Hasil untuk "Neurophysiology and neuropsychology"

Mahmudul Hasan, Phi-Hung Tran, Jingsong Gao et al.

The concept of using photoelectron interferometry in short laser fields to probe electron dynamics and target structures was introduced more than two decades ago. However, the quality of experimental data has remained insufficient for quantitative analysis, largely due to the instability of few-cycle Ti:Sa laser pulses, the current workhorse of short pulses. Here, we report the first systematic strong-field ionization experiments performed with industrial-grade, carrier-envelope-phase (CEP) stabilized, near-single-cycle Yb lasers. By measuring photoelectron momentum distributions in the direct-ionization regime, we show that single-cycle cosine-shaped pulses can separate and enhance both spider-leg and fishbone holographic structures. The spider-leg structure enables extraction of the electron scattering phase from the Ar atomic potential-information typically accessible only through attosecond metrology, while the fishbone structure reveals the orbital-parity contrast between Ar atoms and nitrogen molecules. Our measurements are quantitatively reproduced by both semiclassical Herman-Kluk-propagator and \textit{ab initio} simulations, paving the way for precision studies of electron-molecule scattering with widely accessible industrial-grade lasers.

Maxime Richard, Irénée Frérot, Sylvain Ravets et al.

Exciton-polaritons in semiconductor microcavities exhibit large two-body interactions that, thanks to ever refined nanotechnology techniques, are getting closer and closer to the quantum regime where single-photon nonlinearities start being relevant. To foster additional progress in this direction, in this work we experimentally investigate the microscopic mechanism driving polariton-polariton interactions. We measure the dispersion relation of the collective excitations that are thermally generated on top of a coherent fluid of interacting lower-polaritons. By comparing the measurements with the Bogoliubov theory over both the lower and upper polariton branches simultaneously, we find that polariton-polariton interactions stem dominantly from a mechanism of saturation of the exciton oscillator strength.

Mohammad Amini, Linghao Yan, Orlando J. Silveira et al.

Van der Waals heterostructures are a core tool in quantum material design. The recent addition of monolayer ferroelectrics expands the possibilities of designer materials. Ferroelectric domains can be manipulated using electric fields, thus opening a route for external control over material properties. In this paper we explore the possibility of engineering magneto-electric coupling in ferroelectric heterostructures by studying the interface of bilayer SnTe with iron phthalocyanine molecules as a model system. The molecules act as sensor spins, allowing us to sample the magneto-electric coupling with nanometer precision through scanning tunneling microscopy. Our measurements uncover a structural, and therefore material-independent and intrinsic, mechanism to couple electric and magnetic degrees of freedom at the nanoscale.

Nima L. Wickramasinghe, Dinuka Sandun Udayantha, Akila Abeyratne et al.

Objective: Young children and infants, especially newborns, are highly susceptible to seizures, which, if undetected and untreated, can lead to severe long-term neurological consequences. Early detection typically requires continuous electroencephalography (cEEG) monitoring in hospital settings, involving costly equipment and highly trained specialists. This study presents a low-cost, active dry-contact electrode-based, adjustable electroencephalography (EEG) headset, combined with an explainable deep learning model for seizure detection from reduced-montage EEG, and a multimodal artifact removal algorithm to enhance signal quality. Methods: EEG signals were acquired via active electrodes and processed through a custom-designed analog front end for filtering and digitization. The adjustable headset was fabricated using three-dimensional printing and laser cutting to accommodate varying head sizes. The deep learning model was trained to detect neonatal seizures in real time, and a dedicated multimodal algorithm was implemented for artifact removal while preserving seizure-relevant information. System performance was evaluated in a representative clinical setting on a pediatric patient with absence seizures, with simultaneous recordings obtained from the proposed device and a commercial wet-electrode cEEG system for comparison. Results: Signals from the proposed system exhibited a correlation coefficient exceeding 0.8 with those from the commercial device. Signal-to-noise ratio analysis indicated noise mitigation performance comparable to the commercial system. The deep learning model achieved accuracy and recall improvements of 2.76% and 16.33%, respectively, over state-of-the-art approaches. The artifact removal algorithm effectively identified and eliminated noise while preserving seizure-related EEG features.

Edward Riordan, Monica Ciomaga Hatnean, Geetha Balakrishnan et al.

