This Letter proposed a spectrally efficient polarization division multiplexed (PDM) twin single-sideband (twin-SSB) transmission scheme for direct-detection THz communication systems. The optical ...carrier of the twin-SSB is added at the optical THz converter, rather than being generated at the optical transmitter as in traditional SSB scheme. Hence the direct detection of each polarization branch of the PDM-twin-SSB signals at the THz receiver can be achieved, without active polarization control. Moreover, the SSB field recovery enabled by Kramers-Kronig algorithm can effectively eliminate the signal-to-signal beating interferences and contributes to better polarization de-multiplexing. The feasibility of the proposed scheme is verified with 5.75-GBd 16-quadrature amplitude modulation PDM-twin-SSB signals transmission over the 300-GHz direct-detection THz communication system by simulation. This scheme can not only significantly improve the spectral efficiency of direct-detection THz communication systems, but also effectively enhance the system's operability and robustness.
As the mobile communication evolves from sub-6 GHz to millimeter wave (MMW) frequency bands, the demand for high-speed wireless transmission rates exceeding hundreds of gigabits per second is ...becoming more and more prominent. It is one of the important cornerstones supporting numerous emerging bandwidth-consuming applications represented by the metaverse, digital twin and so on. So far, there is a huge room for improvement in wireless transmission rate, which is far inferior to the transmission capacity of fiber optic links. In this paper, we have proposed and experimentally demonstrated a large-capacity photonics-assisted MMW wireless communication system over 20-km fiber and 1.3-m wireless transmission at the W band. A dual-polarized single-input single-output (SISO) wireless link, instead of the commonly used 2 × 2 multiple-input multiple-output (MIMO) links, is used for the transparent transmission of optical polarization division multiplexing signal, which significantly simplifies the system complexity and enhances its robustness. In addition, the transmission performance is further improved by employing an advanced MIMO Volterra nonlinear equalizer. With the bit error ratio threshold of 2 × 10 −2 , a record single-lane single-carrier wireless air interface rate (WAIR/ch/λ) up to 504 Gb/s has been achieved for the first time. This solution we proposed provides opportunity for progress in the wireless air interface capacity close to the fiber-optic transmission capacity in the fiber-wireless integration transmission systems.
Close friendships are important for mental health and cognition in late childhood. However, whether the more close friends the better, and the underlying neurobiological mechanisms are unknown. Using ...the Adolescent Brain Cognitive Developmental study, we identified nonlinear associations between the number of close friends, mental health, cognition, and brain structure. Although few close friends were associated with poor mental health, low cognitive functions, and small areas of the social brain (e.g., the orbitofrontal cortex, the anterior cingulate cortex, the anterior insula, and the temporoparietal junction), increasing the number of close friends beyond a level (around 5) was no longer associated with better mental health and larger cortical areas, and was even related to lower cognition. In children having no more than five close friends, the cortical areas related to the number of close friends revealed correlations with the density of μ-opioid receptors and the expression of OPRM1 and OPRK1 genes, and could partly mediate the association between the number of close friends, attention-deficit/hyperactivity disorder (ADHD) symptoms, and crystalized intelligence. Longitudinal analyses showed that both too few and too many close friends at baseline were associated with more ADHD symptoms and lower crystalized intelligence 2 y later. Additionally, we found that friendship network size was nonlinearly associated with well-being and academic performance in an independent social network dataset of middle-school students. These findings challenge the traditional idea of 'the more, the better,' and provide insights into potential brain and molecular mechanisms.
The effect of 15 Hz rTMS on both Sham mice and HU mice
It shows that the sketch of recognition memory, synaptic plasticity and protein expressions represents the differences between HU mice and ...HU + rTMS mice. rTMS improves the recognition memory along with synaptic plasticity and increases the expressions of BDNF, TrkB, p-Akt, PSD95, NR2A and NR2B in HU mice. The purple “−’’ implies that HU has merely a small effect on mice; the red “+’’ represents the enhancement effect of rTMS on HU mice.
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•Two-week HU procedure induced recognition memory impairment in mice.•Two-week HU procedure induced synaptic plasticity deficits in mice.•Fifteen Hz rTMS improves recognition memory and synaptic plasticity in HU mice.•Fifteen Hz rTMS enhances NR2A/2B, PSD95 and BDNF/TrkB levels in HU mice.•rTMS is an effective countermeasure against learning and memory deficiency.
