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Motor imagery (MI) electroencephalography (EEG) classification is an important part of the brain-computer interface (BCI), allowing people with mobility problems to communicate with the outside world via assistive devices. However, EEG decoding is a challenging task because of its complexity, dynamic nature, and low signal-to-noise ratio. Designing an end-to-end framework that fully extracts the high-level features of EEG signals remains a challenge. In this study, we present a parallel spatial-temporal self-attention-based convolutional neural network for four-class MI EEG signal classification. This study is the first to define a new spatial-temporal representation of raw EEG signals that uses the self-attention mechanism to extract distinguishable spatial-temporal features. Specifically, we use the spatial self-attention module to capture the spatial dependencies between the channels of MI EEG signals. This module updates each channel by aggregating features over all channels with a weighted summation, thus improving the classification accuracy and eliminating the artifacts caused by manual channel selection. Furthermore, the temporal self-attention module encodes the global temporal information into features for each sampling time step, so that the high-level temporal features of the MI EEG signals can be extracted in the time domain. Quantitative analysis shows that our method outperforms state-of-the-art methods for intra-subject and inter-subject classification, demonstrating its robustness and effectiveness. In terms of qualitative analysis, we perform a visual inspection of the new spatial-temporal representation estimated from the learned architecture. Finally, the proposed method is employed to realize control of drones based on EEG signal, verifying its feasibility in real-time applications.Peripersonal space (PPS) is defined as the space surrounding the body where we can reach or be reached by external entities, including objects or other individuals. PPS is an essential component of bodily self-consciousness that allows us to perform actions in the world (e.g., grasping and manipulating objects) and protect our body while interacting with the surrounding environment. Multisensory processing plays a critical role in PPS representation, facilitating not only to situate ourselves in space but also assisting in the localization of external entities at a close distance from our bodies. Such abilities appear especially crucial when an external entity (a sound, an object, or a person) is approaching us, thereby allowing the assessment of the salience of a potential incoming threat. Accordingly, PPS represents a key aspect of social cognitive processes operational when we interact with other people (for example, in a dynamic dyad). The underpinnings of PPS have been investigated largely in human modelin trauma related-disorders.Two stereoscopic cues that underlie the perception of motion-in-depth (MID) are changes in retinal disparity over time (CD) and interocular velocity differences (IOVD). These cues have independent spatiotemporal sensitivity profiles, depend upon different low-level stimulus properties, and are potentially processed along separate cortical pathways. Here, we ask whether these MID cues code for different motion directions do they give rise to discriminable patterns of neural signals, and is there evidence for their convergence onto a single "motion-in-depth" pathway? To answer this, we use a decoding algorithm to test whether, and when, patterns of electroencephalogram (EEG) signals measured from across the full scalp, generated in response to CD- and IOVD-isolating stimuli moving toward or away in depth can be distinguished. We find that both MID cue type and 3D-motion direction can be decoded at different points in the EEG timecourse and that direction decoding cannot be accounted for by static disparity information. Remarkably, we find evidence for late processing convergence IOVD motion direction can be decoded relatively late in the timecourse based on a decoder trained on CD stimuli, and vice versa. We conclude that early CD and IOVD direction decoding performance is dependent upon fundamentally different low-level stimulus features, but that later stages of decoding performance may be driven by a central, shared pathway that is agnostic to these features. Overall, these data are the first to show that neural responses to CD and IOVD cues that move toward and away in depth can be decoded from EEG signals, and that different aspects of MID-cues contribute to decoding performance at different points along the EEG timecourse.
Intracranial aneurysm wall enhancement (AWE) is independently associated with unstable aneurysms. However, a quantitative analysis of wall enhancement is lacking. This study aims to investigate the relationship between qualitative and quantitative wall enhancement indices (WEIs), traditional risk factors for aneurysms, and clinical ELAPSS/PHASES scores in a large cohort of intracranial saccular aneurysms.