The garnet compound Yb$_3$Ga$_5$O$_{12}$ is a fascinating material that is considered highly suitable for low-temperature refrigeration, via the magnetocaloric effect, in addition to enabling the exploration of quantum states with long-range dipolar interactions. It has previously been theorized that the magnetocaloric effect can be enhanced, in Yb$_3$Ga$_5$O$_{12}$ , via magnetic soft mode excitations which in the hyperkagome structure would be derived from an emergent magnetic structure formed from nanosized 10-spin loops. We study the magnetic field dependence of bands of magnetic soft mode excitations in the effective spin $S = 1/2$ hyperkagome compound Yb$_3$Ga$_5$O$_{12}$ using single crystal inelastic neutron scattering. We probe the magnetically short ranged ordered state, in which we determine magnetic nanoscale structures coexisting with a fluctuating state, and the magnetically saturated state. We determine that Yb$_3$Ga$_5$O$_{12}$ can be described as a quantum dipolar magnet with perturbative weak near-neighbor and inter-hyperkagome exchange interaction. The magnetic excitations, under the application of a magnetic field, reveal highly robust soft modes with distinctive signatures of the quantum nature of the Yb3+ spins. Our results enhance our understanding of soft modes in topological frustrated magnets that drive both the unusual physics of quantum dipolar systems and future refrigerant material design.

Terril L. Verplaetse, Ansel T. Hillmer, Shivani Bhatt et al.

Background: Stress is a potent activator of the hypothalamic-pituitary-adrenal (HPA) axis, initiating the release of glucocorticoid hormones, such as cortisol. Alcohol consumption can lead to HPA axis dysfunction, including altered cortisol levels. Until recently, research has only been able to examine peripheral cortisol associated with alcohol use disorder (AUD) in humans. We used positron emission tomography (PET) brain imaging with the radiotracer [18F]AS2471907 to measure 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1), a cortisol-regenerating enzyme, in people with AUD compared to healthy controls. Methods: We imaged 9 individuals with moderate to severe AUD (5 men, 4 women; mean age = 38 years) and 12 healthy controls (8 men, 4 women; mean age = 29 years). Participants received 93.5 ± 15.6 MBq of the 11β-HSD1 inhibitor radiotracer [18F]AS2471907 as a bolus injection and were imaged for 150–180 min on the High-Resolution Research Tomograph. 11β-HSD1 availability was quantified by [18F]AS2471907 volume of distribution (VT; mL/cm3). A priori regions of interest included amygdala, anterior cingulate cortex (ACC), hippocampus, ventromedial PFC (vmPFC) and caudate. Results: Individuals with AUD consumed 52.4 drinks/week with 5.8 drinking days/week. Healthy controls consumed 2.8 drinks/week with 1.3 drinking days/week. Preliminary findings suggest that [18F]AS2471907 VT was higher in amygdala, ACC, hippocampus, vmPFC, and caudate of those with AUD compared to healthy controls (p < 0.05). In AUD, vmPFC [18F]AS2471907 VT was associated with drinks per week (r = 0.81, p = 0.01) and quantity per drinking episode (r = 0.75, p = 0.02). Conclusions: This is the first in vivo examination of 11β-HSD1 availability in individuals with AUD. Our data suggest higher brain availability of the cortisol-regenerating enzyme 11β-HSD1 in people with AUD (vs. controls), and that higher vmPFC 11β-HSD1 availability is related to greater alcohol consumption. Thus, in addition to the literature suggesting that people with AUD have elevated peripheral cortisol, our findings suggest there may also be heightened central HPA activity. These findings set the foundation for future hypotheses on mechanisms related to HPA axis function in this population.

Ruiqi Liu, Shuang Zheng, Qingqing Wu et al.

Reconfigurable Intelligent Surfaces (RISs) are a novel form of ultra-low power devices that are capable to increase the communication data rates as well as the cell coverage in a cost- and energy-efficient way. This is attributed to their programmable operation that enables them to dynamically manipulate the wireless propagation environment, a feature that has lately inspired numerous research investigations and applications. To pave the way to the formal standardization of RISs, the European Telecommunications Standards Institute (ETSI) launched the Industry Specification Group (ISG) on the RIS technology in September 2021. This article provides a comprehensive overview of the status of the work conducted by the ETSI ISG RIS, covering typical deployment scenarios of reconfigurable metasurfaces, use cases and operating applications, requirements, emerging hardware architectures and operating modes, as well as the latest insights regarding future directions of RISs and the resulting smart wireless environments.

Vijay Sadashivaiah, Madhavi Tippani, Stephanie C. Page et al.