Repetitive transcranial magnetic stimulation (rTMS), which could improve learning and memory, is widely used in psychiatry and neurology as a therapeutic approach. There are few studies reporting effective countermeasures to cognition decline in astronauts during space flight. Accordingly, we examined whether rTMS was able to significantly alleviate the learning and memory deficits induced by hindlimb unloading (HU), a general accepted rodent model to simulate microgravity, in mice. Male C57BL/6 J mice were randomly divided into four groups: Sham, rTMS, HU, and HU + rTMS groups. The hindlimb unloading procedure continued for consecutive 14 days. Meanwhile, high frequency rTMS (15 Hz) was applied for 14 days from the 1st day of HU procedure. The novel object recognition test showed that the recognition memory was evidently impaired in the HU group compared to that in the Sham group, however, rTMS significantly attenuated the impairment of the memory. Furthermore, rTMS significantly improved the HU-induced LTP impairment and increased spine density in the hippocampal dentate gyrus region. Additionally, rTMS enhanced the expressions of postsynaptic function-associated proteins N-methyl-d-aspartic acid receptors (NR2B and NR2 A) and postsynaptic density protein (PSD95), upregulated BDNF/TrkB signaling and increased phosphorylation of protein kinase B (Akt) in the HU + rTMS group. In conclusion, the data suggest that high frequency rTMS may be an effective countermeasure against the learning and memory deficiency, induced by simulated microgravity.
Gestational age (GA) is associated with later cognition and behavior. However, it is unclear how specific cognitive domains and brain structural development varies with the stepwise change of ...gestational duration.
This large-scale longitudinal cohort study analyzed 11,878 early adolescents' brain volume maps at 9-10 years (baseline) and 5685 at 11-12 years (a 2-year follow-up) from the Adolescent Brain Cognitive Development (ABCD) study. According to gestational age, adolescents were divided into five categorical groups: ≤ 33 weeks, 34-35 weeks, 36 weeks, 37-39 weeks, and ≥ 40 weeks. The NIH Toolbox was used to estimate neurocognitive performance, including crystallized and fluid intelligence, which was measured for 11,878 adolescents at baseline with crystallized intelligence and relevant subscales obtained at 2-year follow-up (with participant numbers ranging from 6185 to 6310 depending on the cognitive domain). An additional large population-based cohort of 618,070 middle adolescents at ninth-grade (15-16 years) from the Danish national register was utilized to validate the association between gestational age and academic achievements. A linear mixed model was used to examine the group differences between gestational age and neurocognitive performance, school achievements, and grey matter volume. A mediation analysis was performed to examine whether brain structural volumes mediated the association between GA and neurocognition, followed with a longitudinal analysis to track the changes.
Significant group differences were found in all neurocognitive scores, school achievements, and twenty-five cortical regional volumes (P < 0.05, Bonferroni corrected). Specifically, lower gestational ages were associated with graded lower cognition and school achievements and with smaller brain volumes of the fronto-parieto-temporal, fusiform, cingulate, insula, postcentral, hippocampal, thalamic, and pallidal regions. These lower brain volumes mediated the association between gestational age and cognitive function (P = 1 × 10
, β = 0.017, 95% CI: 0.007-0.028). Longitudinal analysis showed that compared to full term adolescents, preterm adolescents still had smaller brain volumes and crystallized intelligence scores at 11-12 years.
These results emphasize the relationships between gestational age at birth and adolescents' lower brain volume, and lower cognitive and educational performance, measured many years later when 9-10 and 11-12 years old. The study indicates the importance of early screening and close follow-up for neurocognitive and behavioral development for children and adolescents born with gestational ages that are even a little lower than full term.
Uncertainty about potential future threats and the associated anxious anticipation represents a key feature of anxiety. However, the neural systems that underlie the subjective experience of threat ...anticipation under uncertainty remain unclear. Combining an uncertainty-variation threat anticipation paradigm that allows precise modulation of the level of momentary anxious arousal during functional magnetic resonance imaging (fMRI) with multivariate predictive modeling, we train a brain model that accurately predicts subjective anxious arousal intensity during anticipation and test it across 9 samples (total n = 572, both gender). Using publicly available datasets, we demonstrate that the whole-brain signature specifically predicts anxious anticipation and is not sensitive in predicting pain, general anticipation or unspecific emotional and autonomic arousal. The signature is also functionally and spatially distinguishable from representations of subjective fear or negative affect. We develop a sensitive, generalizable, and specific neuroimaging marker for the subjective experience of uncertain threat anticipation that can facilitate model development.
•Developed a model-based reproducibility index for large-scale high-throughput MRI-based studies.•Provided an analytical tool to evaluate the sample size necessary for achieving a desirable ...model-based reproducibility.•Model-based reproducibility >0.99 was observed for a few large sample size analyses.•Both sample size and study-specific experimental factors play important roles in model-based reproducibility assessment.
