of response; and an additive, slower response with a specific (cross-frequency) relation to the phase of the oscillatory component. At the individual trial level, still, responses are found to be highly variable, which can be due to various factors including phase noise and probabilistic activations.

OBJECTIVE: Asthma is an airway inflammatory disease that is affected by neurological and psychological factors. The aim of present review is to investigating the relationship between neural functions and neurobiological changes and asthma symptoms.
METHODS: The information in this article is provided from articles published in English and reputable database using appropriate keywords from 1970 to October 2020.
RESULTS: The symptoms of asthma such as cough, difficult breathing, and mucus secretion get worse when a person is suffering from stress, anxiety, and depression. The function of the insula, anterior cingulate cortex, and hypothalamic-pituitary-adrenal axis changes in response to stress and psychological disease; then the stress hormones are produced from neuroendocrine system, which leads to asthma exacerbation. The evidence represents that psychological therapies or neurological rehabilitation reduces the inflammation through modulating the activity of neurocircuitry and the function of brain centers involved in asthma. Moreover, the neurotrophins and neuropeptides are the key mediators in the neuro-immune interactions, which secrete from the airway nerves in response to brain signals, and they could be the target of many new therapies in asthma.
CONCLUSIONS: This review provides an insight into the vital role of the central and peripheral nervous system in development and exacerbation of asthma and provides practical approaches and strategies on neural networks to improve the airway inflammation and asthma severity.

Although the link between early adversity (EA) and later-life psychiatric disorders is well established, it has yet to be elucidated whether EA is related to distortions in the processing of different facial expressions. We conducted a meta-analysis to investigate whether exposure to EA relates to distortions in responses to different facial emotions at three levels: 1) event-related potentials of the P100 and N170, 2) amygdala functional magnetic resonance imaging responses, and 3) accuracy rate or reaction time in behavioral data.
The systematic literature search (PubMed and Web of Science) up to April 2020 resulted in 29 behavioral studies (n = 8555), 32 functional magnetic resonance imaging studies (n = 2771), and 3 electroencephalography studies (n = 197) for random-effect meta-analyses.
EA was related to heightened bilateral amygdala reactivity to sad faces (but not other facial emotions). Exposure to EA was related to faster reaction time but a normal accuracy rate in response to angry and sad faces. In response to fearful and happy faces, EA was related to a lower accuracy rate only in individuals with recent EA exposure. This effect was more pronounced in individuals with exposure to EA before (vs. after) the age of 3 years. These findings were independent of psychiatric diagnoses. Because of the low number of eligible electroencephalography studies, no conclusions could be reached regarding the effect of EA on the event-related potentials.
EA relates to alterations in behavioral and neurophysiological processing of facial emotions. Our study stresses the importance of assessing age at exposure and time since EA because these factors mediate some EA-related perturbations.

Online gaming is a complex and competitive activity. However, little attention has been paid to brain activities relating to gaming proficiency.
In the current study, fMRI data were obtained from 70 subjects while they were playing online games. Based on their playing, we selected 24 clips from each subject for three levels of gaming proficiency (good, poor, and average), with each clip lasting for 8 seconds.
When comparing the brain responses during the three conditions, good-play trials, relative to poor- or average-play trials, were associated with greater activation of the declive, postcentral gyrus, and striatum. In post-hoc analyses taking the identified clusters as regions of interest to calculate their functional connectivity, activation of the declive during good-play conditions was associated with that in the precentral gyrus and thalamus, and activation in the striatum was associated with that in the inferior frontal gyrus and middle frontal cortex.
Taken together, findings suggest specific regional brain activations and functional connectivity patterns involving brain regions and circuits involved in sensory, motor, automatic and executive functioning and their coordination are associated with better gaming. Specifically, for basic functions, such as simple reaction, motor control, and motor coordination, people need to perform them automatically; for highly cognitive functions, such as plan and strategic playing, people need to engage more executive functions in finishing these works. The automatically processed basic functions spare cognitive resources for the highly cognitive functions, which facilitates their gaming behaviors.

Adolescence is a time that can set the course of alcohol abuse later in life. Sensitivity to reward on multiple levels is a major factor in this development. We examined 736 adolescents from the IMAGEN longitudinal study for alcohol drinking during early (mean age=14.37) and again later (mean age=16.45) adolescence. Conducting structural equation modeling we evaluated the contribution of reward-related personality traits, behavior, brain responses and candidate genes. Personality seems to be most important in explaining alcohol drinking in early adolescence. However, genetic variations in ANKK1 (rs1800497) and HOMER1 (rs7713917) play an equal role in predicting alcohol drinking two years later and are most important in predicting the increase in alcohol consumption. We hypothesize that the initiation of alcohol use may be driven more strongly by personality while the transition to increased alcohol use is more genetically influenced.

OBJECTIVE: Human subjects can tactually estimate the perception of touching fabric. Although many psychophysical and neurophysiological experiments have elucidated the peripheral neural mechanisms that underlie fabric hand estimation, the associated cortical mechanisms are not well understood.
METHODS: To identify the brain regions responsible for the tactile stimulation of fabric against human skin, we used the technology of functional magnetic resonance imaging (fMRI), to observe brain activation when the subjects touched silk fabric actively using fingers.
RESULTS: Consistent with previous research about brain cognition on sensory stimulation, large activation in the primary somatosensory cortex (SI), the secondary somatosensory cortex (SII) and moto cortex, and little activation in the posterior insula cortex and Broca\'s Area were observed when the subjects touched silk fabric.
CONCLUSIONS: The technology of fMRI is a promising tool to observe and characterize the brain cognition on the tactile stimulation of fabric quantitatively. The intensity and extent of activation in the brain regions, especially the primary somatosensory cortex (SI) and the secondary somatosensory cortex (SII), can represent the perception of stimulation of fabric quantitatively.