Abstract Background Multispectral fluorescence imaging coupled with linear unmixing is a form of image data collection and analysis that allows for measuring multiple molecular signals in a single biological sample. Multiple fluorescent dyes, each measuring a unique molecule, are simultaneously measured and subsequently “unmixed” to provide a read-out for each molecular signal. This strategy allows for measuring highly multiplexed signals in a single data capture session, such as multiple proteins or RNAs in tissue slices or cultured cells, but can often result in mixed signals and bleed-through problems across dyes. Existing spectral unmixing algorithms are not optimized for challenging biological specimens such as post-mortem human brain tissue, and often require manual intervention to extract spectral signatures. We therefore developed an intuitive, automated, and flexible package called SUFI: spectral unmixing of fluorescent images. Results This package unmixes multispectral fluorescence images by automating the extraction of spectral signatures using vertex component analysis, and then performs one of three unmixing algorithms derived from remote sensing. We evaluate these remote sensing algorithms’ performances on four unique biological datasets and compare the results to unmixing results obtained using ZEN Black software (Zeiss). We lastly integrate our unmixing pipeline into the computational tool dotdotdot, which is used to quantify individual RNA transcripts at single cell resolution in intact tissues and perform differential expression analysis, and thereby provide an end-to-end solution for multispectral fluorescence image analysis and quantification. Conclusions In summary, we provide a robust, automated pipeline to assist biologists with improved spectral unmixing of multispectral fluorescence images.

Fateme Zare, Paniz Sedighi, Mehdi Delrobaei

Executive function, also known as executive control, is a multifaceted construct encompassing several cognitive abilities, including working memory, attention, impulse control, and cognitive flexibility. To accurately measure executive functioning skills, it is necessary to develop assessment tools and strategies that can quantify the behaviors associated with cognitive control. Impulsivity, a range of cognitive control deficits, is typically evaluated using conventional neuropsychological tests. However, this study proposes a biomechatronic approach to assess impulsivity as a behavioral construct, in line with traditional neuropsychological assessments. The study involved thirty-four healthy adults who completed the Barratt Impulsiveness Scale (BIS-11) as an initial step. A low-cost biomechatronic system was developed, and an approach based on standard neuropsychological tests, including the trail-making test and serial subtraction-by-seven, was used to evaluate impulsivity. Three tests were conducted: WTMT-A (numbers only), WTMT-B (numbers and letters), and a dual-task of WTMT-A and serial subtraction-by-seven. The preliminary findings suggest that the proposed instrument and experiments successfully generated an attentional impulsivity score and differentiated between participants with high and low attentional impulsivity.

Florio M. Ciaglia aand Fabio Di Cosmo

In this paper some reflections on the concept of transition are presented: groupoids are introduced as models for the construction of a ``generalized logic'' whose basic statements involve pairs of propositions which can be conditioned. In this sense, we could distinguish between classical probability theory where propositions can be conditioned if they have a non-zero intersection, from cases where ``non-local'' conditioning are allowed. The algebraic and geometrical properties of groupoids can be exploited to construct models of such non-local description.

Parvin Zarei Eskikand, David B Grayden, Tatiana Kameneva et al.

Computational modeling helps neuroscientists to integrate and explain experimental data obtained through neurophysiological and anatomical studies, thus providing a mechanism by which we can better understand and predict the principles of neural computation. Computational modeling of the neuronal pathways of the visual cortex has been successful in developing theories of biological motion processing. This review describes a range of computational models that have been inspired by neurophysiological experiments. Theories of local motion integration and pattern motion processing are presented, together with suggested neurophysiological experiments designed to test those hypotheses.

Mary Lou Smith

Memory deficits are commonly associated with temporal-lobe epilepsy. Memory may worsen after surgical resection of the temporal lobe. Risk factors for decline are structural integrity of the mesial temporal lobe structures and intact pre-operative memory. Subjective memory complaints are influenced by depression or other psychological disorders. A 16-year-old girl underwent resection from the right lateral and medial temporal lobe and after surgery she complained of a significant memory impairment, which was unexpected given her baseline assessment. Before undertaking a neuropsychological assessment, she was referred for a psychiatric consultation which revealed depression, leading to treatment with anditdepressant medication. Over time she also admitted to severe headaches and inadequate sleep. With these issues addressed, assessment indicated memory performance had not changed relative to her preoperative baseline with stability or improvement in memory across longitudinal assessments. This case illustrates the contribution of mood state and other potential factors in contributing to subjective memory complaints.

Appleton SL, Reynolds AC, Gill TK et al.