In this cross-sectional study, a total of 174 patients (mean age 60.4 ± 9.5 years; 53% women) with 248 asymptomatic unruptured intracranial aneurysms underwent pre- and post-contrast black-blood magnetic resonance imaging (MRI). The extent of AWE was defined as non-AWE (pattern 0), focal AWE (pattern 1), or circumferential AWE (pattern 2). WEI was calculated using wall signal intensities on pre- and post-contrast images. Predicted 3- and 5-year growth risk and 5-year rupture risk were obtained from ELAPSS and PHASES scores, respectively. Uni- and multivariate analyses were conducted to explore the relatind 5-year growth risk, and 5-year rupture risk (r = 0.49 and 0.40, r = 0.49 and 0.40, r = 0.36 and 0.24, respectively; all P less then 0.001). In sum, a larger aneurysm size, non-internal carotid artery/middle cerebral artery location, and irregular shape were independently associated with AWE. Larger areas and higher WEIs were associated with an increased risk of aneurysm growth and rupture. These findings suggest that quantitative AWE metrics should be considered in future large-scale longitudinal studies to evaluate their value in aneurysm risk management.Peripheral nerve function is metabolically demanding and nerve energy failure has been implicated in the onset and development of diabetic peripheral neuropathy and neuropathic pain conditions. Distal peripheral nerve oxygen supply relies on the distribution of red blood cells (RBCs) in just a few, nearby capillary-sized vessels and is therefore technically challenging to characterize. We developed an approach to characterize distal sural nerve hemodynamics in anesthetized, adult male mice using in vivo two-photon laser scanning microscopy. Our results show that RBC velocities in mouse sural nerve vessels are higher than those previously measured in mouse brain, and are sensitive to hindlimb temperatures. Nerve blood flow, measured as RBC flux, however, was similar to that of mouse brain and unaffected by local temperature. Power spectral density analysis of fluctuations in RBC velocities over short time intervals suggest that the technique is sufficiently sensitive and robust to detect subtle flow oscillations over time scales from 0.1 to tens of seconds. We conclude that in vivo two-photon laser scanning microscopy provides a suitable approach to study peripheral nerve hemodynamics in mice, and that local temperature control is important during such measurements.Background Previous studies of atypical antipsychotic effects on cortical structures in schizophrenia (SZ) and bipolar disorder (BD) have findings that vary between the short and long term. In particular, there has not been a study exploring the effects of atypical antipsychotics on age-related cortical structural changes in SZ and BD. This study aimed to determine whether mid- to long-term atypical antipsychotic treatment (mean duration = 20 months) is associated with cortical structural changes and whether age-related cortical structural changes are affected by atypical antipsychotics. Methods Structural magnetic resonance imaging images were obtained from 445 participants consisting of 88 medicated patients (67 with SZ, 21 with BD), 84 unmedicated patients (50 with SZ, 34 with BD), and 273 healthy controls (HC). this website Surface-based analyses were employed to detect differences in thickness and area among the three groups. We examined the age-related effects of atypical antipsychotics after excluding the potentialon.Obstructive sleep apnea hypopnea syndrome (OSAHS) and parasomnia overlap disorder (POD) are types of sleep disorders. When the symptoms of both conditions coexist, the POD symptoms are most likely caused by OSAHS. In these cases, the symptoms of POD will be relieved when OSAHS is effectively treated. We refer to these cases as symptomatic POD (related to OSAHS), which differs in pathophysiology, complications, and treatment from idiopathic POD. It is important to note that the treatment for idiopathic POD may aggravate the symptoms of OSAHS. In this case, we used video polysomnography (v-PSG) on a POD patient with suspected OSAHS to distinguish idiopathic POD from symptomatic POD, to inform the appropriate treatment course. The video results and clinical features lead us to diagnose symptomatic POD, and we treated the patient with auto-set continuous positive airway pressure to address their OSAHS. This course of treatment resolved all POD-related symptoms. Here, we discuss this case and review the relevant literature. This report highlights the importance of the use of v-PSG in the clinical diagnosis, differential diagnosis, and subsequent treatment of POD.
There has been increasing interest in identifying non-invasive, imaging biomarkers for neurodegenerative disorders of the central nervous system (CNS). The aim of this proof-of-concept study was to investigate whether corneal sensory nerve and dendritic cell (DC) parameters, captured using
confocal microscopy (IVCM), are altered in individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD).

Fifteen participants were recruited from the Australian Imaging Biomarkers and Lifestyle (AIBL) study in Melbourne, VIC, Australia. The cohort consisted of cognitively normal (CN) individuals (
= 5), and those with MCI (
= 5) and AD (
= 5). Participants underwent a slit lamp examination of the anterior segment, followed by corneal imaging using laser-scanning
confocal microscopy (IVCM) of the central and inferior whorl regions. Corneal DC density, field area, perimeter, circularity index, aspect ratio, and roundness were quantified using Image J. Quantitative data were derived for corneale of significant nerve abnormalities or a difference in DC density. These findings justify future large-scale studies to assess the utility of corneal IVCM and DC analysis for identifying early stage pathology in neurodegenerative disorders of the CNS.
This study is the first to report morphological differences in corneal DCs in humans with MCI. These differences were evident in both the central and mid-peripheral cornea, and in the absence of significant nerve abnormalities or a difference in DC density. These findings justify future large-scale studies to assess the utility of corneal IVCM and DC analysis for identifying early stage pathology in neurodegenerative disorders of the CNS.
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