Magnetic Resonance Imaging (MRI) technology has been increasingly used in neuroscience studies. Reproducibility of statistically significant findings generated by MRI-based studies, especially association studies (phenotype vs. MRI metric) and task-induced brain activation, has been recently heavily debated. However, most currently available reproducibility measures depend on thresholds for the test statistics and cannot be use to evaluate overall study reproducibility. It is also crucial to elucidate the relationship between overall study reproducibility and sample size in an experimental design. In this study, we proposed a model-based reproducibility index to quantify reproducibility which could be used in large-scale high-throughput MRI-based studies including both association studies and task-induced brain activation. We performed the model-based reproducibility assessments for a few association studies and task-induced brain activation by using several recent large sMRI/fMRI databases. For large sample size association studies between brain structure/function features and some basic physiological phenotypes (i.e. Sex, BMI), we demonstrated that the model-based reproducibility of these studies is more than 0.99. For MID task activation, similar results could be observed. Furthermore, we proposed a model-based analytical tool to evaluate minimal sample size for the purpose of achieving a desirable model-based reproducibility. Additionally, we evaluated the model-based reproducibility of gray matter volume (GMV) changes for UK Biobank (UKB) vs. Parkinson Progression Marker Initiative (PPMI) and UK Biobank (UKB) vs. Human Connectome Project (HCP). We demonstrated that both sample size and study-specific experimental factors play important roles in the model-based reproducibility assessments for different experiments. In summary, a systematic assessment of reproducibility is fundamental and important in the current large-scale high-throughput MRI-based studies.
The photonics-assisted millimeter-wave (MMW) communication technology is attractive to facilitate the MMW application in the upcoming B5G and 6G networks. However, its generated MMW signal by optical ...heterodyne detection usually suffers from serious laser phase noise, which will severely deteriorate the system performance. In this paper, based on a single dual-drive Mach-Zehnder modulator and a single-end photodetector, we first present a simple and spectrally efficient hybrid fiber-wireless double-sideband transmission by employing an overlapping frequency multiplexing scheme. That is, two independent wireless signals with an identical carrier frequency can be simultaneously transmitted in the hybrid fiber-wireless links. To recover the above two overlapped signals, and cancel the concomitant laser phase noise at the same time, a novel digital signal processing method for carrier extraction and signal recovery is further proposed. A proof-of-concept experiment using two independent 3-GBd quadrature phase shift keying (QPSK) signals at W band (92.5 GHz) is performed. After up to 80-km fiber and 3-m wireless transmission, the two QPSK signals can be successfully demodulated, without using the traditional carrier phase estimation algorithm. The proposed scheme not only can double the spectral efficiency of conventional double sideband transmission scheme, but also is immune to its power fading phenomenon induced by chromatic dispersion and robust to the laser phase noise resulting from two free-running lasers in the photonics-assisted MMW communication link.
Sleep duration, psychiatric disorders and dementias are closely interconnected in older adults. However, the underlying genetic mechanisms and brain structural changes are unknown. Using data from ...the UK Biobank for participants primarily of European ancestry aged 38-73 years, including 94% white people, we identified a nonlinear association between sleep, with approximately 7 h as the optimal sleep duration, and genetic and cognitive factors, brain structure, and mental health as key measures. The brain regions most significantly underlying this interconnection included the precentral cortex, the lateral orbitofrontal cortex and the hippocampus. Longitudinal analysis revealed that both insufficient and excessive sleep duration were significantly associated with a decline in cognition on follow up. Furthermore, mediation analysis and structural equation modeling identified a unified model incorporating polygenic risk score (PRS), sleep, brain structure, cognition and mental health. This indicates that possible genetic mechanisms and brain structural changes may underlie the nonlinear relationship between sleep duration and cognition and mental health.
Autism is a neurodevelopmental disorder with great uncertainty in its diagnosis. However, the existing modeling methods for autism diagnosis have not been effectively studied for the uncertainty of ...the diagnosis process so far. In this paper, based on TSK (Takagi-Sugeno-Kang) fuzzy system and combining the association information between functional connections, a new sparse modeling method JGSL-TSK (joint-group-sparse-learning Takagi-Sugeno-Kang) for uncertain joint group is proposed and applied to the auxiliary diagnosis of autism. Firstly, the original rs-fMRI (resting-state functional magnetic resonance imaging) data are preprocessed and extracted to obtain the reduced dimension feature matrix. Secondly, based on the TSK fuzzy system framework, the joint sparse regulari-zation term is introduced to the consequent parameter learning process from the correlation between features, so as to guide the joint selection of features within the same rule and between rules. Finally, the alternating optimization metho