Sarah L Appleton,1,2 Amy C Reynolds,1 Tiffany K Gill,2 Yohannes Adama Melaku,1 Robert J Adams1 1Flinders Health and Medical Research Institute – Sleep Health (Adelaide Institute for Sleep Health), College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia; 2The Adelaide Medical School, University of Adelaide, Adelaide, SA, AustraliaCorrespondence: Sarah L Appleton, Flinders Health and Medical Research Institute -Sleep Health (Adelaide Institute for Sleep Health), College of Medicine and Public Health, Flinders University, Mark Oliphant Building, L2, 5 Laffer Drive, Bedford Park, Adelaide, 5042, SA, Australia, Tel +61 8 74219755, Email sarah.appleton@flinders.edu.auIntroduction: Estimating insomnia prevalence in epidemiological studies is hampered by variability in definitions and interpretation of criteria. We addressed the absence of a population-based estimate of insomnia in Australia using the widely accepted contemporary International Classification of Sleep Disorders (ICSD-3) criteria, which includes sleep opportunity, and has not been applied in studies to date. Consistent use of these criteria across epidemiological studies, however, requires evidence of the clinical utility of a sleep opportunity criterion for targeting strategies.Methods: A cross-sectional national on-line survey (2019 Sleep Health Foundation Insomnia Survey) of Australian adults (18– 90 years, n = 2044) was conducted. Chronic insomnia was defined as sleep symptoms and daytime impairment experienced ≥ 3 times per week, and present for ≥ 3 months, with adequate sleep opportunity (time in bed (TIB) ≥ 7.5 hrs). Self-rated general health (SF-1) and ever diagnosed health conditions (including sleep disorders) were assessed.Results: Chronic difficulties initiating and maintaining sleep and daytime symptoms (n = 788) were more common in females (41.5%) than males (35.3%), p = 0.004. Excluding participants reporting frequent pain causing sleep disruption and TIB < 7.5 hrs generated an insomnia disorder estimate of 25.2% (95% CI: 22.5– 28.2) in females and 21.1% (18.4– 23.9) in males [23.2% (21.2– 25.2) overall]. This compares with 8.6% (7.3– 10.0) with insomnia symptoms and TIB < 7.5 hrs and 7.5% (6.4– 8.7%) ever diagnosed with insomnia. Insomnia symptom groups with TIB < 7.5 and ≥ 7.5 hours demonstrated similar odds of reporting fair/poor health [odds ratio (OR): 3.2 (95% CI: 2.1– 4.8) and 2.9 (95% CI: 2.2– 3.9) respectively], ≥ 1 mental health condition, ≥ 1 airway disease, and multimorbidity.Conclusion: Adults with significant sleep and daytime symptomatology and TIB < 7.5 hrs did not differ clinically from those with insomnia disorder. Consideration of criteria, particularly adequate sleep opportunity, is required to consistently identify insomnia, and establish health correlates in future epidemiological studies. Further evaluation of the clinical utility of the sleep opportunity criterion is also required.Keywords: insomnia, sex, epidemiology, population

Eli Sennesh, Jordan Theriault, Jan-Willem van de Meent et al.

Active inference offers a principled account of behavior as minimizing average sensory surprise over time. Applications of active inference to control problems have heretofore tended to focus on finite-horizon or discounted-surprise problems, despite deriving from the infinite-horizon, average-surprise imperative of the free-energy principle. Here we derive an infinite-horizon, average-surprise formulation of active inference from optimal control principles. Our formulation returns to the roots of active inference in neuroanatomy and neurophysiology, formally reconnecting active inference to optimal feedback control. Our formulation provides a unified objective functional for sensorimotor control and allows for reference states to vary over time.

Xiaonan Zhang, Wei Yan, Ying Xue et al.

Adenosine deaminase acting on RNA1 (ADAR1) is a newly discovered epigenetic molecule marker that is sensitive to environmental stressors. A recent study has demonstrated that ADAR1 affects BDNF expression via miR-432 and is involved in antidepressant action. However, the detailed molecular mechanism is still unclear. We have uncovered a new molecular mechanism showing the involvement of miR-432 and circ_0000418 in mediating the antidepressant action of ADAR1. We demonstrate that the ADAR1 inducer (IFN-γ) alleviates the depressive-like behaviors of BALB/c mice treated with chronic unpredictable stress (CUS) exposure. Moreover, both in vivo and in vitro studies show that ADAR1 differently impacts miR-432 and circ_0000418 expressions. Furthermore, the in vitro results demonstrate that circ_0000418 oppositely affects BDNF expression. Together, our results indicate that ADAR1 affects CUS-induced depressive-like behavior and BDNF expression by acting on miR-432 and circ_0000418. Elucidation of this new molecular mechanism will not only provide insights into further understanding the important role of ADAR1 in stress-induced depressive-like behavior but also suggest a potential therapeutic strategy for developing novel anti-depressive drugs.

Tessa Clarkson, Yvette Karvay, Megan Quarmley et al.

Adolescent males and females differ in their responses to social threat. Yet, threat processing is often probed in non-social contexts using the error-related negativity (ERN; Flanker EEG Task), which does not yield sex-specific outcomes. fMRI studies show inconsistent patterns of sex-specific neural engagement during threat processing. Thus, the relation between threat processing in non-social and social contexts across sexes and the effects perceived level of threat on brain function are unclear. We tested the interactive effect of non-social threat-vigilance (ERN), sex (N = 69; Male=34; 11–14-year-olds), and perceived social threat on brain function while anticipating feedback from ‘unpredictable’, ‘nice’, or ‘mean’ purported peers (fMRI; Virtual School Paradigm). Whole-brain analyses revealed differential engagement of precentral and inferior frontal gyri, putamen, anterior cingulate cortex, and insula. Among males with more threat-vigilant ERNs, greater social threat was associated with increased activation when anticipating unpredictable feedback. Region of interest analyses revealed this same relation in females in the amygdala and anterior hippocampus when anticipating mean feedback. Thus, non-social threat vigilance relates to neural engagement depending on perceived social threat, but peer-based social contexts and brain regions engaged, differ across sexes. This may partially explain divergent psychosocial outcomes in adolescence.

Deniz Bedir, Süleyman E. Erhan

The aim of study is to reveal the relationship between the personality traits of athletes and problematic internet use (PIU), and in this way, to reveal which personality traits athletes tend to PIU. A total of 428 athletes, 204 (47.7%) males and 224 (52.3%) females, who were engaged in amateur and professional level sports in various sports clubs, participated in the study. “Internet Addiction Scale” was used to determine the PIU status of the participants and “Five Factor Model of Personality Scale” was used to determine the personality characteristics. The stepwise regression method was used to determine the level of predicting PIU of personality traits. As a result of the analyzes, it was determined to what extent the variables of extraversion, agreeableness, conscientiousness, neuroticism, openness, and gender predicted PIU and as a result of this process, R = .798, R2 = .637. As a result, it was seen that 63.7% of the total variance in the PIU of the athletes was explained by the personality traits.

Jens Müller, Hongliu Yang, Matthias Eberlein et al.

Seizure forecasting using machine learning is possible, but the performance is far from ideal, as indicated by many false predictions and low specificity. Here, we examine false and missing alarms of two algorithms on long-term datasets to show that the limitations are less related to classifiers or features, but rather to intrinsic changes in the data. We evaluated two algorithms on three datasets by computing the correlation of false predictions and estimating the information transfer between both classification methods. For 9 out of 12 individuals both methods showed a performance better than chance. For all individuals we observed a positive correlation in predictions. For individuals with strong correlation in false predictions we were able to boost the performance of one method by excluding test samples based on the results of the second method. Substantially different algorithms exhibit a highly consistent performance and a strong coherency in false and missing alarms. Hence, changing the underlying hypothesis of a preictal state of fixed time length prior to each seizure to a proictal state is more helpful than further optimizing classifiers. The outcome is significant for the evaluation of seizure prediction algorithms on continuous data.

Francesca Venturini, Michela Sperti, Umberto Michelucci et al.

Extra virgin olive oil (EVOO) is the highest quality of olive oil and is characterized by highly beneficial nutritional properties. The large increase in both consumption and fraud, for example through adulteration, creates new challenges and an increasing demand for developing new quality assessment methodologies that are easier and cheaper to perform. As of today, the determination of olive oil quality is performed by producers through chemical analysis and organoleptic evaluation. The chemical analysis requires the advanced equipment and chemical knowledge of certified laboratories, and has therefore a limited accessibility. In this work a minimalist, portable and low-cost sensor is presented, which can perform olive oil quality assessment using fluorescence spectroscopy. The potential of the proposed technology is explored by analyzing several olive oils of different quality levels, EVOO, virgin olive oil (VOO), and lampante olive oil (LOO). The spectral data were analyzed using a large number of machine learning methods, including artificial neural networks. The analysis performed in this work demonstrates the possibility of performing classification of olive oil in the three mentioned classes with an accuracy of 100$\%$. These results confirm that this minimalist low-cost sensor has the potential of substituting expensive and complex chemical analysis.